Topic/ Feature
Primary Predicate Device (Brainlab
Subject Device (Brainlab Elements

Elements Fibertracking 2.0 (K223106))
Fibertracking 3.0)

Brainlab Elements Fibertracking is an
application for the processing and
visualization of cranial white matter tracts
based on Diffusion Tensor Imaging (DTI)
data for use in treatment planning
procedures.

Brainlab Elements Fibertracking is an
application for the processing and
visualization of cranial white matter tracts
based on diffusion weighted imaging
(DWI) data for use in treatment planning
procedures. It is not intended for diagnostic
purposes. Brainlab Elements Fibertracking


The device itself does not have clinical
indications.

is indicated for planning of cranial surgical
treatments and preplanning of cranial
radiotherapy treatments.

The intended users are medical
professionals. Typical users are:
- Image Guided Surgery (IGS):
Neurosurgeons, Ear-Nose-Throat
(ENT) surgeons and Cranio-
Maxillofacial (CMF) surgeons including
their assistants
Radiotherapy (RT): medical professionals
who perform radiation treatment planning
(medical physicists, radiation oncologists,
dosimetrists, physicians, etc.)

The intended users are medical
professionals. Typical users are:
- Image Guided Surgery (IGS): Surgeons
trained in the areas of neurosurgery
including their assistants.
Radiotherapy (RT): medical professionals
who perform radiation treatment planning
(medical physicists, radiation oncologists,
dosimetrists, physicians, etc.).

In general, there are no demographic,
regional or cultural limitations for patients.
It is up to the user to decide if the system
shall be used to assist a certain procedure.

There are no demographic, regional or
cultural limitations for patients.

The system shall be used in a hospital
office environment or rooms appropriate
for surgical interventions or radiotherapy
planning.

Brainlab Elements can be used on
hardware that fulfills the defined minimum
requirements:
- Operating System: Windows 8.1 64bit
- Minimum 4 logical cores
- Minimum RAM: 6 GB
- Graphics: Direct X compatible
- Display Resolution: 1920 x 1080 (Full HD)

IGS Workstation:
- Operating system: Windows 10
- minimum 4 physical cores
- RAM: 8 GB
- Graphics: DirectX 12 compatible
- Display resolution: 1920 x 1080 (Full HD)
IGS Server / Virtual Machine:
- Operating System: Windows Server 2016
- RAM 16GB
RT Workstation:
- Operating System: Windows 10
- minimum 6 physical cores
- RAM: 48GB
- Graphics card: DirectX 12
- Display resolution: 1920 x 1080 (Full HD)
RT Server / Virtual Machine:
- Operating System: Windows Server 2016
- minimum 12 physical cores
- RAM: 64GB (+16GB per additional user)

- Windows Server 2012 R2 / 2016 / 2019
- Windows 8.1
- Windows 10

- Windows Server 2016
- Windows Server 2019
- Windows Server 2022
- Windows 10


Automatic DTI Preprocessing (by using
component DTI Preprocessing Performer
2.0):
 Eddy Current Correction,
 Motion Correction,
 B-Vector Realignment,
 Denoising,
 Regularization

Automatic DWI Preprocessing (by using
component DWI Performer 3.0):
 Eddy Current Correction,
 Motion Correction,
 B-Vector Realignment,
 Denoising,
 Regularization
 Creation of ODF field for HARDI data

Application offers the following possibilities
to define seed ROIs for Fibertracking (ROI
based Fibertracking):
 Manual 3D Object (as include or exclude
ROI)
 Existing 3D Object(s), e.g. by using ROI
templates
 “Interactive Tracking” to use a dynamic
ROI to generate fiber bundles on the fly

Application offers three sliders to influence
the algorithm’s stopping criteria:
 Minimum FA Threshold (default: 0.2)
 Minimum Length (default: 80 mm)
 Maximum Angulation (default: 20°)
See also topic “Toolarea”.

Application offers sliders to influence the
algorithm’s stopping criteria:
Deterministic tracking using DTI:
 Refinement (remove outliers, default:
10%)
 Minimum FA Threshold (default: 0.2)
 Maximum Angulation (default: 20°)
Probabilistic tracking using CSD:
 Refinement (remove outliers, default:
10%)
 Amplitude (default: 0.1)
 Maximum Angulation (default: 20°)

• Deterministic Tracking Algorithm
based on Combined Single/Dual
Tensor Tracking
Create 3D Objects from Fiber bundles

• Deterministic Tracking Algorithm
based on Combined Single/Dual
Tensor Tracking
• Probabilistic tracking algorithm
• Constrained Spherical Deconvolution
tracking
Create 3D Objects from Fiber bundles
Reference Device K212397
StealthStation S8 Cranial v2.0:
StealthStation S8 Cranial v2.0 offers a


Topic/ Feature
Primary Predicate Device (Brainlab
Subject Device (Brainlab Elements

Elements Fibertracking 2.0 (K223106))
Fibertracking 3.0)

similar algorithm like the new probabilistic
CSD tracking algorithm introduced with
Fibertracking 3.0.

 Fiber bundles are accessible via toggle
control and manageable via In-App
DataSelection.
 ROIs are accessible in sidebar for
drag&drop to fiber bundle.
 ROI-Brush accessible via toolarea.
 Other ROIs directly accessible via
Sidebar.
 Parameter sliders area accessible in
toolarea.
 “Refresh” accessible via toolarea.
 “Erase” accessible via toolarea
 “Objects Exclude” via Sidebar

 Fiber bundles are accessible and
manageable in sidebar control
 ROIs are accessible in sidebar for
drag&drop to fiber bundle and selectable
for editing.
 ROI-Brush accessible via toolarea.
 Other ROIs directly accessible via
Sidebar.
 Parameter sliders area accessible in
toolarea.
 “Refresh” accessible via sidebar.
 “Erase” accessible via toolarea.
 “Objects Exclude” via Sidebar
 Algorithm (DTI or CSD) can be selected
in toolarea
 Measurement of coordinates and FA
values available via toolarea


Subject Device (Brainlab Elements
BOLD MRI Mapping 1.0)

Brainlab Elements BOLD MRI
Mapping provides tools to analyze
blood oxygen level dependent data
(BOLD MRI Data) to visualize the
activation signal and correlation
between brain areas.
The device itself does not have
clinical indications

Brainlab Elements BOLD MRI
Mapping provides tools to analyze
blood oxygen level dependent data
(BOLD MRI Data) to visualize the
activation signal. It is not intended
for diagnostic purposes.
Brainlab Elements BOLD MRI
Mapping is indicated for planning of
cranial surgical treatments.

The intended users are medical
professionals. Typical users are:


- Image Guided Surgery (IGS):
Neurosurgeons, Ear-Nose-
Throat (ENT) surgeons and
CranioMaxillofacial (CMF)
surgeons including their
assistants
Radiotherapy (RT): medical
professionals who perform radiation
treatment planning (medical
physicists, radiation oncologists,
dosimetrists, physicians, etc.)

Image Guided Surgery (IGS):
Surgeons trained in the area of
neurosurgery including their
assistants

Brainlab Elements can be used on
hardware that fulfills the defined
minimum requirements:
- Operating System: Windows 8.1
64bit
- Minimum 4 logical cores
- Minimum RAM: 6 GB
- Graphics: Direct X compatible
Display Resolution: 1920 x 1080
(Full HD)

IGS Workstation:
- Operating system: Windows 10
- minimum 4 physical cores
- RAM: 8 GB
- Graphics: DirectX 12 compatible
- Display resolution: 1920 x 1080
(Full HD)
IGS Server / Virtual Machine:
- Operating System: Windows
Server 2016
- RAM 16GB

- Windows Server 2012 R2 /
2016 / 2019
- Windows 8.1
Windows 10

- Windows Server 2016
- Windows Server 2019
- Windows Server 2022
Windows 10


FUJIFILM Healthcare Americas Corporation


Applicant Contact Ms. Kulkarni Chaitrali


Legally Marketed Predicate Devices 21 CFR 807.92(a)(3)


Device Description Summary 21 CFR 807.92(a)(4)

The Synapse PACS is an enterprise-wide medical information and image management software that runs on standard “off-the-shelf” PC
hardware and Software (OS, browser). Synapse is intended for communication, storage, display, manipulation, measurement, printing,
and processing of images and information acquired from various medical imaging and information systems. As a Software as a Medical
Device (SaMD), Synapse PACS performs these purposes without being part of a hardware medical device.

Intended Use/Indications for Use 21 CFR 807.92(a)(5)

FUJIFILM Synapse PACS Software is intended for use as a web-based application on an off-the shelf PC which meets or exceeds
minimum specifications and is networked with a FUJIFILM Synapse PACS server.
The FUJIFILM Synapse PACS Software can process medical images from DICOM compliant modalities and non-DICOM sources.
FUJIFILM Synapse PACS Software provides toolsets for:
• Performing measurements on DICOM images
• Regional segmentation
• Importing and presenting data from modalities (DICOM and non-DICOM),
• Solving clinical calculations
• Creating and distributing structured reports


FUJIFILM Synapse PACS Software is intended to serve as the primary user interface for the processing of medical images for presentation
on displays appropriate to the medical task being performed. It enables the display, comparison, fusion, and volume rendering of studies
to aid in reading, interpreting, reporting, and treatment planning.
Typical users are radiologists, cardiologists, technologists, sonographers, technicians, nurses, and clinicians.
MIP, MPR Fusion, and volume rendering are not intended for mammography use. FUJIFILM Synapse PACS Software can be used to
process FUJIFILM’s DICOM MG “For Processing” images and also for the display, manipulation, and interpretation of lossless compressed
or non-compressed mammography images that have been received in the DICOM For Presentation format and displayed on FDA-
cleared, DICOM compatible displays for mammography.

Indications for Use Comparison 21 CFR 807.92(a)(5)

There are no differences in the indication for use between the subject device and the primary predicate device.

Technological Comparison 21 CFR 807.92(a)(6)

The differences between the features in the subject device and the primary predicate device are Volume Rendering Techniques, 3D
Tools, Bone Removal, and 2-Point VOI. Although the primary predicate device does not have the features listed, the reference device
have the same features. Because the predicate device and reference device contain the same features, the addition of the features in
version 7.5 do not affect the safety or efficacy of the subject device.

Non-Clinical and/or Clinical Tests Summary & Conclusions 21 CFR 807.92(b)

Non-clinical testing result:
The differences between the features in the subject device and the primary predicate device are Volume Rendering Techniques
including 3D Tools, 2-Point Volume of Interest (VOI), and Bone Removal.
The key addition to Synapse PACS 7.5.0 is the ability to perform volume rendering and 3D volume viewing for CT and MR.
The algorithm is already cleared and marketed for Synapse 3D (K221677, reference device). The volume rendering algorithms were
integrated unchanged into Synapse PACS 7.5.0 (subject device).
The 2-point VOI performs is a semi-automatic segmentation of a lesion in CT and MRI images using the line drawn by the user on the
lesion. The algorithm implemented is the same as already cleared and marketed algorithms for Synapse 3D (K221677, reference device).
In Synapse3D, it is called Tumor Boundary Segmentation algorithm. The algorithm has been integrated into Synapse PACS unchanged
compared to Synapse 3D. Comparison with Synapse 3D (K221677, reference device) provides the same results in Synapse PACS 7.5.0
(subject device).
Bone Removal is a tool that enhances the visibility of vessels in 3D rendered images by masking out bone regions. The tool is based on
an AI algorithm cleared and marketed for Synapse 3D (K221677, reference device). It was improved for Synapse PACS 7.5.0. Comparison
with Synapse 3D (K221677, reference device) showed that the improved algorithm does not affect the safety or efficacy of Synapse PACS
7.5.0 (subject device). Please refer to the Performance Bench Testing for testing with the improved algorithm.
Performance Testing Summary
A. Summary test statistics and acceptance criteria:
Dice Similarity Coefficient (DSC) and 95% Hausdorff Distance (HD) were used as primary and secondary endpoints to validate the
performance of bone extraction algorithm. A pre-defined acceptance threshold of 0.951 was used for DSC. For 95% HD, we pre-define
acceptance range 0.98 mm – 7.31 mm. The thresholds are determined after reviewing existing bone removal models in the literature.
The mean observed dice overlap coefficient and 95% HD with 95% confidence intervals were 0.959 [0.955 – 0.963] and 1.367 mm [1.170
mm – 1.563 mm], respectively, exceeding the predefined acceptance thresholds.
Across the subgroups— region, sex, age band, vendor, slice-thickness bin, body region, contrast—Dice values remained tightly clustered
between 0.94 and 0.97 and 95 % HD never exceeded 2.57 mm. The 5 mm cohort shows a slightly lower Dice (0.942) because thick slices
compress bone detail into fewer voxels, so tiny absolute deviations inflate the overlap metric; the boundary error remains modest (HD =
2.6 mm), confirming clinically acceptable performance.


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

Peter Uhlir
Regulatory Affairs Program Manager
GE HealthCare
Tel: (+36) 70-436-9317
Email: peter.uhlir@gehealthcare.com

Camille Vidal
Senior Director Regulatory Affairs – Digital, AW & SEI
GE HealthCare
Tel: 240-280-5356
Email: Camille.Vidal@gehealthcare.com

Common/Usual Name:
System, Image Processing, Radiological

Primary Classification Name:
Primary Regulation Number:
Primary Product Code:
Secondary Product Code:
Classification:

Medical image management and processing system
21 CFR 892.2050
LLZ
QIH
Class II

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


Primary Predicate Device
Device name:
Common/Usual Name:
Manufacturer:
510(k) number:
Classification Name:
Regulation Number:
Product Code:
Classification:

Volume Viewer Plus
System, X-Ray, Tomography, Computed
GE Medical Systems SCS
K041521
Computed tomography X-Ray System
21 CFR 892.1750
JAK
Class II

Reference Device
Device name:
Common/Usual Name:
Manufacturer:
510(k) number:
Regulation Number /
Classification Name /
Product Code:
Classification:

Spectral Bone Marrow
System, X-Ray, Tomography, Computed
GE Medical Systems, LLC
K223514
21 CFR 892.1750 / Computed tomography X-ray system / JAK
21 CFR 892.2050 / Automated Radiological Image Processing
Software / QIH
Class II

510(k) Premarket Notification Submission - VersaViewer


Specification
Primary Predicate Device:
Subject Device:
Comparison

All anatomies
CT, MR, PET, NM, XACT
DICOM images

All anatomies
CT, MR, PET, NM, XACT,
SCPT, US, CR, DX, RF,
XA, MR PJN, CT GSI, MG
and breast
tomosynthesis (for
presentation only).

Substantially equivalent.
The Image Support of proposed
device is adapted and compatible
with acquisition images evolution.
The image support has been
successfully verified and
validated. No safety and
effectiveness issues are raised by
the expanded scope of modality
coverage.
VersaViewer is not intended for
the displaying of digital
mammography images for
diagnosis.

Axial / Coronal / Sagittal
Oblique / 3D / Volume
Rendering / MIP / minIP /
Average Rendering / Surface
Rendering

Axial / Coronal /
Sagittal
Oblique / 3D / Volume
Rendering / MIP /
minIP and Average
Rendering

Substantially Equivalent
Both the predicate and proposed
devices include the Axial /
Coronal / Sagittal and Oblique /
3D / Volume Rendering / MIP /
minIP and Average Rendering
types.

The following image
manipulations are available:
(cid:120) Magnification
(cid:120) Roam/pan
(cid:120) ww/wl and , ww/wl
presets
(cid:120) simple oblique
(cid:120) link / unlink series.

Usual image
manipulations are
accessible directly from
active annotations in
viewports, through
mouse actions or icons
in the toolbar:
(cid:120) Zoom in / zoom
out
(cid:120) Roam / pan
(cid:120) WW/WL manual
adjustments and
presets panel
(cid:120) Multi oblique
tool: displays
three adjustable
obliques planes
(cid:120) Link / unlink
series

Substantially Equivalent
All the functionalities existed in
Volume Viewer Plus except the
multi-oblique tool.
This tool is like simple oblique
mode, available in Volume Viewer
Plus. It has been added in the
subject device, creating 3
orthogonal obliques views.
This function facilitates user’s
review but doesn’t add or remove
any information.


Yes
Segmentation tools
allow to create or edit
findings on 2D and 3D
views in axial, coronal
or sagittal standard
orientation.
(cid:120) Smart Brush
automatically
adapts brush
shape to the
image density /
signal.
(cid:120) Threshold Brush
selects values
within a given
threshold, with
the possibility to
add a factor to
smooth contour
edges.

Substantially Equivalent
Brush is a new segmentation-
based measurement, but its
result can be obtained by
combination of existing functions
already presented in the
predicate device. It improves and
optimizes the workflow.
This function has already cleared
in GEHC legacy device, BreView
(K233714).

It provides a variety of
methods for sharing
the results with clinical
partners.
(cid:120) Export images
and findings can
be saved as SCPT
series and
networked to
DICOM
destinations for
structured
reporting
purposes.
(cid:120) Copy images and
findings to paste
into personalized
communications.

Substantially Equivalent
Both the predicate and subject
device have capabilities to export
the information displayed in the
application.


Specification
Reference Device:
Subject Device:
Comparison

One View
Spectral Bone Marrow
VersaViewer

Substantially Equivalent
In the subject device, a fully
automated workflow generates
the desired images (colored MD
images of the segmented bone
region overlaid on the
monochromatic base or Virtual
Unenhanced images) as
secondary capture DICOM objects
and networks them to the
preconfigured DICOM
destinations (e.g. PACS) for the
user to review. Similar workflow
already exists in reference device,
Spectral Bone Marrow (K223514).
This change in the subject device
greatly improves the overall
efficiency of the review workflow.

Deep Learning based
segmentation (lung,
liver, bone, aorta, heart
and body (entire body))

Substantially equivalent
The One View feature includes CT
Multi Organ segmentation that
provides a fully automatic
segmentation based on deep-
learning model for six body parts
as lung, liver, bone, aorta, heart
and body (entire body), each with
its own distinctive contrast
parameters:
The deep learning algorithm
employed in the subject device
have been successfully verified
and validated, through
comparison to legacy
segmentation algorithms.


Spectral contrast parameters
(Base keV in greyscale,
Material density image
overlay of Water (HAP) in
color), utilized visualize bone
marrow.

Spectral contrast
parameters (keV, MD
overlay in greyscale or
color), utilized to create
organ contrast.

Substantially Equivalent
One View option of VersaViewer
adjusts the imaging parameters
of several body parts
automatically and displays them
in one image.
In the reference device, Spectral
Bone Marrow (K223514) the
fused image of colored material
density (MD) images (e.g water
(HAP)) of the segmented bone
region overlaid onto the base
monochromatic spectral CT
images or Virtual Unenhanced
images, as secondary capture
DICOM series.
In the subject device same
algorithm output is use but it is
applied for other six body parts as
lung, liver, bone, aorta, heart and
body (entire body),


Fast Spin Echo (3D FSE)
Gradient Echo (3D GRE)

Field Strength Compatibility
1.5T, 3.0T
1.5T, 3.0T, 7.0T

MR system software and activated through purchasable software option keys.


Fully sampled vs ARC 2x1x1.2
1.1
[-4.4, 6.5]

Fully sampled vs Sonic DL 4
1.4
[-2.4, 5.3]

Fully sampled vs Sonic DL 12
6.8
[-4.9, 18.6]


Fully sampled vs ARC 2x1x1.2
-1.5
[-4.4, 1.5]

Fully sampled vs Sonic DL 4
-2.0
[-5.2, 1.3]

Fully sampled vs Sonic DL 12
-2.3
[-10.1, 5.5]


Fully sampled vs ARC 2x1x1.2
3.0
[1.2, 4.9]

Fully sampled vs Sonic DL 4
3.2
[0.7, 5.6]

Fully sampled vs Sonic DL 12
9.1
[2.1, 16.0]

Fully sampled v s Sonic DL 12 6. 8 [-4.9, 18.6] F ully sampled vs Sonic DL 12 -2.3 [ -10.1, 5.5]


Fully sampled vs ARC 2x1x1.2
-0.1
[-0.3, 0.2]

Fully sampled vs Sonic DL 4
-0.1
[-0.4, 0.1]

Fully sampled vs Sonic DL 12
-0.2
[-0.8, 0.4]


Fully sampled vs Sonic DL 4
0.007
[-0.009, 0.023]

Fully sampled vs Sonic DL 12
0.014
[-0.018, 0.046]

Fully sampled v s Sonic DL 12 9. 1 [2.1, 1 6.0] F ully sampled vs Sonic DL 12 -0.2 [-0.8, 0.4]


Number of unique subjects:
Patients:
Healthy Volunteers:

Sites contributing data:
United States:
Outside of United States:

Subjects from clinical sites included examples
of various pathologies representing a mixture
of small, large, focal, diffuse, hyper- and hypo-
intense lesions

Contrast agents were used in a subset of the
data, as clinically indicated

GE HealthCare 1.5T, 3.0T, and 7.0T MR Systems


Traditional 510(k) Premarket Notification


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

Mireille Haddad
Regulatory Affairs Program Manager
GE HealthCare
Email: mireillehaddad@gehealthcare.com

Elizabeth Mathew
Senior Regulatory Affairs Manager
GE HealthCare
Tel: 262-424-7774
Email: elizabeth.mathew@gehealthcare.com

Common/Usual Name:
System, X-Ray, Tomography, Computed

Primary Classification Name:
Primary Regulation Number:
Primary Product Code:
Secondary Product Code:
Classification:

Computed Tomography X-Ray System
21 CFR 892.1750
JAK
QIH
Class II


10(k) Premarket Notifica
tion Submission-CardIQ
Suite

Common/Usual Name:
System, X-Ray, Tomography, C
omput

Classification Name:
Computed tomography X-Ray
System

510(k) Premarket Notification Submission-CardIQ Suite


Specification
Primary Predicate
Subject Device:
Comparison

Image Requirements:
• 120kVp
• Gated cardiac
acquisition
• DFOV - 24 cm -
35 cm
• Slice thickness ≤
3mm
• Non-contrast

Segmentation
and labeling
calcific regions
in the
coronaries


Manual
Segmentation
and labeling of
calcific regions

Computation of
calcium score -
Agatson Score &
Volume Scoring
methods

Substantially Equivalent
In the subject device, the calcium
score is used as input to a percentile
guide in order to be able to compare
the patient's calcium score with a
similar population of individuals.
Though the percentile guide
functionality does not exist in the
predicate device, this functionality
already exists in the reference
device, SmartScore 4.0 (K020929).

Identical
MPR Cardiac Review is intended to
assist readers in the review of
coronary artery imaging. Within this
review step, readers will find tools
aligned with a 2D coronary artery CTA
review, a segmented 3D Volume
Rendering model of the heart, as well
as general overview of all
reconstructions acquired within a
study such a multi-phase cine
acquisitions or delayed enhancement
imaging.


Yes (Contrast-
enhanced and non-
contrast cardiac
exams)

Substantial Equivalent
The predicate device already
segments the heart for contrast-
enhanced exams and the same
algorithm exists in the subject device
with no changes. The subject device
has been updated to add another
deep learning algorithm to segment
non-contrasted heart exams. The
new deep learning algorithm for
heart segmentation of non-
contrasted exams uses the same
model as the previous existing heart
segmentation algorithm for
contrasted exams, however now the
input is changed, and the model is
trained and tested with the non-
contrasted exams.

Substantial Equivalent
In the subject device, a predefined
HU threshold of -200 to 30 is
applied to the ROI and is
automatically generated on the
segmented heart which provides
the visualization of the heart fat
estimate. The estimated volume of
the heart fat is calculated for the
designated CACS phase selected. In
the reference device, CardIQ Xpress
2.0, the same functionality can be
performed using semi-automatic
segmentation tools.


Coronary Centerline
Tracking is available,
includes lumen
segmentation.

Substantially equivalent
The functionality of coronary
centerline tracking already exists in
the predicate device CardIQ Suite.
In the subject device, a new post-
processing step is added to the
coronary centerline tracking
algorithm to generate a new output:
the coronary lumen segmentation.
The lumen segmentation was already
available in the reference device
CardIQ Xpress 2.0. The post-
processing lumen segmentation
added in the subject device uses the
same image processing
methodology, based on pixel
intensity, that was used in CardIQ
Xpress 2.0.
Additionally, the Deep learning
algorithm for coronary tracking in
the subject device has been updated
by retraining to a finer resolution for
more precision and incorporates
some post-processing steps to refine
the centerline and tracking at vessel
ostia, aorta, and vessel bifurcations.

Substantially equivalent
The functionality of coronary
centerline labelling already exists in
the predicate device.
The algorithm coronary labelling has
been improved to increase the
performance but uses a similar
approach as the one in the predicate
device.


Lumen diameter
Quantification
and minimum
diameter
computations
Estimate
(Narrowing
Highlights)

Substantial Equivalent
The lumen diameter quantification
is calculated using a new non-deep
learning algorithm and displayed as
a lumen minimum diameter profile
graph. This profile is equivalent to
the minimum diameter lumen
profile available in the reference
device, CardIQ Xpress 2.0
(K073138).
A local reduction in minimum
diameter in the lumen profile is
color coded based on a signal
processing algorithm.

Substantial Equivalent
The computational method and
user workflow for vascular
measurements in the subject
device, is identical to the reference
device, CardIQ Xpress 2.0
(K073138).


Predicate device (MammoScreen 3)
Subject device (MammoScreen 4)

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

MammoScreen® 4 is a concurrent
reading and reporting aid for physicians
interpreting mammograms. It is
intended for use with compatible full-
field digital mammography and digital
breast tomosynthesis. The device can
also use compatible prior examinations
in the analysis.
Output of the device includes graphical
marks of findings as soft-tissue lesions or
calcifications on mammograms along
with their level of suspicion scores. The
lesion type is characterized as
mass/asymmetry, distortion, or
calcifications for each detected finding.
The level of suspicion score is expressed
at the finding level, for each breast, and
overall for the mammogram.
The location of findings, including
quadrant, depth, and distance from the
nipple, is also provided. This adjunctive
information is intended to assist
interpreting physicians during reporting.
Patient management decisions should
not be made solely based on the analysis
by MammoScreen 4.

Physicians qualified to read
mammograms.

Design
Software-only device
Software-only device

MammoScreen 3 is powered by
artificial intelligence/machine
learning-based software algorithm

MammoScreen 3 outputs a level of
suspicion at the finding, breast and
case level.


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

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

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

Included.
The PCCP in the subject device includes
proposed modifications related to
extending supported image acquisition
systems.


Non-inferiority in standalone cancer detection performance
compared to the previous version of MammoScreen

Positive lower bound of the 95% CI of the difference in
endpoints between the version under evaluation
(MammoScreen 4 on Envision) and the reference version
(MammoScreen 2 on Dimension)

2,950 (each patient underwent a DBT acquisition with two Hologic
mammography systems)

Asian: 16
White: 1180
Black: 94
Other (including American Indian, Alaska Native, Native Hawaiian
or Other Pacific Islander): 14
Hispanic: 88
Not Hispanic: 1136

Density, Lesion type (mass/asymmetries, calcifications, distortion),
Age, Lesion size, Lesion severity, Race, Ethnicity, Data
provenance, Reference standard for negative cases.

Positive cases: biopsy-proven presence of cancer.
Benign cases: cases confirmed by biopsy result and cases
confirmed by imaging follow-up.
Negative cases: verified by imaging follow-up.

Independence of test data from training
data

Data sources are separated into the training/tuning group and the
test group. Sources in the training/tuning group may only be used
for model training and tuning. Sources in the test group may only
be used for external validation of the model’s performances on


Support of GE mammograms (no re-training required)

Support of a new mammography manufacturer other than Hologic
and GE (re-training required) – this modification may also include
the support of GE mammograms in case Modification #1 does not
conclude to the non-inferiority on GE mammograms compared to
Hologic

Non-inferiority of device standalone performance on mammograms
of the manufacturer under evaluation compared to Hologic
mammograms

AUC at the mammogram, breast and finding level (AUC LROC)

The table below lists and describes the anticipated modifications:


• Modification #1: See Table 1.
• Modification #2: See Table 1 (unpaired comparisons) and Table 2
(paired comparisons).

Upon demonstration of the non-inferiority through the
standalone performance testing, changes will be documented in a
minor release amending:
- The Algorithm test protocol and results documents
- The User Guide
- The device label

Upcoming updates are communicated to users through advisory notices
sent by email at least 2 weeks before deployment. Users may choose to
opt-out the update during the 2-week notice period.


MammoScreen
(K192854) on
Hologic FFDM only

MammoScreen 2
(K211541) on
Hologic DBT + FFDM

MammoScreen 2
(K211541) on
Hologic DBT + 2DSM

MammoScreen 3
(K240301) on
Hologic DBT + FFDM
with FFDM priors

MammoScreen 3
(K240301) on
Hologic DBT + 2DSM
with DBT + 2DSM
priors

Table 1: Primary endpoints and acceptance criteria for unpaired comparisons.


Table 2: Primary endpoints and acceptance criteria for paired comparisons.


MammoScreen
(K192854) on
Hologic FFDM only


BrightHeart
7-11 boulevard Haussmann
Paris 75009, France

Christophe Gardella
Chief Technical Officer
Tel. +0033686543950
Email. christophe@brightheart.fr

Submission Correspondent:
Christophe Gardella


Device Trade Name:
BrightHeart View Classifier

Device Common Name:
Fetal ultrasound view classifier

21 CFR §892.2050, Medical image management and
processing system


Subject Device
BrightHeart View
Classifier

Reference Device
HeartAssist feature in
the Samsung V8
Diagnostic
Ultrasound System,
V7 Diagnostic
Ultrasound System.

Applicant
BrightHeart
Ontact Health
Samsung


The Samsung V8 and
V7 are general
purpose, mobile,
software controlled,
diagnostic ultrasound
systems, including
fetal ultrasound.

Model method
Neural networks
Neural networks
Neural networks

Classification of
ultrasound images
into standard views of
fetal heart.

Classification of
ultrasound images
into standard views of
adult heart,
determination cardiac
measurements.

Classification of
ultrasound images
into standard views of
fetal heart scanning,
and detection of
calipers used for
measurements

Identifies standard
views of the heart and
abdomen in images
and video clips.

Identifies standard
views of the heart in
images and video
clips, detection of
cardiac
measurements.


(MammoScreen BD – K241561)
(MammoScreen BD – K243685)

MammoScreen® BD is a software
application intended for use with
compatible full-field digital
mammography and digital breast
tomosynthesis systems.
MammoScreen BD evaluates the
breast tissue composition to provide an
ACR BI-RADS 5th Edition breast
density category. The device is
intended to be used in the population of
asymptomatic women undergoing
screening mammography who are at
least 40 years old.
MammoScreen BD only produces
adjunctive information to aid
interpreting physicians in the
assessment of breast tissue
composition. It is not a diagnostic
software.
Patient management decisions should
not be made solely based on analysis
by MammoScreen BD.

Asymptomatic women undergoing
mammography

Intended user population
Interpreting physicians
Interpreting physicians

Design
Software-only device
Software-only device

Compatible full-field digital
mammography and digital breast
tomosynthesis systems (using
Synthetic 2D (2DSM)) for Hologic.

Compatible full-field digital
mammography and digital breast
tomosynthesis systems (using
Synthetic 2D (2DSM)) for Hologic
and GE.

Breast density assessment based on
ACR BIRADS 5th edition category at
the mammogram level.

Support of Hologic Envision
system and GE
mammograms

Predetermined Change Control Plan
(PCCP) including:


First quartile (Q1): 47.0 Mean: 56.0 Third quartile (Q3):
64.0

White: 49.13%
Asian: 7.63%
Black or African American: 0.43%
Native Hawaiian or Pacific Islander: 0.09%
Unknown: 42.72%


Superiority in standalone performance for density assignment of MammoScreen BD compared
to a pre-determined reference value (Kappa = 0.85).
reference

No change from previous
clearance. Quadratically
weighted Cohen’s kappa
between the density
assessment of
MammoScreen BD and
the established ground
truth.
Kappa quadratic = 89.03
[95% CI: 87.43 – 90.56]

Quadratically weighted
Cohen’s kappa between the
density assessment of
MammoScreen BD and the
established ground truth.
Kappa quadratic = 89.54
[95% CI: 86.88 – 91.69]

Quadratically weighted Cohen’s
kappa between the density
assessment of MammoScreen BD
and the established ground truth.
Kappa quadratic = 93.19 [95% CI:
90.50 – 94.92]

The one-sided p-value for the test H0: Kappa ≤ 0.85 is less than the significance level (α=0.05)
and the lower bound of the 95% confidence interval for Kappa > 0.85 indicating that the
observed weighted Kappa is statistically significantly greater than 0.85.

Range: [40 – 90]
First quartile (Q1): 50.0
Mean: 58.5
Third quartile (Q3 : 66.0
• Age < 55: 570
• 55 ≤ Age < 65: 308
• Age ≥ 65: 269

Range: [36 – 86]
First quartile (Q1): 48.0
Mean: 56.0
Third quartile (Q3): 65.0
• Age < 55: 234
• 55 ≤ Age < 65: 130
• Age ≥ 65: 136

Range: [31 -86]
First quartile (Q1) : 47.0
Mean : 57.2
Third quartile (Q3): 67.0
• Age < 55: 234
• 55 ≤ Age < 65: 130
• Age ≥ 65: 136

White: 273
Asian: 102
Black or African
American: 88
American indian or
alaska native: 4
Native hawaiian or
pacific islander: 4

Asian: 6
White: 401
Black or African
American: 40
Hispanic: 23
Not Hispanic: 388

Asian: 48
White: 48
Black: 41
Other (including American Indian,
Alaska Native, Native Hawaiian or
Other Pacific Islander): 83
Hispanic: 88


The reference standard for breast density value was established by majority rule among the
assessment of 5 breast radiologists with at least 10 years of experience in breast imaging
interpretation.

Independence
of test data
from training
data

Data sources are separated into the training/tuning group and the test group. Sources in the
training/tuning group may only be used for model training and tuning. Sources in the test group
may only be used for external validation of the model’s performances on unseen data (i.e., from
sources entirely left out during training and tuning).
Data used for the standalone performance testing only belongs to the test group.


Modification #1
Support of Siemens Mammograms
(retraining required)

Modification #2
Pre-training of backbone using
Unsupervised Machine Learning (as
opposed to Supervised Machine
Learning)

Data used for
development and
modifications,
representing the
target population

No new data collection is foreseen for this
change.

Superiority in standalone performance for density assignment of MammoScreen BD
compared to a pre-determined reference value (Kappa = 0.85).
reference


Quadratically weighted Cohen’s kappa between the density assessment of
MammoScreen and the established ground truth

Lower bound of the 95% confidence interval > 0.85

Upon demonstration of the superiority through the standalone performance testing,
changes will be documented in a minor release amending:
• The Algorithm test protocol and results documents
• The Device Label, including the User Guide

Upcoming updates are communicated through advisory notices sent by email at least
2 weeks before deployment. Advisory notices contain:
• The new version identification,
• A summary of the change,
• The schedule for the application of the change,
• Statement that the Support team will contact the customer and/or user for
acceptance, training or scheduling of the change, if necessary,
• A link to access the updated User Guide, where the changes mentioned are
reflected.
Users may decide to opt out of the update during the 2-week notice period.
MammoScreen BD does not have its own user interface. The new labelling for
MammoScreen BD will be available on the compatible third-party software once the
update is activated.

Characterization
of the device
before and after
implementation
of changes

The device will be accessible to more centers, and thus to more woman. Prevents
obsolescence of MammoScreen BD. Better representation of breast tissue diversity
leading to higher overall performances and a better generalization on unseen data.

Monitoring,
detection, and
response to
deviations in
device
performance

Therapixel monitors customer sites. The distribution of breast density assessment
obtained is determined on a representative screening distribution, which serves as a
Reference Distribution. Device monitoring compares breast density assessment in
real conditions to the reference distribution and alerts of any deviations. The
investigation can result in a field-safety notice, a Medical Device Report.


AAMI ANSI ES60601-1:2005/(R)2012 & A1:2012 C1:2009/(R)2012 &
A2:2010/(R)2012 (Cons. Text) [Incl. AMD2:2021] Medical electrical
equipment - Part 1: General requirements for basic safety and essential
performance (IEC 60601-1:2005, MOD)

IEC60601-1-2:2014 [Including AMD 1:2021] , Medical electrical
equipment - Part 1-2: General requirements for basic safety and essential
performance - EMC

IEC 60601-2-37 Edition 2.1 2015, Medical electrical equipment – Part 2-
37: Particular requirements for the basic safety and essential performance
of ultrasonic medical diagnostic and monitoring equipment

IEC TR 60601-4-2 Edition 1.0 2016-05, Medical electrical equipment -

with the following FDA-recognized standards.


Part 4-2: Guidance and interpretation - Electromagnetic immunity:
performance of medical electrical equipment and medical electrical
systems

AAMI / ANSI / ISO 10993-1:2018, Biological evaluation of medical
devices – Part 1: Evaluation and testing within a risk management process

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

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

SAMSUNG MEDISON CO., LTD. Traditional 510(k)


Synapse 3D
Base Tools
(V7.0) (This
submission)

Annotations -
Standardized and
Free Text

Table 1 Device Features and Technical Characteristics Comparison Matrix


MPR
・ orthogonal /
oblique /
curved
Multi-Planar
Reconstructio
ns (MPR),
・ Sector and
rectangular
shape MPR
image
viewing
・ MPR for
dental images
・ Multiple MPR
images along
an object
(Slicer)

Maximum,
Average,
Minimum
Intensity
Projection


General image
data management
and
administration
tools

Some new segmentation
applications are added
and implemented using
the same deep learning
method called as “Fully
Convolutional
Network”.

Added new feature.
Note: The new feature


Pancreas Analysis is the
similar to Contour
ProtégéAI (“Reference
Device”), which was
cleared by CDRH via
K213976 on
02/03/2022. This added
new feature does not
raise different questions
of safety and
effectiveness.

Added new feature.
Note: The new feature
Rectal Analysis is the
similar to Contour
ProtégéAI (“Reference
Device”), which was
cleared by CDRH via
K213976 on
02/03/2022. This added
new feature does not
raise different questions
of safety and
effectiveness.

Added new feature.
Note: The new feature
Segmentation Tools is
the similar to Contour
ProtégéAI (“Reference
Device”), which was
cleared by CDRH via
K213976 on
02/03/2022. This added
new feature does not


Added new feature.
Note:
The new feature
Post-reconstruction
request is the same as
the feature available on
the SCENARIA View
(“Reference Device”),
which was cleared by
CDRH via K190841 on
09/13/2019. This added
new feature does not
raise different questions
of safety and
effectiveness.

Added new feature.
Note:
The purpose of this
function is the
visualization of organs,
etc. Therefore, this
added feature does not
raise different questions
of safety and
effectiveness.


Age 22-34 years old 23
35-64 years old 484
65-120 years old 579
Manufacturer SIEMENS 507
GE 288
PHILIPS 260
CANON(TOSHIBA) 22
FUJIFILM(HITACHI) 9


PREDICATE DEVICE:
QANGIO XA 3D (K182611)

QHA (Class 2) – X-ray
Angiographic Imaging
Based Coronary Vascular
Simulation Software

Patient study browser
(used to select the patient
study of interest)

Interactive image handling
(incl. windowing, zooming,
panning, filtering, window-
level)


Cine loop review with
controls for speed, and
frame-by-frame review.

ECG display
(used for ECG signal display
in synchrony with the review
of the XA images)

ISO center calibration
(provided by the
manufacturer of the X-ray
acquisition equipment)

Possibility to edit or delete an
existing analysis

Multiple analyses possible on
a single image

Guided workflow supporting
step-by-step analysis

Selection of the angiographic
series to be used in the
analysis

Selection is now
supported by an AI/ML
model and manual
correction

Selection of the
determination of the start
and end points of the vessel
to be analyzed


Determination of the ED
frame within the series to be
used

Selection is now
supported by a
combination of an AI/ML
model and an analytical
algorithm using the ECG
data and manual
correction

Determination of start and
end frame for flow velocity
calculation

Automatic determination
of the start and end
frame is now supported
by an analytical
algorithm based on
traditional image
processing techniques or
manual indication

Only supported manual
indication of the start and
end frame


Proposed Device: Bunkerhill AAQ
Predicate Device: Briefcase

Bunkerhill AAQ is a radiological image
processing system software indicated for
use in the analysis of CT exams with or
without contrast, that include the L1 – L5
region of the abdominal aorta, in adults
aged 22 and older.
The device is intended to assist
appropriately trained medical specialists
by providing the user with the maximum
axial abdominal aortic diameter
measurement of cases that include the
abdominal aorta. Bunkerhill AAQ is
indicated to evaluate normal and
aneurysmal abdominal aortas and is not
intended to evaluate post- operative
aortas.

BriefCase-Quantification is a
radiological image management and
processing system software indicated for
use in the analysis of CT exams with
contrast, that include the abdominal
aorta, in adults or transitional
adolescents aged 18 and older.
The device is intended to assist
appropriately trained medical specialists
by providing the user with the maximum
abdominal aortic axial diameter
measurement of cases that include the
abdominal aorta (M-AbdAo) BriefCase-
Quantification is indicated to evaluate
normal and aneurysmal abdominal aortas
and is not intended to evaluate post-
operative aortas.

A table comparing the intended use of the subject and predicate devices is provided below.


The Bunkerhill AAQ results are not
intended to be used on a stand-alone basis
for clinical decision-making or otherwise
preclude clinical assessment of cases.
These measurements are unofficial, are
not final, and are subject to change after
review by a qualified interpreting
physician. For final clinically approved
measurements, please refer to the official
radiology report. Clinicians are
responsible for viewing full images per
the standard of care.

The BriefCase-Quantification results are
not intended to be used on a stand-alone
basis for clinical decision-making or
otherwise preclude clinical assessment of
cases. These measurements are
unofficial, are not final, and are subject
to change after review by a radiologist.
For final clinically approved
measurements, please refer to the official
radiology report. Clinicians are
responsible for viewing full images per
the standard of care.


Proposed Device:
Predicate Device:
Summary

Regulation number
21 CFR §892. 2050
21 CFR §892. 2050
Same

CT exams with or
without contrast that
include the abdominal
aorta

CT exams with
contrast that include
the abdominal aorta

Artificial intelligence
algorithm with database
of images.

Output can be optionally
or on-demand be
inserted into the
radiology report;
produces a preview
image annotated with
the maximum axial
diameter measurement.
The original, unmarked
series remains available
in the PACS as
well.

Produces a preview image
annotated with the
maximum axial diameter
measurement. The original,
unmarked series remains
available in the PACS as
well.


-Bunkerhill AAQ, is
hosted on a cloud server,
analyzes applicable CT
images that are acquired
on CT scanner that are
forwarded to Bunkerhill
AAQ.
- The results of the
analysis are exported
in DICOM format, and
are sent to a PACS
destination for review
by medical specialists,
to assist in the

-BriefCase-Quantificat
ion, is hosted on a
cloud server, analyzes
applicable CT images
that are acquired on
CT scanner that are
forwarded to
BriefCase-Quantificati
on.
- The results of the
analysis are exported
in DICOM format, and
are sent to a PACS
destination for review

by medical specialists,
to assist in the
measurement of the
abdominal aorta.

Appropriately trained
medical specialists

Intended location
Medical facility
Medical facility
Same


Classification Description
21 CFR §
Product Code

System, imaging, pulsed doppler,
ultrasonic

System, imaging, pulsed echo,
ultrasonic

Transducer, ultrasonic, diagnostic
892.1570
ITX

Medical image management and
processing system

Diagnostic Intravascular Catheter
870.1200
OBJ*

Common Name Diagnostic Ultrasound System and Transducers


Feature
Feature: R-Trigger
K240850
Comparison

Abdominal, Cardiac Adult, Cardiac other (Fetal), Cardiac
Pediatric, Cerebral Vascular, Cephalic (Adult), Cephalic
(Neonatal), Fetal/Obstetric, Gynecological, Intraoperative
(Vascular), Intraoperative (Cardiac), intra-luminal, intra-
cardiac echo, Musculoskeletal (Conventional),
Musculoskeletal (Superficial), Ophthalmic, Other: Urology,
Pediatric, Peripheral Vessel, Small Organ (Breast, Thyroid,
Testicle), Transesophageal (Cardiac), Transrectal,
Transvaginal, Lung.

Trained healthcare professionals
Intended for sonographers, physicians, and biomedical
engineers who operate and maintain your product.
Before use of the system and user information, the user
must be familiar with ultrasound techniques. Sonography
training and clinical procedures are not included in the User
Manual or with the EPIQ Series Diagnostic Ultrasound
System.

Clinics, hospitals, and clinical point-of-care for diagnosis of
patients.

USA FDA
Class II
Class II
Identical to predicate

Primary Product
IYN
IYN
Identical to predicate

System, Imaging, Pulsed Doppler, Ultrasonic

Primary Regulation
21 CFR 892.1550
21 CFR 892.1550
Identical to predicate

Table 1: Comparison to Predicate for introduction of R-Trigger onto EPIQ


Diagnostic ultrasonic transducer
Ultrasonic pulsed echo imaging
system
Diagnostic intravascular catheter
Automated Radiological Image
Processing Software

Reusable- Systems
Yes
Yes
Identical to predicate

Duration of use
Limited (≤ 24 hours)
Limited (≤ 24 hours)
Identical to predicate

Device Track
Track 3
Track 3
Identical to predicate

The R-Trigger AI software feature on Philips EPIQ and
Affiniti Ultrasound System is intended to support detection
of R-wave peak (R-trigger) as an input to AutoStrain and
AutoMeasure applications, as well as other cardiac clinical
applications. The R-trigger algorithm is planned to be
implemented as workflow enhancement to the AutoStrain
(previously cleared by FDA; K190913) and AutoMeasure
(previously cleared by FDA; K211597) applications on EPIQ
and Affiniti Ultrasound Systems in the VM13 software
release.

The EPIQ ultrasound systems currently detects R-Trigger
events by processing a patient’s ECG signal using the on-
cart physio board.

Similar. In the subject device, the R-Trigger algorithm will
provide an additional method of determining R-Trigger
events for a patient’s acquired ultrasound clip.
Currently, the Ultrasound System requires an ECG signal,
which is processed by the on-cart physio board, to detect R-
Trigger events in the cardiac cycle. These detected events
are used as input into various cardiac clinical applications.
In the subject device, the R-Trigger algorithm will serve as a
back-up for R-Trigger event detection.
Detecting events from the ECG signal on the system will still
be the preferred method. In case the ECG signal is not
usable or not available, the new R-Trigger algorithm will
detect the events.
From a user perspective, their only difference is that they
will be able to use certain cardiac clinical applications on
acquired clips which do not have a usable ECG signal in the
subject device. Otherwise, there are not able changes
visible to the user as both methods work in the background.


Affiniti Series Diagnostic Ultrasound System

Abdominal, Cardiac Adult, Cardiac Other (Fetal), Cardiac
Pediatric, Cerebral Vascular, Cephalic (Adult), Cephalic
(Neonatal), Fetal/Obstetric, Gynecological, Intraoperative
(Vascular), Intraoperative (Cardiac), Musculoskeletal
(Conventional), Musculoskeletal (Superficial), Other: Urology,
Pediatric, Peripheral Vessel, Small Organ (Breast, Thyroid,
Testicle), Transesophageal (Cardiac), Transrectal,
Transvaginal, Lung.

Table 2: Comparison to Predicate for introduction of R-Trigger onto Affiniti


Feature
Feature: R-Trigger
K240850
Comparison

Diagnostic ultrasonic transducer
Ultrasonic pulsed echo imaging
system
Automated Radiological Image
Processing Software

The Affiniti ultrasound systems currently detects R-Trigger
events by processing a patient’s ECG signal using the on-
cart physio board.


Table 1: AutoMeasure Subjects’ Demographics


Table 2: AutoStrain Subjects’ Demographics


Table 3: R-trigger Time Stamp Subjects’ Demographics


Endpoint
Hypothesis
Lower LoA (95% CI)
Upper LoA (95% CI)
Type

Table 4: Relative Bland-Altman Analysis for R-trigger AI-based workflow vs Ground Truth


Hypothesis
Outcomes Comparison
Acceptance Criteria

Table 5: Pearson’s Correlation for R-trigger AI-based workflow vs ground Truth


Table 7: Performance results of the different age – and BMI groups.


Classification Description
21 CFR §
Product Code

System, imaging, pulsed doppler,
ultrasonic

System, imaging, pulsed echo,
ultrasonic

Transducer, ultrasonic, diagnostic
892.1570
ITX

Medical image management and
processing system

Diagnostic Intravascular Catheter
870.1200
OBJ


The subjects whose TTE clips were used in the study were:


Black or African American
45.18% (1791/3964)


Software verification and validation testing


AZmed
10 Rue d’Uzès
75002 Paris, France
Phone: +33 6 72 19 04 19

Anthony JOSEPH
QARA Associate
10 Rue d’Uzès
75002 Paris, France
Phone: +33 6 72 19 04 19
Mail: anthony@azmed.co


Lunit INSIGHT CXR Triage
- Predicate (K220164)

Rayvolve PTX-PE -
Subject device 510(k) file

Device Name
Lunit INSIGHT CXR Triage
Rayvolve

Lunit INSIGHT CXR Triage
is a radiological
computer-assisted triage
and notification software
that analyzes adult chest
X-ray images for the
presence of pre-specified
suspected critical findings

Rayvolve PTX-PE is a
radiological
computer-assisted triage
and notification software
that analyzes chest x-ray
images (Postero-Anterior
(PA) or Antero-Posterior
(AP)) of patients 18 years

Equivalent,
slight precision
on the
intended
patient
population (see
the line
‘intended

of operation vice and the cited predicate device.


(pleural effusion and/or
pneumothorax). Lunit
INSIGHT CXR Triage uses
an artificial intelligence
algorithm to analyze images
for features suggestive of
critical findings and provides
case-level output available
in the PACS/workstation for
worklist prioritization or
triage. As a passive
notification for
prioritization-only software
tool within standard of care
workflow, Lunit INSIGHT
CXR Triage does not send
a proactive alert directly to
the appropriately trained
medical specialists. Lunit
INSIGHT CXR Triage is not
intended to direct attention
to specific portions of an
image. Its results are not
intended to be used on a
stand-alone basis for clinical
decision-making.

of age or older for the
presence of pre-specified
suspected critical findings
(pleural effusion and/or
pneumothorax).
Rayvolve PTX-PE uses an
artificial intelligence
algorithm to analyze the
images for features
suggestive of critical
findings and provides
study-level output available
in DICOM Node Servers
for worklist prioritization or
triage.
As a passive notification for
prioritization-only software
tool within the standard of
care workflow, Rayvolve
PTX-PE does not send a
proactive alert directly to a
trained medical specialist.
Rayvolve PTX-PE is not
intended to direct attention
to specific portions of an
image. Its results are not
intended to be used on a
stand-alone basis for
clinical decision-making.

patient
population for
the
justification)
and for other
DICOM
storage
platforms the
subject device.
Other DICOM
storage
platforms are
equivalent to
PACS.
None of those
precisions
raise new
questions of
safety or
effectiveness

Appropriately trained
medical specialists who are
qualified to interpret chest
radiographs

Equivalent.
Healthcare
professionals
are qualified to
interpret chest
radiographs

Equivalent:
Our dataset
contains
images for
patients of


18-21 years
old.
The
performance
results (see
Appendix 25)
shows that the
performances
of Rayvolve
PTX-PE for
patients
between 18
and 21 years
old are
equivalent to
the results
obtained for
patients older
than 21 years
old. So, it
doesn’t raise
new questions
of safety or
effectiveness,
and maintain
the same level
of performance
than the
predicated
device

Pleural effusion,
pneumothorax
Chest/Lung

Postero-Anterior (PA) or
Antero-Posterior (AP)
chest X-ray

Equivalent.
Inclusion of the
orientation of
the image


acquisition, but
the
performance
testing (see
appendix 25)
has
demonstrated
that Rayvolve
PTX-PE
achieves
equivalent
accuracy on
both AP and
PA views, so
considering
both views
doesn’t raise
new questions
of safety or
effectiveness,
and maintain
the same level
of performance
than the
predicated
device

Algorithm for
pre-specified
critical
findings
detection

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

AI algorithm designed to
detect pleural effusion and
pneumothorax in chest
X-ray images.
Rayvolve PTX-PE uses a
vendor agnostic algorithm
compatible with DICOM
chest X-ray images.


Lunit INSIGHT CXR Triage
- Predicate (K220164)

Rayvolve PTX-PE -
Subject device 510(k) file

Lunit INSIGHT CXR Triage
is designed as a software
module that can be
deployed on several
computing and X-ray
imaging platforms such as
radiological imaging
equipment, PACS, On
Premise or On Cloud.

Rayvolve PTX-PE is
designed as a software
module that can be
deployed on several
computing and X-ray
imaging platforms such as
radiological imaging
equipment, PACS, On
Premise or On Cloud.

Device output
in case of
positive
detection

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

When deployed on other
radiological imaging
equipment Rayvolve
PTX-PE automatically
runs after image
acquisition and prioritizes
and displays the analysis
result through the worklist
interface of
PACS/workstation.
No markup on the original
image. Secondary capture
of the device will indicate
the presence of findings
suspicious of
pneumothorax or pleural
effusion.
Upon image acquisition
from other radiological
imaging equipment (e.g,
X-ray systems), a passive
notification indicating which
studies were flagged by
Rayvolve PTX-PE is
generated.
The notification is


information. It is not
intended to inform any
clinical decision,
prioritization, or action to the
technologist.

contextual and does not
provide any diagnostic
information. It is not
intended to inform any
clinical decision,
prioritization, or action.

Notification
(i.e., recipient
timing and
means of
notification)

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

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

Equivalent:
DICOM
viewers are the
software that
allow to open
the Dicom files
on the
workstations, it
doesn’t raise
new questions
of safety or
effectiveness

Performance
level - Timing
of notification

The average time taken by
the device to analyze the
study and send a
notification to the worklist is
20,76 seconds for pleural
effusion and 20.45 seconds
for pneumothorax

The average time taken by
the device to analyze the
study and send a
notification to the worklist is
19.56 seconds for pleural
effusion and 19.43
seconds for pneumothorax

Equivalent
The
performance
results of the
subject device
are slightly
better than the
results for the
predicate
device, so it
doesn’t raise
new questions
of safety or
effectiveness.

Performance
level -
accuracy of
classification


Lunit INSIGHT CXR Triage
- Predicate (K220164)

Rayvolve PTX-PE -
Subject device 510(k) file

results for the
predicate
device, so it
doesn’t raise
new questions
of safety or
effectiveness.


Brainlab Ltd.
35 Efal Street
Petach-Tikva, Israel 4951132

Manufacturer
Address:
Mfg. Phone:
Contact Person:
Date:

Brainlab Ltd
35 Efal Street
Petach-Tikva, Israel 4951132
Tel.: +972-3-929-0929
Veronika Kravtsov, RA Manager
May 8, 2025

Radiological Image Processing System –
classified as Class 2 QIH and LLZ
Regulation Number 21 CFR 892.2050
TraumaCad Neo (1.1)

TraumaCad Neo (K231498)
PeekMed Web (V1) (K222767)

TraumaCad Neo 1.1 allows surgeons to evaluate digital images
while performing various pre-operative surgical planning and
evaluation of images. This software application enables
surgeons to plan operations on screen, execute measurements,
and facilitates a film-less orthopedic practice. TraumaCad Neo
1.1 also allows post-operative review and assessment of X-ray
images obtained after the surgical procedure, with a feature for
automatic surgery outcome analysis of postoperative total hip
arthroplasty images. The program features an extensive
regularly updated library of digital templates from leading
manufacturers. TraumaCad Neo supports DICOM and is
communicating with Quentry®, a proprietary web-based cloud
service from Brainlab and with other healthcare data platforms,
such as PACS solutions. It is through these healthcare data
platforms, where the medical staff can upload images to plan
their expected results prior to the procedure to create a smooth
surgical workflow from start to finish.

TraumaCad Neo is indicated for assisting healthcare

professionals to analyze orthopedic conditions and to plan

orthopedic procedures by overlaying on relevant radiological

images visual information such as measurements and

prosthesis templates. Clinical judgment and experience are

Pursuant to CFR 807.92, the following 510(k) Summary is provided:


required to properly use the software. The software is no

intended for primary radiological image interpretation or

radiological appraisal. Device is not intended for use on mobile

Comparison of
Technological
Characteristics:

With respect to technology and intended use, TraumaCad Neo
1.1 is substantially equivalent to its predicate devices. Based
upon the outcomes from the Risk Analysis and Performance
Testing Evaluation, Brainlab Ltd. believes that the modification
of TraumaCad Neo 1.0 (predicate device) which allows it to
become TraumaCad Neo 1.1 does not raise additional safety or
efficacy concerns. The following comparison tables depict the
changes.


Features/ Characteristics
TraumaCad Neo 1.1
TraumaCad

Post Operative
Automatically (AI) for
Manually for

Landmark Placement
Hip images, manually
modules


AZmedSAS
10rued’Uzès
75002Paris
Phone:+33643315138

ChristelleBAILLE
HeadofQARA
10rued’Uzès
75002Paris
Phone:+33643315138
Mail:christelle@azmed.co


Manufacturer BrandName CommercialName 510KNumber


Predicate - Auto Lung
Nodule Detection
(K201560)

Rayvolve LN - Subject
device 510(k) file

Regulation Number
21 CFR 892.2070
21 CFR 892.2070


Regulation Description
Medical Image Analyser
Medical Image Analyser

The Auto Lung Nodule
Detection is
computer-aided detection
software to identify and
mark regions in relation to
suspected pulmonary
nodules from 10 to 30 mm
in size. It is designed to
aid the physician to review
the PA chest radiographs
of adults as a second
reader and be used as
part of S-Station, which is
operation software
installed on Samsung
Digital X-ray Imaging
systems. Auto Lung
Nodule Detection cannot
be used on the patients
who have lung lesions
other than abnormal
nodules.

Rayvolve LN is a
computer-aided detection
software device to assist
radiologists to identify and
mark regions in relation to
suspected pulmonary
nodules from 6 to 30mm
size. It is designed to aid
radiologists in reviewing
the frontal (AP/PA) chest
radiographs of patients of
18 years of age or older,
acquired on digital
radiographic systems as a
second reader and be
used with any DICOM
Node server. Rayvolve LN
provides adjunctive
information only and is not
a substitute for the original
chest radiographic image.

Target population
Physician
Radiologists

Device intended as a
second-reader for
physicians interpreting
chest radiographs


ROI marked on the
duplicated input
image

Biocompatibility /
electromagnetic /
magnetic resonance /
Electrical/mechanical /
chemical / thermal /
radiation/ steriliy safety

N/A, the device is a
standalone software/

Reader workflow
Second reader workflow
Second reader workflow


Regulation Number
Regulation Name
Product Code

Medical Image Management and Processing System

Regulation Number, Name and Product Code:


Manufacturer Name:
Clarius Mobile Health Corp.

Automated Radiological Image Processing Software


Device Trade Name:
AI-Rad Companion Prostate MR

Manufacturer Name:
Siemens Medical Solutions USA Inc.


Automated Radiological Image Processing Software


Clarius Ultrasound Transducers
C3 HD3; EC7 HD3

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

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


RATIONALE
(if subject device differs
from predicate device)

Clarius Prostate AI
Clarius Bladder AI
AI-Rad Companion Prostate

Primary Product Code
QIH
QIH
QIH
Same as predicate device.

Automated Radiological
Image Processing Software

Medical Image Management
and Processing System

Regulation Number
21 CFR § 892.2050
21 CFR § 892.2050
21 CFR § 892.2050
Same as predicate device.

Intended for use as an
assistive tool during the
acquisition and
interpretation of ultrasound
images utilizing an artificial
intelligence/machine-
learning algorithm for
segmentation and
measurement of anatomical
structures.

Non-invasive processing of
ultrasound images using
automatic image
segmentation and
measurement of anatomical
structures utilizing artificial
intelligence/ machine
learning algorithms.

Non-invasive processing of
MR images using automatic
image segmentation and
measurement of anatomical
structures utilizing artificial
intelligence algorithms.

Clarius Prostate AI is
intended for semi-automatic
measurements of prostate
volume on ultrasound data
acquired by the Clarius
Ultrasound Scanner (i.e.,
curvilinear and endo-cavitary
scanners). The user shall be
a healthcare professional
trained and qualified in
ultrasound. The user retains
the responsibility of

Clarius Bladder AI is
intended for semi-automatic
non-invasive measurements
of bladder volume on
ultrasound data acquired by
the Clarius Ultrasound
Scanner (i.e., curvilinear and
phased array scanners). The
user shall be a healthcare
professional trained and
qualified in ultrasound. The
user shall retain the ultimate

AI-Rad Companion Prostate
MR is a post-processing
image analysis software that
assists clinicians in viewing,
manipulating, analyzing and
evaluating MR prostate
images for biopsy support.
AI-Rad Companion Prostate
MR provides the following
functionalities:

Both the predicate and
subject device are indicated
for semi-automated
measurements of ultrasound
image data using AI/ML-
based technology. Both
devices detect the
anatomical structure,
perform segmentation,
perform measurements of
the structure, and perform
measurement of the

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


confirming the validity of the
measurements based on
standard practices and
clinical judgment. Clarius
Prostate AI is intended for
use in adult male patients
only.

responsibility of ascertaining
the measurements based on
standard practices and
clinical judgment.

• Automatic segmentation
and quantitative analysis of
the prostate gland
• Manual annotation of
relevant findings
• Presentation and export of
results for further processing
and reporting

structure’s volume. Both the
predicate and subject
devices are intended for use
as an adjunctive ‘tool’ or aid
by the user for the
interpretation of ultrasound
images and are not intended
to replace clinical decision
making. The minor
differences in the indications
for use do not impact the
safety and effectiveness of
the subject device relative to
the predicate device.

Radiological application/
Supported modality

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

Ultrasound image processing
software application
implementing artificial
intelligence including non-
adaptive machine learning
algorithms trained with
clinical and/or artificial
data intended for non-
invasive segmentation and
measurements of ultrasound
data.

Radiological (MR) image
processing software
implementing artificial
intelligence including non-
adaptive machine learning
algorithms trained with
clinical and/or artificial data
intended for automated
segmentation of the
prostate gland with the
possibility of manual
adjustment and annotation.

Quantitative and/or
Qualitative Analysis

Equivalent to the predicate
device. The subject device
performs semi-automated
measurements of the
prostate gland and prostate


RATIONALE
(if subject device differs
from predicate device)

Clarius Prostate AI
Clarius Bladder AI
AI-Rad Companion Prostate

volume, whereas the
predicate device performs
semi-automated
measurements of the
bladder and bladder volume.

Yes – Segmentation of
anatomical structures
(prostate)

Yes – Segmentation of
anatomical structures
(bladder)

Equivalent to the predicate
device. The only difference is
the anatomical structure
(prostate gland vs. bladder).

Yes – Measurement of
anatomical structures
(prostate)

Yes – Measurement of
anatomical structures
(bladder)

Artificial Intelligence
(AI)/Machine Learning (ML)
Image segmentation for
border detection, and
prostate view classification
using a Deep Neural
Network.

Artificial Intelligence
(AI)/Machine Learning (ML)
Image segmentation for
border detection, and
bladder view classification
using a Deep Neural
Network.

Artificial Intelligence
(AI)/Machine Learning (ML)
Image segmentation of the
prostate gland with the
possibility of manual
adjustment and annotation.

Manual adjustment/Manual
editing capability
(Yes or No)

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

Equivalent to predicate
device; same as reference
device.


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

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

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

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

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


Modification
Rationale
Testing Methods
Impact Assessment

Modification of data
input sources (Clarius
probes)

To add data from
current Clarius scanners
and future 510(K)
cleared scanners to the
Clarius Prostate AI
model so the model can
be deployed on more
scanners.

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

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

Summary of planned modifications to Clarius Prostate AI per the PCCP:


within the intended
patient population
will ensure that data
skewing and
concept drift are
mitigated.

Improvement and
optimization of Clarius
Prostate AI’s
performance

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

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

Modification of model
parameter (initial
learning rate)

Improved
performance
metrics of modified
Prostate AI model.
Benefit-Risk
Analysis:


Prostate AI model
(using performance
metrics) and clinical
performance testing
(verification and
validation).

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


Automated radiological image processing software


PRIMARY PREDICATE
CT Cardiomegaly
Innolitics
K232613

Regulatory number
21 CFR 892.2050
21 CFR 892.2050
Same

PRAEVAorta®2 is a software
intended to be run on its own or
as part of another medical
device to automatically
calculate maximum diameters
of anatomical zones from a
DICOM CT image containing
blood vessels
PRAEVAorta2 is designed to
measure the maximal
transverse diameter of vessel
and determine the maximal
general diameter using a non-
adaptative machine learning
algorithm
Intended users of the software
are aimed to the clinical
specialist, physicians or other
licensed practitioners in
healthcare institutions, such as
clinics, hospitals, healthcare
facilities, residential care
facilities and long-term care
services. Any results obtained
from the software by an
intended user other than a
physician must be validated by
the physician responsible of the
patient. The system is suitable
for adults. Its results are not
intended to be used on a
standalone basis for clinical
decision making or otherwise
preclude clinical assessment of
any disease

CT Cardiomegaly is software
intended to be run on its own
or as part of another medical
device to automatically
calculate linear and area
based cardiothoracic ration
(CTR) from a CT image
containing the heart. CT
Cardiomegaly is designed to
measure the maximal
transverse diameter of heart
and maximal inner transverse
diameter of thoracic cavity
and calculate the CTR from an
axial CT slice containing the
heart using a non-adaptative
machine learning algorithm.
Intended users of the
software are aimed to the
physicians or other licensed
practitioners in the
healthcare institutions, such
as clinics, hospitals,
healthcare facilities,
residential care facilities and
long-term care services. The
system is suitable for adults
and transitional adolescents
(18 to 21 years old but
treated as an adult). Its
results are not intended to be
used on a stand-alone basis
for clinical decision making or
otherwise preclude clinical
assessment of any disease.

Equivalent
Indication for use of the
two devices are analyzing
CT scan images.
Both the subject device
and the primary predicate
are using non adaptative
machine learning
algorithms. An observed
difference between the
subject device and the
predicate is the anatomical
zone analyzed in CT scan.
The primary predicate is
assessing the heart while
the subject device is
assessing arteries .
However, these
differences in
technological
characteristics do not
affect safety and
effectiveness of the device
and have been supported
with verification and
validation testing.

Input
CT scan images
CT scan images
Same

6. COMPARAISON OF TECHNOLOGICAL CHARACTERISTICS


- PDF, JSON and DICOM SC
report
- DICOM GSPS

Equivalent
The subject device
proposed the same storage
format as the primary
predicate.
However, it is also
proposing two additional
formats, “DICOM SC
report” and “DICOM GSPS”
This difference in
technological
characteristics does not
affect safety and
effectiveness of the device
and has been supported
with verification and
validation testing.

- Maximal transverse
diameter of vessels (aorta
and iliac arteries)
- Linear measurements
(diameters)
- Various visualization
techniques: 2D/3D

- Linear and area based
cardiothoracic ratio
- Maximal transverse
diameter of the heart
- Maximal inner
transverse diameter of
thoracic cavity

Equivalent to the
predicate.
The subject device is
realizing the similar
measurements as the
primary device.
The main difference
between the primary
predicate and the subject
device is the body part
assessed.
However, these
differences in
technological
characteristics do not
affect safety and
effectiveness of the device
and have been supported
with verification and
validation testing.

Report will be output in the PDF
and JSON file, and DICOM SC
report which is structured with
following information:
- Maximum orthogonal
diameter of
anatomical zones
- Patient information
- Reference value(s)

Report will be output in the
PDF and JSON
file format which is
structured with following
information:
- CTR (both linear
and area-based)
- Patient information
- Reference value(s)

Equivalent
Both devices generate a
reports with a final output
(Maximal Orthogonal
diameter or CTR), which is
used to support medical
diagnosis for a specific
clinical condition and
includes patient
information.

Traditional 510(k) premarket Notification


- Physicians or other
licensed practitioners in
healthcare institutions
- Clinical specialists with
results validated by a
physician

Physician or other licensed
practitioners in the
healthcare institutions

Equivalent
The subject device is also
intended to be used by
clinical specialist, the
results being validated by
the doctor in charge.

Adults and transitional
adolescents (18 to 21 years
old but treated as an adult)

Equivalent.
The subject device is more
restrictive as
the primary predicate.
These differences in
technological
characteristics do not
affect safety and
effectiveness of the device
have been
supported with verification
and validation
testing.

The primary predicate is
more restrictive
as the new device.
However these
differences are supported
with a
performance bench test.

- Healthcare institutions
(clinics, hospitals,
healthcare facilities,
residential care facilities
and long-term care
services)
- Healthcare company
realizing sizing assessment
of vessels)

The subject device is
usable by healthcare
company realizing sizing
assessment
vessels while the primary
predicate is not.
However, these
differences in
technological
characteristics do not
affect
the safety and
effectiveness of the device
and have been supported
with verification
and validation testing

Software device that
operatures on off-the-
shelf hardware


PRIMARY PREDICATE
CT Cardiomegaly
Innolitics
K232613

Software device uses
software algorithms for
image

Diameter measurement
Yes, automated
Yes, automated
Same

Saved in PDF, JSON and DICOM
SC format, DICOM GSPS

The subject device
proposed the same
storage format as the
primary predicate
and one format in common
with the
secondary predicate.
However, it is also
proposing an additional
format “DICOM
GSPS”.
This difference in
technological
characteristics does not
affect safety and
effectiveness of the device
and have been
supported with verification
and validation
testing

- Ubuntu 20.04.5 LTS
(provided as a docker
container)
- Docker 23.0.1 or above

Machine learning based
algorithm (non-adaptative)

- Machine learning based
algorithm (non-
adaptative)

Input of patient data
Command line interface (API)
Command line interface (API)
Same

- Linear (diameters)
measurements
- Automatic segmentation
and quantitative analysis
- Segmentation and analysis
or aortic and iliac arteries

- Linear (diameter, ratio)
- Area based ratio
- Automatic segmentation
and measurements

Equivalent.
The subject device is more
restrictive than
the predicate.
This difference in
technological
characteristics do not
affect safety and
effectiveness of the device
and have been
supported with verification
and validation
testing


Yes. Based on the
same machine
learning algorithm,
multiple rocessing
steps were added
and the calculated
features revised

Yes. Based on a machine
learning algorithm.

Windows/Linux(With
Android option for LVivo EF


provided in the ground truth from all three experts were included. The comparison for


Submitter Name
Roche Molecular Systems, Inc.

2881 Scott Blvd
Santa Clara, CA 95050 USA

Aarti Shukla
Regulatory Affairs Manager, RIS
Phone: (408) 705-7215
Fax: (925) 225-0207
aarti.shukla@roche.com

Automated Total Metabolic Tumor Volume (aTMTV)

QIH, Automated Radiological Image Processing Software


Opulus™ Lymphoma Precision
(subject device)

Artificial Intelligence Machine Learning
(AI/ML) Algorithm

Patients already pathologically diagnosed
with FDG-avid lymphomas

Patients already pathologically diagnosed to
have brain tumors

Standard DICOM format - PET with the
associated attenuation correction CT

Standard DICOM format - four different
MRI sequences

Output
Report and image overlay
Report and image overlay

Segments disease related tracer uptake in
FDG-avid lymphomas

Segments disease related contrast
uptake and FLAIR image intensity
changes in high-grade gliomas (HGG)

Overlay of segmentation mask on input
PET/CT images

Overlay of segmentation mask on input MRI
images

Volumetric measurements derived from
segmented lymphoma disease burden

Volumetric measurements derived
from segmented HGG disease burden

Reference standard (ground truth) was
established using three US board certified
radiologists/nuclear medicine physicians
with expertise in identifying and
segmenting FDG-avid lymphoma related
uptake

Reference standard (ground truth) was
established using three board certified
neuroradiologists with expertise in
identifying and segmenting high grade
gliomas

3. COMPARISON OF TECHNOLOGICAL CHARACTERISTICS WITH PREDICATE DEVICE


validation dataset was not available to the algorithm developers during the algorithm training.


Substantial Equivalence (SE)
and Comments

Subject Device (SD):
Predicate Device (PD):

Product codes: OWB, QIH
Classification name: Image-intensified
fluoroscopic x-ray system
Classification regulation: 21 CFR
892.1650
FDA Clearance: K243884

Product code: OWB, LLZ
Classification name: Image-intensified
fluoroscopic x-ray system
Classification regulation: 21 CFR
892.1650
FDA Clearance: K140138

Similar to PD:
Predicate device is legally
marketed.

COMPARISON OF TECHNOLOGICAL FEATURES TO PREDICATE DEVICE (SE TABLE):


Intended Use
(IU) including
Indications for
Use (IFU)

TAVIPILOT is an intra-operative software
which provides real-time fluoroscopy
detection, tracking and marking of the
Non-Coronary Cusp and the prosthetic
valve, to allow optimal guidance for
precise positioning of the prosthetic
valve, according to the planning phase,
for TAVI/TAVR (transcatheter aortic valve
implantation/replacement) procedures.
The guidance provided by TAVIPILOT is
not intended to substitute the cardiac
surgeon’s or the interventional
cardiologist’s judgment and analysis of
the patient’s condition.
The device is only intended for adults
(i.e., 21 years and older).
Contra-indications:
- Patients who have already undergone a
TAVI/TAVR or SAVR (surgical aortic valve
replacement)
- Patients diagnosed with aortic
insufficiency
- Patients for whom the main access for
the TAVI/TAVR catheter is not femoral
- Patients who have a non-tricuspid
native valve
- Patients who have a permanent
Pacemaker implant or temporary
Pacemaker within 2 cm from the aortic
root, other than the pacing guidewire
- Patients who have thoracic surgical
implants
-Patients who are not adults

HeartNavigator is a tool to assist the
user with the treatment of structural
heart disease using minimal invasive
interventional techniques. In addition
to the conventional live fluoroscopy it
provides the user with tools to plan
and guide the procedure using 3D
image data.

Similar to PD:
SD does not assist the user with
procedure planning.
SD provides support for a
specific structural heart
disease treatment procedure,
namely TAVI/TAVR.

The TAVIPILOT software tool is intended
to be used in combination with FDA
cleared X-ray systems to assist cardiac
surgeons and interventional
cardiologists with the treatment of
structural heart diseases using minimal
invasive interventional techniques for
which TAVI/TAVR is indicated.

The HeartNavigator software tool is
intended to be used in combination
with the primary predicate device
Allura X-ray system (K130638) to assist
cardiac surgeons and interventional
cardiologists with the treatment of
structural heart diseases using
minimal invasive interventional
techniques.

Similar to PD:
Both devices are intended to
assist cardiac surgeons and
interventional cardiologists
with the treatment of structural
heart diseases using FDA
cleared X-Ray C-arm systems
and minimal invasive
interventional techniques.
SD provides support for a
specific structural heart
disease treatment procedure,
namely TAVI/TAVR.

In addition to conventional live
fluoroscopy TAVIPILOT provides the user
with tools to guide the procedure using a
2D projection of the aortic root-related
landmarks and transcatheter aortic
valve overlayed on the 2D X-ray image
data from the FDA cleared X-ray systems

In addition to conventional live
fluoroscopy HeartNavigator provides
the user with tools to plan (by use of
previously acquired DICOM cardiac CT
patient data) and guide the procedure
using a 2D projection of the aortic root-
related landmarks obtained during
planning, on X-ray image data from the
Allura X-ray system.

Similar to PD:
Both PD and SD use 2D
overlay on the fluoroscopic
image for guidance.
SD does not assist the user
with procedure planning in
the planning phase


During Live phase the SD offers
anatomical detection and tracking of the
aortic root-related landmarks and
transcatheter aortic valve which is
overlayed in 2D on the 2D fluoroscopy x-
ray image data using trained AI/ML
model.

During live phase the PD converts the
3D CT-data to a 2D projection of the
aortic root-related landmarks, which is
overlayed on the 2D fluoroscopy x-ray
image.

Different in technology:
Both PD and SD offer
anatomical detection, tracking
and marking of the aortic
root. Both PD and SD use 2D
overlay on the fluoroscopic
image for guidance. SD uses a
trained AI/ML model

TAVIPILOT does not change or influence
the TAVI procedure

HeartNavigator 2.0 does not change or
influence the TAVI procedure

Patient Population:
TAVIPILOT is suitable for patients with
structural heart diseases who are
considered appropriate for treatment
with a TAVI/TAVR procedure.

Patient Population:
HeartNavigator 2.0 is suitable for
patients with structural heart diseases
that have a medical condition for
which the treatment with minimal
invasive interventional techniques
using fluoroscopy is considered
suitable.

Same as PD
SD is specifically suitable for
patients with structural heart
diseases for which TAVI/TAVR is
indicated.

Intended users:
The user is a clinical specialist who is
fully skilled and qualified to perform the
TAVI/TAVR procedure and is responsible
for sound clinical judgement and for
applying the best clinical procedure

Intended users:
The user is a clinical specialist who is
fully skilled and qualified to perform
the structural heart disease procedure
and is responsible for sound clinical
judgement and for applying the best
clinical procedure.

Same as PD
SD’s intended users are skilled
and qualified to perform a
specific structural heart
disease procedure, namely
TAVI/TAVR.

General safety and effectiveness:
To facilitate safe and efficacious
operation of the system by a trained
healthcare professional, instructions for
use are provided as part of the labelling,
as well as training at system handover.

Clinical environment:
TAVIPILOT is intended to be used in the
control room and in the examination
room of an interventional suite and/or
hybrid operating room.

Clinical environment:
HeartNavigator is intended to be used
in the control room and in the
examination room of an interventional
suite and/or hybrid operating room.

Computer (PC) environment
• Windows operating system
• Video capture for receiving C-arm X-
ray fluoroscopic images
• Output to LDM (Large Display
Monitor)

The main operating principle of
TAVIPLIOT consists of the following SW
workflow:
1. Preparing for Live task
2. Live Task

The main operating principle of
HeartNavigator consists of the
following SW workflow:
1. Planning segmentation task
2. Planning measurement task
3. Planning viewing task
4. Planning registration task
5. Preparing for Live task
6. Live Task

Similar to PD:
The intended use of the SD is
not to assists the user with TAVI
procedure planning, therefore
steps 1-4 of the PD steps are
not relevant for the SD.


Substantial Equivalence (SE)
and Comments

Subject Device (SD):
Predicate Device (PD):

TAVIPILOT SW
Workflow –
Preparing for Live
Task

Valve type, valve size and positioning are
selected by the user in the preparing for
live tasks

Valve type, size and positioning are
selected by the user in the preparing
for live tasks.

Same as PD
Both SD and PD requires valve
type, size and positioning input
by the user.

Live task – reception of fluoroscopic
data
Reception of live fluoroscopic stream
from an FDA-cleared X-Ray system

Live task – reception of fluoroscopic
data
Reception of live fluoroscopic stream
from the Allura X-ray system (K130638)

Similar to PD
Both devices receives live
fluoroscopic images from a
cleared X-ray system

Live task – displaying raw fluoroscopic
data
During Live Task the TAVIPILOT is
displayed in addition to the original raw
fluoroscopic data (image), on the large
monitor as a separate fluoroscopic
image with the overlayed guidance
information

Live task – displaying raw
fluoroscopic data
During Live Task the HeartNavigator
2.0 is displayed in addition to the
original raw fluoroscopic data (image),
on the large monitor as a separate
fluoroscopic image with the overlayed
guidance information

Same as PD:
Both SD and PD keep an
original raw fluoroscopic image
flow and provide their guidance
on a separate flow

Live tasks - Aortic root-related
landmarks:
Upon detection, the aortic root-related
landmarks are displayed to the user by
overlaying a 2D landmark on the 2D live
x-ray images.

Live tasks - Aortic root-related
landmarks:
Upon detection, the aortic root-related
landmarks are displayed to the user by
overlaying a 2D landmark (NCC, LCC
and RCC) on the live 2D x-ray images.

Similar to PD:
Both systems display 2D
landmarks on the live 2D
fluoroscopic stream for
marking of the NCC.
SD only displays NCC as a dot,
PD displays NCC, LCC and RCC
as a circle

Live tasks – Transcatheter Aortic Valve
(TAV):
Upon detection, the TAV is displayed to
the user by overlaying a 2D on the live 2D
x-ray images.

Live tasks – Transcatheter Aortic
Valve (TAV):
The TAV is displayed to the user by
overlaying a 2D landmark (2D valve
overlay) on the live 2D x-ray images.

Similar to PD:
Both systems displays 2D
landmarks on the live 2D
fluoroscopic stream for
marking of the TAV.
SD displays TAV as line overlay,
PD displays TAV as multiple line
overlay


Subject Device
Second Opinion® Pediatric

Primary Predicate
Second Opinion
K210365

Dental CADe to aid in dental
radiograph review by HCP

Table 1: Comparison of Second Opinion® Pediatric with the predicate devices.


Second Opinion® Pediatric is a
computer aided detection
("CADe”) software to aid in the
detection of caries in bitewing
and periapical radiographs.
The intended patient population
of the device is patients aged 4
years and older that have
primary or permanent teeth
(primary or mixed dentition) and
are indicated for dental
radiographs.

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

Automated, CADe software that
utilizes machine learning

Detection & display of caries
lesions in intraoral radiographs

Detection and display of anatomy
and pathologies in intraoral
radiographs


149 New Montgomery St, 4th Floor
San Francisco CA 94105

Email: kkoster@ceevra.com
Phone: 415-305-5326


Automated Radiological Image Processing Software


ensured diversity in patient population and scanner manufacturers. Subgroup analysis was performed for

patient age, patient sex, and scanner manufacturers.

were enforced at the level of the scanning institution, namely, studies sourced from a specific institution


Dental automated image processing
software device to aid in reviewing CBCT
radiograph by HCP

Dental automated image processing software device to aid
in reviewing CBCT, IOS and FS medical images by HCP

Second Opinion® 3D is a radiological
automated image processing software
device intended to identify and mark
clinically relevant anatomy in dental
CBCT radiographs; specifically Dentition,
Maxilla, Mandible, Inferior Alveolar Canal
and Mental Foramen (IAN), Maxillary
Sinus, Nasal space, and airway. It should
not be used in lieu of full patient
evaluation or solely relied upon to make
or confirm a diagnosis.
It is designed to aid health professionals
to review CBCT radiographs of patients
12 years of age or older as a concurrent
and second reader.

Relu Creator is a software program for the management,
transfer, and analysis of dental and craniomaxillofacial
image information, and can be used to provide design input
for dental solutions. It displays and enhances digital images
from various sources to support the
diagnostic process and treatment planning. It stores and
provides these images within the system or across computer
systems at different locations.

Utilizes computer vision neural network
algorithms, developed from open-source
models using supervised machine
learning techniques

Table 1: Comparison of Second Opinion® 3D with the predicate devices.


AnatomyID
Anatomy Name
Mean (95% CI)
Median [Min., Max.]
Std.dev.
one-sample t-test (p_value)


Subject Device
Predicate Device
Reference Device

Canon XIDF-AWS801,
Angio Workstation
(Alphenix Workstation),
V9.5 K232526 Canon
Medical Systems

Product Code
Primary QIH. Secondary OWB
LLZ
OWB, JAA

AngioWaveNet is indicated for use
by qualified physicians or under
their supervision to aid in the
analysis and interpretation of X-ray
coronary angiographic cines.
AngioWaveNet is intended for use
in adults during X-ray coronary
angiographic imaging procedures as
a clinically useful complement to
the viewing of standard
angiographic cines acquired during
diagnostic coronary angiography
procedures. AngioWaveNet
software is intended for use to
enhance the visibility of blood
vessels, vascular structures, and
related anatomical features within
angiographic images, which may be
clinically useful to the treating
physician

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

The Angio Workstation (XIDF-
AWS801) is used in
combination with an
interventional
angiography system
(Alphenix series systems,
Infinix-i series systems and
INFX series systems) to provide
2D and 3D imaging of selective
catheter angiography
procedures for the whole body
(includes heart, chest,
abdomen, brain and extremity).
When XIDF-AWS801 is
combined with Dose Tracking
System (DTS), DTS is used with
selective catheter angiography
procedures for the heart, chest,
abdomen, pelvis and brain.

Interventional cardiologists and
related specialists


All X-ray
angiography
systems exporting
to XA DICOM
modality

Canon
Alphenix series systems
Infinix-i series systems
INFX series systems

DICOM
● 512x512 8 or 16 bits
● 1024x1024 8 or 16 bits

On-site client:
Intel Quad Core i7-
4770 3.4GHz minimum
● 32GB Ram
● Windows 10 or 11
Professional

Windows Operating System,
PC Hardware,
CUDA supported
graphics card or
equivalent


Subject Device
Equivalent Device
Equivalent Device

Device name
Clever One v1.0
EzDent-i v3.4
Ez3D-i v5.5

Clever One is dental
imaging software that
is intended to provide
tools for supporting
diagnosis and
treatment.
These tools enable
end users to view and
interpret a series of
DICOM compliant
medical images and
are intended for use
by trained medical
professionals. Clever
One allows users to
load, view, and save
DICOM images from
CT, panoramic,
cephalometric,
intraoral, and other
imaging equipment. It
also provides
functionalities such as
2D viewing, 2D
analysis, 3D
visualization, 3D
analysis.

EzDent-i is dental
imaging software that
is intended to provide
diagnostic tools for
maxillofacial
radiographic imaging.
These tools are
available to view and
interpret a series of
DICOM compliant
dental radiology
images and are meant
to be used by trained
medical professionals
such as radiologist
and dentist.
EzDent-i is intended
for use as software to
acquire, view and save
2D image files, load
DICOM project files
from panorama,
cephalometric, and
intra-oral imaging
equipment.

Ez3D-i is dental
imaging software that
is intended to provide
diagnostic tools for
maxillofacial
radiographic imaging.
These tools are
available to view and
interpret a series of
DICOM compliant
dental radiology
images and are meant
to be used by trained
medical professionals
such as radiologist
and dentist. Ez3D-i is
intended for use as
software to load, view
and save DICOM
images from CT,
panorama,
cephalometric and
intraoral imaging
equipment and to
provide 3D
visualization, 2D
analysis, in various
MPR (Multi-Planar
Reconstruction)
functions.

Clever One is a dental
imaging software
designed to acquire,
process, view, edit,
and analyze medical
images for supporting
diagnostic and
preoperative planning

EzDent-i is a device
that provides various
features to acquire,
transfer, edit, display,
store, and perform
digital processing of
medical images.
EzDent-i is a patient &

Ez3D-i v5.5 is 3D
viewing software for
dental CT images in
DICOM format with a
host of useful
functions including
MPR, 2-dimensional
analysis and 3-


The software
interfaces with dental
imaging equipment,
such as CT,
panoramic,
cephalometric, and
intraoral X-ray
systems, as well as
intraoral cameras, for
image acquisition. It is
designed for use in
network
environments,
allowing users to
upload and download
clinical diagnostic
images and patient
data for enhanced
collaboration and
efficient patient
management.

User Interface
Mouse, Keyboard
Mouse, Keyboard
Mouse, Keyboard

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

32 bit / 64 bit
64 bit
32 / 64 bit
64 bit

Length, Multi Length,
Angle, Multi Angle,
Circle, ROI/Area,
Volume, Profile