Predicate Device:
Arterys Oncology DL
(K173542)

Platform
Chrome Desktop
Client-server, Chrome Desktop

Pan, zoom, rotate, slice scroll (view
multiple slices)
Adjust window level, minimize/maxi-
mize
Orientation labels, scroll sync, ruler

Pan, zoom, rotate, slice scroll (view
multiple slices)
Adjust window level, minimize/maxi-
mize
Orientation labels, cross-reference in-
dicator

Image Display Modes
Yes, static
Yes, static and cine

Can select a viewport layout
and add series to it

3D Image Review
Yes, 3D review of segmented region
Yes, 3D review of the full image

Yes, available only for MR prostate
studies

Yes, available only for lung CT and
liver MR studies


densitas densityai
 ™
(formerly DM-Density )
™


Densitas densityai is a
 ™
software application intended
for use with compatible full
field digital mammography and
digital breast tomosynthesis
systems. Densitas densityai
 ™
provides an ACR BI-RADS Atlas
5th Edition breast density
category to aid interpreting
physicians in the assessment of
breast tissue composition.
Densitas densityai produces
 ™
adjunctive information. It is not
a diagnostic aid.

DM-Density is a software
application intended for use
with compatible full field digital
mammography
systems. DM-Density calculates
percent breast density defined
as the ratio of fibroglandular
tissue to total
breast area estimates.
DM-Density provides these
numerical values for each
breast as well as a density
category to aid interpreting
physicians in the assessment of
breast tissue composition.
DM-Density produces
adjunctive information. It is not
a diagnostic aid.

Addition of breast
tomosynthesis
systems

Symptomatic and
asymptomatic women
undergoing mammography

End Users
Interpreting Physicians
Interpreting Physicians

FFDM
Hologic Selenia Dimensions
Hologic Lorad Selenia
GE Senographe Essential
GE Senographe Pristina
Siemens MAMMOMAT
Inspiration
Siemens MAMMOMAT
Novation DR
Siemens MAMMOMAT Fusion
Siemens MAMMOMAT
Inspiration Prime
Siemens MAMMOMAT
Revelation
Synthetic 2D
Hologic C-View

Addition of new FFDM
scan types and
synthetic 2d
compatibility

DICOM digital mammography
imager – For Presentation;
RCC, LCC, RMLO, LMLO

DICOM full field digital
mammography imager – For
Presentation; RCC, LCC, RMLO,
LMLO

BI-RADS 4th Ed.
For each breast:
● Area of fibroglandular tissue
(cm²)

Removed BI-RADS 4th
edition compatibility


For each patient: densitas
densityai breast density
 ™
grade

● Area of breast (cm²)
● Area-based breast density
(%)
For each patient: DM-Density
breast density grade and
percent breast density
BI-RADS 5th Ed.
For each patient: DM-Density
breast density grade

4-category breast density scale
from 5th  Ed. ACR BI-RADS Atlas

2013

4-category breast density scale
from 4th  Ed. ACR BI-RADS Atlas

2003

DICOM Structured Report and
Secondary Capture

Deployment
Standalone computer
Standalone computer

Data Throughput
600 cases per hour
600 cases per hour

Assessment scope
Results per image
Results per image

Adjusted to reflect
shift to image
feature-based
assessment type


Primary Predicate Device
Filtered Back Projection
(FBP) on uCT 760/780
(K172135)

Secondary Predicate
Device
Deep Learning Image
Reconstruction (K183202)

Utilizes a dedicated Deep
Neural Network (DNN)
which is trained on the CT
Scanner and designed
specifically to generate
high quality CT images

Dedicated deep neural
network (DNN) which is
trained on low dose FBP
images to get normal
dose (high quality) FBP
images

Select recon type and
convolution kernel

Select recon type,
convolution kernel and
strength (noise index
level)

7. Comparison of Technological Characteristics with the Predicate Devices


Aidoc 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).

RAPID ICH 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).

A table comparing the key features of the subject and predicate devices is provided below.


Aidoc 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 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
Aidoc 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.

RAPID ICH 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
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
RAPID ICH 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.

No, the device does not highlight or
direct a user’s attention to a specific
location in the image file.


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.


Classification Name:
Magnetic Resonance Diagnostic Device

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

Vantage Orian 1.5T, MRT-1550, V6.0 with AiCE Reconstruction
Processing Unit for MR


Vantage Orian 1.5T, MRT-1550, V6.0
Vantage Orian 1.5T, MRT-1550, V6.0

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


Predicate Device:
Vantage Orian 1.5T,
MRT-1550, V6.0 (K193021)

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

Allows screen access to 1st level
operating mode

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

Potential emergency
condition and means
provided for shutdown

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


Comparison of the primary currently marketed and predicate

device, MRCAT Pelvis versus the proposed MRCAT Brain

Device
Device
MRCAT Pelvis
MRCAT Brain
Similarities

MRCAT imaging is
intended to
provide the
operator with
information of
tissue properties
for radiation
attenuation
estimation
purposes
in photon external
beam radiotherapy
treatment
planning.


MRCAT Pelvis is
indicated for
radiotherapy
treatment
planning of soft
tissue cancers in
the pelvic region.

MRCAT Brain is
indicated for
radiotherapy
treatment
planning for
primary and
metastatic brain
tumor patients.

No significant
difference.
MRCAT Pelvis
and MRCAT
Brain are
both
indicated for
radiotherapy
treatment
planning in a
defined
region.
Brain tumors
are soft tissue
tumors.

No significant
difference
MR images
obtained in
the same
imaging
session are
inherently in
the same
frame of
reference.


Registration
between
primary and
secondary
image
datasets

Secondary mDixon
MR image, source
data to MRCAT, is
inherently
registered as part
of MRCAT
algorithm with
MRCAT image,
which simplifies
workflow.
Other MR images,
like T2w and
fiducial marker
detection images
are registered
using tools
available in RTP
system

Secondary mDixon
MR image, source
data to MRCAT, is
inherently
registered as part
of MRCAT
algorithm with
MRCAT image,
which simplifies
workflow.
Other MR images,
like T2w images
are registered
using tools
available in RTP
system

No significant
difference
Secondary
MR images
are obtained
in the same
imaging
session
reducing the
possibility of
patient
motion
between
images.

MRCAT image
intensity
information is
provided in
Hounsfield Unit
(HU) values.

No significant
difference.
MRCAT Pelvis
and MRCAT
Brain both
have
continuous
HU value
approach.

Conversion
from primary
image to
density
values used
in dose
calculation

Primary image HU
values are
converted to
densities through
density table
specific for the
MRCAT.

No significant
difference
MRCAT has
specific
density table
that is used in
a similar
manner to CT
specific
density
tables.

Bones are
segmented from
mDixon inphase
and water images
using model based

Bones are
segmented from
mDixon inphase
and water images
using machine

No significant
difference
Segmentation
is done for
both MRCAT


The simulated
dose based on
MRCAT images
shall not differ in
95% of prostate
cancer patients
(gamma analysis
criterion 3%/3mm
realized in 99% of
voxels within the
PTV or exceeding
75% of the
maximum dose)
when compared
with CT based
plan.
The average
simulated dose
based on MRCAT
images shall not
deviate more than
10% for voxels
exceeding 5Gy in
99% of the
indicated patients
in the volume of
sensitive organs
when compared
with CT based
plan.

The simulated
dose based on
MRCAT Brain
images shall not
differ in 95% of the
indicated patients
(gamma analysis
criterion 2%/2mm
realized in 98% of
voxels within the
PTV or exceeding
75% of the
maximum dose)
when compared
with CT‐based
plan.
The average
simulated dose
based on MRCAT
Brain shall not
deviate more than
5% or 1 Gy, which
ever is greater, in
99% of the
indicated patients
in the volume of
sensitive organs
when compared
with CT based
plan.

No significant
difference.
The same
dose
evaluation
methodology
is used for
both
products. The
criteria are
selected
based on the
needs of the
application.

MRCAT accuracy:
± 1 mm accuracy:
200 mm diameter
sphere
± 5 mm accuracy:
500 mm diameter
sphere (limited in
the bore direction
by +/‐ 160 mm
from the z=0 mm
plane )


Predicate Device, (K183202)
(Proposed Device)

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

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

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

Using the same Reference
protocols provided on the
Revolution EVO 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 CT

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

between the predicate device and the proposed device:


Transverse Resolution FWHM @ 1 cm
Pass
≤ 4.7 mm

Transverse Resolution FWHM @ 10 cm
Pass
≤ 5.5 mm

Transverse Resolution FWHM @ 20 cm
Pass
≤ 7.6 mm

Axial Resolution FWHM @ 1 cm
Pass
≤ 5.0 mm

Axial Resolution FWHM @ 10 cm
Pass
≤ 7.0 mm

Axial Resolution FWHM @ 20 cm
Pass
≤ 11.3 mm

Transverse Resolution FWHM @ 1 cm
Pass
≤ 7.3 mm

Transverse Resolution FWHM @ 10 cm
Pass
≤ 7.6 mm

Transverse Resolution FWHM @ 20 cm
Pass
≤ 8.9 mm

Axial Resolution FWHM @ 1 cm
Pass
≤ 6.1 mm

Axial Resolution FWHM @ 10 cm
Pass
≤ 7.3 mm

Axial Resolution FWHM @ 20 cm
Pass
≤ 11.9 mm

≥ 78 kcps @ ≤ 26 kBq/cc
≥ 135 kcps @ ≤ 26 kBq/cc (TrueV)

≥285 kcps @ ≤ 53 kBq/cc
≥ 465 kcps @ ≤ 42 kBq/cc (TrueV)

Scatter Fraction at peak NECR
Pass
≤ 40%

Image Quality (4 to 1) ‐ (% Contrast / Background Variability)


Anzai‐based OncoFreeze
Deviceless OncoFreeze

Volume (relative to static)
-34% ± 23%
-31% ± 19%

images comparing Anzai based gating and deviceless gating.


Difference from ground truth
Single Bed Scatter
Whole Body

In simulation study of phantom
Correction
Scatter correction

Representative region of interest close to
phantom exhibiting high signal

Representative region of interest close to
phantom exhibiting low signal

Representative region of interest inside
phantom

using Single Bed Scatter compared to whole body scatter correction.


Predicate Device 1
uMI 780 (K172143)
including a post-
smoothing function
for PET image
reconstruction

Predicate Device 2
uMI 550 (K182237)
including a post-
smoothing function
for PET image
reconstruction

Onsite on the facility
PET/CT
reconstruction
computer.

The post-smoothing
function uses
Gaussian filtering to
reduce the noise in

The software
employs a
convolutional
neural network

Gaussian
filtering
suppresses the
high frequency


Siemens AG Medical Solutions
Syngo.CT Lung CAD
K143196


Type of Change and Impact to
Safety & Effectiveness

Solid pulmonary nodules in diag-
nostic chest CT acquisitions

The LungCAD software device is a
Computer-Aided Detection (CAD)
tool designed to assist
radiologists in the detection of solid
pulmonary nodules during review of
multi-detector
computed tomographic (MDCT)
thoracic examinations. The software
is an adjunctive tool
that alerts the radiologist to regions
of interest (ROI) that may be initial-
ly overlooked. The
LungCAD software device use is
intended to be used as a second
reader after the radiologist has com-
pleted his/her initial read.


• The syngo.CT Lung CAD de-
vice is a computer-aided detec-
tion (CAD) tool designed to as-
sist radiologists in the detection
of solid pulmonary nodules dur-
ing review of multi-detector
computed tomography (MDCT)
examinations of the chest.
• The software is an adjunctive
tool to alert the radiologist to re-
gions of interest (ROI) that may
have been initially overlooked.
• The syngo.CT Lung CAD de-
vice is intended to be used as a
second reader after the radiolo-
gist has completed his/her initial
read.

Size
• Solid nodules ≥ 3mm and <
10mm
Locations
• full range: central, peripheral
Contours:
• round, irregular

Diameter
• Solid nodules ≥ 3mm and <
20mm
Locations
• full range: central, peripheral
Contours:
• round, irregular

Extended nodule size to 20mm.
No impact as assessed in the evi-
dence provided in the benchmark
analysis provided in this substan-
tial equivalence evaluation. At-
tachment 10 and 12


Reader workflow
second reader workflow
second reader workflow
[Unchanged] and no Impact

Scanners
Siemens multi-detector CT (MDCT)
scanners.

Scan area
The scan area needs to comprise the
entire thorax covering the lung api-
ces to the bases

Scan direction
Cranio-caudal or caudal-cranial

[Unchanged] and no Impact – no-
menclature updating only

Slice overlap
0–25%
Note: Reconstruction overlap is al-
lowed, but gaps are not permitted

Slice Overlap
0–25%
Note: Reconstruction overlap is al-
lowed, but gaps are not permitted

Number of images
Up to 1000 images per series.


Hosting Application
syngo MM Oncology
syngo MM Oncology
[Unchanged] and no Impact

Dose
Diagnostic
Diagnostic
[Unchanged] and no Impact


Preprocessing
Standardization of
the input images
and lung
segmentation

(a) isotropic volume resampling
(b) lung segmentation is performed on a slice-by-
slice approach by identifying the middle of the
lung area, then processing first the upper half of
the lung and then the lower half of the lungs. Slice
processing identifies starting points and traces the
lung contour, slice-by slice. This is followed by
contour smooth and filling.

(a) isotropic volume resampling
(b) lung segmentation is accomplished using a CCN. Initially a
coarse estimation of the lung is performed using a V-net
process. Using two predefined bounding boxes left and right
lungs are initialized. Another V-net is used to segment left and
right lungs. This is followed by up-sampling to the original
image resolution.

Candidate
Generation
Scans through all
slices of the
segmented lung to
search for

(a) isotropic volume is partitioned into subvolumes
(b) Each volume is processed using the divergence
of the 3D gradient field compute a “response vol-
ume” thresholded to yield a list of candidates.
Features are computed (e.g. number of voxels,
sphericity, maximum response value, etc.)
(c) Cascade 1: candidates are passed to two-way

(a) isotropic volume is partitioned into subvolumes
(b) Each subvolume is fed to a CNN to compute features
(“response volume”). Filtering and non-maximum suppression
yield a list of candidates for each subvolume
(c) Cascade 1: candidates above a certain threshold score are
passed to the next step.

Table 1 Summary of Differences between the Subject Device and the Predicate Device


Characteristic
Subject Device
Primary Predicate
Reference Device
Reference Device

Product Code
LLZ, JAK
LLZ, JAK
LLZ, JAK
LLZ

Review Panel
Radiology
Radiology
Radiology
Radiology

AVIEW LCS is intended for the review and analysis and reporting of thoracic CT images for the
purpose of characterizing nodules in the lung in a single study, or over the time course of several

tests, we conclude that the proposed device is substantially equivalent to the predicate devices.


thoracic studies. Characterizations include nodule type, location of the nodule and measurements
such as size (major axis, minor axis), estimated effective diameter from the volume of the nodule,
the volume of the nodule, Mean HU (the average value of the CT pixel inside the nodule in HU),
Minimum HU, Max HU, mass (mass calculated from the CT pixel value), and volumetric measures
(Solid Major; length of the longest diameter measured in 3D for a solid portion of the nodule. Solid
2nd Major: The length of the longest diameter of the solid part, measured in sections perpendicular
to the Major axis of the solid portion of the nodule), VDT (Volume doubling time), and Lung-RADS
(classification proposed to aid with findings). The system automatically performs the measurement,
allowing lung nodules and measurements to be displayed and, also integrate with FDA certified
Mevis CAD (Computer-aided detection) (K043617).

Lung Nodule Assessment and Comparison Option (LNA)

The Lung Nodule Assessment and Comparison Option is intended for use as a diagnostic patient-
imaging tool. It is intended for the review and analysis of thoracic CT images, providing quantitative
and characterizing information about nodules in the lung in a single study, or over the time course
of several thoracic studies. Characterizations include diameter, volume and volume over time. The
system automatically performs the measurements, allowing lung nodules and measurements to be
displayed.

The separately licensed Lung Analysis option is intended for the review and analysis of thoracic CT
images for the purpose of characterizing nodules in the lung in a single study, or over the time
course of several thoracic studies. Characterization include diameter, volume and volume over time.
The system automatically performs the measurement, allowing lung nodules and measurement to
be displayed.

AVIEW provides CT values for pulmonary tissue from CT thoracic datasets. This software can be
used to support the physician quantitatively in the diagnosis. Follow-up evaluation and
documentation of CT lung tissue images by providing image segmentation of sub-structures in the
left and right lung (e.g., the five lobes and airway), volumetric and structural analysis, density
evaluations and reporting tools. AVIEW is also used to store, transfer, inquire and display CT data
sets. AVIEW is not meant for primary image Interpretation in mammography.

Images can be scanned,
loaded from card
readers, or imported
from a radiographic
imaging device

Type of scans
Thoracic CT images
Thoracic CT images
Thoracic CT images

AVIEW LCS is intended for use as diagnostic patient imaging which is intended for the review and
analysis of thoracic CT images. Provides following features as semi-automatic nodule measurement
(segmentation), maximal plane measure, 3D measure and volumetric measures, automatic nodules
detection by integration with 3rd party CAD. Also provides cancer risk based on PANCAN risk
model which calculates the malignancy score based on numerical or Boolean inputs. Follow up
support with automated nodule matching and automatically categorize Lung-RADS score which is
a quality assurance tool designed to standardize lung cancer screening CT reporting and


management recommendations that is based on type, size, size change and other findings that is
reported.

The Lung Nodule Assessment and Comparison Option application is intended for use as a
diagnostic patient imaging tool. It is intended for the review and analysis of thoracic CT images,
providing quantitative and characterizing information about nodules in the lung in a single study,
or over the time course of several thoracic studies. The system automatically performs the
measurements, allowing lung nodules and measurements to be displayed. The user interface and
automated tools help to determine growth patterns and compose comparative reviews. The Lung
Nodule Assessment and Comparison Option application requires the user to identify a nodule and
to determine the type of nodule in order to use the appropriate characterization tool. Lung Nodule
Assessment and Comparison Option may be utilized in both diagnostic and screening evaluations
supporting Low Dose CT Lung Cancer Screening

Lung Analysis aids in measuring and characterizing lung nodules. The interface and automated tools
help to efficiently determine growth patterns and compose comparative reviews. Lung Analysis is
intended for the review and analysis of thoracic CT images for the purpose of characterizing nodules
in the lung in a single study, or over the time course of several thoracic studies. Characterizations
include diameter, volume and volume over time. The system automatically performs the
measurements, allowing lung nodules and measurements to be displayed. The Lung Analysis
Software requires the user to identify a nodule and to determine whether it is a GGO or solid nodule
in order to use the appropriate characterization too.

The AVIEW is a software product which can be installed on a PC. It shows images taken with the
interface from various storage devices using DICOM 3.0 which is the digital image and
communication standard in medicine. It also offers functions such as reading. Manipulation,
analyzing, post-processing, saving and sending images by using the software tools.

Providing ray sum
image, axial, sagittal,
coronal, and oblique
planes.

Providing axial,
sagittal, coronal, and
oblique planes

Rotating to Anterior,
Posterior, Left, Right,
Head, and Foot
direction

Providing VR (Volume
render), MIP
(Maximum Intensity
Projection), MinIP
(Minimum Intensity
Projection) image

Providing Average,
MIP, VIP, MinIP,
SurfaceMIP, Vol,
Rend.

Changing the color
and transparency of
the VR image by
adjusting the OTF
(Opacity Transfer
Function) and saving
as a preset to easily
apply in the VR
setting.

2D and 3D image
2D and 3D image
2D and 3D image
2D and 3D image


Segmentation of lung
airway, lungs and lung
lobes

Nodule Characteristics
Nodule Characteristics
Nodule Characteristics

Automatic calculation
of measurements for
each segmented nodule
 Size of the Major
axis and Minor
axis(mm)
 Diameter of Major
(3D), 2nd Major
(3D), Major(2D),
Minor(2D) (mm)
 Volume(mm³)
 Max, Min, Mean HU
of the nodule((HU)
 Cancer probability
(%)

Automatic calculation
of measurements for
each segmented nodule
 Short axis-Longest
diameter
perpendicular to the
long axis on the
slice(mm)
 Loung Axis-Longest
diameter on an axial
slice(mm)
 Average/Max
3D/Effective
diameter(mm)
 Volume(mm³) Mean
densities(HU)

Automatic calculation
of measurements for
each segmented nodule
 Volume(mm³)
 Mean
diameter(mm)
 Maximum
diameter(mm)
 Short axis
diameter(mm)
 Average/minimum/
maximum densities
(HU)

Comparison and
matching automatic
calculations between
each follow-up scan
and the baseline scan
 Doubling time in
days
 Indicated the change
of the size
 Auto generate Lung-
RADS

Comparison and
matching automatic
calculations between
each follow-up scan
and the baseline scan
 Doubling time in
days
 Percent (%) and
absolute change of
all numerical
parameters (growth
in nodule long axis,
short axis, average
diameter, max 3D
diameter, effective
diameter, volume,
mean HU)

Comparison and
matching automatic
calculations between
each follow-up scan
and the baseline scan
 Elapsed time in
days
 Doubling time in
days Percent (%)
growth in nodule
volume

Loading multiple
studies
Up to 3 studies

Workflow
 Detect and Segment
 Comparison and
Matching
 Results

Workflow
 Detect and Segment
 Point-and-click
detection
 Automated


 Results
Option to integrate
with 3rd party CAD
which automatically
detects the nodules and
generate report.

contouring
 Automated
measurements
 Manual correction

Reporting results
The results include the
following.
 Lung-RADS
 PANCAN risk
calculator
 Auto detect nodule
location by lobe

Reporting results
The results include the
following.
 Patient related
information
 Dictation Table with
Nodule result table
and additional
findings
 Lung-RADS
 Risk Calculator

Reporting results
The results include the
following.
 Dictation Table with
Nodule result table
 Lung-RADS
 Fleischer Criteria

Printing Option
Printing Option
Printing Option
Printing Option


Radiological Computer Assisted Detection and
Diagnosis Software

Classification regulation
21 CFR 892.2090


Device trade name
Transpara™ 1.3.0 (K181704)

Legal Manufacturer
ScreenPoint Medical B.V.


Standard ID
Standard Title
FDA Recognition #

Medical Devices - Application Of Risk
Management To Medical Devices

Medical Device Software - Software Life
Cycle Processes

Decision summary with special controls
for class II radiology device

voluntary FDA recognized standards and guidelines:


Sensitivity @435 keV LLD
Pass
≥ 8.0 cps/kBq
≥ 15.0 cps/kBq

Image Quality (4 to 1) - (% Contrast / Background Variability)

10mm sphere
Pass
≥ 55% / ≤ 10%
≥ 55% / ≤ 10%

13mm sphere
Pass
≥ 60% / ≤ 9%
≥ 60% / ≤ 9%

17mm sphere
Pass
≥ 65% / ≤ 8%
≥ 65% / ≤ 8%

22mm sphere
Pass
≥ 70% / ≤ 7%
≥ 70% / ≤ 7%

28mm sphere
Pass
≥ 75% / ≤ 6%
≥ 75% / ≤ 6%

37mm sphere
Pass
≥ 80% / ≤ 5%
≥ 80% / ≤ 5%

two configurations of the Biograph mCT, a 3-ring version and a 4-ring version.


Sensitivity @435 keV LLD
Pass
≥ 5.0 cps/kBq
≥ 9.4 cps/kBq

Count Rate peak trues
Pass
≥350 kcps @ ≤ 46 kBq/cc
≥575 kcps @ ≤ 40 kBq/cc

10mm sphere
Pass
≥ 10% / ≤ 10%
≥ 10% / ≤ 10%

13mm sphere
Pass
≥ 25% / ≤ 10%
≥ 25% / ≤ 10%

17mm sphere
Pass
≥ 40% / ≤ 10%
≥ 40% / ≤ 10%

22mm sphere
Pass
≥ 55% / ≤ 10%
≥ 55% / ≤ 10%

28mm sphere
Pass
≥ 60% / ≤ 10%
≥ 60% / ≤ 10%

37mm sphere
Pass
≥ 65% / ≤ 10%
≥ 65% / ≤ 10%


∆Volume (relative to static)
-34% ± 23%
-31% ± 19%


Difference from ground truth
In simulation study of phantom

Representative region of interest close to
phantom exhibiting high signal

Representative region of interest close to
phantom exhibiting low signal

Representative region of interest inside
phantom


Siemens
AI‐Rad Companion (Musculoskeletal)

AI‐Rad Companion (Musculoskeletal)
syngo.CT Bone Reading

AI‐Rad Companion (Musculoskeletal) is an image processing
software that provides quantitative and qualitative analysis from
previously acquired Computed Tomography DICOM images to
support radiologists and physicians from emergency medicine,
specialty care, urgent care, and general practice in the evaluation
and assessment of musculoskeletal disease.
It provides the following functionality:
 Segmentation of vertebras
 Labelling of vertebras
 Measurements of heights in each vertebra and indication
if they are critically different
 Measurement of mean Hounsfield value in volume of
interest within vertebra
Only DICOM images of adult patients are considered to be valid
input.

The syngo.CT Bone Reading is image analysis software for CT
volume data sets which has. been continuously acquired with
computed tomography (CT) imaging systems. The software
combines following digital image processing and visualization tools:
 multiplanar reconstruction (MPR) thin/thick, maximum
intensity projection (MIP) thin/thick, inverted MIP
thin/thick, volume rendering technique (VRT)
 geometric measurement tools (distance line, polyline,
marker, arrow, angle)
 HU measurement tools (Pixel lens, ROI circle, ROi
polygonal, ROI freehand, VOl sphere)
 curved MPR visualization (unfolded ribs and spine views),
crosssection MPRs
 tools for creation and editing of anatomical centerline
paths
 tools for creation and editing of anatomical labels
The specific visualizations of spine and rib structures allow for easy
manual identification and marking of pathologies such as bone
lesions or fractures.
Reporting and documentation of results is facilitated by using of
appropriate reporting tool, statistics and creation of ranges and
snapshots


Siemens AI‐Rad Companion
(Musculoskeletal)

Deep‐learning‐based
segmentation of vertebras

Distance measurements
based on segmentation
results and comparison with
neighboring measurements

Manual distance measurements
in vertebra and visual
comparison with neighboring
vertebra(s)

HU measurements based on
segmentation results

Table 1 Predicate Device Comparable Properties


Siemens AI‐Rad Companion
(Cardiovascular)
(K183268)

Deep Image‐to‐image network
for 3D segmentation of organs

Table 2 Reference Device Comparable Properties


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

Medical Device Software –Software
Life Cycle Processes;
IEC 62304 Edition 1.1 2015‐06

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


assisted triage and
notification software

trained radiologists in
workflow triage by

algorithm to analyze
images and highlight


Archiving and
Communication
System (PACS).
HealthVCF does not
send a proactive alert
directly to the user.
HealthVCF does not
provide diagnostic
information beyond
triage and prioritization,
it does not remove
cases from the
radiology worklist, and
should not be used in
place of full patient
evaluation, or relied
upon to make or
confirm diagnosis.

only and not intended for
send a proactive alert

diagnostic use beyond
directly to the user.

notification. The device
HealthVCF does n

does not alter the original
provide diagnostic

medical image and is not
information beyond

intended to be used as a
triage and prioritization,

EasyTriage-Rib, in
radiology worklist, and

clinical information and
place of full patient

professional judgment,
evaluation, or relie

Notification-only,
parallel workflow
tool

Same, both
devices
produce
passive
notifications

User
Radiologist
Bone Health Clinician
Radiologists are

Clinical condition
Clinical condition
Multiple (3 or more) acute
Vertebral compression
Different but


Alert to finding
Yes; notification flagged
Yes; notification
Same
Same

standard of care
removed from worklist
removed from worklist

Body part
Body par
Chest
Chest
Chest and abdomen
Chest and abdomen
Similar, both


[13] Oikonomou A, Prassopoulos P. CT imaging of blunt chest trauma. Insights into imaging. 2011 Jun


[27] Dehghan N, de Mestral C, McKee MD, Schemitsch EH, Nathens A. Flail chest injuries: a review of

outcomes and treatment practices from the National Trauma Data Bank. J Trauma Acute Care Surg.


GE Medical Systems SCS (Establishment Registration Number – 9611343)
283 rue de la Miniere
78530 Buc, France

Lifeng Wang
Regulatory Affairs Manager
GE Healthcare
Phone: +86 10 57083145
Email: lifeng.wang@ge.com

Elizabeth Mathew
Senior Regulatory Affairs Manager
GE Healthcare
Phone: (262) 424-7774
Email: Elizabeth.Mathew@ge.com

➢ Device Name: Hepatic VCAR
➢ Regulation number/ Product Code: 21 CFR 892.1750 Computed tomography
x-ray system / JAK
➢ Secondary Regulation number/ Product Code: 21 CFR 892.2050 Picture
archiving and communications system/ LLZ
➢ Classification: Class II

➢ Device Name: Hepatic VCAR
➢ 510(k) number: K133649
➢ Regulation number/ Product Code: 21 CFR 892.1750 Computed tomography
x-ray system / JAK
➢ Secondary Regulation number/ Product Code: 21 CFR 892.2050 Picture
archiving and communications system/ LLZ
➢ Classification: Class II

Hepatic VCAR is a CT image analysis software package that allows the analysis
and visualization of Liver CT data derived from DICOM 3.0 compliant CT scans.
Hepatic VCAR was designed for the purpose of assessing liver morphology,
including liver lesion, provided the lesion has different CT appearance from
surrounding liver tissue; and its change over time through automated tools for
liver, liver lobe, liver segments and liver lesion segmentation and measurement.
Hepatic VCAR is a post processing software medical device built on the Volume
Viewer (K041521) platform, and can be deployed on the Advantage Workstation

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


(AW) (K110834) and AW Server (K081985) platforms, CT Scanners, and PACS
stations or cloud in the future.
This software will assist the user by providing initial 3D segmentation, vessel
analysis, visualization, and quantitative analysis of liver anatomy. The user has
the ability to adjust the contour and confirm the final segmentation.
In the proposed device, two new algorithms utilizing deep learning technology
were introduced. One such algorithm segments the liver producing a liver contour
editable by the user; another algorithm segments the hepatic artery based on an
initial user input point. The hepatic artery segmentation is also editable by the
user.

Hepatic VCAR is a CT image analysis software package that allows the analysis
and visualization of Liver CT data derived from DICOM 3.0 compliant CT scans.
Hepatic VCAR is designed for the purpose of assessing liver morphology,
including liver lesion, provided the lesion has different CT appearance from
surrounding liver tissue; and its change over time through automated tools for
liver, liver lobe, liver segments and liver lesion segmentation and measurement. It
is intended for use by clinicians to process, review, archive, print and distribute
liver CT studies.
This software will assist the user by providing initial 3D segmentation, vessel
analysis, visualization, and quantitative analysis of liver anatomy. The user has
the ability to adjust the contour and confirm the final segmentation.

The modified Hepatic VCAR employs two deep learning convolutional neural
networks to segment the liver contour and the hepatic artery on CT liver exams
while the predicate device uses a traditional deterministic method to segment the
liver and manual tools to segment the vascular structure including the hepatic
artery. These changes do not change the Indications for Use from the predicate,
and represent equivalent technological characteristics, with no impact on control
mechanism, and operating principle.
The table below summarizes the feature/technological comparison between the
predicate device and the proposed device:
Specification Predicate Device: Proposed Device:
Hepatic VCAR (K133649) Hepatic VCAR
Liver Atlas algorithm based Deep Learning algorithm
segmentation segmentation based segmentation
Hepatic artery Manual segmentation tools Semi-automatic segmentation
segmentation (“autoselect” and scalpel) workflow based on deep
learning segmentation of the
hepatic artery and edition

Predicate Device:
Hepatic VCAR (K133649)

Deep Learning algorithm
based segmentation

Manual segmentation tools
(“autoselect” and scalpel)

Semi-automatic segmentation
workflow based on deep
learning segmentation of the
hepatic artery and edition

510(k) Premarket Notification Submission - Hepatic VCAR


Determination of
Substantial
Equivalence:

Verification and validation including risk mitigations have been executed with
results demonstrating Hepatic VCAR met the design inputs and user needs with
no unexpected results or risks.
Hepatic VCAR was designed and will be manufactured under the Quality System
Regulations of 21CFR 820 and ISO 13485. The following quality assurance
measures have been applied to the development of the device:
• Risk Analysis
• Requirements Reviews
• Design Reviews
• Performance testing (Verification, Validation)
• Safety testing (Verification)
Bench tests that compare the output of the two new algorithms with ground truth
annotated by qualified experts show that the algorithms performed as expected.
A representative set of clinical sample images was assessed by 3 board certified
radiologists using 5-point Likert scale. The assessment demonstrated that
capability of liver segmentation and hepatic artery segmentation utilizing the deep
learning algorithm by Hepatic VCAR.
The substantial equivalence was also based on software documentation for a
"Moderate" level of concern device.

GE Healthcare considers proposed device Hepatic VCAR to be as safe, as
effective, and performance is substantially equivalent to the predicate device.


Feature
Subject Device
Predicate Device
Comparison Results

Enhanced The subject
device supports new
software version
offering improvements
and enhancements over
the predicate

Automated
segmentation of the
prostate gland with the
possibility of manual
adjustment and
annotation

Manual measurements,
segmentations and
marks can be made
within the prostate

Enhanced The subject
device automates the
prostate segmentation,
while still permitting
manual manipulation
and annotation

Enhanced to provide
additional output format

Equivalent The subject
device has been
modified to specific
functionality for the
Prostate MR extension

Equivalent The subject
device has been
modified to expose
configuration options of
existent extensions.

Cloud only solution
with no components
deployed on customer
premise.

Client-server
architecture where the
server processes and
renders the data from
the connected
modalities. Client
provides the UI for
interactive image
viewing and processing.

Modified Architecture
of the clinical extension
is adapted to AI-Rad
Companion Engine and
cloud-based
deployment.

A tabular comparison of the subject device is provided in Table 1 below.


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

Medical Devices –
application of risk
management to medical
devices

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

Digital Imaging and
Communications in
Medicine (DICOM) Set

Information Technology –
Digital Compression and
coding of continuous -tone
still images: Requirements
and Guidelines [including:
Technical Corrigendum
1(2005)]

as with the following voluntary FDA recognized Consensus Standards listed in Table 2 below.


Predicate Device
FDA Clearance
FDA Clearance
Main Product Code

syngo.MR Applications
K180336
April 19, 2018
LLZ, LNH


CorInsights MRI hippocampal volume accuracy was tested using 80 subjects
from the HaRP database as ground truth (Boccardi, et al.).
 CorInsights MRI measured hippocampal volume with an IntraClass
Correlation coefficient of 0.95 and a DICE coefficient of 83% left (standard
deviation 2.5%) and 83% right (standard deviation 2.7%) and a mean
absolute percentage difference of 6.2% left (standard deviation 4.4%) and
5.9% right (standard deviation 5.1%) as compared to ground truth volumes.
CorInsights MRI cortical segmentation accuracy was tested using 80
subjects from a variety of databases with manual ground truth segmentation
generated by neuroanatomy experts.
 CorInsights MRI measured total gray volume with an IntraClass Correlation
coefficient of 0.99, a DICE coefficient of 95% (standard deviation 1.6%),
and a mean absolute percentage difference of 4.5% (standard deviation,
1.8%).
 CorInsights MRI measured cortical subregions with DICE coefficients
ranging from 81-93% and a mean absolute percentage difference range of
4.6% to 13.8% across all regions.
CorInsights MRI Intracranial Volume (ICV) and ventricular accuracy were tested
using an additional 70 subjects from a variety of databases with manual ground
truth segmentation generated by neuroanatomy experts.
 CorInsights MRI measured ICV with an IntraClass Correlation coefficient
of 0.89, a DICE coefficient of 95% (standard deviation 1.1%) and a mean
absolute percentage difference of 5.2% (standard deviation of 4.4%).
 CorInsights MRI measured ventricular accuracy with an IntraClass
Correlation coefficient of 0.98 (left and right), a DICE coefficient of 88%
left (standard deviation 5.2%) and 87% right (standard deviation 5.6%) and
a mean absolute percentage difference of 13.9% left (standard deviation

analyzed to support substantial equivalence:


9.2%) and 15.2% right (standard deviation 9.9%) compared to ground truth
volumes.

In test-retest processing of two different scans from the same subject on
the same scanner on the same day, CorInsights MRI measured volumes
with an average IntraClass Correlation coefficient of 0.97, a DICE
coefficient of 89% (standard deviation 4.0%) and a mean absolute
percentage difference range of 0.7% to 5.8% with an average of 2.3%
(standard deviation 2.7%) across all volumes listed in its report.

Normative
Reference
Database
Development

The CorInsights MRI reference database was developed using T1 weighted MRI
scans from 269 male and 331 female individuals of age 42 to 95 who were
clinically diagnosed to be cognitively normal.
In addition, these individuals were confirmed to be negative for amyloid pathology,
and negative for a variety of other potential confounding abnormalities including
overt vascular disease as evidenced by white matter lesions, stroke or tumor,
normal pressure hydrocephalus, and with no history of traumatic brain injury or
severe neuropsychiatric illness as documented with the data set or provided in the
data set’s inclusion criteria. This screening was performed to ensure that the
CorInsights MRI reference represented normal values without potential influence
by disease, even when asymptomatic.

Validation of
Volume
Measurement
in Clinically
Relevant Cases

Testing of CorInsights MRI included scans acquired from scanners with 1.5T and
3T field strengths, using accelerated and non-accelerated acquisition sequences,
and representing a variety of scanner models from Siemens, GE, and Philips.
Validation testing was conducted using patient scans from ages 45 to 95, with a
broad spectrum of clinical diagnoses including cognitively normal, Mild Cognitive
Impairment, typical and atypical Alzheimer’s disease, and non-Alzheimer’s
dementias. Alzheimer’s disease (AD) cases (confirmed for amyloid positivity)
included late onset AD, Early Onset AD, Posterior Cortical Atrophy (PCA),
Logopenic Progressive Aphasia, and Corticobasal Syndrome. Non-Alzheimer’s
cases included behavioral variant (bv) Frontotemporal Dementia (FTD), semantic
variant (sv) FTD, Nonfluent Primary Progressive Aphasia, Primary Progressive
Aphasia (other), amyloid negative Corticobasal Syndrome, vascular disease,
moderate to severe white matter disease, and ventricular enlargement. Mild
Cognitive Impairment (MCI) cases included early MCI, late MCI, and persons who
converted to a clinical diagnosis of dementia at 12 months post-scan.


Volumes measured by CorInsights MRI were tested using normal subject scans, as
well as data sets expected to have below normal gray tissue volumes or above
normal ventricle volumes based upon well-established literature. These data sets
included individuals with diagnoses of MCI, MCI who converted to a clinical
diagnosis of AD at 12 months post-scan, late onset AD, Early Onset AD, bvFTD,
svFTD, and PCA. CorInsights MRI values were compared to the percentile and z-
score ranges expected based upon peer reviewed published literature for these data
sets, and were confirmed to be in these ranges. Relationships between regions
based on z-score ranking were also compared to published data and were in
agreement with the literature. In all cases, the cognitively normal test group was
confirmed not to differ from the normative reference group or reference values.
In total, more than 1,400 scans from over 1,100 individuals were used in testing of
CorInsights MRI.


GE Medical Systems SCS
Establishment Registration Number - 9611343
283 rue de la Miniere
78530 Buc, France

Elizabeth Mathew
Senior Regulatory Affairs Manager
GE Healthcare, (GE Medical Systems, LLC)
3000 N Grandview Blvd.,
Waukesha, WI - 53188
Phone: (262) 424-7774
Email: Elizabeth.Mathew@ge.com

Helen Peng
Sr. Regulatory Affairs Director
GE Healthcare, (GE Medical Systems, LLC)
3000 N Grandview Blvd.,
Waukesha, WI - 53188
Phone: 262-424-8222
Email: Hong.Peng@ge.com

Device Name:
FastStroke, CT Perfusion 4D

FastStroke, CT Perfusion 4D
FastStroke Gen 2

Primary Regulation
number:
Primary Product
Code:

CFR 892.1750 Computed Tomography X-Ray System
JAK

21 CFR 892.2050 Picture archiving and communications system


510(k) number:
K163281 cleared on January 26, 2017

Predicate Device:
Device Name:
510(k) number:
Regulation number/
Product Code:
Classification:
Manufacturer:

CT Perfusion 4
K052839 cleared on March 10, 2006
21 CFR 892.1750 Computed Tomography X-Ray System
JAK
Class II
GE Medical Systems SCS

Device Description:
NeuroPackage is a solution which contains two medical devices FastStroke and CT Perfusion 4D (Neuro)
in order to help streamline the CT Stroke Workflow. The configuration of NeuroPackage enables the user
to open a single application, FastStroke, which provides them access to both the updated CT Perfusion 4D
and FastStroke applications. However, same as the predicate devices, the capabilities in CT Perfusion 4D
and FastStroke can be offered independently.
CT perfusion 4D is an image analysis software package, which allows the user to produce dynamic image
data and to generate information with regards to changes in image intensity over time. It supports the
analysis of CT Perfusion images (in the head and body) after the intravenous injection of contrast, and
calculation of the various perfusion-related parameters (i.e. regional blood flow, regional blood volume,
mean transit time and capillary permeability). The results are displayed in a user-friendly graphic format as
parametric images.
This software will aid in the assessment of the extent and type of perfusion, blood volume, and capillary
permeability changes, which may be related to stroke or tumor angiogenesis and the treatment thereof.
FastStroke is a CT image analysis software package intended for the purpose of displaying stroke workup
images (i.e. vasculature of the head, non-contrast head and neck at different time points of enhancement) in
a single software, using an optimized workflow. The software is compatible with DICOM 3.0 images and
will assist the user by providing dedicated review steps and optimized display settings to enable fast review
of the images in synchronized formats. In addition, if a multiphase CT Angiogram has been acquired, the
software will fuse the vascular information from these different time points into a single colorized view.
This multiphase information can aid the physician in visualizing the presence or absence of collateral
vessels in the brain, as well as their delay.

510(k) Premarket Notification Submission


The table below summarizes the feature/technological comparison between the predicate device and the

Results from preprocessing
will be populated into email
and sent to pre-defined
distribution list automatically.

Substantial Equivalent
Improved method to
distribute the report to
facilitate user workflow

Predicate Device
CT Perfusion 4
(K052839)

Substantial Equivalent
Improved method for
removing ventricles

In tissue classification it
is restricted which input
parameters can be used
(Blood Volume only for

In tissue classification there
is no restriction as the
software allows the user to
select from 4 input

Substantial Equivalent
Proposed device allows
additional input maps


1st segmentation, Blood
Flow, TMax or MTT only
for modified perfusion).

parameters (Blood Volume,
Blodd Flow, TMax, MTT) to
generate the tissue
classification display.

Report with the images will
be populated into email and
sent to pre-defined
distribution list
automatically.

Substantial Equivalent
Improved method to
distribute the report

Determination of Substantial Equivalence:
NeuroPackage solution which contains FastStroke and CT Perfusion 4D software has successfully
completed the required design control activities per GE’s quality management system that complies to
Quality System Regulations of 21CFR 820 and ISO 13485. The following quality assurance measures have
been applied to the development of the device:
• Risk Analysis and Mitigation
• Requirements Reviews
• Design Reviews
• Performance testing (Verification, Validation)
• Safety testing (Verification)
For the brain ventricle segmentation deep learning algorithm, bench tests that compare the output of the
new algorithm with ground truth annotated by qualified experts show that the algorithm performed as
expected.
The software testing and the corresponding results for all the other changes in FastStroke and CT Perfusion
4D software contained in NeuroPackage solution did not raise new questions of safety and effectiveness
from those associated with predicate devices and demonstrated that modified FastStroke and CT Perfusion
4D performs substantially equivalent to the predicate devices.
The substantial equivalence was also based on software documentation for a "Moderate" level of concern
device.

Conclusion
GE Healthcare considers the modifications to FastStroke and CT Perfusion 4D contained within the
NeuroPackage solution to be as safe, as effective as the predicate devices, and is substantially equivalent to
the predicate devices.


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

Medical Devices –
application of risk
management to medical
devices

Medical device software –
software life cycle

following voluntary FDA recognized Consensus Standards listed in Table 1 below.


processes [Including
Amendment 1 (2016)]

Digital Imaging and
Communications in
Medicine (DICOM) Set

Information Technology –
Digital Compression and
coding of continuous -tone
still images: Requirements
and Guidelines [including:
Technical Corrigendum
1(2005)]


Predicate Device
FDA Clearance
FDA Clearance
Main Product Code

syngo.MR Applications
K182904
July 5, 2019
LLZ


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


Predicate Device
Aidoc Briefcase for ICH triage
(K180647)

Subject Device
Aidoc Briefcase for IFG triage

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 findings.
Notifications include compressed
preview images that are
meant for informational purposes only
and not intended for diagnostic use
eyond 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.

BriefCase is a radiological computer
aided triage and notification software
indicated for use in the analysis of
abdominal 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 Intra-
abdominal Free Gas (IFG) pathologies.
BriefCase uses an artificial intelligence
algorithm to analyze images and
highlight cases with detected findings
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 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 their
professional judgment, to assist with
triage/prioritization of medical images.
Notified clinicians are responsible for
viewing full images per the standard of
care.


DICOM Information about the patient,
study and current image

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

Artificial intelligence algorithm with
database of images

Presentation of a small, compressed,
black and white preview image that is
labeled “Not for diagnostic use”;
The device operates in parallel with
the standard of care, which remains
the default option for all cases.


Category N Sensitivity Specificity AUROC

Device Performance by Dataset and Region


Device Performance by Scanner Spatial Resolution


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 case-level

The Zebra Pneumothorax
device is a software workflow
tool designed to aid the clinical
assessment of adult Chest X-
Ray cases with features
suggestive of Pneumothorax in
the medical care environment.
HealthPNX analyzes cases
using an artificial intelligence
algorithm to identify suspected


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 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.

findings. It makes case-level
output available to a
PACS/workstation for worklist
prioritization or triage.
HealthPNX 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
Pneumothorax or otherwise
preclude clinical assessment of
X-Ray cases.

Classification
21 C.F.R. § 892,2080, Product Code QFM

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

Independent/parallel; no cases are removed from worklist queue

Artificial intelligence algorithm with database of images

Passive notification – flagged for review


Male patient with suspected
or known prostate lesions

Automatically performs a
3D segmentation of the
gland. Users can alter or
make adjustments to the
segmented results in all
three planes. The resulting
segmentation reports
overall gland volume and
sets the stage for UroNav
MR/US guided fusion

The software provides a fully
automatic segmentation of
the prostate, based on a deep
learning model. Contour of
the prostate gland can be
adjusted by the user. Prostate
volume is extracted from
automatic gland
segmentation.

(K192200) to which substantial equivalency is claimed.:


The resulting segmentation
reports overall gland
volume and sets the stage
for UroNav MR/US guided
fusion biopsy

Prostate volume is extracted
from automatic gland
segmentation after validation
of the contour by the user.

Model-based automatic
prostate gland segmentation

Automatic segmentation of
the prostate based on a deep
learning model.


NinesAI (K193351)
AIDoc’s BriefCase (K180647)

Indications for Use
Indications for Use
NinesAI is a parallel workflow tool
BriefCase is a radiological computer

indicated for use by hospital networks
aided triage and notification software

and trained clinicians to identify
indicated for use in the analysis of

images of specific patients to a
non-enhanced head CT images.

radiologist, independent of standard
The device is intended to assist

of care workflow, to aid in prioritizing

and performing the radiological
radiologists in workflow triage by

review. NinesAI uses artificial
flagging and communication of

intelligence algorithms to analyze
suspected positive findings of

head CT images for findings
pathologies in head CT images,

A table comparing the key features of the subject and predicate devices is provided below.


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 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.

The software automatically analyzes
intelligence algorithm to analyze

Digital Imaging and Communications
images and highlight cases with

in Medicine (DICOM) images as they
detected ICH on a standalone

arrive in the Picture Archive and
desktop application in parallel to the

Communication System (PACS)
ongoing standard of care image

using machine learning algorithms.
interpretation. The user is presented

Identification of suspected findings is
with notifications for cases with

not for diagnostic use beyond
suspected ICH findings. Notifications

notification. Specifically, the software

analyzes head CT images of the
that are meant for informational

brain to assess the suspected
purposes only and not intended for

presence of intracranial hemorrhage
diagnostic use beyond notification.

and/or mass effect and identifies
The device does not alter the original

images with potential emergent
medical image and is not intended to

findings in a radiologist’s worklist.
be used as a diagnostic device.

NinesAI is intended to be used as a
to be used in conjunction with other

triage tool limited to analysis of
patient information and based on

imaging data and should not be used
professional judgment, to assist with

relied upon to make or confirm a
Notified clinicians are responsible for

diagnosis. Additionally, preview
viewing full images per the standard

images displayed to the radiologist
of care.

User Population
Radiologists
Radiologists
Radiologists

Characteristics
detecting emergent findings sending
detecting emergent findings sending

notifications to the workstation.
notifications to the workstation.

Components
- Artificial Intelligence
- Artificial Intelligence

- Notification Technology
- Notification Technology

Findings Covered
Findings Covered
Intracranial Hemorrhage and Mass
Intracranial Hemorrhage

Data Acquisition
Non contrast CT scan of the head
Non contrast CT scan of the head
Non contrast CT scan of the head or

View DICOM Data
View DICOM Data
DICOM information about the patient,
DICOM information about the patient,

study and current image
study and current image

Preview Images
Presentation of notification and
Presentation of notification and

preview of the study for initial
preview of the study for initial

assessment not meant for diagnostic
assessment not meant for diagnostic

purposes. This is done via desktop
purposes. This is done via desktop

notification or via DICOM series.
notification.

The device operates in parallel with
The device operates in parallel with

the standard of care, which remains
the standard of care, which remains


The primary endpoints for each algorithm are listed below:


The time-savings data for Intracranial Hemorrhage is listed below:


The time-savings data for Mass Effect is listed below:


FX is indicated for radiographs of the following industry-standard radiographic views and study types.


In accordance with 21 CFR 80
7.87(h) and (21 CFR 807.92) the 5

Primary Submission
Donna-Bea Tillman, Ph.D.

Secondary Submission
Robert Lindsey, Ph.D.

Device Common Name or
Radiological computer assisted det

Classification Name:
software for fracture

Predicate Device: OsteoDet
ect (DEN180005)


Applicant
Imagen Technologies
Imagen Technologies

Ankle
Clavicle
Elbow
Femur
Forearm
Hip
Humerus
Knee
Pelvis
Shoulder
Tibia / Fibula
Wrist

Patient Population
Adults ≥ 22 years of age
Adults ≥ 22 years of age

Secure local processing and
delivery of DICOM images

DICOM node
(e.g., imaging device,
intermediate DICOM node,
PACS system, etc.)

Imaging device or intermediate
DICOM node

PACS system, image annotations
toggled on or off

PACS system, image annotations
made on copy of original image


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

Classification Panel: Radiology, Cardiovascular


Feature
KOSMOS System
GE Vscan Extend Ultrasound
Eko Duo Model E5

(This 510(k) submission)
System (K180995)
(K170874)

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 Extend is a general purpose
diagnostic ultrasound imaging
system for use by qualified and
trained healthcare professionals
enabling visualization and
measurement of anatomical
structures and fluid. Its pocket-
sized portability and simplified
user interface enables integration
into examination and training
sessions indoors and in other
environments 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
monitoring, and triage.
With the phased array transducer
on the sector probe, the specific
clinical applications and exam
types include: Cardiac;
Abdominal; Renal; OB/GYN;
Urology; Fetal, Evaluation of
Presence of Fluid; Imaging
Guidance for Needle/Catheter
Placement (e.g. paracentesis,
pericardiocentesis, thoracentesis,
amniocentesis); Peripheral
Vascular Imaging (e.g. arteries
and veins); Thoracic/Lung (e.g.
pleural motion/sliding, line
artifacts); Adult Cephalic; and
Pediatrics.
With the addition of the linear
array transducer on the single dual
headed probe solution, the specific
clinical applications and exam
types are expanded to include:
Peripheral vascular imaging (e.g.
lower extremity, carotid);
Procedure Guidance for Arterial or
Venous Vessels (e.g. central lines,
upper extremity); Small Organs
(e.g. thyroid); Musculoskeletal
(Long Bone; Hip, shoulder, elbow
and Knee Joints); Evaluation of
Presence of Fluid; Thoracic/Lung
(e.g. pleural motion/sliding, line
artifacts); and Pediatrics.
Type of Use: Prescription Use
(Part 21 CFR 801 Subpart D)

The Eko Model E5 System is
intended to be used by healthcare
professionals to electronically
amplify, filter, and transfer body
sounds and single-channel
electrocardiogram (ECG)
waveforms. The Eko Model E5
System also displays ECG
waveforms and phonocardiogram
waveforms on the accompanying
mobile application for storage and
sharing (when prescribed or used
under the care of a physician). It
can be used to record heart sounds
and cardiac murmurs, bruits,
respiratory sounds, and abdominal
sounds during physical
examination in normal patients or
those with suspected diseases of
the cardiac, vascular, pulmonary,
or abdominal organ systems. The
device can be used on adults and
pediatrics.
The data offered by the device is
only significant when used in
conjunction with physician over
read as well as consideration of
other relevant patient data.
The device should not be used on
infants weighing less than 10kg.
Type of Use: Prescription Use (Part
21 CFR 801 Subpart D)


Ultrasound Substantial Equivalence (Technological Characteristics)

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

Phased Transducer (only):
Anatomy/ Region of Interest:
Fetal – OB/GYN
Abdominal
Pediatric
Adult Cephalic
Cardiac Adult
Cardiac Pediatric
Peripheral Vascular
Thoracic/Pleural
Interventional Guidance:
Nonvascular

2D / B-mode
M-mode
Color Doppler
Combination Modes
Harmonic Imaging

2D / B-mode
Color Doppler
Combination Modes
Harmonic Imaging

DA and ECG Substantial Equivalence (Technological Characteristics)

Audio microphone + digital signal
processing
Sampling Rate: 12.7 kHz

Audio microphone + digital signal
processing
Sampling Rate: 4000 Hz

Diaphragm (100 – 500 Hz), Bell
(20 – 200 Hz, Midrange (50 – 500
Hz), Extended ((20 – 2000 Hz)

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

Single-channel, 2 stainless steel
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
Kosmos Torso (probe)

Sounds and ECG waveforms can
be visualized and recorded on the
Kosmos Bridge (tablet) with or
without an internet connection

Sounds and ECG tracings can be
visualized on a Bluetooth device
using the Eko App. The app can be
used to visualize waveforms and
tracings without an internet
connection; however an internet
connection is necessary to save the
data.


Feature
KOSMOS System
GE Vscan Extend Ultrasound
Eko Duo Model E5

(This 510(k) submission)
System (K180995)
(K170874)

Handheld tablet display unit
(proprietary): 146 x 216 x 59 mm,
657 g
Display: 8”
Probe: 150 x 56 x 35 mm, 260 g

Handheld tablet display unit
(proprietary): 168 x 76 x 22 mm,
321 g
Display: 12.7 cm, 720 x 1280
pixels resolution
Sector probe: 129 x 32 x 25 mm,
85 g
Dual probe: 129 x 39 x 38 mm,
120 g

Handheld Unit: 119 x 47 x 16 mm
Weight: 208 g

Mains and battery operated
(rechargeable lithium ion battery)

Battery operated (rechargeable
lithium ion battery)

Probe Lens: RTV silicone 664
Probe Housing: Polysulfone
thermoplastic
Probe Cemented Joint: RTV
silicone 832
ECG Leadwires: Thermoplastic
urethane

Unknown (information not
publicly available); however,
transducer material and other
patient contact materials are
biocompatible

6061 machined aluminum
enclosure
High-impact ABS thermoplastic

Wireless networking (IEEE
802.11 b/g/n/ac supported)

Wireless networking (IEEE
802.11 b/g/n supported)

Wireless networking (Bluetooth
4.0 low-energy)


AI-Rad Companion
Organs RT is a post-
processing software
intended to automatically
contour DICOM CT
imaging data using deep-
learning-based
algorithms.
Contours that are
generated by AI-Rad
Companion Organs RT
may be used as input for
clinical workflows
including external beam
radiation therapy
treatment planning. AI-
Rad Companion Organs
RT must be used in
conjunction with
appropriate software
such as Treatment
Planning Systems and
Interactive Contouring

It is used by
radiation
oncology
department to
register
multimodality
images and
segment (non-
contrast) CT
images, to
generate needed
information for
treatment
planning,
treatment
evaluation and
treatment
adaptation.

syngo.via RT Image Suite is a
3D and 4D image
visualization, multi-modality
manipulation and
contouring tool that helps the
preparation and response
assessment of treatments such
as, but not limited to those
performed with radiation (for
example, Brachytherapy,
Particle Therapy, External
Beam Radiation Therapy).
It provides tools to efficiently
view existing contours, create,
edit, modify, copy contours of
regions of the body, such as
but not limited to, skin
outline, targets and organs-at-
risk. It also provides
functionalities to create and
modify simple treatment
plans. Contours, images and
treatment plans can
subsequently be exported to a
Treatment Planning System.
The software combines

not raise different questions of the safety and effectiveness.


Segmentation Feature & Technological Characteristics

Atlas-based, machine
learning and deep-learning
based contouring

Segmentation of
Organ at Risk in
the Anatomic
Regions

No Limitation on
scanner model,
DICOM compliance
required.

No Limitation
on scanner
model,
DICOM 3.0
compliance
required.

No Limitation on TPS
model, DICOM
compliance required.

No Limitation
on TPS model,
DICOM 3.0
compliance
required.

-Adult use only
-Not intended
to be used as a
stand-alone
diagnostic
device

There are no known
specific situations that
contraindicate the use of
this device.

AI-Rad Companion
Organs RT is designed
for use only in adult
populations.
AI-Rad Companion
Organs RT is designed
for any patient for
whom relevant
modality scans are
available. More
specifically, the
software is validated
on previously acquired
CT DICOM volumes
for radiation therapy
treatment planning,
including, head and

Any patient
type for whom
relevant
multimodality
images and
segment (non-
contrast) CT
images are
available.

Any patient type for whom
the relevant modality scan
data is available.

Traditional 510(k) Submission: AI-Rad Companion Organs RT


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

Limited to
patients
previously
selected for
Radiation
Therapy.
However,
AccuContour
can be used for
treatment
evaluation and
treatment
adaptation.

AI-Rad Companion
(Engine) architecture
enabling the
deployment of AI Rad
Companion Organs RT
in the Cloud. The UI is
provided using a web-
based interface.

Client-server architecture
where the server processes
and renders the data. Client
provides the UI for
interactive image viewing
and processing

Creating, editing and
deletion of organ
templates. Customize
predefined structure
database with mapping
to international
nomenclature schemes.

Creating, editing and
deletion of structure
templates. Customize
predefined structure
database with mapping to
international nomenclature
schemes.

AI-Rad Companion
Organs RT
automatically
processes input image
data and sends the
results as DICOM-RT
Structure Sets to a
user-configurable
target node.

AccuContour
automatically
processes input
image data

Rapid Results workflow
feature allows the
configuration of automatic
organ contouring and
optionally send DICOM-
RT files to a target
DICOM-Node for further
processing.

Contour
visualization and
editing feature

AI-Rad Companion
Organs RT provides
basic result preview of
automatic

AccuContour
provides basic
result preview
of automatic

syngo.via RT Image Suite
provides advanced contour
visualization feature of


segmentation results,
and no editing feature
of the automatic
segmented contour.

The target performance
was validated using
113 cases distributed to
two cohorts. Cohort
A-Clinical Routine
Treatment Planning
CT (Siemens; Head
and Neck, Thorax and
Abdomen Pelvis) and
Cohort B-Multi
Vendor Coverage (GE
and Phillips; Head and
Neck).
To objectively evaluate
the target performance,
the DICE coefficient,
the absolute symmetric
surface distance
(ASSD) and the fail
rate was evaluated.
The segmentation
performance of the
subject and reference
device were equivalent
as well as the overall
performance compared
to the predicate device.

The
segmentation
performance
was validated
using datasets
from China
and the USA
using three
major vendors
(GE, Siemens
and Phillips).
The
segmentation
accuracy is
evaluated
using DICE
coefficient.

The target performance was
validated using 32 cases
with various fields of view.
To objectively evaluate the
target performance, the
DICE coefficient & the
absolute symmetric surface
distance (ASSD) were
evaluated. The
segmentation performance
of the subject and predicate
device were equivalent.

User Interface –
Results Preview
(Confirmation)

Basic visualization
functionality of
original data and
generated contours

Basic result
preview of
automatic
segmentation
results. Manual
contouring is
possible.

Standard visualization tools
(window levels, MPR,
MIP, VRT). Manual
contouring is possible.

Design to be used by
trained clinicians.


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

Medical Devices –
application of risk
management to medical
devices

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

Digital Imaging and
Communications in
Medicine (DICOM) Set

Information Technology –
Digital Compression and
coding of continuous -tone
still images: Requirements
and Guidelines [including:
Technical Corrigendum
1(2005)]


AI-Rad Companion Organs RT
MED: 0.85
MED: 2.0 mm

the subject device and predicate device are comparable in DICE and Hausdorff Distance.


Predicate Device
FDA Clearance
FDA Clearance
Main Product

AccuContour
K191928
February 28, 2020
QKB

AI-Rad Companion Organs RT is substantially equivalent to the following predicate device:


Manufacturer
Device Name
Application No.

Viz.ai, Inc. (Primary)
ContaCT
DEN170073


Viz ICH
ContaCT (DEN170073)
BriefCase (K180647)

Transfer, store,
and process
DICOM images

Acquires medical image data
from DICOM compliant
imaging devices and
modalities.

Computed Tomography, non-
contrast (NCCT)

Computed Tomography,
contrast-enhanced (CTA)

Initial assessment; non-
diagnostic purposes

DICOM Information about the
patient, study and current
image.


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


Age Range (years)
Sensitivity [95% Cl]
Specificity [95% Cl]


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


Intraparenchymal Hemorrhage (IPH)
0.98 [0.91, 1.0]

Intraventricular Hemorrhage (IVH)
1.00 [0.74, 1.0]

Subarachnoid Hemorrhage (SAH)
0.60 [0.26, 0.88]

Subdural Hemorrhage (SDH)
0.85 [0.62, 0.97]


Performance Stratified by Slice Thickness


Sensitivity below/equal
Threshold [95% Cl]


Features/Characteristics
LVivo
TomTec-Arena 1.0 K132544

Calculate
and measurement
of LV, RV and
Bladder

Calculation and
measurement LV, RV,
fetal and abdomen

DiA’s LVivo platform is
intended for non-
invasive processing of
ultrasound images to
detect, measure, and
calculate relevant
medical parameters of
structures and function
of patients with
suspected disease.

Indication for use of Tom-
Tec- Arena software are
diagnostic review,
quantification and reporting of
cardiovascular, fetal, and
abdominal structures and
functions of patients with
suspected disease.


Features/Characteristics
LVivo
LVivo K130779 & K161382

DiaCardio’s LVivo Software
Application is intended for
non-invasive processing of
already acquired
echocardiographic images in
order to detect, measure, and
calculate the left ventricular
wall for left ventricular
function evaluation. This
measurement can be used to
assist the clinician in a
cardiac evaluation.

LVivo EF, LVivo SG,
LVivo SAX, LVivo RV &
LVivo Bladder

Off line EF
evaluation using
DICOM clips of any

vendor
Automated ED and
ES frames selection

assessment
Manual editing by user
capability

Minimum of 7 border
points manipulation
(dragging) and online
contour presentation.
Possible to apply to
any frame in the clip.
Border detection is
recalculation is
applied to the entire
clip.

Yes. 7 border points
manipulation (dragging) and
online contour presentation.
Possible to apply to any
frame in the clip.
Border detection is
recalculation is applied to
the entire clip.


Volume calculation by
Simson's method of
discs

Displaying full clip with
border tracking. And
table with results for
each cycle for selected
ED & ES frames for
each beat.

Enables presentation EF
results for different cycle

Image segmentation for
border detection
For the RV- Deep
Learning Technology

Image segmentation for
border detection
From image processing

Less than 1s per cycle
for biplane evaluation

Capability or a part of a
bigger package (device)
for LV function
evaluation


Windows/Linux (with
Android Mobile
Option for LVivo EF)


335 Madison Avenue, 16th Floor
New York, NY 10017

Alan Nelson
Chief Science Officer, Radformation


AutoContour, AutoContouring, AutoContour Agent,
AutoContour Web Application

Picture archiving and communications system


Table 3: Substantial Equivalence AutoContour vs. RTx & Workflow Box

Subject Device:
AutoContour
Radformation

Predicate Device:
Workflow Box (K181572)

Any patient type for
whom relevant modality
scan data is available.


None – software only
application. The software
application does not
deliver or depend on
energy delivered to or
from patients
(Substantially
Equivalent)

Trained radiation
oncology personnel
(Substantially
Equivalent)

Designed to be used by
trained clinicians

Design: Data
Visualisation/Gr
aphical User
Interface

Contains both an
automated processing
component and Data
Visualisation / Graphical
User Interface
(Substantially
Equivalent)

None – the proposed
device has no data
visualization
functionality. All data
processing is
automated and does

not require user
interaction. A control
interface is provided for
system administration
and configuration only

Design: View
manipulation
and Volume
rendering

Window and level, pan,
zoom, cross-hairs, slice
navigation, fused views.
(Subject Device
functionality is a subset
of Predicate Devices)

Window and level, pan,
zoom, cross-hairs, slice
navigation. Maximum or

minimum intensity projection
(MIP), volume rendering,
color rendering, surface
rendering, multi-planar
reconstruction (MPR), fused

views, gallery views.

Manual Rigid
registration.
(Subject Device
functionality is a subset
of Predicate Devices)

Registration for the
purposes of
replanning/re-contouring
and atlas based
contouring. The
algorithms used for
image registration are
the same for both
predicate and proposed
devices.

Manual and Landmark
Rigid. Automatic multi-modal

rigid. Mono-modal and
multi-modal deformable
registration. Motion correction
in hybrid scans and gated
scans. Registration for the
purposes of
re-planning/recontouring and
atlas based contouring.

Machine learning based
contouring and manual
ROI manipulation.
(Subject Device

Atlas Based contouring,
registration based
re-contouring, machine

2D and 3D ROIs,
semi-automatic ROI
definition, isocontour ROIs
using threshold and


functionality is a subset
of Predicate Devices)

percentage of maximum,
one-click seed-pointing
contouring, manual ROI

manipulation, ROI

transformation, Atlas-based
contouring.

Design:
Region/volume
of interest
measurements
and size
measurements

None – not applicable
(Substantially
Equivalent)

Intensity, Hounsfield units,
activity and SUV
measurements including min,
max, mean, peak, standard
deviation, total glycolytic
activity, median, histogram,
max and mean ratio to
reference region. Gray for RT
Dose. Size measurements
include 2D and 3D
measurements including
rulers and volume, line
profile.

Regions table with charting
supports analysis of
measurement over multiple
studies using standard
protocols such as RECIST,
PERCIST and WHO

CT input for contouring
or manual
registration/fusion.
MR, PET input for
manual
registration/fusion only.
DICOM RTSTRUCT for
output
(Minor differences)

CT, MR, DICOM

RTSTRUCT for image

processing. Any valid
DICOM data for data
routing

Static and gated CT and

PET, and static MR, SPECT,

NM, DICOM RT

No built-in reporting,
supports exporting
DICOM RTSTRUCT file.
(Minor differences)

Supports routing and
distribution of images to
other DICOM nodes
including to custom
executables determined
by the user.

Yes– Distribution of DICOM
compliant Images into other
DICOM compliant systems.
Built-in basic reporting

Compatibility
with the
environment
and other
devices

Compatible with data
from any DICOM
compliant scanners for
the applicable modalities.
Agent Uploader
component compatible
with Microsoft Windows.

Compatible with data from
any DICOM compliant
scanners for the applicable
modalities. Compatible

with Microsoft Windows.

Integration with Mirada DBx
application launcher and data
browser.


Cloud-based automatic
contouring service
compatible with Linux.
Web application Server
based application
compatible with Linux
with frontend compatible
with all modern web
browsers..
(Minor differences)

TCP/IP
(Subject Device
functionality is a subset
of Predicate Devices)

Agent Uploader
supporting Microsoft
Windows 10 (64-bit) and
Microsoft Windows
Server 2016.
Cloud-based Server
based automatic
contouring application
compatible with Linux.
Web application Server
based application
compatible with Linux
with frontend compatible
with all modern web
browsers.
(Minor differences)

Server based application
supporting Microsoft
Windows 10 (64-bit) and
Microsoft Windows
Server 2016.

Workstation and Server
based application supporting
Windows Server 2008 R2,
SP1 and Windows 7 (64-bit)

Support for
radiation
treatment
planning

AutoContour is intended
to assist radiation
treatment planners in
contouring and reviewing
structures within medical
images in preparation for
radiation therapy
treatment planning
(Subject Device intended
use is a subset of
predicate devices)

“Contours generated by
Workflow Box may be
used as an input to
clinical workflows
including, but not limited
to, radiation therapy
treatment planning”

“RTx supports the loading
and saving of DICOM RT
objects and allows the user to
define, import, display,
transform, store and export
such objects including
regions of interest structures
and dose volumes to
radiation therapy planning
systems.”


Characteristic
Subject Device
Primary Predicate
Reference Device
Reference Device
Reference Device
Reference Device

Device Name
AVIEW 2.0
AVIEW
AVIEW
Imbio CT Lung
AVIEW LCS
AI-Rad
Calcium Scoring

tests, we conclude that the proposed device is substantially equivalent to the predicate devices.


Product Code
LLZ, JAK
LLZ
JAK
LLZ, JAK
JAK
JAK

Review Panel
Radiology
Radiology
Radiology
Radiology
Radiology
Radiology

AVIEW provides CT values for pulmonary tissue from CT thoracic and cardiac datasets. This software could be used to support the physician
quantitatively in the diagnosis, follow up evaluation and documentation of CT lung tissue images by providing image segmentation of sub-structures in
lung, lobe, airways and cardiac, registration of inspiration and expiration which could analyze air trapping on lung, volumetric and structure analysis,
density evaluation and reporting tools. AVIEW is also used to store, transfer, inquire and display CT data set on premise and as cloud environment as
well to allow users to connect by various environment such as mobile devices and chrome browser. Characterizing nodules in the lung in a single study,
or over the time course of several thoracic studies. Characterizations include nodule type, location of the nodule and measurements such as size (major
axis, minor axis), estimated effective diameter from the volume of the nodule, volume of the nodule, Mean HU(the average value of the CT pixel inside
the nodule in HU), Minimum HU, Max HU, mass(mass calculated from the CT pixel value), and volumetric measures(Solid major; length of the longest
diameter measured in 3D for solid portion of the nodule, Solid 2nd Major: The length of the longest diameter of the solid part, measured in sections
perpendicular to the Major axis of the solid portion of the nodule), VDT (Volume doubling time), and Lung-RADS (classification proposed to aid with
findings). The system automatically performs the measurement, allowing lung nodules and measurements to be displayed and, integrate with FDA
certified Mevis CAD (Computer aided detection) (K043617). It also provides CAC analysis by segmentation of four main artery (right coronary artery,
left main coronary, left anterior descending and left circumflex artery then extracts calcium on coronary artery to provide Agatston score, volume score
and mass score by whole and each segmented artery type. Based on the score, provides CAC risk based on age and gender.

AVEIW provides CT values for pulmonary tissue from CT thoracic datasets. This software can be used to support the physician quantitatively in the
diagnosis, followup evaluation and documentation of CT lung tissue images by providing image segmentation of sub-structures in the left and right lung
(e.g., the five lobes and airway), volumetric and structural analysis, density evaluations and reporting tools. AVIEW is also used to store, transfer, inquire
and display CT data sets. AVEIW is not meant for primary image Interpretation in mammography.

The Imbio CT Lung Density Analysis Software provides reproducible CT values for pulmonary tissue, which is essential for providing quantitative
support for diagnosis follow up examinations. The Imbio CT Lung Density Analysis Software can be used to support the physician in the diagnosis and
documentation of pulmonary tissue images (e.g., abnormalities) from CT thoracic datasets. Three-D segmentation and isolation of sub-compartments,
volumetric analysis, density evaluation, and reporting tools are provided.

AVIEW LCS is intended for the review and analysis and reporting of thoracic CT images for the purpose of characterizing nodules in the lung in a single
study, or over the time course of several thoracic studies. Characterizations include nodule type, location of the nodule and measurements such as size
(major axis, minor axis), estimated effective diameter from the volume of the nodule, the volume of the nodule, Mean HU(the average value of the CT
pixel inside the nodule in HU), Minimum HU, Max HU, mass(mass calculated from the CT pixel value), and volumetric measures (Solid Major, length
of the longest diameter measured in 3D for a solid portion of the nodule. Solid 2nd Major: The length of the longest diameter of the solid part, measured
in sections perpendicular to the Major axis of the solid portion of the nodule), VDT(Volume doubling time), and Lung-RADS (classification proposed
to aid with findings). The system automatically performs the measurement, allowing lung nodules and measurements to be displayed and, also integrate
with FDA certified Mevis CAD (Computer-aided detection) (K043617)

AI-Rad Companion (Cardiovascular) is processing software that provides quantitative and qualitative analysis from previously acquired Computed
Tomography DICOM images to support radiologists and physicians from emergency medicine, specialty care, urgent care, and general practice in the
evaluation and assessment of cardiovascular disease.
It provides the following functionality:
 Segmentation and volume measurement of the heart
 Quantification of the total calcium volume in the coronary arteries
 Segmentation of the aorta
 Measurement of maximum diameters of the aorta at typical landmarks
 Threshold-based highlighting of enlarged diameters
The software has been validated for non-cardiac chest CT data with filtered backprojection reconstruction from Siemens Helathineers, GE Healthcare,
Philips, and Toshiba/Canon, Additionally, the calcium detection feature has been validated on non-cardiac chest CT data with iterative reconstruction
form Siemens Healthineers.
Only DICOM images of adult patients are considered to be valid input.

From user specified sets of CT cardiac images, Calcium Scoring can be used to;
 Allow the user to interactively indicate regions of detected calcification
 To allow the user to allocate each detected region to one of several coronary arteries
 To estimate algorithmically a score for the amount of detected calcification in each allocated artery
 To prepare reports including reports including calcium score data, Imagery, ECG traces, Comparison of scroe to cited literature and additional
relevant information.
The calcium-scoring package is a diagnostic tool that can be used to evaluate the calcified plaques in the coronary arteries, which is a risk factor for
coronary artery disease. Calcium scoring may be used to monitor the progression or regression overtime of the amount or volume of calcium in the
coronary arteries, which may be related to the prognosis of a cardiac attack.

User Interface
Monitor, Mouse,
Monitor, Mouse,
Monitor, Mouse,
Monitor, Mouse,
Monitor, Mouse,
Monitor, Mouse,


Keyboard Keyboard Keyboard Keyboard Keyboard Keyboard

Images can be scanned,
loaded from card
readers, or imported
from a radiographic
imaging device

Image format
DICOM
DICOM
DICOM
DICOM
DICOM
DICOM

Ruler (line and 3D),
Tapeline (curve, poly
and3D), Angle (3-point,
4point, and 3D), pixel
values, area of ROI
(rectangle, circle,
ellipse), volume

Ruler (line and 3D),
Tapeline (curve, poly
and3D), Angle (3-
point, 4point, and 3D),
pixel values, area of
ROI (rectangle, circle,
ellipse), volume

Axial, sagittal, and
coronal image, oblique
slice, cube view

Panning, rotating,
zooming, windowing,
inverting, Coloring,
Oblique, Note (text
overlay), Coloring

Panning, rotating,
zooming, windowing,
Coloring, Oblique,
Note (text
overlay), Coloring

The AVIEW is a software product which can be installed on a PC. It shows images taken with the interface from various storage devices using DICOM
3.0 which is the digital image and communication standard in medicine. It also offers functions such as reading, manipulation, analyzing, post-processing,
saving and sending images by using the software tools. And is intended for use as diagnostic patient imaging which is intended for the review and analysis
of CT scanning. Provides following features as semi-automatic nodule management, maximal plane measure, 3D measures and volumetric measures,
automatic nodule detection by integration with 3rd party CAD. Also provides Brocks model which calculated the malignancy score based on numerical
or Boolean inputs. Follow up support with automated nodule matching and automatically categorize Lung-RADS score which is a quality assurance tool
designed to standardize lung cancer screening CT reporting and management recommendations that is based on type, size, size change and other findings
that is reported. It also automatically analyzes coronary artery calcification which support user to detect cardiovascular disease in early stage and reduce
the burden of medical.

The AVIEW is a software product which can be installed on a PC. It shows images taken with the interface from various storage devices using DICOM
3.0 which is the digital image and communication standard in medicine. It also offers functions such as reading. Manipulation, analyzing, post-processing,
saving and sending images by using the software tools.

The Imbio CT Lung Density Analysis Software (Imbio LDA) IS A SET OF IMAGE POST-PROCESSING ALGORITHMS THAT PERFORM IAMGE
SEGMENTATION, REGISTRATION, THRESHOLDING, AND CLASSIFICATION ON ct images of juman lungs.
The algorithms within the Imbio CT Lung Density Analysis Software are combined into a single command-line or through scripting. The Imbio CT Lung
Density Analysis Software program performs segmentation, then registration, then thresholding and classification. The program reads in DICOM
datasets, processes the data, then writes output DICOM files to a specified directory.
The Imbio CT Lung Density Analysis Software is a command-line software application that analyzed DICOM CT Lung images datasets and generated
reports and DICOM output that show the lungs segmented and overlaid with colorpcodings representing the results of its thresholding and classification
rules. It has simple file management functions for input and output, and separate modules that implement the CT image-processing algorithms. Imbio
CT Lung Density Analysis Software does not interface directly with any CT or data collection equipment; instead the software imports data files
previously generated by such equipment.

AVIEW LCS is intended for use as diagnostic patient imaging which is intended for the review and analysis of thoracic CT images. Provides following
features as semi-automatic nodule measurement (segmentation), maximal plane measure, 3D measure and volumetric measures, automatic nodules
detection by integration with 3rd party CAD. Also provide cancer risk based on PANCAN risk model which calculated the malignancy score based on
numerical or Boolean inputs. Follow up support with automated nodule matching and automatically categorize Lung-RADS score which is a quality
assurance tool designed to standardize lung cancer screening CT reporting and management recommendations that is based on type, size, size change
and other findings that is reported.

In general, AI-Rad Companion (Cardiovascular) is a software only image post-processing application that uses deep learning algorithms to post-process
CT data of the thorax. As an update to the previously cleared devices, the following modifications have been made;
1) Modified indication for Use Statement
2) Support of software AI-Rad Companion CT VA10A
a) heart segmentation including measurement (modified)
b) calcium detection based on deep learning algorithm (modified)
c) Aorta segmentation (modified)


d) AHA landmarks for labeling and diameter measurement of the aorta, including threshold-based aorta diameter classification (modified)
3) subject device claims list
The subject device AI-Rad Companion (Cardiovascular) is an image processing software that utilizes deep learning algorithms to provide quantitative
and qualitative analysis from previously acquired Computed Tomography DICOM image to support radilogists and physicians from emergency medicine,
specialty care, urgent care, and general practice in the evaluation and assessment of disease of the thorax. The subject devcei support the following device
specific functionality.
 Segmentation and volume measurement of heart
 Identification and measurement of volume with high Hounsfield values- related to coronary calcification
 Segmentation of the aorta determination of 9 Landmarks.
 Computation of cross-sectional MPRs at the 9 landmarks and their maximum diameter
 Measurement of maximum diameters of the aorta at typical landmakrs.
Threshold-based classification of diameters into different categories

Calcium Scoring is a software package running on the 3Dvirtuoso workstation that allows the user to mark regions of detected calcification in CT cardiac
images, to assign each region to a coronary artery, and to calculate the Agatston score and other information from the identified pixels. Film and paper
reports of the results can also be prepared. Calcium Scoring is also a cost-effective alternative to Electron Beam CT (EBCT), since it produces calcium
scores that correlated to the EBCT’s gold standard, but at a much lower cost.

This receives DICOM
data from CT by
DICOM communication
Conducts DICOM data
communication with
PACS. It also imports
DICOM file directly,
saves by using export
function.

Retrieve image data
over the network via
DICOM

Fully automatic lungs,
lobes and airways
segmentation using
deep-learning
algorithms

Semi-automatic
segmentation of
lungs, lobes and
airways.

Visualization of multi-
planar reconstructed
(MPR) images and 3D
rendered images, with
color-defined
Hounsfield Unit (HU)
ranges.

Visualization of
multi-planar
reconstructed (MPR)
images and 3D
rendered images,
with color-defined
Hounsfield Unit
(HU) ranges.

Calculation of LAA
(Lower Attenuation
Area) index with HU
density histogram.
Volume measurements
and percentile index

Calculation of LAA
cluster size distribution
with D-slope

Calculation of LAA
cluster size
distribution with D-
slope

Graphical visualization
of the above
quantification results for
reporting

Export of quantification
results to CSV tables

Visualization of LAA%
for each of 5 lobes

Measurements of the
airway branches, such
as, lumen area and wall
area