Coronary 2D Review is
intended to assist
readers in the review of
coronary artery imaging.
Within this review step,
readers will find tools
aligned with a 2D
coronary artery CTA
review as well as
general overview of all
reconstructions
acquired within a study
such a multi-phase cine
acquisitions or delayed
enhancement imaging.
It provides various
review tools:
* Multi oblique tools to
generate chamber,
vessel or lesion views
in any desired
orientations
* Cine mode to view
multi-phase data in
motion
* 2D distance, ROI
* Rendering
Note: A segmented 3D
Volume Rendering
model of the heart is not
available.

Coronary 2D Review is
renamed as ‘MPR
Cardiac Review’ and has
the same intended
purpose as the
predicate device which
is intended to assist
readers in the review of
coronary artery imaging.
Within this review step,
readers will find tools
aligned with a 2D
coronary artery CTA
review, a segmented 3D
Volume Rendering
model of the heart
(NEW), as well as
general overview of all
reconstructions
acquired within a study
such a multi-phase cine
acquisitions or delayed
enhancement imaging.
It provides various
review tools:
* Multi oblique tools to
generate chamber,
vessel or lesion views
in any desired
orientations
* Cine mode to view
multi-phase data in
motion
* 2D distance, ROI
* Rendering

Substantially equivalent.
The only difference in the subject device
is the introduction of a new deep
learning algorithm to automatically
segment heart and provide a segmented
3D Volume Rendering model of the
heart. The functionality to segment heart
in 3D already exists in the reference
device CardIQ Xpress 2.0 (K073138). The
reference device uses mathematical
morphology operations and Hounsfield
Unit based thresholds to segment the
heart in 3D. In the subject device, a fully
convolutional neural network trained
and validated on annotated CT images is
used to segment the heart.
From the user perspective the output of
the segmentation, the editing capability
and workflow remains the same
between the subject device and
reference device. The main reason to
incorporate the deep learning algorithm
is to improve the workflow efficiency.


Specification
Primary Predicate
Subject Device:
Comparison

CardIQ Suite provides a
variety of methods for
sharing the results with
clinical partners.
* Calcium Score results
and scored images can
be saved as DICOM SR
series and networked to
DICOM destinations for
structured reporting
purposes.
* Copy individual
images or the results
table to paste into
personalized
communications.
* Screen capture
individual images and
results to save data
pertinent to the patient
file for selective
archiving needs.
* Generate file for
importing into
customized report
templates or research
file management needs
* Export selected Images

Substantial Equivalent
Deep-Learning Algorithms are
incorporated in the subject device to
automatically segment coronary,
automatically track and label coronary
centerline in order to improve workflow
efficiency. The same functionalities
already exist in the reference device
CardIQ Xpress 2.0 (K073138), the
difference is in how the functionality is

510(k) Premarket Notification Submission-CardIQ Suite


implemented in the devices. For the
Coronary tree segmentation, the
reference device, CardIQ Xpress 2.0
(K073138) utilizes signal processing
methods to achieve coronary
segmentation, whereas in the subject
device a deep-learning based algorithm
is implemented to perform the same
function.
For the Coronary centerline tracking, the
reference device CardIQ Xpress 2.0
utilizes mathematical morphology,
leveraging on hessian filters and ray
tracing to provide the coronary
centerline tracking, whereas in the
subject device a deep-learning based
algorithm is implemented to perform the
same function. The prerequisite for this
algorithm is that the Coronary tree
segmentation must be performed.
For the Coronary labeling, the reference
device CardIQ Xpress 2.0 utilizes a rules-
based algorithm, based on the
knowledge of the anatomy of the
coronaries, whereas in the subject
device a deep-learning based algorithm
is implemented to perform the same
function. The prerequisite for this
algorithm is that the Coronary tree
segmentation and Coronary centerline
tracking must be performed.
From the user perspective the output of
the coronary segmentation, tracking and
labeling, the editing capability for
coronary segmentation, tracking and
labeling and the workflow remains the
same between the subject device and
reference device. The main reason to
incorporate the deep learning algorithms
is to improve the workflow efficiency.


Subsystem
Revolution Ascend
Revolution Ascend Sliding

(Predicate Device, K213938)
(Proposed Device)

Revolution Ascend Gantry
- Bore size: 75cm
- Physical Tilt
Performix 40 Plus X-Ray Tube
- Supports 40 mm beamwidth
- Liquid Metal rotor bearing
JEDI60DC High Voltage Generator
- Peak Power: 72 kW
-55 kW option (software limit
on mA)
NGX Collimator (75cm bore)
- 40 mm max z-coverage
Merc40H Detector
- Backlit Diode technology
- Chiclet Module design
- GE low noise ASIC technology
used for signal conversion

Revolution Ascend Sliding Gantry
- Bore size: 75cm
- Physical Tilt: Disabled
Performix 40 Plus X-Ray Tube
- Supports 40 mm beam width
- Liquid Metal rotor bearing
JEDI60DC High Voltage Generator
- Peak Power: 72 kW
NGX Collimator (75cm bore)
- 40 mm max z-coverage
Merc40H Detector
- Backlit Diode technology
- Chiclet Module design
- GE low noise ASIC technology used
for signal conversion


- VT1700v Table
- Lite Table
- Table accessories

Patient Support equipment is stationary in
the horizontal axis, Gantry moves
horizontally with rails system.

The patient table moves horizontally
to the gantry bore during a CT exam
while the gantry is stationary

The gantry mounted on a transporter
moves horizontally on rails towards the
patient who is positioned on a patient
support device that is stationary. The
transporter uses substantial design and
manufacturing process as the reference
device cleared in K091673.

FBP
ASIR-V (K133640)
DLIR cleared with Revolution Ascend
(K212067, K230807).


AI-Rad Companion (Pulmonary)
AI-Rad Companion (Pulmonary)

Creation of a lung segmentation
mask by combining the
segmentation masks of 5 lung
lobes.

Computation of segmentation
masks of the five lung lobes (right
upper (RUL), right middle (RML),
right lower (RLL), left upper (LUL)
and left lower (LLL) lobe) for a
given CT data set of the chest.

The parenchyma evaluation uses
the lobe mask, counts all voxels per
lobe, counts image voxels below -
950 HU, and calculates the
percentages of these voxels relative
to the total number of voxels.
Additionally, it sums the individual
lobe results and calculates the
percentage for the complete lung.

The percentages are likewise
dedicated to the 4 ranges. Name of
ranges and their ranges are
configurable by the user.


AI‐based identification of areas
with elevated Hounsfield values.
Threshold‐based identification of
highest elevated Hounsfield values
inside these elevated regions, by a
predefined threshold of ‐200 HU

Visualization of
segmentation
and parenchyma
results

Color overlay of MPR and VRT
with evaluation results

Segmentation of solid and sub-solid
lung lesions including the following
data:
• Relative change of
maximum 2D diameter [%]
• relative change of
maximum orthogonal 2D
diameter [%]
• relative change of mean 2D
diameter [%],
• relative change of
maximum 3D diameter [%]
• Relative change of volume
(volume doubling time [d],
negative growth [%])

Segmentation of lung lesions
including the following data:
• Relative change of
maximum 2D diameter [%]
• relative change of
maximum orthogonal 2D
diameter [%]
• relative change of mean 2D
diameter [%],
• relative change of
maximum 3D diameter [%]
• Relative change of volume
(volume doubling time [d],
negative growth [%])

Enhanced –
addition of
sub-solid
lesion
segmentation

Visualization of
lesion
segmentation
results

Correlation of segmented lung
lesions with known priors using the
data from the lesion segmentation.


Medical Devices – Application
of usability engineering to
medical devices [including
Corrigendum 1 (2016)]

Medical Devices – application
of risk management to medical
devices

Medical device software –
software life cycle processes
[Including Amendment 1
(2016)]

Digital Imaging and
Communications in Medicine
(DICOM) Set

Medical devices – symbols to
be used with information to be
supplied by the manufacturer

voluntary FDA recognized Consensus Standards listed in Table 1 below.


Average DICE ≥ predicate
Bias & RMSE ≤ predicate
LoA in line with predicate LoA

Performance was analyzed in relation to the predicate’s
solid nodule segmentation performance
Median nodule size range for sub-solid is 10mm-20mm
LoA for 10mm-20mm ≥ 95% for all three diameter
metrics

Average DICE score for sub-solid nodules ≥ average
DICE for predicate solid nodules

Average DICE not smaller than DICE of overall cohort
minus 1 STD
Bias of three metrics not exceed ±1 STD
RMSE of three metrics not exceed RMSE of overall
cohort +1 STD each


Canon/Toshiba: 18
GE: 35
Philips: 15
Siemens: 32


Predicate Device
FDA Clearance
FDA Clearance
Main Product Code


Classification Description
21 CFR §
Product Code

System, imaging, pulsed doppler,
ultrasonic

System, imaging, pulsed echo,
ultrasonic

Transducer, ultrasonic, diagnostic
892.1570
ITX

Automated Radiological Image
Processing Software

Diagnostic Intravascular Catheter
870.1200
OBJ*

Common Name Diagnostic Ultrasound System and Transducers


EPIQ Series Diagnostic
Diagnostic Ultrasound

Feature
Affiniti Series Diagnostic
Affiniti Diagnostic
Comparison

Not applicable since the
application is new

are substantially equivalent to the predicate devices (K211597) and reference device (K231190).


The proposed Smart
Doppler View ID feature is
intended to be used Adult
Cardiology Transthoracic
examinations to automate
the navigation of the
Calculations Package
group associated with
Doppler Measurements.
Without the Smart Doppler
View ID feature, users
must manually navigate to
the desired Doppler
Calculations Package
Group on the Ultrasound
System to perform a
measurement. The Smart
Doppler View ID feature
automates this navigation
and selects the associated
Calculations Package
group for the user based
on the provided Doppler
Spectrum acquired by the
user.
Automated selection of
Calculation Package
Groups by Smart Doppler
View ID:
• Aortic Valve
• Mitral Valve
• Tricuspid Valve
• Pulmonic Valve
• Venous Flow
• TDI Vel & Ratio

Manual selection by the
user of Calculations
Package group on the
ultrasound system
associated with
measurement groups on
the ultrasound system.
Manual selection of
Calculation Package
Groups by the user:
• Aortic Valve
• Mitral Valve
• Tricuspid Valve
• Pulmonic Valve
• Venous Flow
• TDI Vel & Ratio

Subject of this submission.
The Smart Doppler View ID
automates the selection of
Calculations Package group
on the ultrasound system
during Adult Cardiology
Transthoracic examinations,
where the predicate and
reference devices require
users to manually navigate to
their desired Calculations
Package group to perform
subsequent measurements.
The Smart Doppler View ID
feature does not perform any
measurements itself and is
only intended to automate the
selection of the Calculations
Package group associated
with an acquired doppler
spectrum.
There is no change to the
Calculation Package Groups
available to the user.

After a user acquires a
doppler spectrum, a
Calculations Package
group is automatically
highlighted on the
ultrasound system display
for the user by Smart
Doppler View ID. From the
highlighted Calculations
Package group, the user
may select a desired
measurement to perform
on the image. If the user
disagrees with the
highlighted Calculations
Package group, they can
manually navigate to their
desired Calculations
Package group.

After a user acquires a
doppler spectrum, the user
must manually navigate to
the desired Calculations
Package group. From the
manually selected
Calculations Package
group, the user may select
a desired measurement to
perform on the image.

The only difference with Smart
Doppler View ID is that the
Measurement Calculations
Package group is
automatically highlighted for
the user after a doppler
spectrum is acquired. Without
Smart Doppler View ID, users
must manually navigate to
their desired Calculations
Package group.
There is no change to the
user’s functionality once the
Calculations Package group is
selected for them compared to
their workflow without Doppler
View ID.


EPIQ:
X5-1, X5-1c, and S5-1 are
already commercially
available and compatible
with the EPIQ Ultrasound
System.
Affiniti:
S5-1, X5-1, and S4-2 are
already commercially
available and compatible
with the Affiniti Ultrasound
System.
No new transducers.
Transducer modes for
Smart Doppler View ID:
2D, PWD, CWD, TDI. No
new transducer modes.

The K231190 submission
introduced the mL26-8
transducer. This transducer
is not compatible with the
proposed Smart Doppler
View ID feature.

No new transducers or modes
are being introduced in this
submission. All transducers
are already available with the
EPIQ and Affiniti Ultrasound
Systems.

No measurements are
performed by the Smart
Doppler View ID feature.
Any cardiac adult TTE
measurements resulting
from the view selection are
performed either manually
by the user or by the
commercially available
AutoMeasure function
(K211597).

No new measurements are
being introduced in this
submission. The subject of this
submission is to provide
workflow enhancements using
an artificial intelligence -
application.

Algorithm accuracy of
97.5% (95%CI 96.3%,
98.3%), p-value <0.0001
compared to the ground
truth

N/A – the equivalent
functionality is performed
manually by users to select
the appropriate calculation
package group (touch
screen group)


Race
White
Asian
Black or African American
American Indian or Alaska Native
Native Hawaiian or Other Pacific Islander
Mixed/More than one race
Other/Unknown/Not Reported

The demographic distribution of the study population includes the following:


Medical image management and processing system

MRIMath i2contour is intended for the semi-automatic
labeling, visualization, and volumetric quantification
of WHO grade 4 glioblastoma (GBM) from a set of
standard MRI images of male or female patients 18
years of age or older who are known to have
pathologically proven glioblastoma.
Volumetric measurements may be compared to past
measurements if available. MRIMath i2contour is not
to be used for primary diagnosis and is not intended to
be the sole diagnostic metric.

NS-HGlio is intended for the semi-automatic
labeling, visualization, and volumetric
quantification of high-grade brain glioma (WHO
grade 3 astrocytoma, WHO grade 4 astrocytoma and
WHO grade 4 glioblastoma) from a set of standard
MRI images of male or female patients 18 years of
age or older who are known to have pathologically
proven high-grade glioma.
Volumetric measurements may be compared to past
measurements if available. NS-HGlio is not to be
used for primary diagnosis, and is intended to be
used by qualified clinical personnel as an additional
source of information and is not intended to be the
sole diagnostic metric.

Similar except the subject
device is specific for
glioblastoma (GBM)

Male or female patients 18 years of age or older who
are known to have pathologically proven glioblastoma

Male or female patients 18 years of age or older who
are known to have pathologically proven high-grade
glioma

Similar with the subject device
is limited to GBM

MRI:
Acquired using two different MRI sequences either in
2D or 3D using a specified protocol: T1 post-contrast
(T1c) or FLAIR.

MRI:
Acquired using four different MRI sequences either
in 2D or 3D using a specified protocol: T1, T2, T1
post-contrast (T1c) and FLAIR.

Lesion Review
2D and 3D
2D and 3D
Similar

Semi-automatic and manual segmentation of
glioblastoma

Semi-automatic and manual segmentation of high-
grade glioma

Volumetric measurements of the combination of the
enhancing and necrosis subcomponents of the T1c, and
the combination of edema, tumor, and necrosis
subcomponents in the FLAIR images of glioblastoma

Volumetric measurement of the edema, necrosis, and
enhancing sub-components of high-grade glioma

Table 1 - Comparison of Subject vs. Predicate


- Provides volumetric measurements of glioblastoma
and the tumor + edema + necrosis subcomponents in
FLAIR and the enhancing + necrosis subcomponents
in T1c series
- Includes segmentation of the tumor + edema +
necrosis subcomponents in FLAIR and the enhancing
+ necrosis subcomponents in T1c series
- Automatically compares results to prior scans when
available
- Provides PDF Report of output data

- Provides volumetric measurements of glioblastoma
and the enhancing, necrosis, and edema sub-
components
- Includes segmentation of sub-components
- Automatically compares results to prior scans when
available
- Provides PDF Report of output data

Input
FLAIR or T1c Series
T1, T2, FLAIR and T1c Series
Different

Grade 3 astrocytoma, grade 4 astrocytoma,
grade 4 GBM

Using three US board certified neuroradiologists with
expertise in measuring GBM

Using three US board certified neuroradiologists with
expertise in measuring high grade gliomas


Regulation Number
Regulation Number
Regulation Name
Primary Product

Ultrasonic Pulsed Doppler Imaging System

Regulation Number
Regulation Number
Regulation Name
Secondary

Medical Image Management and Processing System

Regulation Number, Name and Product Code:


Ultrasonic Pulsed Doppler Imaging System
Ultrasonic Pulsed Echo Imaging System
Medical Image Management and Processing System


Clarius Ultrasound App (Clarius App) for iOS;
Clarius Ultrasound App (Clarius App) for Android

K213436). Clarius OB AI is not a stand-alone software device.


Criteria
SUBJECT DEVICE
PREDICATE DEVICE
RATIONALE

Clarius OB AI
Sonio Detect
from predicate device)

510(k) Holder/ Manufacturer
Clarius Mobile Health Corp.
Sonio
Not applicable

Submission Reference
Current Submission
K230365
Not applicable

The “IYN” primary product
code is the same as the
predicate device and the
“QIH” secondary product
code is the same as the
predicate device.

Ultrasonic Pulsed Doppler Imaging
System;
Medical Image Management and
Processing System

Ultrasonic Pulsed Doppler Imaging
System;
Ultrasonic Pulsed Echo Imaging System;
Medical Image Management and
Processing System

The “Ultrasonic Pulsed
Doppler Imaging System”
and the “Medical Image
Management and
Processing System” device
classification names are
the same as the predicate
device.

The “21 CFR § 892.1550”
regulation number and the
“21 CFR § 892.2050”
regulation number are the
same as the predicate
device.

Intended for use as an assistive tool/aid
during the acquisition and interpretation
of fetal ultrasound images through non-
invasive processing of ultrasound images
utilizing an artificial intelligence/machine-
learning algorithm.

Clarius OB AI is intended to assist in
measurements of fetal biometric
parameters (i.e., head circumference,
abdominal circumference, femur

Sonio Detect is intended to analyze fetal
ultrasound images and clips using
machine learning techniques to
automatically detect views, detect

Both the predicate and
subject device are
indicated for analysis of
fetal ultrasound images

Table 1 - Comparison of the Subject Device to the Legally Marketed Predicate Device


length, bi-parietal diameter, crown
rump length) on ultrasound data
acquired by the Clarius Ultrasound
Scanner (i.e., curvilinear scanner).
The user shall be a healthcare
professional trained and qualified in
ultrasound. The user retains the
responsibility of confirming the
validity of the measurements based
on standard practices and clinical
judgment. Clarius OB AI is indicated
for use in adult patients only.

anatomical structures within the views
and verify quality criteria of the views.
The device is intended for use as a
concurrent reading aid during the
acquisition and interpretation of fetal
ultrasound images.

using AI/ML techniques.
Both devices detect
various fetal anatomies;
the predicate device
provides qualitative
information to the user,
whereas the subject
device provides semi-
automated quantitative
information regarding
fetal biometrics. Both the
predicate and subject
devices are intended for
use as an adjunctive ‘tool’
or aid by the user for the
interpretation of fetal
ultrasound images and are
not intended to replace
clinical decision making.
The differences in the
indications for use do not
impact the safety and
effectiveness of the
subject device relative to
the predicate device.

Radiological application/ Supported
Ultrasound
Ultrasound
Same as predicate device.

Clinical application(s)
Obstetrics/Fetal
Obstetrics/Fetal
Same as predicate device.

Ultrasound image processing software
application implementing artificial
intelligence utilizing non-adaptive
machine learning algorithms trained with
clinical and/or artificial data intended for


Criteria
SUBJECT DEVICE
PREDICATE DEVICE
RATIONALE

Clarius OB AI
Sonio Detect
from predicate device)

non-invasive analysis (i.e., quantitative
and/or qualitative) of ultrasound data.

Quantitative and/or Qualitative
Analysis

Fetal biometry/measurement of fetal
biometric parameters (i.e., HC, AC, BPD,
CRL, FL)

Detection, verification, and qualitative
analysis of fetal anatomical structures

The subject device
performs semi-automated
measurements of fetal
biometrics, whereas the
predicate device detects,
verifies, and performs
qualitative analysis of fetal
anatomies.

Algorithm Methodology
Artificial Intelligence (AI)
Artificial Intelligence (AI)
Same as predicate device.

Automation (Yes or No)
Yes
Yes
Same as predicate device.

Healthcare setting (e.g., hospital, clinic)

Intended Users
Licensed healthcare professionals
Licensed healthcare professionals
Same as predicate device.

The subject device is
embedded in the
ultrasound app, which is
part of the ultrasound
system, whereas, the
predicate device is cloud-
based, stand-alone
software.


IEC 62304:2006 + A1:2015 - Medical device software — Software life cycle processes

ISO 14971:2019 Medical devices — Application of risk management to medical devices

NEMA PS 3.1 - 3.20 (2022d) Digital Imaging and Communications in Medicine (DICOM) Set

IEC 62366-1:2015 + A1:2020 Medical devices — Part 1: Application of usability engineering to
medical devices

ISO 15223-1:2021 Medical devices — Symbols to be used with medical device labels, labelling
and information to be supplied


Modification
Rationale
Testing Methods
Impact Assessment

Improvement and
optimization of Clarius
OB AI’s performance

Re-training of the OB AI
model with new data to
optimize its
performance followed
by internal testing and
a comparison of the
original OB AI model to
the modified OB AI
model (using
performance metrics)
and clinical
performance testing
(verification and
validation).

Improved
performance
metrics of modified
OB AI model with
increased accuracy
and more robust
gestational age
estimates displayed
to users.
Benefit-Risk
Analysis:
Benefits: Improved
performance;
generalization for
diverse cases.
Risks: Overfitting;
unintended bias.
Risk Mitigation:
Proper
regularization
techniques and
cross-validation and
dropout will be
employed to
mitigate overfitting.
Internal testing and
verification will be
conducted to
mitigate unintended
biases.

Modification of model
training methods and
parameters

Internal testing and a
comparison of the
original OB AI model to
the modified OB AI
model (using

Improved
performance
metrics of modified
OB AI model.

Summary of changes to Clarius OB AI per the PCCP:


Benefit-Risk
Analysis:
Benefits: Improved
performance;
generalization for
diverse cases.
Risks: Overfitting;
unintended bias.
Risk Mitigation:
Proper
regularization
techniques and
cross-validation and
dropout will be
employed to
mitigate overfitting.
Internal testing and
verification will be
conducted to
mitigate unintended
biases.

Modification of post-
processing algorithms

Improvement and
optimization of Clarius
OB AI’s performance
and robustness

Internal testing and a
comparison of the
original OB AI model to
the modified OB AI
model (using
performance metrics)
and clinical
performance testing
(verification and
validation).

Improved
performance
metrics of modified
OB AI model.
Benefit-Risk
Analysis:
Benefits: Improved
performance;
generalization for
diverse cases.
Risks: Overfitting;
unintended bias.
Risk Mitigation:
Proper
regularization
techniques and
cross-validation and
dropout will be
employed to
mitigate overfitting.


Internal testing and
verification will be
conducted to
mitigate unintended
biases.

To enable use of Clarius
OB AI on newer models
of the 510(k)-cleared
Clarius Ultrasound
Scanner system

Re-training of the OB AI
model to expand its use
with new data sources
(i.e., new 510(k)-
cleared models of the
Clarius Ultrasound
Scanner), internal
testing, and clinical
performance testing
(verification and
validation) to assesses
its performance with
the new data input
sources.

By accommodating a
wider array of image
geometries and
characteristics with
the use of new
510(k)-cleared
Clarius scanners, the
updated OB AI
model will be better
equipped to handle
different models of
the Clarius
Ultrasound Scanner
used in varying
clinical scenarios.
Benefit-Risk
Analysis:
Benefits: Enhanced
compatibility;
Flexibility for diverse
clinical settings.
Risks: Data skewing
and concept drift.
Risk Mitigation:
Internal testing and
verification datasets
within the intended
patient population
will ensure that data
skewing and
concept drift are
mitigated.


Subject device: CINA-iPE Software
Predicate device: BriefCase Software

CINA-iPE is a radiological computer-
aided triage and notification software
indicated for use in patients
undergoing contrast-enhanced CT
scans (not dedicated CTPA protocol)
for other clinical indications than
pulmonary embolism
suspicion, including at least a part of
the lung. The device is intended to
assist hospital networks and trained
radiologists in workflow triage by
flagging and communicating
suspected positive findings for
incidental Pulmonary Embolism
(iPE). The device is indicated for
adults and transitional adolescents
(18 to 21 years old but treated as
adults).
CINA-iPE uses an artificial
intelligence algorithm to analyze
images and highlight cases with
detected incidental PE on a
standalone application in parallel to
the ongoing standard of care image
interpretation. The user is presented
with notifications for cases with
suspected incidental PE findings.
The device is not designed to detect
PE in subsegmental arteries.
Notifications include compressed
preview images that are meant for
informational purposes only and are
not intended for
diagnostic use beyond notification.
The device does not alter the original
medical image, and it is
not intended to be used as a
diagnostic device.
The results of CINA-iPE
are intended to be used in
conjunction with other patient
information and based on
professional judgment to assist with
triage/prioritization of medical

BriefCase is a radiological computer
aided triage and notification software
indicated for use in the analysis of
contrast-enhanced chest CTs (not
dedicated CTPA protocol) in adults or
transitional adolescents age 18 and
older. The device is intended to assist
hospital networks and appropriately
trained medical specialists in workflow
triage by flagging and communication of
suspect cases of incidental Pulmonary
Embolism (iPE) pathologies. The device
is intended to be used on single energy
exams only.
BriefCase uses an artificial intelligence
algorithm to analyze images and flag
suspect cases on a standalone desktop
application in parallel to the ongoing
standard of care image interpretation.
The user is presented with notifications
for suspect cases. Notifications include
compressed preview images that are
meant for informational purposes only
and not intended for diagnostic use
beyond notification. The device does not
alter the original medical image and is
not intended to be used as a diagnostic
device.
The results of BriefCase are intended to
be used in conjunction with other patient
information and based on their
professional judgment, to assist with
triage/prioritization of medical images.
Notified clinicians are responsible for
viewing full images per the standard of
care.


images. Notified clinicians are
ultimately responsible for reviewing
full images per the standard of care.

Appropriately trained medical specialists

Chest or exams including at least a
part of the lung

Contrast-enhanced CT scans (not
dedicated CTPA protocol) containing
at least a part of the lung

Contrast-enhanced chest CTs (but not
dedicated CTPA protocol)

DICOM information about the
patient, study and current image

No; device does not mark, highlight,
or direct users’ attention to a specific
location in the original image

Artificial intelligence algorithm with
database of images

Presentation of a compressed,
grayscale, unannotated image that is
marked “not for diagnostic use” is
displayed as a preview function.

Presentation of a low-quality,
compressed grayscale preview image
that is captioned “Not for diagnostic use”.

No. The device operates in parallel
with the standard of care, which
remains the default option for all
cases.

-iPE image processing application
- Compatibility of use with the CINA
Platform device (worklist and Image
Viewer) or other medical image
communications device,

-AHS module/Orchestrator (image
acquisition).
- ACS module (image processing).
- Aidoc Worklist application for workflow
integration (worklist and non-diagnostic
basic Image Viewer).


Classification Name
Regulation
Product Code

Common Name: Ultrasound elastography system


Table 1: Lower and upper limits of repeatability for each imaging feature.


Site 1 (North Carolina, USA), n = 35
Site 2 (Unknown State, USA) , n = 31 Site 3
(North Carolina, USA), n = 13
Site 4 (North Carolina, USA), n = 12
Site 5 (Iowa, USA), n = 4
Site 6 (North Carolina, USA), n = 3
Site 7 (North Carolina, USA), n = 2
Site 8 (Unknown State, USA), n = 1
Site 9 (North Carolina, USA), n = 1
Site 10 (Missouri, USA), n = 1

Breast Cancer, n = 23
Lung Cancer, n = 20
Prostate, n = 16
Melanoma, n = 15
Head & Neck Cancer, n = 8
Lymphoma, n = 7
Colorectal Cancer, n = 6
Other, n = 5
Gynecological Cancer, n = 3

Unreported, n = 75
White, n = 25
Hispanic, n = 2
Black, n = 1


TRAQinform IQ
Quantitative Total Extensible

Trained medical professionals including, but
not limited to, radiologists, oncologists,
nuclear medicine physicians, medical imaging
technologists, dosimetrists and physicists.

A software tool to aid in evaluation and
information management of digital medical
images.

TRAQinform IQ is a software only device that
provides quantitative analysis of lesions
identified as Regions of Interest (ROI) in
PET/CT DICOM compliant imaging data
acquired, interpreted, and reported on per local
practice prior to device use.
Clinicians responsible for patient care and for
ordering TRAQinform Reports as an adjunct to
locally reported image interpretation do not
interact directly with the device. Clinicians
responsible for local image interpretation do
not interact with the device and generate their
reporting before and independently of the
TRAQinform Report.
The TRAQinform Report is generated by the
device manufacturer and signed by a U.S.
board certified physician responsible for
supervising central report generation and
qualified to practice nuclear
radiology/medicine. The TRAQinform Report is
for use by trained medical professionals
including but not limited to oncologists, nuclear
radiologists/physicians, medical imaging
technologists, dosimetrists, and physicists.

Quantitative Total Extensible Imaging
(QTxI) is a software tool used to aid in
evaluation and information management
of digital medical images by trained
medical professionals including, but not
limited to, radiologists, oncologists,
nuclear medicine physicians, medical
imaging technologists, dosimetrists and
physicists. The medical modalities of
these medical images include, but are
not limited to, DICOM CT and PET as
supported by ACR/NEMA DICOM 3.0.


TRAQinform IQ
Quantitative Total Extensible Imaging

TRAQinform IQ software contains the
following functionalities:
• Automated matching of ROI between
previously performed CT and PET/CT
DICOM 3.0 volumetric medical
images.
• In order to perform automated
matching of ROI and quantitative
analysis of previously performed CT
and PET/CT DICOM 3.0 volumetric
medical images, the software initially
performs the following functions:
▪ Machine learning skeletal and
anatomic structure
segmentation.
▪ Threshold-based ROI
identification and contouring.
• Automated quantitative analysis to
assess previously performed CT and
PET/CT DICOM 3.0 volumetric
medical images, including: change in
total volume and density of each
identified ROI, and change in
Fludeoxyglucose F18 (FDG) tracer
uptake of each identified ROI among
images.
• Generation of images of the anatomy
combined with spatial and quantitative
information, including computed
classification of quantitative FDG ROI
changes.

QTxI assists in the following indications:
• Receive, store, retrieve, display
and process digital medical
images
• Create, display and print reports
from those images
• Provide medical professionals
with the ability to display,
register, and fuse medical
images
• Identify Regions of Interest (ROIs)
and perform ROI contouring
allowing quantitative/statistical
analysis of full or partial body scans
• Evaluate quantitative change in
ROIs (total or partial body;
individual ROI within individual) with
3D interactive rendering of images
with highlighted ROIs.


For multi-timepoint quantitative analysis,
recommended use is in adult patients 22
years and older with partial or whole-body
PET/CT acquired following administration
of FDG per approved drug prescribing
information and with the second FDG
administration separated from the first by
a period not to exceed 12 months.
For single-timepoint quantitative analysis,
recommended use is in adult patients 22
years and older with partial or whole-body
PET/CT following administration of FDG,
a PSMA targeted PET drug, or a SSTR-
targeted PET drug per approved drug
prescribing information.
Discrepancies between TRAQinform IQ
and local PET/CT reporting have been
investigated and use of TRAQinform IQ
has not been established for binary
patient level progression or non-
progression decisions without
multidisciplinary review. Discrepancies
between TRAQinform IQ and local
PET/CT reporting that could impact
patient care should therefore prompt
consultation with subject matter experts
(for example, in tumor board), with a
patient-centered focus on discrepant
imaging regions and with blinded or
otherwise neutral adjudication regarding
interpretation/classification source.
TRAQinform IQ is not intended to
diagnose any disease, replace the
diagnostic procedures for interpretation of
CT or PET/CT images, recommend any
specific treatment, nor is it intended to
replace the skill and judgement of a
qualified medical professional.


CT and PET/CT images as supported by
ACR/NEMA DICOM 3.0
Radiotracers for multiple timepoints: FDG
Radiotracers for single timepoint: FDG,
PSMA-targeted PET drug, or a SSTR-
targeted PET drug

DICOM, CT, MRI, SPECT and PET as
supported by ACR/NEMA DICOM 3.0
Radiotracers: NaF PET

Secure Cloud Environment with Web
Browser Interface

Automatic Threshold based ROI
identification in bone and anatomical
structures

TRAQinform IQ allows the importation of
physician established contours of ROI

Segmentation of bone to identify skeletal
structures and segmentation of
anatomical structures to identify organs.
Segmentation is driven by machine
learning algorithms.

Atlas based segmentation of bone to identify
skeletal structures

Scan-to-scan registration and ROI
matching allows automatic
quantification of ROIs and assessment
of changes/differences in ROI:
• Changes in ROI shape
• Single ROI splitting into multiple
ROI
• Multiple ROI combining into a
single ROI
• ROI appearing, disappearing,
and re- appearing across
images
Quantitative analysis of functional and
anatomical data for CT and PET/CT
scans, including:
• Volume of each identified
ROI on each image
• Change in volume of each
identified ROI among images
• Total volume of all identified
ROI on each image

Scan-to-scan registration and ROI matching
allows automatic quantification of ROIs and
assessment of changes/differences in ROI.
Quantitative/statistical analysis of full or
partial-body scans


• Change in total volume of all
identified ROI on each image
• Heterogeneity of change in volume
of each identified ROI
For PET scans:
• Tracer uptake (SUVmax,
SUVtotal, SUVmean,
SUVhetero) of each identified
ROI on each image
• Change in tracer uptake
(SUVmax, SUVtotal, SUVmean)
of each identified ROI among
images
• Total tracer uptake (SUVmax,
SUVtotal, SUVmean, SUVhetero)
of all identified ROI on each
image
• Change in total tracer uptake
(SUVmax, SUVtotal, SUVmean,
SUVhetero) of all identified ROI
on each image
• Heterogeneity of change in tracer
uptake (SUVhetero) among
identified ROI
For CT scans:
• Radio density (HUmax,
HUtotal, HUmean, HUhetero)
for each identified ROI on
each image
• Changes in radio density (HUmax,
HUtotal, HUmean) of all identified
ROI on each image
• Change in total radio density
(HUmax, HUtotal, HUmean,
HUhetero) of all identified ROI on
each image
• Heterogeneity of change in radio
density (HUhetero) among
identified ROI
2D Graphical renderings of medical
images, including Maximum Intensity
Projections of the PET and CT, with
overlayed and labeled/color-coded ROI for
inclusion in TRAQinform Reports.
3D labeled contours for ROI, anatomic
structures, and skeletal structures.


510(k)
Product Code
Trade Name
Manufacturer

K183105
LLZ
Mimics Medical
Materialise NV

Acorn 3D Software (AC-SEG-4009); Acorn 3DP Model (AC-101-XX)


Algorithmic with little or no
direct human control

A combination of
algorithmic and direct
human control

Machine Learning
algorithm used to
automatically segment
individual vertebrae

Algorithmic based tools
that do not incorporate
machine learning.

Spinal anatomy:
 Thoracic (T1-T12)
 Lumbar (L1-L5)

Musculoskeletal &
craniomaxillofacial bone:
 Short
 Long
 Flat
 Sesamoid
 Irregular


Device→
Acorn Segmentation
Mimics Medical
D2P

Manufacturer
Mighty Oak Medical
Materialise N.V.
3D Systems

Acorn Segmentation is intended for use as a
software interface and image segmentation
system for the transfer of CT or CTA medical
imaging information to an output file. Acorn
Segmentation is also intended for measuring and
treatment planning. The Acorn Segmentation
output can also be used for the fabrication of
physical replicas of the output file using additive
manufacturing methods, Acorn 3DP Models. The
physical replica can be used for diagnostic
purposes in the field of musculoskeletal and
craniomaxillofacial applications.
Acorn Segmentation and 3DP Models should be
used in conjunction with expert clinical judgment.

Mimics is intended for
use as a software
interface and image
segmentation system
for the transfer of
medical imaging
information to an
output file. Mimics
Medical is also
intended for
measuring and
treatment planning.
The Mimics Medical
output can be used
for the fabrication of
physical replicas of
the output file using
traditional or additive
manufacturing
methods.
The physical replica
can be used for
diagnostic purposes in

The D2P software is
intended for use as a
software interface
and image
segmentation system
for the transfer of
DICOM imaging
information from a
medical scanner to
an output file. It is also
intended as pre‐
operative software for
surgical planning. For
this purpose, the
output file may be
used to produce a
physical replica. The
physical replica is
intended for
adjunctive use along
with other diagnostic
tools and expert
clinical judgement for


the field of
orthopaedic,
maxillofacial and
cardiovascular
applications.
Mimics Medical
should be used in
conjunction with
expert clinical
judgment.

diagnosis, patient
management, and/or
treatment selection of
cardiovascular,
craniofacial,
gastrointestinal,
genitourinary,
neurological, and/or
musculoskeletal
applications.

Acorn Segmentation is image processing software
that allows the user to import, visualize and
segment medical images, check and correct the
segmentations, and create digital 3D models.

D2P is image
processing software
that allows the user to
import, visualize and
segment medical
images, check and
correct the
segmentations, and
create digital 3D
models.

Regulatory Class
Class II
Class II
Class II

Acorn Segmentation is an image processing
software that allows the user to import, visualize
and segment medical images, check and
correct the segmentations, and create digital 3D
models. The models can be used in Acorn
Segmentation for measuring, treatment planning
and producing an output file to be used for
additive manufacturing (3D printing). Acorn
Segmentation is structured as a modular
package. This includes the following functionality:
 Importing medical images in DICOM format
 Viewing images and DICOM data
 Selecting a region of interest using generic
segmentation tools
 Segmenting specific anatomy using
dedicated semi-automatic tools or fully
automatic algorithms
 Verifying and editing a region of interest
 Calculating a digital 3D model and editing
the model
 Measuring on images and 3D models
 Exporting 3D models to third-party packages
Acorn Segmentation contains both machine
learning based auto-segmentation as well as
semi-automatic and manual segmentation tools.
The auto-segmentation tool is only intended to be
used for thoracic and lumbar regions of the spine
(T1-T12 and L1-L5). Semi-automatic and manual
segmentation tools are intended to be used for all
musculoskeletal and craniomaxillofacial
anatomy. The following table provides a definition

Mimics Medical is
image processing
software that allows
the user to import,
visualize and segment
medical images,
check and correct the
segmentations, and
create digital 3D
models. The models
can be used in Mimics
Medical for
measuring, treatment
planning and
producing an output
file to be used for
additive
manufacturing (3D
printing). Mimics
Medical also has
functionality for linking
to third party software
packages. Mimics
Medical is structured
as a modular
package. This includes
the following
functionality:
 Importing
medical images
in DICOM format
and other
formats (such as

The D2P software is a
stand‐alone modular
software package
that provides
advanced
visualization of DICOM
imaging data. This
modular package
includes, but is not
limited to the following
functions:
 DICOM viewer
and analysis
 Automated
segmentation
 Editing and pre‐
printing
 Seamless
integration with
3D Systems
printers
 Seamless
integration with
3D Systems
software
packages
 Seamless
integration with
Virtual Reality
visualization for
non‐diagnostic
use.


and the anatomical location(s) for each tool’s
intended use.
Semi-
Automatic Manual
Automatic
A
Algorithmic combination
Directly
with little or of
controlled
Definition no direct algorithmic
by a
human and direct
human
control human
control
Machine
Learning
Algorithmic
algorithm
based tools Manual
used to
Tool that do not tools
automat-
Type incorporate requiring
ically
machine user input.
segment
learning.
individual
vertebrae
Musculo-
Musculo- skeletal &
skeletal & craniuma-
Spinal cranioma- xillofacial
Anatom- anatomy: xillofacial bone:
ical  Thoracic bone:  Short
Location (T1-T12)  Short  Long
(s)  Lumbar  Long  Flat
(L1-L5)  Flat  Sesa-
 Sesamoid moid
 Irregular  Irreg-
ular
Acorn 3DP Model is an additively manufactured
physical replica of the virtual 3D model
generated in Acorn Segmentation. The output file
from Acorn Segmentation is used to additively
manufacture the Acorn 3DP Model.

BMP, TIFF, JPG
and raw images)
 Viewing images
and DICOM data
 Selecting a
region of interest
using generic
segmentation
tools
 Segmenting
specific anatomy
using dedicated
semi-automatic
tools or fully
automatic
algorithms
 Verifying and
editing a region
of interest
 Calculating a
digital 3D model
and editing the
model
 Measuring on
images and 3D
models
 Exporting
images,
measurements
and 3D models
to third-party
packages
 Planning
treatments
(surgical cuts
etc.) on the 3D
models
 Interfacing with
packages for
Finite Element
Analysis
 Creating Python
scripts to
automate
workflows

Acorn Segmentation is a standalone modular
software package. This module includes, but is
not limited to the following functions:
Image Import
 Importing medical images in DICOM format
Image Processing
 Processing of images with common noise-
reduction filters
 Editing of spatial arrangement of images
Visualization
 Viewing images and DICOM data
Segmentation
 Selecting a region of interest using generic
segmentation tools
 Segmenting specific anatomy using
dedicated semi-automatic tools

Mimics Medical is
structured as a
modular package.
This includes the
following functionality:
Image Import
 Importing
medical images
in DICOM format
and other formats
(such as BMP,
TIFF, JPG and raw
images)
Image Processing
 Processing of
images with
common noise-
reduction filters

D2P is structured as a
modular package.
This includes the
following functionality:
Image Import
 Importing
medical images
in DICOM format
and other
formats (such as
BMP, TIFF, JPG
and raw images)
Image Processing
 Processing of
images with
common noise-
reduction filters


Algorithmic
with little or
no direct
human
control

A
combination
of
algorithmic
and direct
human
control

Machine
Learning
algorithm
used to
automat-
ically
segment
individual
vertebrae

Algorithmic
based tools
that do not
incorporate
machine
learning.

Spinal
anatomy:
 Thoracic
(T1-T12)
 Lumbar
(L1-L5)

Musculo-
skeletal &
cranioma-
xillofacial
bone:
 Short
 Long
 Flat
 Sesamoid
 Irregular

Musculo-
skeletal &
craniuma-
xillofacial
bone:
 Short
 Long
 Flat
 Sesa-
moid
 Irreg-
ular


Device→
Acorn Segmentation
Mimics Medical
D2P

 Segmenting specific vertebral anatomy
using machine-learning-based fully
automatic algorithms
 Verifying and editing a region of interest
Measurement
 Measuring on images and 3D models
Image Export
 Exporting images and 3D models to third-
party packages
3D Models
 Calculating a digital 3D model and editing
the model
 Smoothing a 3D model
 Importing 3D models
Treatment Planning
 Importing of third-party STLs to visualize
planned interactions with anatomy as
represented in DICOM images
Other features
 Using a collection of images and masks as a
training dataset for machine-learning
segmentation algorithm

 Editing of spatial
arrangement of
images
 Processing of
imaging data for
removal of
common artifacts
(e.g. scatter)
Visualization
 Viewing images
and DICOM data
Segmentation
 Selecting a
region of interest
using generic
segmentation
tools
 Segmenting
specific anatomy
using dedicated
semi-automatic
tools or fully
automatic
algorithms
 Verifying and
editing a region
of interest
Measurement
 Measuring on
images and 3D
models
Image Export
 Exporting images,
measurements
and 3D models
to third-party
packages
3D Models
 Calculating a
digital 3D model
and editing the
model
 Wrapping a 3D
model
 Smoothing a 3D
model
 Importing 3D
models
Treatment Planning
 Importing of
third-party STLs to
visualize planned
interactions with
anatomy as
represented in
DICOM images
 Planning
treatments
(surgical cuts
etc.) on the 3D
models

 Editing of spatial
arrangement of
images
Visualization
 Viewing images
and DICOM data
Segmentation
 Selecting a
region of interest
using generic
segmentation
tools
 Segmenting
specific anatomy
using dedicated
semi-automatic
tools or fully
automatic deep
learning tools
 Verifying and
editing a region
of interest
Measurement
 Measuring on
images and 3D
models
Image Export
 Exporting images
and 3D models
to third-party
packages
3D Models
 Calculating a
digital 3D model
and editing the
model
 Smoothing a 3D
model
 Importing 3D
models
Treatment Planning
 Importing of
third-party STLs to
visualize planned
interactions with
anatomy as
represented in
DICOM images
 Planning
treatments
(surgical cuts
etc.) on the 3D
models
Other features
View DICOM images
in VR without
segmentation


Other features
 Interfacing with
packages for
Finite Element
Analysis
 Creating Python
scripts to
automate
workflows

The Acorn Segmentation output can be used for
the fabrication of physical replicas of the output
file using additive manufacturing methods. The
physical replica can be used for diagnostic
purposes in the field of musculoskeletal and
craniomaxillofacial applications.

The Mimics Medical
output can be used
for the fabrication of
physical replicas of
the output file using
traditional or additive
manufacturing
methods. The physical
replica can be used
for diagnostic
purposes in the field of
orthopedic,
maxillofacial and
cardiovascular
applications.

The D2P output file
may be used to
produce a physical
replica. The physical
replica is intended for
adjunctive use along
with other diagnostic
tools and expert
clinical judgement for
diagnosis, patient
management, and/or
treatment selection of
cardiovascular,
craniofacial,
gastrointestinal,
genitourinary,
neurological, and/or
musculoskeletal
applications.


EFAI Bonesuite XR Bone Age Pro Assessment Syst


EFAI Bonesuite XR Bone Age Pro Assessment System (BAP-XR-100)


EFAI BONESUITE XR BONE AGE
PRO ASSESSMENT SYSTEM
(EFAI BAPXR) is designed to view
and quantify bone age from 2D
Posterior Anterior (PA) view of
left-hand radiographs using deep
learning techniques to aid in the
analysis of bone age assessment of
patients between 2 to 16yearsoldfor
pediatric radiologists. The results
should not be relied upon alone by
pediatric radiologists to make
diagnostic decisions. The images
shall be with left hand andwristfully
visible within the field of view, and
shall be without any major bone
destruction, deformity, fracture,
excessive motion, or other major
artifacts.

MEDO ARIA is designed to view
and quantify ultrasound image data
using machine learning techniques
to aid trained medical professionals
in diagnosis of developmental
dysplasia of the hip (DDH). The
device is intended to be used on
neonates and infants, aged 0 to 12
months.

6. Comparison of Technological Characteristics with Predicate Device


● Angle(alphaangle)
● Distanceratio(coverage)


Predicate Trade Name (Primary Predicate is listed first)


Percent positive
or
average and
standard deviation

Body mass index (BMI)
15 to 49 (mean 6±18)

POCUS device (not high-end cardiac ultrasound system)

Bedside ultrasound exam (outside of the echo lab)

Myocardial infarction (MI past \ recent)

Heart failure (HF) or cardiomyopathy (CMP)

Renal dysfunction including chronic kidney disease (CKD)

Ischemic heart disease (IHD including past angioplasty or cardiac
surgery)

Cardiac valve disease (any valve and of any severity)

Clinical characteristics of the AISAP CARIDO V1.0 training data set


Clinical characteristics of the clinical study data set


Type of Magnet
Superconducting
Superconducting
Same

≤ 2.400 ppm @ 50 cm DSV
≤ 0.800 ppm @ 45cm DSV
≤ 0.390 ppm @ 40 cm DSV
≤ 0.110 ppm @ 30 cm DSV
≤ 0.038 ppm @ 20 cm DSV
≤ 0.020 ppm @ 10 cm DSV


Wireless UIH Gating Unit
REF 453564324621
ECG module Ref
989803163121
SpO2 module Ref
989803163111
(alternative)

1 cm: FWMH≤3.2 mm
10 cm: FWHM≤3.6 mm
20 cm: FWHM≤4.8 mm

1 cm: FWMH≤3.2 mm
10 cm: FWHM≤3.6 mm
20cm: FWHM≤4.8 mm


Scatter fraction,
count losses and
randoms
measurement

NECR peak:≥110 kcps
True peak: ≥300 kcps
Scatter Fraction: ≤0.46

maximum value of the bias at
or below necr peak activity
value:≤10%


Table 2 Comparison to Reference device#1


Table 3 Comparison to Reference device#2


Table 4 Comparison to Reference device#3


The contrast recovery coefficient of 17mm spheres is updated from 55% to 65%, while
historical test data shows the test results can meet 65% requirement.
The difference did not raise new safety and effectiveness concerns.

CASS is substantially equivalent to BSSFP and acquires two different phase cycling angle
images and combine them by MIP operation to reduce dark band artifact.
The difference did not raise new safety and effectiveness concerns.

PASS is substantially equivalent to GRE and acquires two different type (SSFP_FID and
SSFP_SE) echoes image and combine them to achieve hybrid contrast image.

In this submission, the noise control term was changed from total variation regularization
to smoothed total variation regularization.
The difference did not raise new safety and effectiveness concerns.

EasyScan of the proposed device supports more body part than that of the predicate
device. In this submission, shoulder and abdomen are included.
The difference did not raise new safety and effectiveness concerns.

QGuard-Imaging is expected for automatic monitoring of MR images for motion artifacts
and providing real-time prompts to assist technicians in image quality control.
The difference did not raise new safety and effectiveness concerns.

EasyCrop is a function that enables automatic cropping of vascular images scanned with
the TOF_3D protocol to simplify the workflow, which allows users to obtain interference-
free vascular MIP images and automatically rotated MIP images with different angles


when the scan is completed and images are generated. After enabling the EasyCrop
function, the original images of TOF_3D will still be saved.
The difference did not raise new safety and effectiveness concerns.

MoCap-Monitoring is a motion monitoring module which is periodic and is inserted into
a pulse sequence. It can realize real-time motion monitoring in imaging scanning and
provides an alert when motion occurs.
The difference did not raise new safety and effectiveness concerns.


Specification
Proposed
Predicate Device:
Reference
Reference

Table 1. Comparison of the Proposed Device, Predicate Device and Reference Devices


To aid in clinical
detection of
pathologic and/or
non-pathological
dental features in
radiographs of
permanent teeth

To aid in clinical
detection of
pathologic
and/or non-
pathological
dental features
in radiographs of
permanent teeth

Velmeni for
Dentists (V4D) is
a concurrent-read,
computer-assisted
detection software
intended to assist
dentist in the
clinical detection
of dental caries,
fillings/
restorations, fixed
prostheses, and
implants in digital
bitewing,
periapical, and
panoramic
radiographs of
permanent teeth
in patients 15
years of age or
older. This device
provides
additional
information for
dentists in
examining
radiographs of
patients’ teeth.
This device is not
intended as a
replacement for a
complete
examination by
the dentist or their
clinical judgment
that considers
other relevant

The Overjet
Caries Assist
(OCA) is a
radiological,
automated,
concurrent read,
computer-
assisted
detection
software intended
to aid in the
detection and
segmentation of
caries on
bitewing and
periapical
radiographs. The
device provides
additional
information for
the dentist to use
in their diagnosis
of tooth surface
suspected of
being carious.
The device is not
intended as a
replacement for
complete
dentist’s review
or their clinical
judgment that
takes into
account other
relevant
information from
the image,

Denti.AI Detect is
a Computer-
Assisted
Detection (CADe)
software device
intended to be
used by dental
professionals,
comprising
dentists and
dental specialists,
while reading
extraoral and
intraoral 2D
dental
radiographs. The
device aims to
assist in
detecting and
highlighting
uncategorized
regions of
interest (ROIs)
within the teeth
area, which
include caries
and periapical
radiolucency, as
a second reader.
The device is
also intended to
aid in the
measurements of
mesial and distal
bone levels
associated with
each tooth. The
device is aimed

Second
Opinion® is a
computer aided
detection
("CADe”)
software to
identify and mark
regions in
relation to
suspected dental
findings which
include Caries,
Discrepancy at
the margin of an
existing
restoration,
Calculus,
Periapical
radiolucency,
Crown (metal,
including zirconia
& non-metal),
Filling (metal &
non- metal), Root
canal, Bridge,
and Implants. It
is designed to aid
dental health
professionals to
review bitewing
and periapical
radiographs of
permanent teeth
in patients 12
years of age or
older as a


Specification
Propos
Predicate Device:
Reference
Reference

information from
the image,
patient history,
or actual in vivo
clinical
assessment.
Final diagnosis
and patient
treatment plans
are the
responsibility of
the dentist.

patient history,
and actual in vivo
clinical
assessment.

to be used with
images from the
patients of 22
years age and
older without
remaining
primary
dentition. The
device is not
intended to
replace a
complete
clinician's review
or clinical
judgment that
considers other
relevant
information from
the image or
patient history.

Patients requiring
dental services,
all sexes, at least
15 years of age,
and with
permanent
dentition

Patients requiring
dental services,
all sexes, at least
12 years of age,
and with
permanent
dentition

Patients
requiring dental
services, all
sexes, at least
22 years of age
or older

Patients
requiring dental
services, all
sexes, at least
12 years of age
or older


Digital
intraoral files
of bitewing
and periapical
radiographs
and digital
extraoral files
of panoramic
radiograph

Digital files of
bitewing and
periapical
radiographs

Intraoral (bitewing
and periapical)
Extraoral
(panoramic)

Caries,
restorations,
fixed
prostheses,
and implants

Caries, margin
discrepancy-MD,
calculus,
periapical
radiolucency-PR,
crown, bridges,
implants, root
canals, and
fillings


View
Lesion-Level Sensitivity( 95% CI1 )

Table 2, Lesion-Level Sensitivity for Caries


False Positives Per Image Mean (95% CI1)


Aided (95% CI)
Unaided (95% CI)
Difference (95% CI)


Picture Archiving and Communications System


Predicate Device
Manufacturer
FDA 510(k)

AmCAD-UT
AmCad BioMed Corporation
K203555


Description
Subject Device
Predicate Device (K203555)

Manufacturer
PIUR Imaging GmbH
AmCad BioMed Corporation

Product Code /
QIH / 21CFR 892.2050
QIH / 21CFR 892.2050

PIUR tUS Infinity is a computer-aided
detection device intended to assist and
support the medical professionals in the
diagnostic workflow of thyroid and
thyroid nodules acquired from FDA-
cleared ultrasound systems, including
image documentation, analysis, and
reporting. The device supports the
physician with additional information
during image review, including
quantification and visualization of
sonographic characteristics of thyroid
nodules.
PIUR tUS Infinity may be used on any
adult patient aged 22 and older,
independent of gender, linguistic and
cultural background, or health status,
unless any of the contraindications
apply.
PIUR tUS Infinity device is not
intended for body contact (including
skin, mucosal membrane, breached or
compromised surfaces, blood path
indirect, tissues, bones, dentin, or
circulation blood).

AmCAD-UT is a Windows-based
computer-aided detection (CADe)
device intended to assist the medical
professionals in analyzing thyroid
ultrasound images, acquired from
FDA-cleared ultrasound systems.
The region of interest (ROI) of a
user-selected thyroid nodule is
defined by users or suggested by an
Al contouring algorithm. After the
initial review of the ultrasound
images by the physicians, the device
further provides detailed information
with quantification and visualization
of sonographic characteristics of
thyroid nodules. The device is
intended for use on ultrasound
images of discrete thyroid nodules
larger than Icm, for which a biopsy
recommendation is required.

Table 4: Substantial Equivalence Comparison Table


Functional
Capability of
Image Processing

The device performs 2D to 3D
reconstruction to generate volumetric
data of a thyroid. User-selected
computer vision and machine learning
algorithm suggested volumes of thyroid
lobe and nodules are visualized to be
confirmed by user. The system provides
a user interface for the user to manually
select sonographic characteristics of
each nodule (hyperechoic foci,
echogenicity, texture, margin,
orientation and anechoic areas) from
which an ACR TI-RADS score will be
computed.

AmCAD-UT analyzes the user-
defined or AI-suggested regions of
interest (ROI) of a user-selected
thyroid nodule for detection and
quantification of sonographic
characteristics (hyperechoic foci,
echogenicity, texture, margin,
orientation and anechoic areas). The
device further provides detailed
information with visualization of
sonographic characteristics of
thyroid nodules.

Device provides quantification and
visualization of sonographic
characteristics based on 3D volumetric
data. Results provide proposals to be
reviewed and confirmed by physicians.

AmCAD-UT is to provide
quantification and visualization of
sonographic characteristics after
physicians’ initial review of the
images.

The device can export volumetric data,
annotated screenshots and reports.
Report can contain both sides of the
patient and includes all relevant
diagnostic information.

The image can be annotated with the
detected sonographic characteristics
and be recorded by the device. The
software also automatically
generates reports given the user
preference inputs in the analysis
process.

Type of Film to be
Digital ultrasound videoclip (cineloop)
Digital ultrasound image

Based on computer vision, machine
learning, pattern recognition and
quantification method.

Based on AI, Statistical Pattern
Recognition and Quantification
method

The ground truth to be established for
performance studies of the device are
annotated data sets labeled by medical
specialists.

The ground truth to be established
for performance studies of the device
is the ROI labeled by a panel of
specialists.

Operating System
Standard PC or review station
Same

Clinical
Thyroid Lesions
Thyroid cancers

Image Type
Ultrasound volume image
Ultrasound Image


Description
Subject Device
Predicate Device (K203555)

DICOM format:
Secondary Capture Image Storage -
1.2.840.10008.5.1.4.1.1.7
Multi-frame Grayscale Byte Secondary
Capture Image Storage -
1.2.840.10008.5.1.4.1.1.7.2
Multi-frame True Color Secondary
Capture Image Storage -
1.2.840.10008.5.1.4.1.1.7.4
Refer to: DICOM-Conformance
Statement-PIUR tUS Infinity

Results from standalone performance
testing of machine learning algorithm
suggested ROIs of user-selected
nodules

Results from standalone performance
testing of AI suggested ROI’s of
user-selected nodules

Infinity Box
Infinity Sensor
Infinity Software

N/A – Predicate is a software only
device (SaMD)

Acquires medical image data from
DICOM compliant Ultrasound imaging
devices

Data / Image
Ultrasound image via DICOM format
Same


Name of contact person:
Mr. Bryan Bhoelai


Medical specialty
Radiology
Radiology
Identical

CFR Reference
21 CFR 892.2050
21 CFR 892.2050
Identical

Medical Image management
and Processing System

Automated Radiological
Image Processing Software

Substantially equivalent,
the subject device has a
more specific common
name because of the
presence of nonadaptive
machine learning
algorithms.

Substantially equivalent,
the subject device has a
more specific product code
because of the presence of
nonadaptive machine
learning algorithms.

The LumiNE US software is
intended for the
visualization of medical
images to provide insights in
anatomy and pathology in
preparation of surgical
treatment. As such, the
software allows for the
conversion of 2D patient
imaging into 3D models, and
for the visualization of 2D
and 3D patient imaging
including Augmented Reality.
When accessing the LumiNE
US software from a wireless
head-mounted display (HMD)
or PC monitor, images
viewed are for informational
purposes only and not
intended for diagnostic use.
The LumiNE US software is
intended for use by a
(neuro)surgeon,
(neuro)surgical resident or a
medical professional that is
qualified by a hospital to
prepare medical imaging for
surgeons. For the conversion
of medical imaging into 3D
models, Magnetic Resonance
Imaging (MRI) and/or
Computed Tomography (CT)
imaging of adult patients are
required. The LumiNE US
software is intended to be
used for visualization in
preparation of surgery, and
not for diagnostic use.
Therefore, segmentation and
visualization of pathology
can only be used for
previously known and pre-
diagnosed conditions.
LumiNE US can only be used
for contrast-enhanced T1 MR
scans (semi-automatic
segmentation of known

VSI HoloMedicine® is a
software device for displaying
digital medical images
acquired from CT, Angio CT,
MRI, CBCT, PET, and SPECT
sources. It is intended to
visualize 3D imaging
holograms of the patient for
pre-operative planning outside
and/or inside the surgical
room.
When accessing VSI
HoloMedicine® from a wireless
head-mounted display (HMD)
or PC monitor, images viewed
are for informational purposes
only and not intended for
diagnostic use. VSI
HoloMedicine® is indicated for
use by qualified healthcare
professionals including
surgeons, radiologists,
physicians, and technologists.


tumor, skin, brain, and
ventricles), or for CT scans
(threshold-based
segmentation).
The LumiNE US MRI T1
tumor segmentation
function can only be used in
case of a single intracranial
contrast enhancing tumor,
diagnosed by a
neuroradiologist or a
neurosurgeon, with a
minimal volume of 2.0 cc (0.1
in3) and a minimal diameter
in any direction of 15 mm
(0.6 inch), and a maximum
volume of 100cc (6.1 in3)
and a maximal diameter in
any direction of 75 mm (3.0
inch).

The device specifically
focuses on visualization of
medical images and
preparation of surgical
treatment, for patients at
the age of 22 or older

The device is a software
which allows for viewing of
DICOM data. Therefore, its
intended use is without any
restrictions regarding patient
population

Different, but no impact on
safety and effectiveness.

• Cloud based storage of
patient data (including
anonymizer) and viewer
• Microsoft HoloLens 2
• Browser based
(universal) mobile device
viewer

• Cloud based storage for
patient data
• Microsoft HoloLens 2
• Streaming hardware hub
to connect image
modalities directly to
Microsoft HoloLens 2
• Anonymizer (for video’s)

• CT
• angio CT
• MRI
• CBCT
• PET CT
• SPECT CT

Substantially equivalent,
the subject device uses MRI
and CT imaging data, while
the predicate device allows
to use a broader range of
imaging modalities. Thus,
the predicate device allows
to view more data types in
the HoloLens.

• DICOM
• 3D formats: STL GLTF
• PDF
• JPEG
• PNG

• DICOM
• 3D formats: OBJ, STL
• PDF
• JPEG
• PNG
• MP4

Substantially equivalent,
both the subject device as
well as the predicate device
support DICOM imaging as
well as 3D format types.
The predicate device
additionally supports data
types which allow video
streaming.

• General manipulation in
HoloLens (grab, move,


• Fusion of 3D objects
with source image data
(web browser and
Microsoft HoloLens 2)
• General manipulation in
HoloLens (grab, move,
zoom, hide, change color
etc.)
• Surgical preparation
tools which allow
markings on 3D models
in Microsoft HoloLens 2
• Sharing (remote and co-
located)

zoom, hide, change color
etc.)
• Surgical Preparation Tools
(draw, measure, etc).
• Sharing (remote, but not
co-located).

• Both the predicate
device and Lumi enable
marking on 3D models
in HMD for planning
purposes.
• Lumi allows for saving
revisions on 3D models
(both web and
Microsoft HoloLens 2)
• Lumi allows validation
of 3D models.

Communication
between headset and
computer

• Web browser (computer)
and Microsoft HoloLens 2
connect to cloud
environment.
• Wireless encrypted
connection with Microsoft
HoloLens 2. Hardware to
stream data from image
acquisition system directly
to Microsoft HoloLens 2.

Substantially equivalent,
VSI uses additional
hardware to connect to
image acquisition systems.
Communication for both
the subject as well as the
predicate device is wireless,
and data encrypted.

This viewing feature enables
the display of CT, MRI, CBCT,
Angio CT, PET CT and SPECT CT
images into axial, coronal and
sagittal orientations

Substantially equivalent for
CT and MRI.

• 3D volume rendering in
web browser.
• Option to create manual
segmentation to
visualize results in
Microsoft HoloLens 2.

3D perspective views of CT,
MRI, CBCT, Angio CT, PET CT
and SPECT CT images sets that
have been transformed into
volumes. It also provides
presets to enable users to alter
the visualization parameters
of the 3D views to highlight
features.

Different, but no impact on
safety and effectiveness.
Both the subject as well as
predicate device present 2D
imaging information in 3D,
however, the predicate
device does not include
image segmentation
functionality.

Creating and saving of 3D
models and marks thereon
on HMD for planning
purposes.

Saving and loading
configurations of medical
images, marks, and 3D models
on HMD.
Ability to save and load
combinations and
arrangement of objects
displayed in the 3D space on
HoloLens for planning
purposes.
Possibility to create
annotation like drawings.

Web browser (computer) and
Microsoft HoloLens 2 connect
via wireless encrypted


Software verification and
validation was performed
and demonstrates that the
LumiNE US software
performs as intended in the
specified use conditions.
Documentation is provided
as recommended by FDA’s
Guidance for Industry and
FDA Staff ‘Content of
Premarket Submissions for
Device Software Functions’.
In addition, non-clinical
testing was performed to
evaluate the performance of
the semi-automated
segmentation algorithm
against manual
segmentation data.
Visual quality testing on
software using the Microsoft
HoloLens 2 Head-Mounted
Display has been performed.
Non-clinical and clinical data
demonstrate that the
LumiNE US software is as
safe, as effective, and
performs as well as the
legally marketed device
predicate.

Visual quality testing on
software using the Microsoft
HoloLens Headset has been
performed.
Non-clinical and clinical data
demonstrate that VSI
Holomedicine is as safe, as
effective, and performs as well
as the legally marketed device
predicate. Software
verification and validation
demonstrate that the VSI
Holomedicine should perform
as intended in the specified
use conditions.


Characteristic
Proposed Device
Predicate Device
Significant Differences

Preoperative planning
software for surgery

The Preview Shoulder
software is intended to be

the predicate device as noted in the following table.


used as a tool for
orthopedic surgeons to
develop pre-operative
shoulder plans based on
a patient CT imaging
study.
The import process allows
the user to select a
DICOM CT scan series
from any location that the
user’s computer sees as
an available file source.
3D digital representations
of various implant models
are available in the
planning software.
Preview Shoulder allows
the user to digitally
perform the surgical
planning by showing a
representation of the
patient’s shoulder
anatomy as a 3D model
and allows the surgeon to
place the implant in the
patient’s anatomy.
The software allows the
surgeon to generate a
report, detailing the output
of the planning activity.
Experience in usage and
a clinical assessment are
necessary for a proper
use of the software. It is
to be used for adult
patients only and should
not be used for diagnostic
purposes.

Preview Shoulder allows
the surgeon to perform
the pre-surgical planning
for the following
subspeciality:
Upper Limb: Total
Shoulder Replacement

Type of Use
Prescription Only
Prescription Only


The software is installed
and started from the
user’s computer.

Receives medical images
from various sources
locally available to the
user’s computer.
Preview Shoulder does
not communicate directly
to a PACS system.

The software processes
the CT image, which
allows the implant to be
overlapped/ placed in
both the original scan
images and/or the 3D
model reconstruction of
the bone for surgical
planning.

Similar
Post-processing algorithm
is added to further refine
the 3D mesh quality.
Algorithm is added to
calculate humerus-side
features used for implant
selection, placement, and
pre-surgical planning.

The software allows the
implant rendering to be
overlapped/placed in the
3D model reconstruction
of the bone that results
from the processed CT
image(s).
The software facilitates
the placement and
rendering of scapula and
humerus implants for
anatomic partial or total
shoulder arthroplasty and
reverse total shoulder
arthroplasty.

The software allows the
implant rendering to be
overlapped/placed in the
3D model reconstruction
of the bone that results
from the processed CT
image(s).
The software facilitates
the placement and
rendering of scapula
implants for anatomic
partial or total shoulder
arthroplasty and reverse
total shoulder
arthroplasty.

Similar
Humerus implants are
added to implant planning
library.

Support for
digital
prosthetic
materials
provided by
the
manufacturers


Human
intervention for
image
interpretation

Ability to add
additional
modules when
available


Classification Name:
Magnetic Resonance Diagnostic Device

Regulation Number:
90-LNH (Per 21 CFR § 892.1000)

Vantage Fortian / Orian 1.5T, MRT-1550, V9.0 with AiCE
Reconstruction Processing Unit for MR


System
Predicate Device
Reference Device

Vantage Fortian/Orian 1.5T, MRT-1550, V8.0 with
AiCE Reconstruction Processing Unit for MR

Vantage Galan 3T, MRT-1550, V9.0 with AiCE
Reconstruction Processing Unit for MR

Marketed By
Canon Medical Systems USA, Inc.
Canon Medical Systems USA, Inc.

Clearance Date
October 25, 2022
August 30, 2023


Item
Subject Device:
Predicate Device:
Notes

Vantage Fortian/Orian 1.5T,
Vantage Fortian/Orian 1.5T,

with AiCE Reconstruction
with AiCE Reconstruction

Processing Unit for MR
Processing Unit for MR

Operational Modes
Normal and 1st Operating Mode
Normal and 1st Operating Mode
Same

Allows screen access to 1st level
operating mode

4W/kg for whole body (1st
operating mode specified in IEC
60601-2-33:
2010+A1:2013+A2:2015)

Potential emergency
condition and means
provided for shutdown

Shutdown by Emergency Ramp
Down Unit for collision hazard for
ferromagnetic objects


883SantaCruz Ave,Suite205
Menlo Park, CA94025UnitedStates

Applicant ContactTelephone:
(925) 324-8467

611GatewayBlvd, Ste120
South SanFrancisco,CA 94080 UnitedStates

Correspondent Contact:
Mr.Jared Seehafer

Correspondent ContactTelephone:
(415) 638-9554

Classification Name:
System, ImageProcessing, Radiological

Predicate #:K223623
Predicate TradeName: SubtleMR
Predicate Manufacturer:Subtle Medical


AiMIFYimplementsanimage
enhancementalgorithmusing
convolutionalneuralnetworkbased
filtering.Themodelperformsnon-linear
scalingofthecontrastuptakebetweenthe
pre-andpost-contrastimagestoimprove
thevisualizationoftheareasinthebrain
thathaveabsorbedthecontrastmaterial.

AiMIFYprocessestwoinputimages(T1
pre-contrastandT1post-contrast)and
outputsasingleimagewithahigher
relativeCNR.

Table 2.Summary ofTechnological CharacteristicsComparison


ProprietaryName
EFAI CARDIOSUITE CTA ACUTE AORTIC SYN


EFAI CARDIOSUITE CTA ACUTE AORTIC SYNDROME
ASSESSMENTSYSTEM


EFAI CARDIOSUITE CTA
ACUTE AORTIC SYNDROME
ASSESSMENT SYSTEM (EFAI

BriefCase is a radiological
computer-aided triage and notification
software indicated for use in the analysis


AASCTA) is a radiological
computer aided triage and
notification software indicated for
use in the analysis of chest or
chest-abdomen CTA in adults aged
22 and older. The device is
intended to assisthospitalnetworks
and appropriately trained medical
specialists in workflow triage by
flagging and communicating
suspected positive cases of aortic
dissection(AD)oraorticintramural
hematoma(IMH)pathology.
EFAI AASCTA uses an artificial
intelligence algorithm to identify
suspected findings. It makes
case-level output available to a
PACS/workstation for worklist
prioritization or triage. EFAI
AASCTA is not intended to direct
attention to specific portions or
anomalies of an image. Its results
are not intended to be used on a
stand-alone basis for clinical
decision-making nor is it intended
to rule out AAS or otherwise
preclude clinical assessment of
computed tomographyangiography
cases.

of CT exams with contrast (CTA and CT
with contrast) that include the chest in
adults or transitional adolescents aged 18
and older. Thedeviceisintendedtoassist
hospital networks and appropriately
trained medical specialists in workflow
triage by flagging and communicating
suspected positive cases of aortic
dissection (AD) pathology. BriefCase
uses an artificial intelligencealgorithmto
analyze images and highlight cases with
detected findings on a standalone
application in parallel to the ongoing
standard ofcareimageinterpretation.The
user is presented with notifications for
cases with suspected findings.
Notifications include compressed
preview images that are meant for
informational purposes only and not
intended for diagnostic use beyond
notification. The device doesnotalterthe
original medical image and is not
intended to be used as a diagnostic
device. The results of BriefCase are
intended to be used in conjunction with
other patient information and based on
the user's professional judgment, toassist
with triage/prioritization of medical
images. Notified clinicians are
responsible for viewing full images per
thestandardofcare.

Hospital networks and
appropriately trained medical
specialists

Hospital networks and appropriately
trainedmedicalspecialists

CT exams with contrast (CTA and CT
withcontrast)thatincludethechest

Notification-only
(notification
alerts),parallel
workflowtool


Specification
Subject Device
Predicate Device
Comparison
Impact to Safety &

Device name
Syngo Carbon Enterprise Access
Syngo Carbon Space VA30A
New version of the

Manufacturer
Siemens Healthcare GmbH
Siemens Healthcare GmbH
Same

Syngo Carbon Enterprise Access is
indicated for display and rendering of
medical data within healthcare
institutions.

Syngo Carbon Space is a software
intended to display medical data and to
support the review and analysis of
medical images by trained medical
professionals.
Syngo Carbon Space "Diagnostic
Workspace" is indicated for display,
rendering, post-processing of medical
data (mostly medical images) within
healthcare institutions, for example, in
the field of Radiology, Nuclear
Medicine and Cardiology.
Syngo Carbon Space "Physician
Access" is indicated for display and
rendering of medical data within
healthcare institutions.


Syngo Carbon Enterprise Access is
not intended for the diagnosis of
digital mammography images and
digital pathology reading.
Syngo Carbon Enterprise Access is
not intended to be used for diagnostic
purpose on mobile devices in the
United States of America (USA).
Syngo Carbon Enterprise Access is
not intended to be used as a sole basis
for clinical decisions.

Syngo Carbon Space "Diagnostic
Workspace" is not intended for
diagnosis of digital mammography
images.
Syngo Carbon Space "Diagnostic
Workspace" is not intended to be used
as a sole basis for clinical decisions.
Syngo Carbon Space "Physician
Access" is not intended for diagnosis
of digital mammography images.
Syngo Carbon Space "Physician
Access" is not intended to be used for
diagnostic purpose on mobile devices
in the United States of America
(USA).
Syngo Carbon Space "Physician
Access" is not intended to be used as
a sole basis for clinical decisions.

Syngo Carbon Enterprise Access is
based on a client-server architecture

Syngo Carbon Space is based on a
client-server architecture

Standard network protocols like
TCP/IP and standard communication
protocol including DICOM (2016a)
and non-DICOM objects. Supports
interfacing with HL7 (v2.5 / v2.3.1 /
v2.3 / FHIR R4).


• MPR: MPR
• MIP: MIP,
• MinIP View
• AVG
• MED
• Invert Image

• MPR: MPR, MPR Thick,
MPR/MPR*
• MIP: MIP, MIP Thin
• MinIP View
• VRT*: Plain VRT, Adapt VRT,
VRT Thin, Cinematic VRT
• Fused View *
• Invert Image
* available in in Diagnostic
Workspace only

The additional AVG
and MED are non
AI/ML Algorithms

This differences
between the
predicate device and
the subject device
doesn’t impact the
safety and
effectiveness of the
subject device as the
necessary measures
taken


Measurement,
Evaluation/Inte
rpretation
Tools

• Distance (Distance line)
• Pixel Lens
• Angle
• Elipse Annotation
• Polygon
• Freehand
• Capture

• Distance (Distance line, Distance
Polyline)
• Angle and Angle on stack*
• 2D ROI (Circle, Freehand,
Polygonal, Auto Contour) *
• 3D VOI (Sphere, Freehand) *
• Pixel Lens
• Ranges (Parallel, Radial, Radial
Sliced, Curved, Spine) *
• Lesion Quantification*
• Assisted Perpendicular Tool*
• Automatic Organ Segmentation*
• Interactive Tissue Segmentation*
• Time Curve, Time ROI*
• SUV Measurement*
• Automatic Anatomy Labeling
(rib, spine) *
• Next Study/Previous
Study/Nearline study*
• Change Geometry*
• Snapshot
• CT Lung Change*
• MR General Reading*
• Alpha Blending*
* Available in in Diagnostic
Workspace only

The tool set in the
subject device is
enhanced.


Supported D
ICO
M image object display: D
ICO
M image object di
splay:

•
Secondary capture objects
•
Secondary capture
objects

D
ICO
M non-image object display: D
ICO
M non-image obje
ct disp

N
on-
DICOM file display: N
on-
DICOM file displa
y:

•
Images: BMP, GIF, JPEG
•
Images: BMP, GIF
, JPEG

(JFIF), JPEG 2000, JPEG-LE,
(JFIF), JPEG 2000,
JPEG-

JPEG-LS, PCX, PNG, PNM,
JPEG-LS, PCX, PN
G, PN

•
Video: FLV, H.264, H.265,
•
Video: FLV, H.264
, H.26

INDEO2, INDEO3, INDEO4,
INDEO2, INDEO3
, INDE


Specification
Subject Device
Predicate Device
Comparison
Impact to Safety &

VP8, VP9, WMV1, WMV2,
WMV3
Text Documents: CDA (XML), PDF

VP8, VP9, WMV1, WMV2,
WMV3
• Text Documents: CDA (XML),
PDF


Client – Mobile device
iPadOS ≥ 14, Safari web browser

None
Syngo Carbon Enterprise Access is a
pure viewing software and it has no
influence on the image acquisition
devices.

None
Syngo Carbon Space is a pure
viewing and/or post-processing
software and it has no influence on
the image acquisition devices.

None
No automated diagnostic
interpretation capabilities like CAD
are included. All image data are to be
interpreted by trained personnel.

Clinical
condition the
device is
intended to
diagnose, treat,
or manage

No limitation on the clinical condition
of the patient.

No limitation concerning the patient
population (e.g., age, weight, health,
condition)

Site of the body
the device is
intended to be
used

No limitation concerning region of
body or tissue type


Syngo Carbon Enterprise Access is
used in departmental environments
within healthcare institutions.
For reading images certified monitors
are required (e.g., medical diagnostic
displays).

Syngo Carbon Space “Diagnostic
Workspace” is used in Radiology,
Nuclear Medicine and Cardiology
environments (e.g., darkened/ shaded
rooms).
Syngo Carbon Space "Physician
Access" is used in departmental
environments within healthcare
institutions.
For reading images certified monitors
are required (e.g., medical diagnostic
displays).

Device Type
Software application
Software application
Same

Syngo Carbon Enterprise Access is
based on a client-server architecture

Syngo Carbon Space is based on a
client-server architecture

N/A – this is a browser based
application

Client installation is prevented
automatically in case if the system
doesn’t have the recommended
operating system. Also during the
launch of the client every time, the
compatibility to the server version is
checked and request to
update/upgrade to client in case of
mismatch.


Specification
Subject Device
Predicate Device
Comparison
Impact to Safety &

• User access control
• Audit Trail
• Documentation of system
security information, Network
traffic & Firewall control
• Support of virus / malware
protection
• System Hardening (OS level and
Network level)

Hardware is not understood as part of
the medical device but needs to
comply with the minimum
requirements as specified by Syngo
Carbon Enterprise Access

Hardware is not understood as part of
the medical device but needs to
comply with the minimum
requirements as specified by Syngo
Carbon Space.

Yes, with reduced color palette,
clearer structure, and text labels on
icons. Floating panels increases the
user friendliness as the user can move
the panels wherever they are
convenient with.


• Search, browse & open data for
display from syngo.share core &
remote DICOM nodes
• Search, browse & open data for
display from external XDS(-I)
repository)
• Archive functionality (upload
medical data to syngo.share core
for archive)
• Document properties functions
(metadata modification and
tagging)
• Correct & re-arrange functions
• Restore (trigger fetch from
archive) functions
• Distribution, export & sharing
functions
• Inbox - access to medical data
shared by other users

• Search, browse & open data for
display from syngo.share core &
remote DICOM nodes
• Search, browse & open data for
display from external XDS(-I)
repository) **
• Archive functionality (upload
medical data to syngo.share core
for archive)
• Document properties functions
(metadata modification and
tagging)
• Correct & re-arrange functions
• Restore (trigger fetch from
archive) functions
• Distribution, export & sharing
functions
• Inbox - access to medical data
shared by other users **
**available in Physician Access only


Yes, with a fast overview of the
displayed and not displayed data
(series, images) of the loaded studies,
quickly identify the relevant
series/images for reading, and bring
data (timepoints/series/images) into
display in an efficient manner
(Drag&Drop).
Study / Timepoints are marked with
individual colors for better
identification.

Yes, with a fast overview of the
displayed and not displayed data
(series, images) of the loaded studies,
identify not yet seen series/images*,
quickly identify the relevant
series/images for reading, and bring
data (timepoints/series/images) into
display in an efficient manner
(Drag&Drop).
Study / Timepoints are marked with
individual colors for better
identification.
The Series Navigator is called
Document Preview for Physician
Access.
* available in in Diagnostic
Workspace only

Findings panel collects
measurements, annotations, and
graphical objects. Additionally, the
user can create new findings, edit
findings. It also allows creation of
automatic findings.


No dedicated report creation
functionality supported in Syngo
Carbon Enterprise Access

No dedicated report creation
functionality supported in Syngo
Carbon Space.
Structured findings can be
automatically transferred to external
third-party reporting system via FHIR
interface for creation of structured
report content [e.g. (Powerscribe [by
Nuance], SmartReports [by Smart
Reporting)]

Not applicable since Syngo Carbon
Enterprise Access does not create data
or images that is transferred/stored.

Diagnostic Workspace:
Syngo Carbon Space Diagnostic
Workspace does not store data or
images.
Created results for a study (e.g.
DICOM PR, SR objects) are stored in
syngo.share core in context of the
original study. syngo.share core is
responsible for long term archiving of
the original study and created results.
Physician Access:
Not applicable since Syngo Carbon
Space Physician Access does not
create data or images that is
transferred/stored.


Provides access to patient history –
other studies of patient stored in
remote DICOM nodes. Also provides
a study content preview along with
access to nearline studies and prior
RIS reports

Provides access to patient history –
other studies of patient stored in
syngo.share core or
remote DICOM nodes. Also provides
a study content preview Along with
access to nearline studies and prior
RIS reports

Optimization &
preparation/
Spatial
Operation tools

• Image Preview
• Zoom/Pan
• Synch, Align
• Windowing
• Flip (Horizontal, Vertical)
• Blow-up
• Scroll
• Movie
• Magnifier

• Image Preview
• Zoom/Pan
• Fit to Segment*, Fit to
Acquisition Size*
• Synch, Align
• Windowing
• Rotate (2D image or 3D
Volume*)
• Flip (Horizontal, Vertical)
• Shutters On/Off*
• Blow-up
• Scroll
• Movie
• Clipping*
• Punching and Masking*
• Magnifier
* available in in Diagnostic
Workspace only


Specification
Subject Device
Predicate Device
Comparison
Impact to Safety &

• Arrow*
• Marker*
• Text
* available in in Diagnostic
Workspace only

Diagnostic workspace:
Provides printing functionality with
able to review, modify the images
along with selecting the print sheet
format exposing then the DICOM
printer.
Also, able to monitor the printing
status and retry a printing task, if
needed.
Note
• DICOM printer must be configured as DICOM
nodes
• Grayscale & color printing is supported
Phyisican Access:
Provides printing functionality on a
paper printer.

Yes, with search, indexing, filtering,
library function and document
collections.


Prior FFDM Unsupported Unsupported Unsupported Supported Unsupported

DBT Unsupported Unsupported Unsupported Unsupported Unsupported

2DSM Unsupported Unsupported Unsupported Unsupported Unsupported


Predicate device (MammoScreen 2)
Subject device (MammoScreen 3)

MammoScreen 2 is a concurrent
reading and reporting aid for
physicians interpreting screening
mammograms. It is intended for use
with compatible full-field digital
mammography and digital breast
tomosynthesis systems.
Output of the device includes marks
of findings on mammograms along
with their type and level of suspicion
scores. The level of suspicion score is
expressed at the finding level, for
each breast, and overall for the
mammogram.

MammoScreen 3 is a concurrent
reading and reporting aid for
physicians interpreting screening
mammograms. It is intended for use
with compatible full-field digital
mammography and digital breast
tomosynthesis systems. The device
can also use compatible prior
examinations in the analysis.
Output of the device includes
graphical marks of findings as soft-
tissue lesions or calcifications on
mammograms along with their level of
suspicion scores. The lesion type is
characterized as mass/asymmetry,
distortion, or calcifications for each
detected finding. The level of
suspicion score is expressed at the
finding level, for each breast, and
overall for the mammogram.
The location of findings, including
quadrant, depth, and distance from the
nipple, is also provided. This
adjunctive information is intended to
assist interpreting physicians during
reporting.
Patient management decisions should
not be made solely based on the
analysis by MammoScreen 3.


Physicians qualified to read
mammograms.

Design
Software-only device
Software-only device


MammoScreen 2 is powered by
artificial intelligence/machine
learning-based software algorithm

MammoScreen 2 outputs a level of
suspicion at the finding, breast and
case level.

For each detected finding
MammoScreen 2 classifies them as
soft tissue lesion or calcifications.

For each detected finding
MammoScreen 3 classifies them as
mass/asymmetry, distortion or
calcifications.

questions of safety and effectiveness than the previous version.


MammoScreen 2 doesn’t provide a
localization.

For each finding MammoScreen 3
provides a quadrant, a depth and a
distance to the nipple.

FFDM or 2DSM & DBT or FFDM
& DBT, with an optional prior
(FFDM or 2DSM & DBT) expect
for the former.


Minimum: 32
Maximum: 93
Mean: 58
25th percentile: 49
75th percentile: 65

White: 37%
Black: 16%
Asian: 18%
American Indian / Alaska native: 0.8%
Native Hawaiian / Pacific islander: 0.2%
Unspecified: 28%

information about the test population is provided in the table below:


) submission Mamm
oScreen 3
Page 8 of
13

positive cases negative cases (95% CI) (95% CI) (95% CI)


Results are summarized in the following table:


SK U-Tower, 9 Seongnam-daero, Bundang-gu, Seongnam-si, Gyeonggi-do, 13558
Republic of Korea

Hannah Taggart, MS
Empirical Technologies
1-719-457-1152
htaggart@empiricaltech.com

Date Summary was Prepared:
June 25, 2024

Trade or Proprietary Name:
Hyper Insight - ICH

Radiological Computer-Assisted Triage And Notification Software

Classification & Regulation #:
Class II per 21 CFR §892.2080


510k Number
Trade or Proprietary or Model Name
Manufacturer
Product Code
Predicate Type

K193658
Viz ICH
Viz.ai, Inc.
QAS
Primary


Hyper Insight - ICH is a notification-only workflo
w tool for trained clinicians to identify patients' br
ain CT images and share them with medical speci
alists in parallel with standard patient care workflo
w. Hyper Insight - ICH uses deep learning-based
AI algorithms to analyze images to find suspected
intracranial hemorrhage and notifies and shares the
findings to medical specialists. Identification of im
ages with suspected intracranial hemorrhage is for
notification purposes only, not diagnostic purposes.
In particular, this medical device analyzes non-cont
rast brain CT images, and if a suspected intracrani
al hemorrhage is identified, it sends a notification
to medical specialists, who are advised to review t
hese images. Images may be previewed through th
e mobile app but are for informational purposes o
nly and are not intended to be used for diagnostic
purposes other than notifications and previews. T
he medical specialist who received the notification
is responsible for reading the image in a diagnosti
c viewer.
Hyper Insight - ICH is limited to the purpose of
analysis of image data and should not be used as
a substitute for a full patient assessment or relied
upon to make or confirm a diagnosis.

Viz ICH is a notification-only, parallel workflow tool f
or use by hospital networks and trained clinicians to id
entify and communicate images of specific patients to a
specialist, independent of standard of care workflow.
Viz ICH uses an artificial intelligence algorithm to anal
yze images for findings suggestive of a prespecified cli
nical condition and to notify an appropriate medical spe
cialist of these findings in parallel to standard of care i
mage interpretation. Identification of suspected findings
is not for diagnostic use beyond notification. Specificall
y, the device analyzes non-contrast CT images of the b
rain acquired in the acute setting and sends notification
s to a neurovascular or neurosurgical specialist that a s
uspected intracranial hemorrhage has been identified and
recommends review of those images. Images can be p
reviewed through a mobile application. Images that are
previewed through the mobile application may be comp
ressed and are for informational purposes only and not
intended for diagnostic use beyond notification. Notified
clinicians are responsible for viewing non-compressed i
mages on a diagnostic viewer and engaging in appropri
ate patient evaluation and relevant discussion with a tre
ating physician before making care-related decisions or
requests. Viz ICH is limited to analysis of imaging dat
a and should not be used in-lieu of full patient evaluati
on or relied upon to make or confirm diagnosis. Viz I
CH is contraindicated for analyzing non-contrast CT sca
ns that are acquired on scanners from manufacturers ot
her than General Electric (GE) or its subsidiaries (i.e.
GE Healthcare). This contraindication applies to NCCT
scans that conform to all applicable Patient Inclusion C
riteria, are of adequate technical image quality, and wo
uld otherwise be expected to be analyzed by the device
for a suspected ICH.

Environment of use
Clinical/Hospital Environment
Clinical/Hospital Environment

Radiologist, emergency medicine physicians, neuros
urgeons, neurologist

Radiologist, emergency medicine physicians, neurosurgeo
ns, neurologist

Clinical Condition
Acute Intercranial Hemorrhage (ICH)
Intercranial Hemorrhage (ICH)


Independent of
standard of care
workflow

Transfer, store, and
process DICOM im
ages

Acquires medical image data from DICOM compli
ant imaging devices and modalities.

Acquires medical image data from DICOM compliant i
maging devices and modalities.

Preview Images
Initial assessment; non-diagnostic
Initial assessment; non-diagnostic

DICOM Information about the patient, study and c
urrent image.

DICOM Information about the patient, study and curren
t image.

Image viewing and
manipulation
(window,pan,zoom)

AI findings (Suspected ICH or Case Processed)

Results Receiver
PACS/Workstation
PACS/Workstation


Age Range (years)
Subject Device
K193658

Sensitivity Specificity Sensitivity Specificity

Age Subgroup Performance Data Comparison


Gender Subgroup Performance Data Comparison


Slice Thickness Subgroup Performance Data Comparison


Clinical Site
Sensitivity [95% Cl]
Specificity [95% Cl]

As part of a secondary analysis, the company stratified the device performance by various confounding variables:


Gender
Sensitivity [95% Cl]
Specificity [95% Cl]


Race
Sensitivity [95% Cl]
Specificity [95% Cl]

Native
Hawaiian or
Other Pacific
Islander


Performance Stratified by Slice Thickness

Slice Thickness
Sensitivity [95% Cl]
Specificity [95% Cl]


Performance Stratified by CT scanner’s manufacturer

CT scanner’s manufacturer
Sensitivity [95% Cl]
Specificity [95% Cl]


Displays the patient geometry and structures in three
dimensions, with the possibility to rotate the patient
image. If available, the dose distribution and beam
modifiers are shown as well.

The process of replanning the treatment for a patient,
based on information about e.g. patient geometry,
biology and dose delivery acquired during treatment.

Modeling of the radiation beam using a limited set of
measurements on the clinical beam for commissioning
treatment machines to make them available for
treatment planning.

Definition of beam orientations, apertures and various
beam modifiers in order to manually create a treatment
plan.

Manual or automatic definition of isocenter, selection of
treatment unit from the set of commissioned treatment
machines, and specification of gantry/couch/collimator
angles.

Displays the beam’s eye view of the patient structures,
fluence and beam modifier settings for any beam.

Tools for planning of HDR brachytherapy treatments.
Includes channel reconstruction and optimization and
editing of dwell times.

CyberKnife planning is completely integrated in
RayStation. This includes optimization of high quality
treatment plans collimated with MLC, fixed cones or iris
cones, as well as support for all CyberKnife Synchrony
techniques for target tracking and real time motion
synchronization.

Establishing a point-to-point mapping between two
images using a deformation model. Used for mapping of
dose and structures between images.

Export of images, structure set, plan, and dose according
to the DICOM RT standard.