Fully-automated
Semi-Automated and manual

Yes. Prior segmentation results
are provided numerically.

Quantitative Analysis of
Regions-of-Interest

Yes. Including ROI Volumes, and
histogram statistics of optional
quantitative maps.

Results displayed in tabular and
graphical formats.

Yes, including single and multi-
compartment diffusion models.

Automated fusion of segmentation
results and parametric maps.

Automated fusion of
segmentation results.

Display/measurement data can be
viewed, accepted, or rejected by a
physician.

Hospital, Clinic, Imaging Center,
Medical Offices

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Primary Predicate Device: SubtleMR – K191688 by Subtle Medical, Inc., Class II, CFR

892.2050, classification with product code LLZ.

SwiftMR, is software used as a Medical Device (SaMD) consisting of a software algorithm

that enhances images taken by MRI scanners. The device only processes DICOM

images for the end User and is intended to be used by radiology technologists in an

The device’s inputs are standard of care MRI images in DICOM format. The deep

learning algorithm produces enhanced images as outputs with reduced noise and

increased sharpness in DICOM format. The device applies both denoising and sharpness


Item
Predicate Device
Subject Device
Differences

Software device that
operates on off-the-
shelf computer
hardware

Differences are basically in the
computer operating system but also
may have some differences in the
processor speeds, amount of RAM
memory, monitors, and hard drive
space requirements. However, the
subject device and the predicate
device are substantially equivalent

and is equivalent in performance to existing legally marketed devices.


in the areas of technical
characteristics, general function,
application, and intended use and
the computer platform differences
do not raise any new potential
safety risks. Therefore, it is our
determination that there is “No
impact on safety or efficacy” and
there are no new potential or
increased safety risks.

The software processes
DICOM
compliant image data

Modalities
MRI
Same as predicate
No Difference

The predicate software
implements an image
enhancement algorithm
using convolutional
neural network-based
filtering. Original
images are enhanced
by running through a
cascade of
filter banks, where
thresholding and
scaling operations are
applied. Separate
neural network-based
filters are obtained for
noise reduction and
sharpness increase.
The parameters of the
filters were obtained
through an image
guided optimization
process.

SwiftMR implements an
image enhancement
algorithm using
convolutional
neural network-based
filtering. Original
images are enhanced
by running through a
cascade of
filter banks, where
thresholding and
scaling operations are
applied. Neural
network-based filters
that simultaneously
perform noise reduction
and sharpness
increase functions are
obtained. The
parameters of the filters
were obtained through
an image guided
optimization process.

The only difference is in how the
neural network-based filter exists.
As for the predicate device, there
are separate filters for noise
reduction and sharpness increase.
On the other hand, there are neural
network-based filters that
simultaneously perform both
functions for the subject device.
However, the same functions, which
are noise reduction and sharpness
increase, are applied by the filters.
Therefore, the difference does not
raise new questions of safety or
effectiveness.

The predicate software
operates on DICOM
files on the file system,
enhances the images,
and stores the
enhanced images on
the file system. The
receipt of original
DICOM image files and
delivery of enhanced
images as DICOM files
depends on other
software systems.
Enhanced images co-
exist with the original
images.


GE Medical Systems, LLC (GE Healthcare)
3200 N. Grandview Blvd.,
Waukesha, WI 53188
USA

Brian R. Zielski
Regulatory Affairs Leader
Phone: 262-227-3596
Email: Brian.Zielski@GE.com

Glen Sabin
Senior Director, Regulatory Affairs
Phone: 262-894-4968
Email: Glen.Sabin@GE.com

Common/Usual Name:
Magnetic Resonance Diagnostic Device

Classification Names:
Regulation
Number:

Magnetic Resonance Diagnostic Device
21 CFR 892.1000

Predicate Device(s):
SIGNA 7.0T (K201615)

In accordance with 21 CFR 807.92 the following summary of information is provided:


SIGNA 7.0T is a high performance magnetic resonance
imaging system designed to support high resolution imaging
at 7.0T in particular anatomical regions determined by the
available RF coils. The system includes a 7.0T
superconducting magnet and an ultra-high performance
gradient coil with a 60 cm patient bore, supporting scanning
in axial, coronal, sagittal, oblique, and double oblique planes
using a variety of pulse sequences, imaging techniques,
acceleration methods, and reconstruction algorithms.
This 510(k) submission is for the SIGNA 7.0T MR System, and
has been triggered by the addition of the AIR Recon DL
software feature and inclusion of installed base magnet
system upgrades.

The addition of the AIR Recon DL feature and installed base
magnet system upgrades does not impact the intended use
of the SIGNA 7.0T system. The Indications for Use remain
identical:
The SIGNA 7.0T system is a whole-body magnetic resonance
scanner designed to support high resolution, high signal-to-
noise ratio, and short scan times. It is indicated for use as a
diagnostic imaging device to produce axial, sagittal, coronal,
and oblique images, spectroscopic images, parametric maps,
and/or spectra, dynamic images of the structures and/or
functions of the head and extremities.
The images produced by the SIGNA 7.0T system reflects the
spatial distribution or molecular environment of nuclei
exhibiting magnetic resonance. These images and/or spectra
when interpreted by a trained physician yield information
that may assist in diagnosis.
The device is intended for patients > 20 kg / 44 lb.

The SIGNA 7.0T employs the same fundamental scientific
technology as its predicate device.
The software used on the proposed SIGNA 7.0T system has
been modified to include the AIR Recon DL feature. The user
interface provides operators of the system with new options

510(k) Premarket Notification Submission


for selecting AIR Recon DL and adjusting the associated level
of image noise reduction. The resulting images can have
higher SNR and improved sharpness compared to images
reconstructed without AIR Recon DL.
AIR Recon DL has been previously cleared for use with GE
Healthcare’s 3T SIGNA Premier system through K193282.
Due to the technical similarities, SIGNA Premier (K193282) is
used as a reference device for this submission.
Upgrades to SIGNA 7.0T are also being expanded to be
compatible with additional 7.0T magnets in the installed
base.

Determination of
Substantial Equivalence:

Summary of Non-Clinical Tests:
The AIR Recon DL feature has undergone performance
testing. These tests were designed to evaluate the AIR Recon
DL feature and its impact on image quality, including SNR,
sharpness, and low contrast detectability.
The nonclinical testing demonstrated that AIR Recon DL does
improve SNR and image sharpness while maintaining low
contrast detectability. AIR Recon DL was also able to
maintain image SNR and did not sacrifice sharpness for
images acquired with a reduced scan time. The nonclinical
testing passed the defined acceptance criteria, and did not
identify any adverse impacts to image quality or other
concerns related to safety and performance.
Simulations and analyses were performed for the different
installed base magnet types to ensure equivalence.
Summary of Clinical Tests:
Objective measures of in vivo images were analyzed to
confirm that AIR Recon DL improves SNR and image
sharpness for typical clinical use cases.
A reader study was performed on images with and without
AIR Recon DL feature. Radiologists were asked to rate the
images, and to comment on any notable aspects related to
image quality. This study showed that AIR Recon DL feature
provides images with better SNR and equivalent or better
sharpness. The radiologists uniformly preferred the AIR
Recon DL images for clinical evaluation.


GE Healthcare, (GE Medical Systems, LLC)
3000 N. Grandview Blvd
Waukesha, WI 53188 USA

Chris Paulik
Regulatory Affairs Program Manager
GE Healthcare
262-894-5415
Christopher.A.Paulik@ge.com

Diane Uriell
Regulatory Affairs Director
GE Healthcare
262-290-8218
Diane.Uriell@ge.com

Critical Care Suite with Endotracheal Tube Positioning AI Algorithm

Automated Radiological Image Processing Software

Regulation Name: Medical Image Management and Processing System
Regulation: 21 CFR 892.2050
Classification: Class II
Product Codes: QIH

QLAB Advanced Quantification Software (K191647)
Regulation Name: Picture archiving and communications system
Regulation: 21 CFR 892.2050
Classification: Class II


Critical Care Suite (K183182)
Regulation Name: Radiological computer aided triage and notification software
Regulation: 21 CFR 892.2080
Classification: Class II
Product Codes: QFM

Critical Care Suite with Endotracheal Tube Positioning AI Algorithm is an additional AI
Algorithm incorporated into the Critical Care Suite software previously cleared under
K183182. It introduces the Endotracheal Tube Positioning AI Algorithm which is a
quantification tool that analyzes frontal chest x-ray images and based on the data in the
image determines the location of the tip of an intubated patient’s endotracheal tube,
determines the location of the carina, and then calculates and displays the vertical
distance between them. The distance provided is within the x-ray detector imaging
plane and does not take into account the geometric magnification resultant from the
geometry of the x-ray acquisition based on source to image distance (SID), patient size,
or any impacts due to patient rotation or tube rotation. This information can aide
clinical care teams and radiologists to determine the proper placement of the
endotracheal tube in an intubated patient. All algorithms previously cleared under
K183182 are still available with Critical Care Suite, including the Pneumothorax Detection
Algorithm for triage and notification.
The benefit of the proposed modification is not specific to the platform on which it is
deployed. This benefit applies to all previously cleared computational platforms for
Critical Care Suite, including PACS, On Premise, On Cloud and Digital Projection
Radiographic Systems. The Optima XR240amx was chosen as the initial platform for
deployment because endotracheal tube placement images are almost exclusively
acquired on mobile X-ray systems due to the immobilization of the patients being
intubated with an endotracheal tube.

Critical Care Suite with Endotracheal Tube Positioning AI Algorithm is intended to
provide automated radiological image processing and analysis tools implementing
artificial intelligence including nonadaptive machine learning algorithms trained with
clinical and/or artificial data.

Critical Care Suite is a suite of AI algorithms for the automated image analysis of frontal
chest X-rays acquired on a digital x-ray system.
Critical Care Suite with the Endotracheal Tube Positioning AI algorithm produces an on-
screen image overlay that detects and localizes an endotracheal tube, locates the
endotracheal tube tip, locates the carina, and automatically calculates the vertical
distance between the endotracheal tube tip and carina. This information is also
transmitted to the radiologist for review.


Intended users include licensed qualified healthcare professionals (HCPs) trained to
independently place and/or assess endotracheal tube placement and radiologists.
Critical Care Suite with Endotracheal Tube Positioning AI Algorithm should not be used
in-lieu of full patient evaluation or solely relied upon to make or confirm a diagnosis. It is
not intended to replace the review of the X-ray image by a qualified healthcare
professional. Critical Care Suite with the Endotracheal Tube Positioning AI Algorithm is
indicated for adult-size patients.

Critical Care Suite with Endotracheal Tube Positioning AI Algorithm employs the same
fundamental scientific technology as its predicate device. It is a deep learning locked AI
algorithm that can be deployed on several computing platforms such as PACS, On
Premise, On Cloud or Imaging Systems. The patient and user populations are identical to
what is provided with Critical Care Suite, adult-sized patients. The Endotracheal Tube
Positioning AI Algorithm is an automated radiological image processing and analysis tool,
which is equivalent to the image analysis and quantification algorithms provided in the
QLAB Advanced Quantification Software.
The differences between Critical Care Suite with Endotracheal Tube Positioning AI
Algorithm and QLAB Advanced Quantification Software are the acquisition systems that
provide the images as well as the specific anatomies that are being analyzed. Critical
Care Suite with Endotracheal Tube Positioning AI Algorithm analyzes chest radiographic
images where QLAB Advanced Quantification Software analyzes ultrasound images of
the heart. This difference does not impact the safety or efficacy of Critical Care Suite
with Endotracheal Tube Positioning AI Algorithm since both devices analyze images using
deep learning AI technology to identify/visualize anatomical structure and then provide
quantification measurements based on that data to aide qualified healthcare
professionals trained on endotracheal tube placement and radiologists.


Critical Care Suite with Endotracheal Tube
Positioning AI Algorithm

QLAB Advanced Quantification Software
(K191647)

Picture archiving and communications system
Class II, QIH

Targeted clinical
condition,
anatomy, and
imaging modality

Endotracheal Tube Positioning Visualization and
Quantification
Chest/Lung
Frontal Chest X-Ray Imaging

Right Ventricle Visualization and Quantification
Heart
Ultrasound Heart Imaging

AI deep learning algorithms designed to visualize
and quantify endotracheal tube positioning in
frontal chest X-ray images

AI deep learning algorithm designed to visualize and
quantify the right ventricle within heart ultrasound
images

professionals trained on endotracheal tube placement and radiologists.


Critical Care Suite with Endotracheal Tube Positioning AI Algorithm specific verification
was conducted to demonstrate proper implementation of Critical Care Suite software
design requirements.
Regression testing on the Optima XR240amx feature functionality was conducted to
verify proper integration of Critical Care Suite with Endotracheal Tube Positioning AI
Algorithm into the Optima XR240amx software and device. Validation was performed on
Optima XR240amx with integrated Critical Care Suite with Endotracheal Tube Positioning
AI Algorithm.
Design verification and validation testing was performed to confirm that the safety and
effectiveness of the device has not been affected. The test plans and results have been
executed with acceptable results.
Summary of Clinical Tests:
The performance of the Endotracheal Tube Positioning AI Algorithm was tested against a
ground truth dataset. The ground truth dataset contained a sufficient number of images
to adequately analyze all the primary and secondary endpoints and the results met the
defined passing criteria.
The Endotracheal Tube Positioning AI Algorithm achieved an AUC of 0.9999 (0.9998,
1.0000), a sensitivity of 0.9941 (0.9859, 1.0000) and a specificity of 1.0000 (1.0000,
1.0000) for ETT detection. Additionally, the Endotracheal Tube Positioning AI Algorithm
achieved an ETT tip to Carina distance measurement success rate of 0.9851 (0.9722,
0.9981), a carina localization success rate 0.9851 (0.9722, 0.9981), an ETT tip localization
success rate of 0.9524 (0.9296, 0.9752) and an ETT localization success rate (DICE) of
0.9881 (0.9765, 0.9997).

Determination
of Substantial
Equivalence:

The introduction of Critical Care Suite with Endotracheal Tube Positioning AI Algorithm
does not result in any new potential safety risks, and has the same technological
characteristics, and performs as well as the predicate devices currently on the market.
After analyzing design verification and validation testing on the bench it is the conclusion
of GE Healthcare that the Critical Care Suite with Endotracheal Tube Positioning AI
Algorithm software to be as safe, as effective, and performance is substantially
equivalent to the predicate device.


Item
InferRead CT Stroke.AI
Aidoc Briefcase ICH (K180647)
Comparison

InferRead CT Stroke.AI is a
radiological computer aided triage
and notification software for use in
the analysis of Non-Enhanced Head
CT images. The device is intended to
assist hospital networks and trained
radiologists in workflow triage by
flagging suspected positive findings
of intracranial hemorrhage (ICH).
InferRead CT Stroke.AI uses an
artificial intelligence algorithm to
analyze images and highlight cases
with detected ICH on a standalone
desktop application in parallel to the
ongoing standard of care image
interpretation. The user is presented
with a worklist with marked cases of
suspected ICH findings. The device
does not alter the original medical

BriefCase is a radiological computer
aided triage and notification software
indicated for use in the analysis of non-
enhanced head CT images. The device is
intended to assist hospital networks and
trained radiologists in workflow triage
by flagging and communication of
suspected positive findings of
pathologies in head CT images, namely
Intracranial Hemorrhage (ICH).
BriefCase uses an artificial intelligence
algorithm to analyze images and
highlight cases with
detected ICH on a standalone desktop
application in parallel to the ongoing
standard of care
image interpretation. The user is
presented with notifications for cases
with suspected ICH

InferRead CT Stroke.AI
and the previously cleared
BriefCase (K180647)
have the same intended
use and\indications for use
in terms of finding
suspected intracranial
hemorrhage in non
contrast head CT, flagging
suspected cases, and
indicating the case to the
attention of the clinician.

Detailed Comparison of the Subject and Predicate Devices


image, does not remove cases from
queue, and is not intended to be used
as a diagnostic device. If the clinician
does not view the case, or if a case is
not flagged, cases remain to be
processed per the standard of care.
The results of InferRead CT
Stroke.AI are intended to be used in
conjunction with other patient
information and based on
professional judgment, to assist with
triage/prioritization of medical
images. Notified clinicians are
responsible for viewing full images
per the standard of care.

findings. 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 professional
judgment, to assist with
triage/prioritization of medical images.
Notified clinicians are responsible for
viewing full images per the standard of
care.

Both are designed to be
used by the radiologist,
prompt the radiologist to
start preemptive triage of
a flagged case

Both are indicated for use
in analysis of non-
enhanced head CT

Non contrast CT scan of the head or
neck

DICOM information about the
patient, study and current image

Both display DICOM
information for
informational purposes
only


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

Neither marks, highlights
or directs attention to a
specific location in the
original image

Artificial intelligence algorithm with
database of images

Both use artificial
intelligence algorithm
with a database of images

Yes, pop-up notifications, case level
indicator

In both, the suspected
cases are indicated to the
user. The subject device
provides case level
indicator and allow the
user to sort suspected
cases to the top.

Presentation of a preview of the
study for initial assessment not
meant for diagnostic purposes
The device operates in parallel
with the standard of care, which
remains the default option for all
cases

Both allow the user to
view the image. The
device is intended to work
in parallel with standard
of care.

Neither removes cases
from the worklist queue.


Automated Radiological Image Processing Software

Medical image management and processing system


The qER-Quant device is intended for
automatic labeling, visualization and
quantification of segmentable brain
structures from a set of Non-Contrast
head CT (NCCT) images. The software is
intended to automate the current
manual process of identifying, labeling
and quantifying the volume of
segmentable brain structures identified
on NCCT images.
qER-Quant provides volumes from NCCT
images acquired at a single time point
and provides a table with comparative
analysis for two or more images that
were acquired on the same scanner with
the same image acquisition protocol for
the same individual at multiple time
points.
The qER-Quant software is indicated for
use in the analysis of the following
structures: Abnormal Intracranial
Hyperdensities, Lateral Ventricles and
Midline Shift.

The Icobrain device is intended for
automatic labeling, visualization and
volumetric quantification of segmentable
brain structures from a set of MR or NCCT
images. This software is intended to
automate the current manual process of
identifying, labeling and quantifying the
volume of segmentable brain structures
identified on MR or NCCT images.
Icobrain consists of two distinct image
processing pipelines: icobrain cross and
icobrain long.
icobrain cross is intended to provide
volumes from MR or NCCT images acquired
at a single time point.
icobrain long is intended to provide changes
in volumes between two MR images that
were acquired on the same scanner, with
the same image acquisition protocol and
with same contrast at two different
timepoints.
The results of icobrain cross cannot be
compared with the results of icobrain long.

- Software package
- Operates on off-the-shelf hardware
(multiple vendors)
- DICOM compatible
- Segmentation by deep learning
(supervised voxel classification with
Convolutional Neural Networks)

- Software package
- Operates on off-the-shelf hardware
(multiple vendors)
- DICOM compatible
- Segmentation by classical machine
learning and deep learning (supervised
voxel classification with Convolutional
Neural Networks)

Multiple electronic reports with
volumetric information of brain
structures and midline shift AND
Annotated DICOM Images

Reference
Standard for
Performance
testing

Accuracy
Manually labeled images for all
structures
Reproducibility

Accuracy
Manually labelled or simulated ground truth
for MRI images
Manually labeled images (lesions and
midline shift) and images labeled by
previously cleared Icobrain MRI software for
CT images (lateral ventricles and whole
brain)
Reproducibility


MRI measurement changes compared on
test-retest images; simulation study used
for CT measurements

Comparison of Differences between qER-Quant and the predicate device

Non-contrast CT from a single or
multiple time points

T1-weighted and fluid-attenuated inversion
recovery (FLAIR) MR images from a single or
multiple time points and/or
Non-contrast CT from a single time point

Target structures
analyzed on NCCT
scans

Intracranial hyperdensities, lateral
ventricles and midline shift

Intracranial hyperdensities, lateral
ventricles, basal cisterns and midline shift


Absolute error versus ground truth
(volume in ml or shift in mm)

Structure (Number of Scans)
Mean (Standard
Median (10th -
Mean (95%

Deviation)
90th percentile)
confidence interval)


Predicate Device
Volpara Imaging Software 1.5.6
(K182310)

Submission Device
Volpara Imaging Software 3.2

VolparaDensity is a software
application intended for use with the
raw data from digital breast x-ray
systems, including tomosynthesis.
VolparaDensity calculates and
quantifies a density map and from
that determines volumetric breast
density as a ratio of fibroglandular
tissue and total breast volume
estimates. Volpara provides these

Volpara Imaging Software1 is a
software application intended for use
with the raw data from digital breast
x-ray systems, including
tomosynthesis. Volpara Imaging
Software calculates and quantifies a
density map and from that
determines volumetric breast density
as a ratio of fibroglandular tissue and
total breast volume estimates.

Table 1. Substantial Equivalence Comparison


numerical values along with a BI-RADS
breast density 4th or 5th Edition
category to aid health care
professionals in the assessment of
breast tissue composition.
VolparaDensity is not an interpretive
or diagnostic aid and should be used
only as adjunctive information when
the final assessment of breast density
category is made by an MQSA-
qualified interpreting physician.

Volpara Imaging Software provides
these numerical values along with a
BI-RADS breast density 4th or 5th
Edition category and quality
assurance metrics (i.e., dose and
pressure) to aid healthcare
professionals in the assessment of
breast composition. Volpara Imaging
Software is not a diagnostic aid and
should be used only as adjunctive
information when the final
assessment of breast density category
is made by an MQSA-qualified
interpreting physician.

Intended Users
Health Care Professionals
Health Care Professionals

Image Source
Digital mammography images
Digital mammography images

Digital mammograms from
mammography or tomosynthesis
systems, including those obtained
using with curved paddles.

• Volume of Fibroglandular tissue
• Volume of Breast
• Volumetric Breast Density
• BIRADS 4th or 5th Edition Breast
Density Category, with
highlighting above a certain
volumetric threshold or if focal
density present
• Average thickness of dense tissue
• Maximum thickness of dense
tissue (and location)


• Maximum volume of dense tissue
above any 1 cm2 square region
(and location)
• Image quality assessment metrics

Density map in DICOM SCI format, for
visualization as user specifies

Classification
21 CFR 892.2050; LLZ
21 CFR 892.2050; LLZ


Description and Comparison of the Subject Device to the Predicate Device

Reference Point Management allows to edit the position, color, and type
of Points of Interest (POI).
Modification:
The workflow for POI creation and editing has been slightly adapted to improve
usability without modification of the functionality.

Transmission of reference points with the offset details to a movable laser system
for patient marking.
Modification:
• Saving of sent POIs
• Removal of default value for laser calibration offset
• Consistency checks for laser calibration offset (only for integrated laser)
• Minor usability improvements

With Contouring, the user can create, delete, and edit Volumes of Interest (VOIs).
Modification:
The routine contouring feature has been enhanced for the subject device to
include a tool to cut a structure at a user-defined axial level.

• Loading and storing of DICOM RT structure sets, creating, editing and deletion
of structures and POIs.
• Creating, editing and deletion of structure templates.
• Customize predefined structure database with mapping to international
nomenclature schemes.
Modifications:
The Structure Set Management provides a set of improvements to optimize the
workflow including:
• Structure Set approval
• Enhanced color picker
• Structure sorting by type
• Manual and automated merging of structure sets
• Streamlined rapid results configuration
• Filter for auto-contourable structures
• Merge / expand structure via structure templates

The synthetic CT feature provides functionality to create a CT-density equivalent
image series out of multiple MR-image-series.
Modification:
The algorithm for brain and pelvis synthetic CTs has been changed from Atlas
based to a deep-learning algorithm.

provided as Table 4 below for the software version SOMARIS/8 VB60:


Basic Feature The set provides basic feature of the subject device.


Digital Imaging and Communications in
Medicine (DICOM) Set; PS 3.1 – 3.20

Medical Device Software –Software Life Cycle
Processes; 62304:2015-06 (Edition 1.1)

Medical devices – Application of risk
management to medical devices; 14971 Second
Edition 2007-03-01

covering electrical and mechanical safety listed below:


Medical devices - Part 1: Application of
usability engineering to medical devices
IEC 62366-1:2015

Traditional: 510(k): syngo.via RT Image Suite


Manufacturer
AIbolit Technologies, LLC
Ceevra

Ceevra Reveal 2.0
Image Processing System

510(k) Number
Subject Device - TBD
K173274

Radiological Image
Processing System / QIH -
LLZ

Radiological Image Processing
System / LLZ

Regulation / Class
21 CFR 892.2050 – Class II
21 CFR 893.2050 – Class II

Aibolit 3D+ is intended as a
medical imaging system that
allows the processing, review,
analysis, communication and
media interchange of multi-
dimensional digital images
acquired from CT imaging
devices. It is also intended as
software for preoperative
surgical planning, training,
patient information and as
software for the intraoperative
display of the multidimensional
digital images. Aibolit 3D+ is
designed for use by health
care professionals and is
intended to assist the clinician
who is responsible for making
all final patient management
decisions.

Ceevra Reveal 2.0 is intended as
a medical imaging system that
allows the processing, review,
analysis, communication
and media interchange of multi-
dimensional digital images
acquired from CT or MR imaging
devices. It is also intended as
software for preoperative surgical
planning, and as software for the
intraoperative display of the
aforementioned multidimensional
digital images. Ceevra Reveal 2.0
is designed for use by health care
professionals and is intended to
assist the clinician who is
responsible for making all final
patient management decisions.

Capture and enhancement of
(DICOM) digital video images
via software-based conversion
to 2-D and 3-D anatomical
structure images that can be
manipulated for viewing

Intended Users
Health care professionals
Health care professionals

Healthcare facilities such as
hospitals and clinics


AIBOLIT 3D+ is intended for
use as a medical imaging
system that allows the
processing, review, analysis,
communication and media
interchange of multi-
dimensional digital images
acquired from CT imaging
devices. It is also intended as
software for preoperative
surgical planning, and as
software for the intraoperative
display of multi- dimensional
digital images. AIBOLIT 3D+
is designed for use by health
care professionals and is
intended to assist the clinician
who is responsible for making
patient management
decisions.

Intended as a medical imaging
system that allows the
processing, review, analysis,
communication and media
interchange of multi- dimensional
digital images acquired from CT
or MR imaging devices. It is also
intended as software for
preoperative surgical planning,
and as software for the
intraoperative display of the
aforementioned multi-
dimensional digital images.
Ceevra Reveal 2.0 is designed for
use by health care professionals
and is intended to assist the
clinician who is responsible for
making all final patient
management decisions.

AIBOLIT 3D+ is a software
only device that permits
electronic image uploads,
provides image conversion
and allows viewing on a
mobile device or standard
computer monitor.

The Ceevra Reveal 2.0 Video
Processor is a software only
device that permits electronic
image uploads, provides image
conversion and allows viewing on
a mobile device or standard
computer monitor.

Generation of 2D and 3D
images from DICOM data
Organ segmentation and
structure identification
Dimensional and volume
references
Multi-axis image rotation
Organ transparency
Organ retraction animation


Physician uploads DICOM
images and specifies desired
anatomical segments of
interest
Radiologist annotates sample
(segments) images
AI software facilitates
annotation of available images
under guidance and control by
the Radiologist
Imaging technician generates
multi-axis rotatable image and
retraction model
Radiologist reviews images
generated by imaging
technician and returns output
file to requesting physician

Physician uploads DICOM images
and specifies desired anatomical
segments of interest
Imaging technician annotates
sample (segments) images
Imaging technician generates
multi-axis rotatable image and
returns output file to requesting
physician

List of organ structures to be
annotated and displayed,
patient ID and demographics

By Radiologist (MD) – Manual
annotation is done for all CT
slices with optional use of
AI/ML algorithms as
determined by Radiologist and
with Radiologist’s approval

By Imaging Technician – Manual
annotation done for all CT slices –
No software used for annotation

Unknown proprietary method
used to identify organ structures

3D image file generated by 3rd
party software (3D Slicer)
following Radiologist review
and approval of annotation


Proprietary software assigns
color coding to each structure
identified by Radiologist and
displays color-coded image
with labeled key to
color/structure identity

Proprietary software assigns color
coding to each structure identified
by imaging technician and
displays color-coded image with
key to color/structure identity

Only the radiologist can alter
or edit images following review
– User physicians cannot edit
images - Physicians have
option to show or hide organs
on display

Imaging technician can edit
images generated by the system
software – User physicians
cannot edit images - Physicians
have option to show or hide
organs on display

3D image can be displayed on
standard monitor, smart phone
(with separate software) or Virtual
Imaging 3D headset

Organ structure dimensions,
volume, organ labels, patient
ID, CT date and demographics

Organ structure dimensions,
volume, organ labels, patient ID
and demographics

Physician user can show or
hide individual organ
structures, zoom capability,
rotational capability and
transparency capability

Physician user can show or hide
individual organ structures, zoom
capability, rotational capability,
transparency capability (current
version)


MM Oncology Updated syngo.CT LungCAD Integration (K203258)

MI Workflows Visualization of 4D data in all layouts
(MI General, FAST Ranges Enhancements
MI Cardiology, Auto Layout Improvements
Gaussian filtering of PET Data
Interactive Spectral Imaging
Usability Improvements

MI Cardiology OpenApps framework for ISAs (including Cedars, Corridor
4DM, and syngo MBF)
Spill-Over Factors (within syngo MBF)
Automatic window/level for each frame (within syngo MBF)
Global Time Activity Curve (within syngo MBF)

Calibrated I123-FP-CIT normal databases in Striatal

Analysis (within Striatal Analysis workflow of Scenium)


UNMODIFIED Device
PowerLook Density Assessment

MODIFIED Device
PowerLook Density Assessment V4.0

Medical Image Management and
Processing System

Regulation Number
21 CFR 892.2050
21 CFR 892.2050


PowerLook Density Assessment is a
software application intended for use
with digital breast tomosynthesis
synthesized 2D images from
tomosynthesis exams. PowerLook
Density Assessment provides an ACR
BI-RADS Atlas 5th Edition breast
density category to aid health care
professionals in the assessment of
breast tissue composition. PowerLook
Density Assessment produces
adjunctive information. It is not a
diagnostic aid.

Symptomatic and asymptomatic women
undergoing mammography.

Synthetic views from tomosynthesis
systems

DICOM synthetic 2D images generated
from breast tomosynthesis data

DICOM structured report or DICOM
secondary capture.

For each patient:
• ACR BI-RADS® Atlas 5th
Edition breast density
category
• Fractional indication of
distance inside breast density
category

Deployment
Standalone computer
Standalone computer

Supported Digital Breast
Tomosynthesis Systems

• Hologic Selenia
Dimensions/3Dimensions
(C-View)
• GE Senographe Essential
with SenoClaire (V-Preview)
• GE Senographe Pristina (V-
Preview)


Subject Device
Predicate Device
Substantially


In MammoScreen, a range of medical image
processing and machine learning techniques are
implemented. The system includes ‘deep learning’
modules for recognition of suspicious
calcifications and soft tissue lesions. These
modules are trained with very large databases of
biopsy-proven examples of breast cancer and
normal tissue.


The intended use of Philips EPIQ series diagnostic ultrasound systems is diagnostic ultrasound imaging and fluid flow analysis of
the human body, with the following indications for use:
Abdominal, Cardiac Adult, Cardiac other (Fetal), Cardiac Pediatric, Cerebral Vascular, Cephalic (Adult), Cephalic (Neonatal),
Fetal/Obstetric, Gynecological, Intra-cardiac Echo, Intra-luminal, Intraoperative (Vascular), Intraoperative (Cardiac),
Musculoskeletal (Conventional), Musculoskeletal (Superficial), Other: Urology, Pediatric, Peripheral Vessel, Small Organ
(Breast, Thyroid, Testicle), Transesophageal (Cardiac), Transrectal, Transvaginal, Lung.
The clinical environments where Philips EPIQ diagnostic ultrasound systems can be used include clinics, hospitals, and clinical
point-of-care for diagnosis of patients.
When integrated with Philips EchoNavigator, the systems can assist the interventionalist and surgeon with image guidance during
treatment of cardiovascular disease in which the procedure uses both live X-ray and live echo guidance.
The systems are intended to be installed, used, and operated only in accordance with the safety procedures and operating
instructions given in the product user information. Systems are to be operated only by appropriately trained healthcare
professionals for the purposes for which they were designed. However, nothing stated in the user information reduces your
responsibility for sound clinical judgement and best clinical procedure.

The intended use of the Affiniti Series Diagnostic Ultrasound Systems is diagnostic ultrasound imaging and fluid flow analysis of
the human body with the following Indications for Use:
Abdominal, Cardiac Adult, Cardiac other (Fetal), Cardiac Pediatric, Cerebral Vascular, Cephalic (Adult), Cephalic (Neonatal),
Fetal/Obstetric, Gynecological, Intraoperative (Vascular), Intraoperative (Cardiac), Musculoskeletal (Conventional),
Musculoskeletal (Superficial), Other: Urology, Pediatric, Peripheral Vessel, Small Organ (Breast, Thyroid, Testicle),
Transesophageal (Cardiac), Transrectal, Transvaginal, Lung.
The clinical environments where the Affiniti Diagnostic Ultrasound Systems can be used include Clinics, Hospitals, and clinical
point-of-care for diagnosis of patients.
The systems are intended to be installed, used, and operated only in accordance with the safety procedures and operating
instructions given in the product user information. Systems are to be operated only by appropriately trained healthcare
professionals for the purposes for which they were designed. However, nothing stated in the user information reduces your
responsibility for sound clinical judgment and best clinical procedure.


Medical Image
Management and
Processing System

Picture archiving
and communication
system

QIH*
Automated
radiological image
processing software

LLZ
System, image
processing,
radiological

1. Patient population
Adult
Pediatric and Adult

2. Receive, store, transmit,
post process, display and
allow manipulation of
medical MR images

3. Client/server functionality
to connect to a PACS
(Picture Archiving and
Communication System) and
to activate software license.

4. Visualization of 2D and 2D
+ time of single or multiple
datasets.

7. Cardiac function analysis
including ejection fraction
assessment, local
myocardial mass, thickness
and thickening.

8. Aorta study including
length and area
measurements, compliance,

Table 1: Technological Characteristics Comparison Table


In accordance with 21 CFR 807
.87(h) and 21 CFR 807.92 the 510(

Submission Correspondent:
Donna-Bea Tillman, Ph.D.

Device Common Name:
Picture Archiving and Communica

Classification Name
21 CFR 892.2050 Medical Image


21 CFR 892.2090
Radiological Computer Assisted
Detection and Diagnosis software

A reading aid for physicians
interpreting screening FFDM
acquired with compatible
mammography systems, to identify
findings and assess their level of
suspicion.

Women undergoing FFDM screening
mammography

Physicians interpreting FFDM
screening mammograms

Design
Software-only device
Software-only device

Lunit INSIGHT MMG is a radiological
Computer-Assisted Detection and
Diagnosis (CADe/x) software device
based on an artificial intelligence
algorithm intended to aid in the
detection, localization, and

The ScreenPoint Transpara™
system is intended for use as a
concurrent reading aid for physicians
interpreting screening mammograms
from compatible FFDM system, to
identify regions suspicious for breast

Table 1 – Comparison Between Subject and Predicate Devices


characterization of suspicious areas
for breast cancer on mammograms
from compatible FFDM systems. As
an adjunctive tool, the device is
intended to be viewed by interpreting
physicians after completing their
initial read. It is not intended as a
replacement for a complete
physician’s review or their clinical
judgement that takes into account
other relevant information from the
image or patient history. The Lunit
INSIGHT MMG uses screening
mammograms of the female
population.

cancer and assess their likelihood of
malignancy. Output of the device
includes marks placed on suspicious
soft tissue lesions and suspicious
calcifications; region based scores,
displayed upon the physician’s query,
indicating the likeliho‐od that cancer is
present in specific regions; and an
overall score indicating the likelihood
that cancer is present on the
mammogram. Patient management
decisions should not be made solely
on the basis of analysis by
Transpara™.

Device output
in case of
positive
detection

Output of the device includes marks
with visualized map such as heatmap
placed on suspicious lesions for
breast cancer; lesion score,
indicating the likelihood of presence
of the malignancy in specific regions;
and an abnormality score indicating
the likelihood of the presence of
malignancy per-breast in the
mammogram. The per-breast
abnormality score takes maximum
score from two views (i.e., CC, MLO)
of a breast which is the maximum
lesion score in the breast.

Output of the device includes marks
in outlines placed on suspicious soft
tissue lesions and suspicious
calcifications; region based scores,
displayed upon the physician’s query,
indicating the likeliho‐od that cancer is
present in specific regions; and an
overall score indicating the likelihood
that cancer is present on the
mammogram.


Score 1-100 indicating likelihood of
presence of malignancy (from low
suspicion to high suspicion).
Breast level:
Score 1-100 indicating the level of
suspicious of malignancy.
The maximum scores from two view
(i.e., CC, MLO) of a breast which is
the maximum lesion score in the
breast
Exam level: None

Continuous score 1-100 indicating
the level of suspicion of malignancy
(from low suspicion to high
suspicion).
Breast level: None
Exam level: 10-point scale score
indicative of higher frequency of
cancer positive

Reader study:
 240 cases
 12 radiologists
cf. Reading time was not measured
in this study.
ROC AUC:
radiologists AUC (unaided) = 0.754
radiologists AUC (aided) = 0.805
Standalone Performance Test:
 2412 cases

Reader study:
 240 cases
 14 radiologists
Reading time:
 146 seconds (unaided
session)
 149 seconds (with
Transpara™)
AUC:
 radiologists AUC (unaided) =
0.866
 radiologists AUC (aided) =
0.886


ROC AUC = 0.903
 standalone AUC = 0.887

In Lunit INSIGHT MMG, a range of
medical image processing and
machine learning techniques are
implemented. The system includes
‘deep learning’ algorithm applied to
images for recognition of suspicious
lesions for breast cancer. The
machine learning components are
trained to detect suspicious lesions
for breast cancer with large
databases of biopsy-proven cases of
breast cancer, benign lesions and
normal tissues.

In Transpara, a range of medical
image processing and machine
learning techniques are implemented.
The system includes ‘deep learning’
algorithm applied to images for
recognition of suspicious lesions for
breast cancer. The machine learning
components are trained to detect
suspicious lesions for breast cancer
with large databases of biopsy-
proven cases of breast cancer,
benign lesions and normal tissues.


#" „fl(cid:29) fl" ‚"‚fl„(cid:27)"(cid:26)(cid:30)"‚„ •(cid:30)fl•


Manufacturer Name
Zebra Medical Vision, Ltd.


Manufacturer Name
GE Medical Systems, LLC


Technological
Proposed Device:
Primary Predicate Device:
Secondary Predicate Device:

Characteristics
Lunit INSIGHT CXR Triage
HealthCXR (K192320)
Critical Care Suite (K183182)

Radiological Computer Assisted
Prioritization Software Class II,
QFM

Lunit INSIGHT CXR Triage is a
radiological computer-assisted triage
and notification software that
analyzes adult chest X-ray images for
the presence of pre-specified
suspected critical findings (pleural
effusion and/or pneumothorax).
Lunit INSIGHT CXR Triage uses an
artificial intelligence algorithm to
analyze images for features
suggestive of critical findings and
provides case-level output available
in the PACS/workstation for
worklist prioritization or triage.
As a passive notification for
prioritization-only software tool
within standard of care workflow,
Lunit INSIGHT CXR Triage does
not send a proactive alert directly to
the appropriately trained medical
specialists. Lunit INSIGHT CXR
Triage is not intended to direct
attention to specific portions of an
image or to anomalies other than

The Zebra HealthCXR device is a
software workflow tool designed to
aid the clinical assessment of adult
Chest X-Ray cases with features
suggestive of pleural effusion in the
medical care environment.
HealthCXR analyzes cases using an
artificial intelligence algorithm to
identify suspected findings. It makes
case-level output available to a
PACS/workstation for worklist
prioritization or triage. HealthCXR 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 Pleural Effusion
or otherwise preclude clinical
assessment of X-Ray cases.

Critical Care Suite is a computer
aided triage and notification device
that analyzes frontal chest x-ray
images for the presence of pre-
specified critical findings
(pneumothorax). Critical Care Suite
identifies images with critical findings
to enable case prioritization or triage
in the PACS/workstation.
Critical Care Suite is intended for
notification only and does not
provide diagnostic information
beyond the notification. Critical Care
Suite should not be used in-lieu of
full patient evaluation or solely relied
upon to make or confirm a diagnosis.
It is not intended to replace the
review of the x-ray image by a
qualified physician.
Critical Care Suite is indicated for
adult-size patients.


pleural effusion and/or
pneumothorax. Its results are not
intended to be used on a stand-alone
basis for clinical decision-making.

Appropriately trained medical
specialists who are qualified to
interpret chest radiographs.

Pleural effusion, pneumothorax
Chest/Lung
Frontal Chest X-ray

Pleural effusion
Chest/Lung
Frontal Chest X-ray

Pneumothorax
Chest/Lung
Frontal Chest X-ray

Algorithm for
pre-specified
critical findings
detection

AI algorithm designed to detect
pleural effusion and pneumothorax
in chest X-ray images.
Lunit INSIGHT CXR Triage uses a
vendor agnostic algorithm
compatible with DICOM chest X-ray
images.

AI algorithm designed to detect
pleural effusion in chest X-ray
images.
HealthCXR employs a vendor
agnostic algorithm compatible with
DICOM chest X-ray images.

AI algorithm designed to detect
pneumothorax in frontal chest X-ray
images.
Critical Care Suite uses a vendor
agnostic algorithm compatible with
DICOM frontal chest X-ray images.

Lunit INSIGHT CXR Triage is
designed as a software module that
can be deployed on several

HealthCXR is designed as a software
module that can be deployed on

Critical Care Suite is designed as a
software module that can be
deployed on several computing and


Technological
Proposed Device:
Primary Predicate Device:
Secondary Predicate Device:

Characteristics
Lunit INSIGHT CXR Triage
HealthCXR (K192320)
Critical Care Suite (K183182)

computing and X-ray imaging
platforms such as radiological
imaging equipment, PACS, On
Premise or On Cloud.

PACS and Standalone desktop
application, Zebra Worklist.

X-ray imaging platforms such as
Digital Projection Radiographic
Systems, PACS, On Premise or On
Cloud.

Device output
in case of
positive
detection

When deployed on other radiological
imaging equipment, Lunit INSIGHT
CXR Triage automatically runs after
image acquisition and prioritizes and
displays the analysis result through
the worklist interface of
PACS/workstation.
No markup on original image.
Secondary capture of the finding.
Upon image acquisition from other
radiological imaging equipment (e.g.
X-ray systems), an on-device,
technologist notification indicating
which cases were flagged by Lunit
INSIGHT CXR Triage in PACS, is
generated 15 minutes after
interpretation by the user. The on-
device notification is contextual and
does not provide any diagnostic
information. It is not intended to

Integration module notifies the
PACS/workstation for prioritization
through the worklist interface.
No markup on original image.

Critical Care Suite enables case
prioritization or triage through direct
communication of the Critical Care
Suite notification during image
transfer to the PACS.
No markup on original image
Upon image acquisition on a Digital
Projection Radiographic System, an
on-device, technologist notification is
generated 15 minutes after exam
closure, indicating which cases were
prioritized by Critical Care Suite in
PACS. The technologist notification
is contextual and does not provides
any diagnostic information. The on-
device, technologist notification is
not intended to inform any clinical
decision, prioritization, or action.


inform any clinical decision,
prioritization, or action to the
technologist.

Passive notification.
Images with suspicion of pleural
effusion and/or pneumothorax are
flagged in PACS/workstation.

Passive notification.
Images with suspicion of pleural
effusion are flagged in
PACS/workstation.

Passive notification.
Images with suspicion of
pneumothorax are flagged in
PACS/workstation.

Where PACS/Workstation PACS/Workstation PACS/Workstation

Performance
level –
Timing of
notification

The average time taken for the
notification to travel from the Lunit
INSIGHT CXR Triage to the point
at which the result is displayed in the
destination PACS/RIS/EPR worklist
is 14.66 seconds.

Passive notification is visible upon
transfer to the PACS with a delay of
about 22 seconds for image transfer
to the cloud, computation, and
results transfer.

The average time to acquire,
annotate, process and transfer an
image from the x-ray system to
PACS was measured and found to
take 42 seconds on average. Exams
arrive on PACS with the passive
notification already incorporated,
therefore there is no delay for image
transfer or computation. The
worklist prioritization happens
immediately once the exam is
received on the PACS.


Technological
Proposed Device:
Primary Predicate Device:
Secondary Predicate Device:

Characteristics
Lunit INSIGHT CXR Triage
HealthCXR (K192320)
Critical Care Suite (K183182)

Performance
level –
accuracy of
classification


Radiological Computer-Assisted Prioritization Software

The HealthPPT device is substantially equivalent to the following device:


Predicate Device
AIMI-Triage CXR PTX
(K193300)

The Zebra HealthPPT device
is a software workflow tool
designed to aid the clinical
assessment of adult frontal
Chest X-Ray cases with
features suggestive of
pneumoperitoneum in the
medical care environment.
HealthPPT analyzes cases
using an artificial intelligence
algorithm to identify
suspected findings. It makes
case-level output available to
a PACS/workstation for
worklist prioritization or
triage. HealthPPT is not
intended to direct attention to
anomalies other than
pneumoperitoneum.
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. Its results are not

The AIMI-Triage CXR
PTX Application is a
notification-only triage
workflow tool for use by
hospital networks and
clinics to identify and
help prioritize chest
X-rays acquired in the
acute setting for review
by hospital radiologists.
The device operates in
parallel to and
independent of standard
of care image
interpretation workflow.
Specifically, the device
uses an artificial
intelligence algorithm to
analyze images for
features suggestive of
moderate to large sized
pneumothorax; it makes
caselevel output available
to a PACS/workstation
for worklist prioritization
or triage. Identification of
suspected cases of
moderate to large sized
pneumothorax is not for
diagnostic use beyond

A comparison of the technological characteristics with the predicate is summarized below.


intended to be used on a
stand-alone basis for clinical
decision-making nor is it
intended to rule out
pneumoperitoneum or
otherwise preclude clinical
assessment of X-Ray cases.

notification. The
AIMI-Triage CXR PTX
Application is limited to
analysis of imaging data
as a guide to possible
urgency of adult chest
X-ray image review, and
should not be used in lieu
of full patient evaluation
or relied upon to make or
confirm diagnoses.
Notified radiologists are
responsible for engaging
in appropriate patient
evaluation as per local
hospital procedure before
making care-related
decisions or requests. The
device does not replace
review and diagnosis of
the X-rays by
radiologists. The device is
not intended to be used
with plain film X-rays.

Notification-only,
parallel workflow
tool

Identify patients
with prespecified
clinical condition

Different but as
per the product
classification
definition, both
identify “time
sensitive imaging.”

Yes; notification flagged for
review on hospital worklist or
Zebra application

Similar,
HealthPPT can be
directly integrated
for notification on
the hospital
worklist or on the
Zebra application.
Both notifications
operate in parallel


Independent of
standard of care
workflow

Aids prompt
identification of
cases with
indicated findings

Presentation of a compressed
preview image for initial
assessment, not meant for
diagnostic purposes.
The device operated in
parallel with the standard of
care, which remains the
default option for all cases.

Presentation of
notification for initial
assessment not meant for
diagnostic purposes. The
device operates in parallel
with the standard of care,
which remains the default
option for all cases.

Similar,
HealthPPT
provides an
additional
compressed image
as a preview only,
not for diagnostic
use.

Different, but all
operating points
comply with DEN
170073 Special
control 1(iii).


HERA W9/HERA W10
(K192319)
Primary Predicate

GE Medical Systems
Ultrasound and
Primary Care
Diagnostics, LLC

The HERA W9/ HERA
W10 Diagnostic
Ultrasound System and
transducers are intended
for diagnostic
ultrasound imaging and
fluid analysis of the
human body.

The RS85 Ultrasound
Diagnostic System and
probes are designed to
obtain ultrasound images
and analyze body fluids.

The Voluson SWIFT,
Voluson SWIFT+ is
a general-purpose
diagnostic
ultrasound system
intended for use by
qualified and trained
healthcare
professionals for
ultrasound imaging,
measurement,
display and analysis
of the human body
and fluid.

- Q Scan
- ClearVision
- MultiVision
- Panoramic
- NeedleMate+
- AutoIMT+
- Elastoscan+

(Changed an algorithm of BiometryAssist to AI version).


- E-Thyroid
- E-Breast
- E-Strain
- S-Detect for Breast
- S-Detect for
Thyroid
- ADVR
- 3D Imaging
- (Volume Data
Acquisition)
- 3D Imaging
presentation
- 3D Cine/4D Cine
- 3D Rendering
MPR
- 3D XI
MSV/Oblique
View
- Volume CT
- 3D MagiCut
- Volume
Calculation
- (VOCAL, XI
VOCAL)
- XI STIC
- HDVI
- RealisticVue
- CEUS+
- HQ-Vision
- MV-Flow
- CrystalVue
- CrystalVue Flow*
- 5D CNS+
- 5D Follicle
- 5D Heart Color
- 5D Limb Vol
- 5D LB
- 5D NT
- 2D NT
- IOTA-ADNEX
- BiometryAssist
- E-Cervix
- LumiFlow
- ShadowHDR
- MPI+*
- Slice A
- HeartAssist *
- ViewAssist

- E-Thyroid
- E-Breast
- E-Strain
- S-Detect for Breast
- S-Detect for
Thyroid
- ADVR
- 3D Imaging
- (Volume Data
Acquisition)
- 3D Imaging
presentation
- 3D Cine/4D Cine
- 3DRendering MPR
- 3D XI
MSV/Oblique View
- Volume CT
- 3D MagiCut
- Volume Calculation
- (VOCAL, XI
VOCAL)
- XI STIC
- HDVI
- RealisticVue
- CEUS+
- HQ-Vision
- MV-Flow
- CrystalVue
- CrystalVue Flow*
- 5D CNS+
- 5D Follicle
- 5D Heart Color
- 5D Limb Vol
- 5D LB
- 5D NT
- 2D NT
- IOTA-ADNEX
- BiometryAssist
- E-Cervix
- LumiFlow
- ShadowHDR
- MPI+*

- E-Thyroid
- E-Breast
- E-Strain
- S-Detect for Breast
- S-Detect for
Thyroid
- ADVR
- 3D Imaging
- (Volume Data
Acquisition)
- 3D Imaging
presentation
- 3D Cine/4D Cine
- 3D Rendering MPR
- 3D XI
MSV/Oblique View
- Volume CT
- 3D MagiCut
- Volume Calculation
- (VOCAL, XI
VOCAL)
- XI STIC
- HDVI
- RealisticVue
- CEUS+
- HQ-Vision
- MV-Flow
- CrystalVue
- CrystalVue Flow
-
-
-
-
-
-
- 2D NT
- IOTA-ADNEX
- BiometryAssist
- LumiFlow
- ShadowHDR

HERA W9/ HERA W10 Diagnostic Ultrasound Systems


Software
CrystalVue Flow
Not Supported
Supported

Hardware
Internal DVD
Not Included
Included

Active array probe port
3 port (default), 4 port(option)
4 port

The differences between HERA W9 and HERA W10 in the subject device are as below.


ANSI AAMI ES60601-1:2005/(R)2012 and A1:2012, C1:2009/(R)2012 and A2:2010
/(R)2012
Medical Electrical Equipment - Part 1: General Requirements for basic safety and
essential performance.

IEC60601-1-2: 2014(4th Edition), Medical electrical equipment - Part 1-2: General
requirements for basic safety and essential performance - EMC

IEC60601-2-37:2007 + A1:2015, Particular requirements for the safety of ultrasonic
medical diagnostic and monitoring equipment

ISO 10993-1, Biological evaluation of medical devices -- Part 1: Evaluation and testing
within a risk management process.

ISO 14971:2007, Medical devices - Application of risk management to medical devices

NEMA UD 2-2004 (R2009)
Acoustic Output Measurement Standard for Diagnostic Ultrasound Equipment Revision
3

applications comply with voluntary standards.


Primary:
Aquilion Exceed LB
(TSX‐202A/3) V10.6
with AiCE‐i

JAK:
System, X‐ray,
Tomography,
Computed

Reference:
Dual Energy System
Package, CSDP‐001A


Aquilion Exceed LB
(TSX‐202A/3) V10.6 with AiCE‐i

SUREStart
12 measurements/s
12 measurements/s


Up to 3 pairs of Volume and
Multiview reconstructions can be
prescribed.

Single Energy Metal Artifact
Reduction (SEMAR)

Quantum Denoising Software
(QDS)
Adaptive Integrative Dose
Reduction 3D (AIDR 3D),
AIDR 3D Enhanced
AiCE
(Advanced Intelligent Clear‐IQ
Engine)
 Abdomen and Pelvis
 Chest
 Extremities
 Brain
 Inner ear

Magnified
reconstruction ‐
Available magnification
Size (D‐FOV)

BODY / BODY SHARP: Min. 100
mm
LUNG: Min. 100 mm
BONE: Min. 50 mm
INNER EAR: Min. 50 mm
BRAIN LCD / CTA: Min. 100 mm
Max. 700 (900*) mm
*Option


Spectronic Medical AB
Karbingatan 36
254 67 Helsingborg
SWEDEN

Per Bruhn
Manager of Quality Assurance and Regulatory Affairs
Spectronic Medical AB
Tel: +46 735 116042
Email: per.bruhn@spectronic.se

Device trade name:
Common Name:
Classification Regulation:
Classification Name:
Panel:
Classification:
Product Code:

MRI Planner
MRI Planner
21 CFR 892.5050
Medical charged-particle radiation therapy system
Radiology
Class II
MUJ, QKB

Device name: MRCAT Brain
Manufacturer: Philips Medical Systems MR Finland
510(k) Clearance: K193109
Classification Regulation: 21 CFR 892.5050
Classification Name: Medical charged-particle radiation therapy system
Classification Panel: Radiology
Device Class: II
Product Code: MUJ

Reference Device 1:
Device name: MRCAT Pelvis
Manufacturer: Philips Medical Systems MR Finland
510(k) Clearance: K182888
Classification Regulation: 21 CFR 892.5050
Classification Name: Medical charged-particle radiation therapy system
Classification Panel: Radiology
Device Class: II
Product Code: MUJ
Reference Device 2:
Device name: Limbus Contour
Manufacturer: Limbus AI, Inc.
510(k) Clearance: K201232
Classification Regulation: 21 CFR 892.2050
Classification Name: Medical image management and processing system
Classification Panel: Radiology
Device Class: II
Product Code: LLZ

The product MRI Planner is a stand-alone software providing information
to the treatment planning process prior to radiotherapy. Based on a DICOM

The following summary of the present 510(k) submission is provided:


MR image stack, the software generates synthetic CT images that can be
used for attenuation calculations in radiotherapy treatment planning for the
pelvis, brain and head-neck regions. In addition, the software also
generates contours of anatomical structures in the MR image stack, to be
used as a starting point for the manual delineation work required in
radiotherapy treatment planning. Contours are generated for prostate cancer
patients only (bladder, colon and femoral heads).
MRI Planner utilizes pre-trained machine learning models to perform both
the conversion to synthetic CT and the automated structure contouring. The
models for synthetic CT generation was trained using a dataset comprising
MR and CT images for 244 patients acquired in the treatment position at
four hospitals. The model for prostate cancer patient auto contouring was
trained using a dataset comprising MR images for 175 patients acquired in
the treatment position at four hospitals, together with in-house generated
expert manual contours. MRI Planner does not display or store DICOM
images. The user is advised to use existing softwares for radiotherapy
treatment planning to display and modify generated images and contours.
MRI Planner runs on a standard x86-64 compatible system with a CUDA
capable NVIDIA GPU and requires Ubuntu Linux 18.04 operating system.

MRI Planner is a software-only medical device intended for use by trained
radiation oncologists, dosimetrists and physicists to process images from
MRI systems to
1) provide the operator with information of tissue properties for radiation
attenuation estimation purposes in photon external beam radiotherapy
treatment planning, and to
2) derive contours for input to radiation treatment planning by assisting in
localization and definition of healthy anatomical structures.
MRI Planner is not intended to automatically contour tumors or tumor
clinical target volumes.
MRI Planner is indicated for radiotherapy planning of adult patients for
primary and metastatic cancers in the brain and head-neck regions, as well
as soft tissue cancers in the pelvis region.
MRI Planner generates synthetic CT images for radiation attenuation
estimation purposes for the pelvis, brain and head-neck regions only. MRI
Planner generates automatically derived contours of the bladder, colon and
femoral heads, for prostate cancer patients only.

MRI Planner provides the indications for use of the Predicate Device. The
Predicate Device has the intended use to provide the operator with
information of tissue properties for radiation attenuation estimation
purposes in photon external beam radiotherapy treatment planning.
MRI Planner includes the intended use of the Predicate Device, as it
provides the operator with information of tissue properties for radiation
attenuation estimation purposes in photon external beam radiotherapy
treatment planning. Additionally, it provides the functionality of auto
contouring, which is not believed to raise additional safety concerns.
As such, the indications for use of MRI Planner does not raise any

Spectronic Medical 510(k) Premarket Notification Submission


additional or different concerns regarding safety or effectiveness as
compared to the Predicate Device.

Both MRI Planner and the Predicate Device are machine learning based.
Reference Device 1 was used as predicate device for the Predicate Device
and is therefore also technologically equivalent. Both the Predicate Device
and Reference Device 1 generates similar outputs as MRI Planner in the
form of synthetic CT images. Since MRI Planner has similar technological
characteristics as both the Predicate Device and Reference Device 1 with
regard to synthetic CT generation, no differences in risk have been
identified between the products.
Both MRI Planner and Reference Device 2 use pre-trained machine
learning models to derive contours. Since MRI Planner has similar
technological characteristics as Reference Device 2 with regard to deriving
contours, no differences in risk have been identified between the products.

Dose accuracy bench test
The conducted bench tests evaluate the dosimetric equivalence of MRI
Planner generated synthetic CT (sCT) and conventional CT. Dosimetric
agreement was evaluated by comparing mean doses to target and non-target
volumes as well as by means of gamma evaluation. The non-target sCT-CT
dose difference was evaluated by computing the mean dose difference in
all sub-volumes of the dose matrix not overlapping the target. The
acceptance criteria was that 99% of cases should have no sub-volumes with
an sCT-CT dose difference in excess of 1.0 Gy or 5% of the CT-dose. Two
variations of gamma evaluation were conducted; one focusing on the high
dose area (cut off at 75% of the maximum dose) and the other considering
also the medium dose regions (cut off at 25% of the maximum dose). In the
high dose gamma a 3%/3mm criteria was used for the pelvic and head-neck
anatomical regions, while a 2%/2mm criteria was used for brain cases. The
gamma index passing rate requirement was 99% for pelvis and head-neck,
and 98% for brain. In the medium dose range gamma evaluation the stricter
2%/2mm criteria was used for all anatomical regions, while requiring a
99% gamma index passing rate.
The average sCT-CT mean target dose difference was found to be 0.02% ±
0.31% and -0.02% ± 0.25% for the anatomical regions pelvis, and head-
neck and brain, respectively. No cases displayed any sub-volumes with
sCT-CT dose differences in excess of 5% or 1.0 Gy.
At least 95% of cases met the passing criteria across all gamma evaluations
and anatomical regions. In the high dose gamma evaluation, 100.0% of
cases passed the individual passing rate criterion for all anatomical regions,
while the average gamma index passing rate was 99.9%, 99.8% and 99.8%
for pelvis, head neck and brain, respectively. In the medium dose gamma
evaluation, 98.3% and 100.0% of cases passed the individual passing rate
criterion for pelvis, and head-neck and brain, respectively, while the
average gamma index passing rate was 99.7%, 99.5% and 99.9% for pelvis,
head neck and brain, respectively.
Dosimetric bench test data for pelvis consisted of MR (T2w) and CT
images for 58 unique pelvis cancer patients acquired in the treatment
position at six different hospitals. Patient distribution was 16% female and
84% male, age range 51-88 years, 41% of patient images were acquired in
the US and 59% outside the US.


Dosimetric bench test data for head-neck-brain consisted of MR (T1-
Dixon) and CT images for 75 unique head-neck-brain cancer patients
acquired in the treatment position at four different hospitals. Patient
distribution was 39% female and 64% male, age range 41-85 years, 55% of
patient images were acquired in the US and 45% outside the US.
MRI data was acquired at six different MRI scanner models, from two
different vendors, with field strengths of 1.5T and 3T.
Auto contouring bench test
The conducted bench tests evaluates the automatically generated prostate
patient delineations (of bladder, colon and femoral heads) against manual
delineations, using two common metrics; Dice score (DSC) and 95%
Hausdorff distance (HD).
The average DSC was found to be 0.95 ± 0.03, 0.90 ± 0.04 and 0.96 ± 0.01
for bladder, colon and femoral head delineations, respectively. The average
95% HD was found to be 2.69 ± 1.82, 4.96 ± 3.91 and 2.04 ± 0.49 for
bladder, colon and femoral head delineations, respectively.
Auto contouring bench test data for prostate cancer patients consisted of
MR (T2w) images for 51 unique male prostate cancer patients acquired in
the treatment position at five different hospitals, together with manually
generated delineations of bladder, colon and femoral heads. Patient age
range was 51-88 years, 39% of patient images were acquired in the US and
61% outside the US.
Manual delineations were generated by two expert truthers using the
consensus approach, based on US clinical guidelines. The manual
delineations for the bench tests were generated at a separate time from the
generation of the training dataset. The truthers were involved in the
development of the product and the generation of the training dataset, but
not in the training and tuning of the segmentation model. Both truthers
were employed by the manufacturer at the time of performing the manual
delineations for the bench test.

Non-clinical test summary and
conclusion

MRI Planner complies with the following international and FDA-
recognized consensus standards:
ISO 14971 Second edition 2007-03-01
Medical devices – Application of risk management to medical devices
IEC 62304 Edition 1.1 2015-06
CONSOLIDATED VERSION Medical device software – Software life
cycle processes
IEC 62366-1:2015
Medical devices – Part 1: Application of usability engineering to medical
devices
IEC 82304-1 Edition 1.0 2016-10
Health software – Part 1: General requirements for product safety
Non-clinical verification and validation tests have been performed


Multiple detector ring size
configurations (15, 20, 25 cm axial
FOV)

Multiple detector ring size
configurations (15, 20, 25, 30 cm
axial FOV).

Detector Unit
SiPM-based light sensor with ASIC
Same

LYSO scintillator crystal
LYSO or LGSO scintillator crystals

Revolution EVO - Full suite of cleared
CT application software with
modifications (K131576)

Revolution EVO - Full suite of cleared
CT application software with
modifications including Deep
Learning Image Reconstruction
(DLIR) K193170

Whole body dynamic acquisition
capability enabled by manually
performing multiple passes that are
also referred as static scans of a
patient

Whole body dynamic acquisition
capability with automation to help
the user to perform the scan with
adequate user interface and
dedicated tools to improve the user
experience

Allows the operator to move the
patient table from the operator
console within the operator room,
rather than from the gantry control
panel for landmarking

510(k) Premarket Notification Submission


RSL-D-RS-11.0 510(k) Summary RayStation 11.0


AAMI ANSI ES60601-1:2005/(R)2012 and A1:2012, C1:2009/(R)2012
and A2:2010/(R)2012 (Consolidated Text) Medical electrical equipment -
Part 1: General requirements for basic safety and essential performance
(IEC 60601-1:2005, MOD)

IEC60601-1-2: 2014(4th Edition) , Medical electrical equipment - Part 1-
2: General requirements for basic safety and essential performance - EMC

IEC 60601-2-37 Edition 2.0 2007, Medical electrical equipment – Part 2-
37: Particular requirements for the basic safety and essential performance
of ultrasonic medical diagnostic and monitoring equipment

AAMI / ANSI / ISO 10993-1:2009/(R)2013, Biological evaluation of
medical devices – Part 1: Evaluation and testing within a risk management
process

ISO 14971:2007, Medical devices - Application of risk management to
medical devices

NEMA UD 2-2004 (R2009) Acoustic Output Measurement Standard for
Diagnostic Ultrasound Equipment Revision 3


883 Santa Cruz Ave, Suite 205
Menlo Park, CA 94025

Trade name: SubtlePET
Manufacturer: Subtle Medical, Inc.
Regulation Number: 21 CFR 892.1200
Regulation Name: Emission computed tomography
system
Device Class: Class II
Product Codes: KPS, LLZ
510(k) Number: K182336
510(k) Clearance Date: November 30, 2018


Predicate Device
Subject Device
Differences

SubtlePET is an image
processing software
intended for use by
radiologists and nuclear
medicine physicians for
transfer, storage, and noise
reduction of
fluorodeoxyglucose (FDG)
and amyloid PET images
(including PET/CT and
PET/MRI).”

SubtlePET is an image
processing software
intended for use by
radiologists and nuclear
medicine physicians for
transfer, storage, and
noise reduction of
fluorodeoxyglucose
(FDG), amyloid, 18F-
DOPA, 18F-DCFPyL, Ga-
68 Dotatate, and Ga-68
PSMA radiotracer PET
images.

Substantially similar. The
subject device IFU
removes reference to
PET/CT and PET/MRI
images as the specific
models for those images
have been removed, while
listing additional tracers to
reflect the update of the
main machine learning
model for PET images to
accommodate those
tracers.


Software package that operates on
off-the-shelf hardware

The software processes DICOM
compliant image data

The software employs a
convolutional neural network-
based method in a pixel’s
neighborhood to generate the
value for each pixel.
Using a residual learning
approach, the software predicts
the noise components and
structural components. The
software separates these
components, which enhances the
structure while simultaneously
reducing the noise.

fluorodeoxyglucose (FDG),
amyloid, 18F-DOPA,
18F-DCFPyL, Ga-68 Dotatate,
Ga-68 PSMA

Table 3. Summary of Technological Characteristics Comparison.


Operating system
MS Windows 10
MS Windows 10

Automatic and manual
segmentation of object

Safety - For use only by a
licensed professional

conclude that Segment 3DPrint is substantially equivalent to the predicate device.


signed distance difference, and 95th is the 95th percentile of the absolute distance.


GE Healthcare (Tianjin) Company Limited
No. 266 Jingsan Road, Tianjin Airport Economic Area
Tianjin, P.R. China 300308

GE Medical Systems, LLC
3200 N Grandview BLVD. Waukesha, WI USA 53188

Glen Sabin
Director, Regulatory Affairs
GE Healthcare
Phone: 262- 5216848
E-mail: glen.sabin@ge.com

Huande Li
Regulatory Affairs Manager
GE Healthcare
Phone: 86-010-57083027
E-mail: huande.li@ge.com

Magnetic Resonance Diagnostic Device per 21 CFR
892.1000

In accordance with 21 CFR 807.92 the following summary of information is provided:


SIGNA™ Prime is a whole body magnetic resonance scanner
designed to support high resolution, high signal to-noise ratio, and
short scan times. The systems use a combination of time-varying
magnet fields (Gradients) and RF transmissions to obtain
information regarding the density and position of elements
exhibiting magnetic resonance. The system can image in the
sagittal, coronal, axial, oblique, and oblique planes, using various
pulse sequences, imaging techniques and reconstruction
algorithms. The system features a 1.5T superconducting magnet
with 60cm bore size. The system is designed to conform to NEMA
DICOM standards (Digital Imaging and Communications in
Medicine).

The SIGNA Prime is a whole body magnetic resonance scanner
designed to support high resolution, high signal-to-noise ratio, and
short scan times. It is indicated for use as a diagnostic imaging
device to produce axial, sagittal, coronal, and oblique images,
spectroscopic images, parametric maps, and/or spectra, dynamic
images of the structures and/or functions of the entire body,
including, but not limited to, head, neck, TMJ, spine, breast, heart,
abdomen, pelvis, joints, prostate, blood vessels, and
musculoskeletal regions of the body.
Depending on the region of interest being imaged, contrast agents
may be used. The images produced by SIGNA Prime
reflect the spatial distribution or molecular environment of nuclei
exhibiting magnetic resonance.
These images and/or spectra when interpreted by a trained
physician yield information that may assist in diagnosis.

The SIGNA™ Prime employs the same fundamental scientific
technology as its predicate devices.
SIGNA™ Prime builds on the 1.5T IPM magnet, newly designed
Gradient Driver, new designed RF transmit architecture, new


The changes in technology do not impact the indications for use.
The indications for use have not changed, other than to reflect the
SIGNA™ Prime product name.
Therefore, the intended use is the same as the predicate device in
accordance with the FDA’s guidance document “The 510(k)
Program: Evaluating Substantial Equivalence in Premarket
Notifications [510(k)]”, dated 28 July 2014.

Comparison of
Technological
Characteristics

Overall, the SIGNA™ Prime employs the same fundamental
scientific technology as the predicate device.
System Design: There are five notable technological differences
between the SIGNA™ Prime and the predicate device: the 1.5T
IPM magnet, newly designed Gradient Driver, new designed RF
transmit architecture, new designed RF receiving chain and
new software platform application suite.
Operating Principles: The SIGNA™ Prime functions using the
same operating principles as the predicate device.
Materials: The SIGNA™ Prime and the predicate device both use
flame retardant materials.
Safety and Performance Testing: Both the SIGNA™ Prime and
the predicate device comply with the same safety and performance
testing (see Determination of Substantial Equivalence, below).
These technological differences do not raise any different
questions regarding safety and effectiveness. Both devices must
address questions of whether they provide an adequate level of
image quality appropriate for diagnostic use. The performance
data described in this submission include results of both bench
testing and clinical testing that show the image quality
performance of SIGNA™ Prime compared to the predicate device.


The sample clinical images demonstrate acceptable diagnostic
image performance of the SIGNA™ Prime in accordance with the
FDA Guidance “Submission of Premarket Notifications for
Magnetic Resonance Diagnostic Devices” issued on November 18,
2016. The image quality of the SIGNA™ Prime is substantially
equivalent to that of the predicate device.
Substantial Equivalence Conclusion:
The indications for use of the proposed device are comparable to
the claimed predicate device. The SIGNA™ Prime employs
equivalent technology to the claimed predicate device.
Additionally, the results from the above non-clinical tests
demonstrate that the device performs as intended. Therefore, the
SIGNA™ Prime is substantially equivalent to the predicate device
to which it has been compared.

In conclusion, GE Healthcare considers the SIGNA™
Prime to be as safe, as effective, with performance that
is substantially equivalent to the predicate device.


Trade/Proprietary Name:
UNiD Sp
ine Analyz


MEDICREA UNiD™ Spine Analyzer v4.0
MEDICREA UNiD™ Spine Analyzer v2.0

Manufacturer
MEDICREA International, Inc.
MEDICREA International, Inc.

510(k) Number
To be determined
K180091 (Special)

Medical Image Management and
Processing System (MIMPS)

Picture Archiving and Communication
System (PACS)

Regulation Number
21 CFR §892.2050
21 CFR §892.2050

The UNiD Spine Analyzer is intended
for assisting healthcare professionals
in viewing and measuring images as
well as planning orthopedic surgeries.
The device allows surgeons and service
providers to perform generic, as well
as spine related measurements on
images, and to plan surgical
procedures. The device also includes
tools for measuring anatomical
components for placement of surgical
implants. Clinical judgment and
experience are required to properly
use the software.

Operating System
Windows + MAC
Windows + MAC

Table 5A – Substantial Equivalence Comparison


The measurement panel allows a user
to view the measured values of each
tool. The device allows surgeons and
service providers to perform generic,
as well as spine related measurements
on images, and to plan surgical
procedures. The device also includes
tools for measuring anatomical
components for placement of surgical
implants. Complementary to the pre-
op measure, this panel also displays
the simulated values and shows the
normative value. Quality for the
measurement is given coloring, the
simulated values depending on
reference values.

MEASURING TOOLS: Contains all
measurement tools (angle, LLordo,
line, circle, pelvic, T1SPi, SVA)
New features internally documented
and released include SA Analysis,
Sagittal wizard, Coronal wizard,
Transitional anatomy, Cervical, Lenke
classification, and Guide spline.

MEASURING TOOLS: Contains all
measurement tools (angle, LLordo,
line, circle, pelvic, T1SPi, SVA).

SURGICAL TOOLS: Contains all surgery
tools (wedge, open, resect)
New features internally documented
and released include wedge auto,
open auto, and resect auto surgical
tools.

SURGICAL TOOLS: Contains all surgery
tools (wedge, open, resect).

IMPLANTS: Contains all implants (UNiD
Rod, cage, cage selection, screw, screw
selection).
New features internally documented
and released include UNiD Rod Auto,
cage auto, screw wizard, and postop
screw.


The subject device update also
includes the addition of a selection of
implant templates among a
preselected database of Medtronic
standard implants cleared in in the
following 510(k)s: K073291, K083026,
K091813, K100175, K110543, K113528,
K120368, K150135, K152277, K172199,
K172328, and K201267.

Human intervention
for interpretation and
manipulation of
images

Reference
information provided
to user during surgical
planning

Display of reference data to user
during surgery planning:
Normative data
Predictive model outputs from one of
three predictive models, depending on
procedure type (degenerative, adult
deformity, pediatric deformity)


QLAB
Voluson
Follicle Clarity
Equivalence

(Predicate Device)
(Reference Device)
(Subject Device)
Description

QLAB Advanced
Quantification Software
13.0

Voluson E6/E8/
E8Expert/E10 Diagnostic
Ultrasound System

Picture Archiving and
Communications
System

-Ultrasonic Pulsed Doppler
Imaging System
-Ultrasonic Pulsed Echo
Imaging System
-Diagnostic Ultrasound
Transducer

QLAB Advanced
Quantification Software
is a software application
package. It is designed
to view and quantify
image data acquired on
Philips ultrasound
systems.

The device is a general-
purpose ultrasound system.
Specific clinical
applications remain the
same as previously
cleared: Fetal/OB,
Abdominal (including
GYN, pelvic and infertility
monitoring/follicle
development); Pediatric;
Small Organ (breast,
testes, thyroid, etc.);
Neonatal and Adult

Follicle Clarity Software
is a software application
package. It is designed to
view and quantify image
data acquired on
compatible ultrasound
systems.

Same2
Predicate and
subject devices are
software intended to
quantify image data
on compatible
ultrasounds.
The subject device
intended use is the
same as the
SonoAVC software
included in the
reference device.

Table 1: Overview of Substantial Equivalence


Cephalic; Cardiac (adult
and pediatric); Musculo-
skeletal Conventional and
Superficial; Peripheral
Vascular; Transvaginal;
Transrectal; and
Intraoperative (abdominal,
PV and neurological).1

QLAB software
includes multiple
features for automated
detection and
measurement of
structures in
gynecological,
obstetrics, cardiac, and
other clinical
applications. K191647
describes the particular
application for
measuring cardiac
structures within the
ultrasound images using
automatic segmentation
technology. The
software utilizes
“locked” (non-adaptive)
machine learning
algorithms to identify
the contours of the
targeted structure within
the ultrasound image.
A report of
measurement data is
displayed.

SonoAVC software detects
hypoechoic structures (i.e.,
follicles) in transvaginal
ultrasound images and
measures their size. The
software utilizes
algorithms to identify the
contours of the targeted
structure within the
ultrasound image. A
report of measurement
data is displayed.

Follicle Clarity software
detects hypoechoic
structures (i.e., follicles)
in transvaginal ultrasound
images and measures
their size. The application
measures structures
within the ultrasound
images using automatic
segmentation technology.
The software utilizes
“locked” (non-adaptive)
machine learning
algorithms to identify the
contours of the targeted
structure within the
ultrasound image. A
report of measurement
data is displayed.

Equivalent
All of the software
systems utilize
proprietary
algorithms to detect
and quantify
structures within
ultrasound images.
Subject and
predicate devices
utilize machine
learning/AI
algorithms to
identify specific
contours of the
anatomy using
automatic
segmentation
technology and
quantify structures
based on this
analysis.
Subject and
reference devices
specifically detect
and analyze follicle
number and size.

Software application
(SonoAVC software is
supplied with the Voluson
ultrasound hardware)

Required Patient
Clinical Data
(Imaging) Format

-Voluson, E6, E8, E10
-Philips
-Siemens Acuson
Version

Equivalent
Subject device has
been validated to
process ultrasound
images from Philips
and Voluson
ultrasound systems
and others.


(Predicate Device, K193170)
(Proposed Device)

Utilizes a dedicated Deep Neural
Network (DNN) which was
trained on the Revolution family
CT Scanners and designed
specifically to generate high
quality CT images

Select recon type and strength
(Low, Medium, High).

Using the same Reference
protocols provided on the
Revolution EVO system for
ASiR-V

Using the same Reference
protocols provided on the
Revolution Ascend system for
ASiR-V

Image noise, low contrast
detectability, spatial resolution,
and low signal artifact
suppression as good or better
than ASiR-V on Revolution EVO

Image noise, low contrast
detectability, spatial resolution,
and low signal artifact
suppression as good or better
than ASiR-V on Revolution
Ascend

510(k) Premarket Notification Submission – DLIR


Medical Image Management and Processing System

ClariPi Inc.
3F, 70-15, Ihwajang-gil, Jongno-gu
Seoul, Korea, Republic of [03088]

equivalent to the following commercially available software:


ClariCT.AI, is a software device
intended for networking,
communication, processing and
enhancement of CT images in
DICOM format regardless of the
manufacturer of CT scanner or
model.

Noise reduction is performed with the
use of pre-trained deep learning
models.

Window Operating System,
PC Hardware, CUDA supported
graphics card or equivalent.

Window or Linux Operating System.
PC Hardware supported graphics
card or equivalent.

and the subject device is identical in performance to the legally marketed device.


Classification Name
21 CFR Number
Product Code

Ultrasonic Pulsed Doppler Imaging System

Ultrasonic Pulsed Echo Imaging System
892.1560
IYO

Diagnostic Ultrasound Transducer
892.1570
ITX

Traditional 510(k) Premarket Notification – Kosmos


Kosmos is intended to be
used by qualified and
trained healthcare
professionals in the
clinical assessment for
the following clinical
applications by acquiring,
processing, displaying,
measuring, and storing
ultrasound images, or
synchronized ultrasound
images,
electrocardiogram (ECG)
rhythms, and digital
auscultation (DA) sounds
and waveforms.
With respect to its
ultrasound imaging
capabilities, Kosmos is a
general purpose
diagnostic ultrasound
system used in the
following clinical
applications and modes
of operation:
• Clinical
Applications:
Cardiac,
Thoracic/Lung,
Abdominal,
Vascular/Peripheral
Vascular,
Musculoskeletal, and
interventional
guidance (includes
needle/catheter
placement, fluid
drainage, and nerve
block)
• Modes of Operation:
B-mode, M-mode,
Color Doppler,
Pulsed-Wave (PW)
Doppler,
Continuous-Wave
(CW) Doppler,
Combined Modes of
B+M, and B+CD,
B+PW, B+CW, and
Harmonic Imaging
Kosmos is intended to be
used in clinical care and
medical education
settings on adult and
pediatric patient
populations.

Kosmos is intended to be
used by qualified and
trained healthcare
professionals in the clinical
assessment of the cardiac
and pulmonary systems and
the abdomen by acquiring,
processing, displaying,
measuring, and storing
synchronized ultrasound
images, electrocardiogram
(ECG) rhythms, and digital
auscultation (DA) sounds
and waveforms.
With respect to its
ultrasound imaging
capabilities, Kosmos is a
general purpose diagnostic
ultrasound system used in
the following clinical
applications and modes of
operation:
• Clinical Applications:
Cardiac,
Thoracic/Lung,
Abdominal, Peripheral
Vascular, and Image
Guidance for
Needle/Catheter
Placement
• Modes of Operation:
B-mode, M-mode,
Color Doppler,
Combined Modes of
B+M and B+CD, and
Harmonic Imaging
Kosmos is intended to be
used in clinical care and
medical education settings
on adult and pediatric
patient populations. The
device is non-invasive,
reusable, and intended to
be used on one patient at a
time.
Type of Use: Prescription
Use (Part 21 CFR 801
Subpart D)

Vscan Air is a battery-
operated software-based
general-purpose
ultrasound imaging
system for use by
qualified and trained
healthcare professionals
or practitioners that are
legally authorized or
licensed by law in the
country, state or other
local municipality in
which he or she practices.
The users may or may not
be working under
supervision or authority
of a physician. Users may
also include medical
students working under
the supervision or
authority of a physician
during their education /
training. The device is
enabling visualization and
measurement of
anatomical structures and
fluid including blood
flow.
Vscan Air’s pocket-sized
portability and simplified
user interface enables
integration into training
sessions and examinations
in professional healthcare
facilities (ex. Hospital,
clinic, medical office),
home environment,
road/air ambulance and
other environments as
described in the user
manual. The information
can be used for
basic/focused assessments
and adjunctively with
other medical data for
clinical diagnosis
purposes during routine,
periodic follow-up, and
triage.
Vscan Air supports Black/
white (B-mode), Color
flow (Color doppler),
Combined (B + Color
Doppler) and Harmonic
imaging modes with both
the curved and linear

Addition of the following
Clinical Applications:
• Vascular
• Musculoskeletal
• Fluid Drainage
• Nerve Block
Addition of the following
modes of operation:
• Pulsed-Wave (PW)
Doppler
• Continuous-Wave
(CW) Doppler
• Combined Modes of
B+PW and B+CW


The device is non-
invasive, reusable, and
intended to be used on
one patient at a time.
Type of Use:
Prescription Use (Part 21
CFR 801 Subpart D)

array transducers.
With the curved array
transducer of the dual
headed probe solution, the
specific clinical
applications and exam
types include: abdominal,
fetal/obstetrics,
gynecological, urology,
thoracic/lung, cardiac
(adult and pediatric, 40 kg
and above),
vascular/peripheral
vascular, musculoskeletal
(conventional), pediatrics,
interventional guidance
(includes free hand
needle/catheter
placement, fluid drainage,
nerve block and biopsy).
With the linear array
transducer of the dual
headed probe solution, the
specific clinical
applications and exam
types include:
vascular/peripheral
vascular, musculoskeletal
(conventional and
superficial), small organs,
thoracic/lung, ophthalmic,
pediatrics, neonatal
cephalic, interventional
guidance (includes free
hand needle/catheter
placement, fluid drainage,
nerve block, vascular
access and biopsy).
Type of Use: Prescription
Use (Part 21 CFR 801
Subpart D)

Ultrasound Substantial Equivalence (Technological Characteristics)


Phased Array
Transducer:
Anatomy/ Region of
Interest:
• Abdominal
• Pediatric
• Cardiac Adult
• Cardiac Pediatric
• Peripheral Vascular
• Thoracic/Lung
Interventional Guidance:
• Nonvascular

Phased Array
Transducer:
Anatomy/ Region of
Interest:
• Abdominal
• Pediatric
• Cardiac Adult
• Cardiac Pediatric
• Peripheral Vascular
• Thoracic/Lung
Interventional Guidance:
Nonvascular

Linear Array
Transducer:
Anatomy/ Region of
Interest:
• Vascular/Peripheral
Vascular
• Musculoskeletal
Interventional guidance
• Needle/catheter
placement
• Fluid drainage
• Nerve block

Linear Array
Transducer:
Anatomy/ Region of
Interest:
• Vascular/peripheral
vascular
• Musculoskeletal
(conventional and
superficial)
• Small organs
• Thoracic/lung
• Ophthalmic
• Pediatrics
• Neonatal cephalic
Interventional guidance
• Free hand
needle/catheter
placement
• Fluid drainage
• Nerve block
• Vascular access and
biopsy

Addition of Linear Array
Transducer Clinical
Applications

Phased Array
Transducer:
1.5 – 4.5 MHz with center
frequency 3Hz

Linear Array
Transducer:
4-11 MHz with center
frequency 7.5 MHz

Linear Array
Transducer :
3-12 MHz with center
frequency of 7.7 MHz

Addition of technological
characteristics for Linear
Array Transducer

Phased Array
Transducer:
• B-mode
• M-mode
• Color Doppler

Addition of the following
modes of operation:
• Pulsed-Wave (PW)
Doppler
• Continuous-Wave


• Pulsed-Wave (PW)
Doppler
• Continuous-Wave
(CW) Doppler
• Combined Modes:
B+M, B+CD,
B+PW, and B+CW
• Harmonic Imaging

• Combination Modes:
B+M, B+CD
• Harmonic Imaging

(CW) Doppler
• Combined Modes:
B+PW and B+CW

Linear Array
Transducer:
• B-mode
• Color Doppler
• Combined Modes of
B + CD
• Harmonic Imaging

Addition of Linear Array
Transducer B-mode

DA (Digital Auscultation) and ECG Substantial Equivalence (Technological Characteristics)

Audio microphone +
digital signal processing
Sampling Rate: 12.7 kHz

Analog gain: 20 dB
Digital gain: user
adjustable up to 25 dB

Sounds can be listened to
in real time using a
digital-to-analog binaural
headset

3-lead, single-channel,
user-supplied commercial
electrodes


Combines trunk cable and
three leadwires into a
single, non-sterile,
reusable assembly that
forms a conduction
channel for transmitting
signals from user-supplied
clip-style electrodes
affixed to patient skin to
the Thor probe

Sounds and ECG
waveforms can be
visualized and recorded
on the Thor tablet with or
without an internet
connection

Handheld tablet display
unit (proprietary) –
Kosmos Bridge
• Height: 146 mm
• Width: 216mm
• Depth: 59mm
• Weight: 657g
Kosmos Torso Probe
(Phased Array – ECG,
DA, and Ultrasound)
• Height: 150mm
(excluding cable (the
hard plastic housing
length))
• Width: 56mm
• Depth: 35mm
• Weight: 290 grams
(with ferrite-
equipped cable)
• Cable dimensions:
1.8 meters
Kosmos Torso-One Probe
(Phased Array –
Ultrasound Only)
• Height: 150 mm
(excluding cable (the
hard plastic housing
length))
• Width: 56 mm
• Depth: 35 mm
• Weight: 275 grams
(with ferrite-
equipped cable)
• Cable dimensions:

Handheld tablet display
unit (proprietary) –
Kosmos Bridge
• Height: 146 mm
• Width: 216mm
• Depth: 59mm
• Weight: 657g
Kosmos Torso Probe
• Height: 150mm
(excluding cable (the
hard plastic housing
length))
• Width: 56mm
• Depth: 35mm
• Weight: 290 grams
(with ferrite-equipped
cable)
• Cable dimensions: 1.8
meters

Dimension and weight
(maximum)
• Length: 131
• Width: 64
• Height: 31
• Weight: 205 +/- 3g
Linear Array Transducer
• Footprint: 40 mm x 7
mm (lens)

Addition of the following
transducers:
• Kosmos Torso-One
(Ultrasound-Only
Probe)
• Kosmos Torso-One
– USB (Ultrasound-
Only Probe)
• Kosmos Lexsa
(Linear Probe)


1.8 meters
Kosmos Torso-One Probe
USB (Phased Array –
Ultrasound Only)
• Height: 150 mm
(excluding cable (the
hard plastic housing
length))
• Width: 56 mm
• Depth: 35 mm
• Weight: 267 grams
(with ferrite-
equipped cable)
• Cable dimensions:
1.5 meters
Kosmos Lexsa Probe
(Linear Array)
• Height: 150 mm
(excluding cable (the
hard plastic housing
length))
• Width: 56 mm
• Depth: 35 mm
• Weight: 275 grams
(with ferrite-
equipped cable)
• Cable dimensions:
1.8 meters

Mains and battery
operated (rechargeable
lithium ion battery)

Probe and ECG
Leadwires materials are
biocompatible

Probe and ECG Leadwires
are biocompatible

• Kosmos Bridge:
IP22
• All Probes: IPX7

• Kosmos Bridge: IP22
• Torso Probe: IPX7

• IEEE 802.11
a/b/g/n/ac
• Bluetooth 4.2 or later


CISPR 11:2015+
AMD1:2016+AMD2:2019
CSV Consolidated version

Industrial, scientific and medical equipment -
Radio-frequency disturbance characteristics -
Limits and methods of measurement

Medical electrical equipment - Part 1: General
requirements for basic safety and essential
performance (IEC 60601-1:2005, MOD)

Medical electrical equipment - Part 1-2:
General requirements for basic safety and
essential performance - Collateral Standard:
Electromagnetic disturbances - Requirements
and tests

Medical electrical equipment - Part 1-6:
General requirements for basic safety and
essential performance - Collateral standard:
Usability

Medical electrical equipment - Part 2-37:
Particular requirements for the basic safety and
essential performance of ultrasonic medical
diagnostic and monitoring equipment

Biological evaluation of medical devices - Part
1: Evaluation and testing within a risk
management proce

Medical devices - Application of risk
management to medical devices

62304 Edition 1.1 2015-06
CONSOLIDATED
VERSION

Medical device software - Software life cycle
processes

Medical devices - Part 1: Application of
usability engineering to medical devices
[Including CORRIGENDUM 1 (2016)]

Medical devices - Symbols to be used with
medical device labels, labelling, and
information to be supplied - Part 1: General
requirements

characteristics as the predicate devices.


62359 Edition 2.1 2017-09
CONSOLIDATED
VERSION

Ultrasonics - Field characterization - Test
methods for the determination of thermal and
mechanical indices related to medical
diagnostic ultrasonic fields

Acoustic Output Measurement Standard for
Diagnostic Ultrasound Equipment Revision 3

ANSI AAMI
EC53:2013
ECG trunk cables and patient leadwires

Principles for medical device security - Risk
management.

A Compendium Of Processes, Materials, Test
Methods, And Acceptance Criteria For
Cleaning Reusable Medical Devices


Contact Person:
Vicki Lin (Regulatory Specialist)

Date Summary Prepared:
September 10, 2021


Radiological Image Processing Software for
Radiation Therapy

Regulation Number / Product Code:
21 CFR 892.2050 / QKB


Device Name
VBrain-OAR
AccuContour™
iPlan

VBrain-OAR is a
software device intended
to assist trained
radiotherapy personnel

It is used by radiation
oncology department to
register multimodality
images and segment
(non-contrast) CT

iPlan's indications for
use are the viewing,
presentation and
documentation of
medical imaging,

Table 5-1. Comparison with the Predicate and Reference Devices.