Fast scintillator array coupled to photodiode array.
33 (WFOV) or 23 (EFOV) configurable high resolution (HR)
modules comprising 192 detector rows X pitch 0.5mm (Z
direction, measured at scanner center).
10 (WFOV) or 20 (EFOV) configurable low resolution (LR).
EFOV includes 10 modules on each wing while WFOV
includes 10 modules on one wing. comprising 48 detector
rows X pitch 2.0mm
Analog to digital conversion per channel on the detection
module.
1D antiscatter collimator.

Fast scintillator array coupled to photodiode array.
33 (WFOV) or 23 (EFOV) configurable high resolution (HR)
modules comprising 192 detector rows X pitch 0.5mm (Z
direction, measured at scanner center).
10 (WFOV)-20 (EFOV) configurable low resolution (LR).
EFOV includes 10 modules on each wing while WFOV
includes 10 modules on one wing. comprising 48 detector
rows X pitch 2.0mm
Analog to digital conversion per channel on the detection
module.
1D antiscatter collimator.

Contactless transmission (capacitive coupling). Rate up to
6.25 GBit/sec

Power and control
Brush contact slipring
Brush contact slipring
Same

Rotation drive
Direct drive DC motor
Direct drive DC motor
Same

2 x MCS 2093 X ray tubes by Varex Imaging Corp.
Single ended grounded rotating anode
Anode angle 13 degrees
1.0 MHU anode heat capacity
Grid controlled focal spot modulation in X direction
Small and large focal spots
Max kVp: 140 kV
Max power: 72 KW

Motorized vertical and horizontal motion.
Optional lateral motion
Cantilever carbon fiber patient cradle.

Motorized vertical and horizontal motion.
Optional lateral motion.
Cantilever carbon fiber patient cradle.


Proposed devices –
Primary Predicate devices –
Discussion

Low Dose CT Lung Cancer Screening (LD LCS) Option

The Cleared Arineta’s SpotLight / SpotLight Duo

(K230370) CT X-ray System (with DLIR option)

Image reconstruction
Multicore PC and GPU
Multicore PC and GPU
Same

Modified FDK cone beam algorithm adapted for dual tubes
geometry.
Adaptive filter to reduce directional noise in low level raw
data (MBAF).
Non-local means algorithm MBAF2 (optional).
For WFOV configuration, adapted to reconstruct high
resolution images according to detector configuration, lower
resolution images outside FOV covered by high resolution
detectors.
For extended FOV configuration, adapted to reconstruct high
resolution images up to FOV250mm, lower resolution
images outside FOV250mm.
ASIR-CV or DLIR AI based image reconstruction algorithm.

Substantially the same
reconstruction technology,
except the ASIR-CV and AI-
based DLIR image
reconstruction algorithms.
The proposed LD LCS
option is not compatible with
DLIR and ASIR-CV.
The LD LCS option is
available with or without
MBAF2.

Metal parts (mostly steel and aluminum)
Lead and tungsten for X-ray shielding
PCB, electronic components and electronic cables
components
Table top made of carbon fiber reinforced resin
Covers made pf molded polymers and reinforced resins
Oil in X-ray tubes cooling systems
Detector scintillators made of CdWO4 and Gadolinium
Oxysulfide (GOS) used in other legally marketed CT
scanners

Metal parts (mostly steel and aluminum)
Lead and tungsten for X-ray shielding
PCB, electronic components and electronic cable
components
Table top made of carbon fiber reinforced resin
Covers made pf molded polymers and reinforced resins
Oil in X-ray tubes cooling systems
Detector scintillators made of CdWO4 and Gadolinium
Oxysulfide (GOS) used in other legally marketed CT
scanners

Wall supply 380 to 480 V 3 phase
Max power demand 115 kVA
Max X ray power (total for two tubes) 72kW


Laser alignment lights: gantry bore external lasers. <0.1mW
per laser beam
Three lead ECG trigger module, powered by medical grade
power supply through the system PDU

Provided with software in three domains:
• Console software
• Image reconstruction software
• Embedded software

Substantially the same, with
minor changes in the added
LD LCS protocols (for
medium and large patients)
per AAPM guidelines.

Max Rotation speed
250 RPM (0.24 sec per rotation)
250 RPM (0.24 sec per rotation)
Same

0.16 sec (partial), 0.24 sec (full scan) – FOV up to 250mm
0.24 sec (full scan) – HR imaging at FOV above 250mm for
asymmetric detector

Max axial coverage in
140mm (280 slices x 0.5mm pitch)
140mm (280 slices x 0.5mm pitch)
Same

25cm - 250mm at high resolution
WFOV - High resolution images at configurable FOV
between 250mm and 450mm
EFOV – Lower resolution in the FOV between HR coverage
and 450mm

17.5 lp/cm cutoff at center
10.0 lp/cm cutoff at radius above 125mm (outside FOV
250mm) covered by HR detectors
7.0 lp/cm cutoff at radius above 125mm (outside FOV
250mm) covered by LR detectors

Max Patient weight
227 Kg (500 lbs)
227 Kg (500 lbs)
Same


Proposed devices –
Primary Predicate devices –
Discussion

Low Dose CT Lung Cancer Screening (LD LCS) Option

The Cleared Arineta’s SpotLight / SpotLight Duo

(K230370) CT X-ray System (with DLIR option)

Operator console table
NG2000 Table slickers
Bar code reader
Uninterruptible Power Supply
Head& hands and knees support

CT number accuracy - In a low signal situation such as with LD LCS, the CT number measured in a nodule may be compromised. In LCS, the CT number may be a reference against
potentially calcified nodules.
CT number uniformity - In a low signal situation such as LD LCS, maintaining sufficient CT number uniformity throughout the lung and various structures is important for more robust
detectability of nodules. Uniformity is needed to maintain CT number separation between structures.
Image noise (standard deviation) - As dose is reduced, background noise in the image increases. If this noise becomes too large, nodule detectability and sizing measurement may
be compromised.
Modulation Transfer Function (MTF) - MTF is a measure of the high contrast spatial resolution performance of the system. Nodules in the lung are high contrast objects and therefore,
MTF should be preserved at lower dose conditions.
Visual Resolution/Image Artifacts - This relates to the evaluation of images to assess their visual resolution using high contrast bar patterns and evaluation of the degree of artifacts
(e.g., low signal streaks, beam hardening). These tests are relevant because of the high contrast detection task of relatively small objects for this application. Streak or beam
hardening may obscure pathology and affect CT number accuracy.
Noise Power Spectrum (NPS) - Similar to standard deviation of noise, changes in noise texture may result in nodule detection becoming more challenging especially if there is a
significant shift in the frequency of the noise, and/or an increase in amplitude of the NPS plot.
Slice Thickness - The ability to produce slice thicknesses (FWHM of the slice sensitivity profile) that are close to the nominal slice thickness is important in defining clear edges and
boundaries of the nodule and in nodule sizing.
Contrast to Noise (CNR) - Sufficient CNR is needed to detect solid and non-solid nodules in the lung. This metric is similar to SNR but accounts for the contrast between an object
and the background. Arineta believes this is the primary figure of metric to evaluate nodule detectability.
The image quality metrics were used for evaluation to determine substantial equivalence. Each metric is provided with a description of the impact/relevance of the metric for LCS. All
IQ metrics used for both the proposed and the predicate device are the same.


Predicate Device
Subject Device
Remark/Discussion

CoLumbo is an image post-
processing and measurement
software tool that provides
quantitative spine
measurements from
previously-acquired DICOM
lumbar spine Magnetic
Resonance (MR) images for
users’ review, analysis, and
interpretation. It provides the
following functionality to
assist users in visualizing,
measuring and documenting
out-of-range measurements:
• Feature segmentation;
• Feature measurement;
• Threshold-based labeling
of out-of-range
measurement; and
• Export of measurement
results to a written report
for user’s review, revise
and approval.
CoLumbo does not produce or
recommend any type of
medical diagnosis or
treatment. Instead, it simply
helps users to more easily
identify and classify features
in lumbar MR images and
compile a report. The user is
responsible for
confirming/modifying settings,
reviewing and verifying the
software-generated
measurements, inspecting out-

CoLumbo is an image post-
processing and measurement
software tool that provides
quantitative spine
measurements from
previously-acquired DICOM
lumbar spine Magnetic
Resonance (MR) images for
users’ review, analysis, and
interpretation. It provides the
following functionality to
assist users in visualizing,
measuring and documenting
out-of-range measurements:
• Feature segmentation;
• Feature measurement;
• Threshold-based labeling
of out-of-range
measurement; and
• Export of measurement
results to a written report
for user’s review, revise
and approval.
CoLumbo does not produce
or recommend any type of
medical diagnosis or
treatment. Instead, it simply
helps users to more easily
identify and classify features
in lumbar MR images and
compile a report. The user is
responsible for
confirming/modifying
settings, reviewing and
verifying the software-
generated measurements,
inspecting out-of-range
measurements, and approving
draft report content using

Highly similar
Indications for use
are the same with the
list of
contraindications
changed.

Table 1 – Comparison of Technological Characteristics with Predicate Device


of-range measurements, and
approving draft report content
using their medical judgment
and discretion.
The device is intended to be
used only by hospitals and
other medical institutions.
Only DICOM images of MRI
acquired from lumbar spine
exams of patients aged 18 and
above are considered to be
valid input. CoLumbo does not
support DICOM images of
patients that are pregnant,
undergo MRI scan with
contrast media, or have post-
operational complications,
scoliosis, tumors, infections,
fractures.

their medical judgment and
discretion.
The device is intended to be
used only by hospitals and
other medical institutions.
Only DICOM images of MRI
acquired from lumbar spine
exams of patients aged 18
and above are considered to
be valid input. CoLumbo
does not support DICOM
images of patients that are
pregnant, undergo MRI scan
with contrast media, or have
post-operational
complications, tumors,
infections.

Radiologist and neuro- and
spine-surgeons

The intended patient
population is not subject to
any restrictions.
Automation support requires
images of patients of 18 years
and older, not pregnant,
without post-operational
complications, scoliosis,
tumors, infections, fractures.

The intended patient
population is not subject to
any restrictions.
Automation support requires
images of patients of 18 years
and older, not pregnant,
without post-operational
complications, tumors,
infections.

Yes
Segmentation and
quantitative analysis

Yes
Quantitative comparison of
structure with normative data
or user-set thresholds

CoLumbo 510(k) Premarket Notification Smart Soft Healthcare


Deep Convolutional
Image-to-Image Neural
Network

• Focal disk material outside
VB projection and its
migration – descending
and ascending;
• Disk outside VB
projection;
• Dural sac cross-sectional
area;
• Nerve root deviation;
• Vertebral body height;
• Disk height;
• Lordotic angle;
• Spondylolisthesis
slippage;

• Focal disk material outside
VB projection;
• Descending (caudal) and
ascending (cranial) disk
material outside of the
intervertebral space;
• Disk outside VB
projection;
• Dural sac cross-sectional
area;
• Nerve root deviation;
• Vertebral body height;
• Disk height;
• Lordotic angle;
• Spondylolisthesis
slippage;
• Аngle of lateral spinal
curvature;
• Facet joint diameter;
• Posterior epidural fat size;
• Muscle fat infiltration
percentage;
• Foramen diameter;
• Lateral recess diameter;
• Dural sac anterior-
posterior diameter;
• Spinal canal diameter;
• Disk Material Outside of
Endplate Margins Size;

Highly similar
The Subject Device
supports several
more measurements.


• Ligament Flavum
Thickness;
• Vertebral Body Zone with
Changed Intensity Size.
• Vertebral Body Width
Difference AP Size.


IEC 62304:2006/AMD 1:2015 Medical device software — Software life cycle
processes — Amendment 1

IEC 82304-1:2016 Health software — Part 1: General requirements for product safety

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

IEC 62366-1:2015+AMD1:2020 Medical devices — Part 1: Application of usability
engineering to medical devices

Table 2 - Voluntary Conformance Standards


Feature/Characteristic
Predicate Device
Subject Device
Comparison

The VMS+ is an
adjunct to existing
ultrasound imaging
systems and is
intended to record,
analyze, store and
retrieve digital
ultrasound images for
computerized 3-
dimensional image
processing.
The VMS+ is
indicated for use
where Left Ventricle
(LV), Right Ventricle
(RV), Left Atrium
(LA), and Right
Atrium (RA) volumes
and ejection fractions
are warranted or
desired.

Generates a 3D
surface model of the
4 chambers and

same as the predicate with acceptable results.


End-systolic volumes
(EDV, ESV), Ejection
Fractions (EF), Stroke
Volumes and Cardiac
Outputs.

Executing on a
computer, processes
data acquired by the
sensor system in
conjunction with the
output from the
ultrasound
equipment, to enable
tracking of anatomic
landmark points from
the 2D images and
conversion of those
points into 3D data
points.

Requires placement
of anatomic
landmarks on the 2D
images. On-screen
guide is provided to
user for point
placement first
guesses. User must
manually adjust first
guess point
placements as
required.
Landmarks are then
used to build an
accurate 3D
constructed shape
mesh (defined by
vertices, edges, and
faces).

Requires placement of
anatomic landmarks on
the 2D images. On-
screen guide is
provided to user for
point placement first
guesses. Alternatively,
automated point
placement first guesses
can be generated via a
button press. User
must manually adjust
first guess point
placements as
required.
Landmarks are then
used to build an
accurate 3D
constructed shape
mesh (defined by
vertices, edges, and
faces).

VMS+ 4.0 is equivalent
to VMS+ 3.0. The
automated control point
first guess placement is
added to improve user
workflow efficiency.
Users must still
modify/confirm control
point placement after
an automated first
guess.
Internal user validation
of the final location of
control points using the
on-screen guide versus
automated first
guesses was assessed.
Additionally, verification
tests were performed
against doctors’ point
placement.
Thus, the difference
does not raise different
questions of safety and
effectiveness.


Knowledge-based
reconstruction located
locally on the system,
which accepts the 3D
data points generated
through the use of the
position sensor
system and provides
the computation
engine for generating
a 3D surface
construction of the
four chambers and
accompanying
volume measurement
and ejection fractions
of the four chambers
of the four chambers
of the heart, either at
end-diastolic and/or
end-systolic.

Knowledge-based
reconstruction located
locally on the system,
which accepts the 3D
data points generated
through the use of the
position sensor system
and provides the
computation engine for
generating a 3D
surface construction of
the four chambers and
accompanying volume
measurement and
ejection fractions of the
four chambers of the
four chambers of the
heart, either at end-
diastolic and/or end-
systolic.

Console (system) and
Workstation
(standalone)

Touchscreen for
image capture, a
video-input connector
to receive image data
from an ultrasound
machine, off-the-shelf
real-time video
capture card to
receive image data
from an ultrasound
machine, and 3D
positional tracking
system to receive
position and
orientation
information.


Feature/Characteristic
Predicate Device
Subject Device
Comparison

Magnetic-based; free-
hand scanning;
consisting of
mechanical arm,
transmitter,
ultrasound transducer
sensor, and
associated
electronics.

Magnet-free; free-hand
scanning; consisting of
ultrasound transducer
sensor,
transmitter/sensor on
patient, and associated
electronics.

VMS+ 4.0 is equivalent
to VMS+ 3.0 with the
only difference being
that the magnet has
been removed from
transmitter/sensor as
an improvement. The
way in which the device
operates remains the
same; both systems
are free-hand scanning.
In addition, the
performance of the new
device is the same as
the predicate device.
Thus, the difference
does not raise different
questions of safety and
effectiveness.

Surface device; intact
skin; A-limited (<24h)

Can import 3D echo
and MRI studies for
volumetric analysis.

The software
components are
responsible for
providing the user
with controls for
managing the
hardware operation,
capturing ultrasound
images, marking up
images with key
anatomical features,
invoking the
reconstruction
algorithm, displaying
the resulting
construction and
generating the
corresponding report.

Power requirements:
AC :100V- 240V,
Frequenzy:50-60Hz


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

Brian R. Zielski
Sr. Lead Specialist, Regulatory Affairs - MR
Phone: 262-227-3596
Email: brian.zielski@gehealthcare.com

Andrew Menden
Director, Regulatory Affairs - MR
Phone: 262-308-5719
Email: andrew.menden@gehealthcare.com

Common / Usual Name:
Magnetic Resonance Diagnostic Device

Magnetic Resonance Diagnostic Device per 21 CFR
892.1000

Predicate Device(s):
SIGNA Premier (K193282)

Reference Device(s):
SIGNA Champion (K233728)

SIGNA MAGNUS is a 3.0T high-performance magnetic
resonance imaging system designed to support imaging
of the head, neck, TMJ and limited cervical spine. The
system supports scanning in axial, coronal, sagittal,
oblique, and double oblique planes using a variety of
pulse sequences, imaging techniques, acceleration
methods, and reconstruction algorithms. The system can
be delivered as a new system installation, or as an
upgrade to existing compatible whole-body 3.0T MR
systems from GE HealthCare.

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


Key aspects of the system design:
• An asymmetrically designed, head-only gradient coil
that achieves up to 300 mT/m peak gradient
amplitude and 750 T/m/s peak slew rate.
• A graduated patient bore size, starting at 74 cm at
the entry down to 37 cm at isocenter.
• Uses the same magnet as a conventional whole-
body 3.0T system, with integral active shielding and a
zero boil-off cryostat.
• Can be installed as a new system or upgraded from
an existing compatible whole-body 3.0T MR system.
• A dockable mobile patient table.
• Oscillating Diffusion ENcoding (ODEN) - a spectral
diffusion technique that uses a sinusoidal diffusion
gradient waveform.

SIGNA MAGNUS system is a head-only magnetic
resonance scanner designed to support high resolution,
high signal-to-noise ratio, diffusion-weighted imaging,
and short scan times. SIGNA MAGNUS is indicated for use
as a diagnostic imaging device to produce axial, sagittal,
coronal, and oblique images, spectroscopic images,
parametric maps, and/or spectra, dynamic images of the
structures and/or functions of the head, neck, TMJ, and
limited cervical spine on patients 6 years of age and
older. Depending on the region of interest being imaged,
contrast agents may be used.
The images produced by SIGNA MAGNUS reflect the
spatial distribution or molecular environment of nuclei
exhibiting magnetic resonance. These images and/or
spectra, when interpreted by a trained physician, yield
information that may assist in diagnosis.

SIGNA MAGNUS employs the same functional scientific
technology as its predicate device.

SIGNA MAGNUS and the predicate device’s Indications
for Use are substantially equivalent. While the predicate
is intended for all anatomies, SIGNA MAGNUS is intended
for only the head, neck, TMJ, and cervical spine.


As such, GE HealthCare considers that SIGNA MAGNUS
has the same intended use as the predicate device in
accordance with the FDA’s guidance document “The
510(k) Program: Evaluating Substantial Equivalence in
Premarket Notifications [510(k)]”, dated 28 July 2014.

Comparison of
Technological
Characteristics:

Overall, SIGNA MAGNUS employs the same fundamental
scientific technology as the predicate device.
System Design: Both SIGNA MAGNUS and the predicate
device include the 3.0 T magnet, RF transmit
architecture, RF receive chain and software application
suite. However, the most notable technological
difference between the SIGNA™ MAGNUS and the
predicate device are:
• Gradient System: The SIGNA MAGNUS can deliver
a peak gradient amplitude of 300 mT/m and peak
gradient slew rate of 750 T/m/s compared to the
predicate’s peak gradient amplitude of 80 mT/m
and peak gradient slew rate of 200 T/m/s. PNS
and CS thresholds are also significantly different
between the two systems, allowing more
performance to be used on the SIGNA MAGNUS
system.
• Applications: The SIGNA MAGNUS uses the SIGNA
Works suite of applications with the addition of
Oscillating Diffusion ENcoding (ODEN) - a spectral
diffusion technique that uses a sinusoidal
diffusion gradient waveform. ODEN is not offered
on the predicate device.
• Field-of-View (FOV): The SIGNA MAGNUS FOV
(26cm x 26 cm x 26cm) is intended for head, neck,
TMJ, and limited cervical spine scanning. As such,
a smaller maximum imaging FOV is specified
compared to the predicate device with an FOV of
50cm x 50cm x 50cm.
• Bore Size: Unlike the straight cylindrical patient
bore of the predicate device, the SIGNA MAGNUS


system has a stepped progressively narrowing
patient bore. The widest part at the patient bore
entry accommodates the arms and torso. It has a
74 cm inner diameter. The patient bore diameter
at the shoulders is narrowed to 54 cm. At the
head, the SIGNA MAGNUS patient bore diameter
is 37 cm compared to 70 cm for the predicate
device.
• Receive Channels: The SIGNA MAGNUS has 64
independent RF channels to account for the
imaged anatomies of head, neck, TMJ, and limited
cervical spine, compared to 146 for the predicate
device which is used for whole-body imaging.
• Max RF Power Output: The SIGNA MAGNUS has
7.5 kW peak total maximum RF power output
compared to 30 kW for the predicate device.
Operating Principles: SIGNA MAGNUS functions using
the same operating principles as the predicate device.
Materials: SIGNA MAGNUS and the predicate device
both use the same materials.
Safety and Performance Testing: Both SIGNA MAGNUS
and the predicate device comply with the same safety
and performance testing (see Determination of
Substantial Equivalence, below).
These technological differences do not raise any
questions regarding safety and effectiveness. Both
devices must address questions of whether they provide
an adequate level of image quality appropriate for
diagnostic use. The performance data described in this
submission include results of both bench testing and
clinical testing that show the image quality performance
of SIGNA MAGNUS compared to the predicate device.

Determination of
Substantial Equivalence:

Summary of Non-Clinical Tests:
SIGNA MAGNUS and the predicate device were subject to
similar risk management testing to demonstrate
substantial equivalence of safety and performance.


October 10, 2023. The image quality of SIGNA MAGNUS
is substantially equivalent to that of the predicate device.
Substantial Equivalence Conclusion:
The indications for use of the proposed device are
comparable to the claimed predicate device. SIGNA
MAGNUS employs equivalent technology to the claimed
predicate device.
Additionally, the results from the above non-clinical tests
demonstrate that the device performs as intended.
Therefore, SIGNA MAGNUS is substantially equivalent to
the predicate device to which it has been compared.

In conclusion, GE Healthcare considers SIGNA MAGNUS
to be at least as safe and effective, and its performance is
substantially equivalent to the predicate device.


Suite 2.114, Level 1, 477 Pitt Street
Sydney NSW 2000
Australia


Radiological Computer-Assisted Diagnostic Software (CADx) for
Lesions Suspicious for Cancer


EchoSolv AS performed consistently across all subgroups, refer to the results in the table below.


QIH - Automated Radiological Image Processing Software
LLZ - System, Image Processing, Radiological

Primary Predicate:
Manufacturer: CorticoMetrics, LLC
Trade Name: THINQ
510(k) Number: K192051
Product Code: LLZ

Secondary Predicate:
Manufacturer: AMRA Medical AB
Trade Name: AMRA Profiler
510(k) Number: K211983
Product Code: LNH


883SantaCruz Ave,Suite205
Menlo Park, CA94025UnitedStates

Applicant ContactTelephone:
(650) 397-8709

611GatewayBlvd, Ste120
South SanFrancisco,CA 94080 UnitedStates

Correspondent Contact:
Mr.Jared Seehafer

Correspondent ContactTelephone:
(415) 638-9554

Predicate #:K201616
Predicate TradeName: SyMRI
Predicate Manufacturer:SyntheticMR AB


extensor hallucis longus, and fibularis tertius.


Topic
AMRA Profiler (510k Number:
MuscleView

A service that is provided with a
cloud-based service using an
automated image-analysis pipeline
(with manual quality control for scan
preprocessing and label quality
control)

Software package that operates on a
virtual machine within off-the-shelf
hardware

The service processes DICOM
compliant image data in accordance
with a required MRI protocol.

The software processes DICOM
compliant image data

Collected Series: 3D Dixon water and
fat phase.
Region of Interest: Lower extremity,
Upper body as well
Supported Field Strength:

The same except that we support a
larger variability in scan properties
and coverage

Table 2. Summary of technological characteristic comparison.


Direction of Capture: Axial
Supported In-Plane Resolution:
Supported Slice Spacing:
Note: Rigid conformity to MRI
protocol is needed.

Concierge Service. Data is provided
and analyzed, and results returned

The software is designed for use on
a workstation with a web-based user
interface. Functionalities are largely
the same.

12 individual muscles and 6 muscle
groups across the lower and upper
extremity and liver

Eighty (8 bones, 72 muscles)
individual structures on both the left
and right side for the lower extremity
focused region.

Structure volume, muscle fat
infiltration, and derived metrics
including asymmetry, muscle length,
and cross-sectional area

Labeled muscle segmentations
automatically generated using non-
rigid image registration to atlases
utilizing 2D analysis techniques

AI segmentation model-based
approach using a library of expert
contours for training, MuscleView
uses a machine learning-based
method to train CNNs from expert
contours to perform segmentation on
the target images to generate
contours


Factor
Groups
Training data
Validation data

Ethnicity
(based on regional
demographics)


Specification
Predicate Device 1
Proposed Device

Xeleris V Processing and Review
Clarify DL

OSEM-based Iterative Image
Reconstruction with integrated deep
learning model trained to reduce noise

feature / technological differences between the predicate device and the proposed device:


Specification
Predicate Device 2
Proposed Device

including Smart Console
on StarGuide’s Smart Console

OSEM-based and BSREM-based Iterative
Image Reconstruction with integrated deep
learning model trained to reduce noise

510(k) Premarket Notification Submission for Clarify DL


Diagnoly
60 Avenue Rockefeller
69008 Lyon, France
+33(0)4.78.76.85.75

Ivan Voznyuk
Chief Executive Officer
Diagnoly
Phone: +33(0)6.95.87.04.55
Email: ivan@diagnoly.com

Nima Akhlaghi
Associate Director, Digital Health Regulatory Affairs
MCRA, LLC
Phone: 202.742.3889
Email: nakhlaghi@mcra.com


Accessory to Ultrasonic Pulsed Doppler Imaging System, 21 CFR 892.1550
Accessory to Ultrasonic Pulsed Echo Imaging System, 21 CFR 892.1560
Medical image management and processing system, 21 CFR 892.2050


Heart views
Quality criteria within the views

4.1 Definition of a complete examination


(B) 4CH
(B9) FOP
Foramen Ovale flap (Vieussens valve)

Four chamber view
(B10) FO
Open Foramen Ovale

Connection between crux and atrial septum (vestibular septum)

(B14) Cr
Atrioventricular valve offset in crux

Connection between interventricular septum and crux

Septum between pulmonary artery trunk and ascending aorta

Right Ventricular Outflow Tract view
(D8) aAo
Ascending aorta

Side space on the left of ductus / pulmonary artery


Predicate device:
Sonio Detect
(Cardiac Features)
K240406

Comparison between
Proposed and
Predicate device

Cardiac-related
features in Sonio
Detect

Cardiac-related
SonolystLive in the
Voluson Expert
18/20/22

Substantially
equivalent
Primary codes are the
same for all devices

- Ultrasonic Pulsed
Doppler Imaging
System, 21 CFR
892.1550
- Ultrasonic Pulsed
Echo Imaging System,
21 CFR 892.1560
- Diagnostic
Ultrasound
Transducer, 21 CFR
892.1570, 90-ITX

- Accessory to
Ultrasonic Pulsed
Doppler Imaging
System, 21 CFR
892.1550
- Accessory to
Ultrasonic Pulsed
Echo Imaging System,
21 CFR 892.1560
- Medical image
management and
processing system,
21 CFR 892.2050

Substantially
equivalent
All devices are class II
devices subject to
510(k) regulatory
pathway.

The predicate device
is a software that
aims at helping
sonographers,
OB/GYNs, MFMs and
Fetal surgeons (all
three designated as
healthcare
professionals i.e.
HCP) to perform their
routine fetal heart
ultrasound

The reference device
is a software that
aims at helping
sonographers,
OB/GYNs, MFMs and
Fetal surgeons (all
three designated as
healthcare
professionals i.e.
HCP) to perform their
routine fetal heart
ultrasound

FETOLY-HEART is a
software that aims at
helping
sonographers,
OB/GYNs, MFMs and
Fetal surgeons (all
three designated as
healthcare
professionals i.e.
HCPs) to perform
their routine fetal
heart ultrasound

Substantially
equivalent
The subject device
and the predicate
devices have the
same objective.


The predicate device
is intended to analyze
fetal ultrasound
images and clips
using machine
learning techniques
to automatically
detect heart views,
detect anatomical
structures within the
views and verify
quality criteria of the
views.
The device is
intended for use as a
concurrent reading
aid during the
acquisition and
interpretation of fetal
ultrasound images.

The device is a
general purpose
ultrasound system
intended for use by
qualified and trained
healthcare
professionals.

FETOLY-HEART is
intended to analyse
fetal ultrasound
images and clips
using machine
learning techniques
to automatically
detect heart views
and quality criteria
within the views. The
device is intended for
use as a concurrent
reading aid during
the acquisition and
interpretation of fetal
ultrasound images.
FETOLY-HEART is
indicated for use
during routine fetal
heart examination of
2nd and 3rd
trimester pregnancy
(gestational age:
from 17 to 40 weeks).

Substantially
equivalent
Indications for Use
are the same
between predicate
and subject devices.

Pregnant women
during the 2nd and
3rd trimester of
pregnancy

Pregnant women
during the 2nd
trimester of
pregnancy

Substantially
equivalent
Subject device has
the same intended
patient population
than the predicate
devices.

- Images labeled with
correct fetal heart
view for patient cases

Substantially
equivalent
Performance testing
has successfully
validated the clinical
outcomes

- Quality criteria
identified as
“Verified” when
detected and “Not
verified” when not
detected

- Quality criteria
identified as “Found”
when detected and
“Not found” when
not detected

Substantially
equivalent
In the subject device,
quality criteria
bounding box
localization can be


Qualified healthcare
professional
specialized in
prenatal ultrasound
imaging

Substantially
equivalent
Subject device has
the same intended
users as the predicate
devices.

Substantially
equivalent
Clinical application is
the same for subject
and predicate
devices.

Different
The PCCP in the
subject device
includes proposed
modifications related
to modifying model
training
hyperparameters,
additional retraining
with new training and
validation datasets
collected, and
addition/removal of
heart quality criteria.

Detection of 4ch, 3vx,
LVOT, RVOT and Abd
views (complete
implementation of
ISUOG
recommendations)

Substantially
equivalent
The subject device
includes the
detection of the same
views than the
predicate device.


Functionality 2: completeness illustration

Automatic suggestion
of views from a
sequence of images.

Automatic extraction
of views from a
sequence of images.

Substantially
equivalent
This image selection
functionality is a
feature absent in the
predicate device but
present in the
reference device.
Software testing has
been performed to
validate its use and
does not introduce
new questions of
safety and
effectiveness.

Accepts images and
image sequences
from ultrasound
machines

Substantially
equivalent
The input data is the
same for the subject
device and the
predicate and
reference devices.

Artificial Intelligence:
Utilizes computer
vision algorithms to
analyze ultrasound
images and provides
visualization of
detected landmarks
and views

Substantially
equivalent
The subject device
and the primary
predicate device use
both artificial
intelligence.


Compatible with
ultrasound system
from GE Medical,
Samsung, Canon and
Philips

Compatible with
ultrasound system
from GE Medical,
Samsung and Canon

Substantially
equivalent
This compatibility has
been tested and
validated as part of
device
generalizability in the
performance testing
study.

The user can interact
with the software to
override the
software’s outputs.
The user has the
ability to review and
edit/override the
matching at any time
during or at the end
of the exam.

Substantially
equivalent
User interactions are
the same between
primary predicate
and subject devices.


Modification
Rationale
Testing Methods
Impact Assessment

Modification of
training and/or
validation datasets

Increase or recovery (in
case of data drift) of
FETOLY-HEART’s
performance.

Re-training of the FETOLY-
HEART model with new
data to optimize its
performance followed by
internal testing and a
comparison of the initial
model to the modified
model using performance
metrics on the test
dataset.

Increased performance metrics of the
modified model for view or quality
criteria detection.
Benefits: Increase or recovery of
performance; generalization for
diverse cases.
Risks: Performance decrease
(overfitting, unintended bias).
Risk mitigation: The modified model
will be tested for superiority on the
performance study test dataset which
will contain new unseen data.

Modification of
model training
hyperparameters

Improvement and
optimization of FETOLY-
HEART’s performance

Re-training of the FETOLY-
HEART model with new
parameters to optimize its
performance followed by
internal testing and a
comparison of the initial
model to the modified
model using performance

Increased performance metrics of the
modified model for view or quality
criteria detection.
Benefits: Increased performance;
generalization for diverse cases.
Risks: Performance decrease
(overfitting, unintended bias).

Summary of changes to FETOLY-HEART per the PCCP:


Fetal heart view
Point
Bootstrap CI
Point
Bootstrap CI


Quality criterion
Point
Bootstrap CI
Point
Bootstrap CI
Point
Bootstrap CI

Connection between
crux and atrial septum

Connection between
interventricular
septum and crux


Document number: 300-TEMP-
17 version 01
Page 13 / 1


Gestational age
3rd trimester
243 (50.6%)
1075 (47.0%)

Scanner manufacturer
Samsung
297 (61.9%)
1405 (61.4%)

Image digital quality
Average
815 (35.6%)

Image type
Full exam video frame
145 (6.3%)

The subgroups distribution is summarized in the table below:


Asian and Pacific Islander
23 (4.8%)
107 (4.7%)

Race and ethnicity
Hispanic
43 (9.0%)
209 (9.1%)


ECHELON Synergy V10.0 (K233687)
ECHELON Synergy MRI System

Super-conducting magnet, horizontal bore,
1.5 Tesla

Bore dimension
Circle shape with diameter 70cm
Circle shape with diameter 70cm

Rise Time
254μsec to 33mT/m
254μsec to 33mT/m

Duty Cycle
85% (Gating max), 10% at full power
85% (Gating max), 10% at full power


☐ Manufacturing Process
☐ Labeling
☐ Technology


Receiver Coils
FlexFit Neuro Coil
FlexFit Neuro Coil

FlexFit Blanket Coil A,
FlexFit Blanket Coil B

Breast Coil
Breast Support Kit 2
Breast Coil 17
Breast Support Holder

Flex M Coil, Flex S Coil
Flex M Coil, Flex S Coil


iCardio.aiEchoMeasureis
softwarethatisusedtoprocess
previouslyacquired
DICOM-compliantcardiac
ultrasoundimages,andtomake
measurementsontheseimages
inordertoprovideautomated
estimationofseveralcardiac
measurements.Thedata
producedbythissoftwareis
intendedtobeusedtosupport
qualifiedcardiologists,
sonographers,orotherlicensed
professionalhealthcare
practitionersforclinical
decision-making.
iCardio.aiEchoMeasureis
indicatedforuseinadult
patients.

LibbyEcho:Prioissoftwarethat
isusedtoprocesspreviously
acquiredDICOM-compliant
cardiacultrasoundimages,andto
makemeasurementsonthese
imagesinordertoprovide
automatedestimationofseveral
cardiacmeasurements.Thedata
producedbythissoftwareis
intendedtobeusedtosupport
qualifiedcardiologists,
sonographers,orotherlicensed
professionalhealthcare
practitionersforclinical
decision-making.
LibbyEcho:Prioisindicatedfor
useinadultpatients.


1. LeftVentricularVolume(A2C,
A4C,andBiplane;Systoleand
Diastole)
2. LeftVentricularDiameter
(SystoleandDiastole)
3. RightVentricularDiameter
4. PosteriorWallThickness
5. AorticAnnulusDiameter
6. LeftVentricularOutflowTract
Diameter
7. SinusofValsalvaDiameter
8. Sinotubular JunctionDiameter
9. LeftAtriumDimension
10. InterventricularSeptal
Thickness

1. EjectionFraction
2. LeftVentricleVolume(A2C,A4C,
Biplane;SystoleandDiastole)


VUNO Med-Chest X-ray Triage/
VUNO Med-CXR Link Triage

Radiological computer aided triage
and notification software

Radiological Computer-Assisted
Prioritization Software For Lesions

Manufacturer
VUNO Inc.
Qure.ai Technologies

VUNO Med-Chest X-ray
Triage/VUNO Med-CXR Link
Triage is a radiological computer-
assisted triage and notification
software that analyzes adult chest X-
ray images for the presence of pre-
specified suspected critical findings
(pleural effusion and/or
pneumothorax).
VUNO Med-Chest X-ray
Triage/VUNO Med-CXR Link
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,
VUNO Med-Chest X-ray
Triage/VUNO Med-CXR Link
Triage does not send a proactive
alert directly to the appropriately
trained medical specialists. VUNO
Med-Chest X-ray Triage/VUNO
Med-CXR Link Triage is not
intended to direct attention to
specific portions of an image or to
anomalies other than pleural
effusion and/or pneumothorax. Its
results are not intended to be used
on a stand-alone basis for clinical

qXR-PTX-PE is a radiological
computer-assisted triage and
notification software that analyzes
adult chest X-ray images for the
presence of pre-specified suspected
critical findings (pleural effusion
and/or pneumothorax).
qXR-PTX-PE 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,
qXR-PTX-PE does not send a
proactive alert directly to the
appropriately trained medical
specialists. qXR-PTXPE is not
intended to direct attention to
specific portions of an image or to
anomalies other than pleural
effusion and/or pneumothorax. Its
results are not intended to be used
on a standalone basis for clinical
decision-making.


Trained radiologists and healthcare
professionals

Radiologists, clinicians, and other
appropriately trained medical
specialists qualified to read chest
radiographs

Pneumothorax, Pleural effusion on
Chest/Lung Frontal Chest X-rays

Algorithm for
pre-specified
critical findings
detection

VUNO Med-Chest X-ray Triage/
VUNO Med-CXR Link Triage uses
an AI algorithm to detect
pneumothorax and pleural effusion
on chest X-ray images.
VUNO Med-Chest X-ray Triage/
VUNO Med-CXR Link Triage uses
a vendor agnostic algorithm
compatible with DICOM chest X-
ray images.

qXR-PTX-PE uses an AI algorithm
to detect pneumothorax and pleural
effusion on chest X-ray images.
qXR-PTX-PE uses a vendor
agnostic algorithm compatible with
DICOM
chest X-ray images.

Device output in
case of positive
detection

When deployed on other
radiological imaging equipment,
VUNO Med-Chest X-ray
Triage/VUNO Med-CXR Link
Triage will automatically run after
image acquisition to perform triage.
It displays the analysis result
through the worklist interface of
PACS/workstation.
No markup of the conditions will be
done 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 is generated.

When deployed on other
radiological imaging equipment,
qXR-PTX-PE will automatically run
after image acquisition to perform
triage. It displays the analysis result
through the worklist interface of
PACS/workstation.
No markup of the conditions will be
done 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 is generated.

Passive notification. Images with
suspicion of pneumothorax and/or


pleural effusion are flagged in
PACS/workstation/DICOM viewer.

Where
generated
results(i.e.,
DICOM files)
are stored

Performance
level
- Timing of
notification

The average time taken for the
notification to travel from VUNO
Med-Chest X-ray Triage/VUNO
Med-CXR Link Triage to the point
at which the result is displayed in
the destination Picture Archiving
and Communication System(PACS)
or workstation/digital radiographic
processing system (ex. digital
radiography, digital X-ray system
etc.) is below 10 seconds.

The average time taken for the
notification to travel from qXR-
PTX-PE to the point at which the
result is displayed in the destination
Picture Archiving and
Communication System(PACS) or
workstation/digital radiographic
processing system (ex. digital
radiography, digital X-ray system
etc.) is 10 seconds.

Performance
level
- Accuracy of
classification


AUC (95% CI)
Sensitivity (95% CI)
Specificity (95% CI)


Proprietary Name
Nano-X AI HealthCCSng device

Classification Name
Computed tomography x-ray system.


Cleared Device:
Nano-X AI HealthCCSng device

The HealthCCSng V2.0 device is substantially equivalent to the following cleared Device:


Cleared Device:
Nano-X AI Ltd. HealthCCSng Device
(K210085)

The HealthCCSng device is intended
for use as a non-invasive post-
processing software to evaluate
calcified plaques in the coronary
arteries, which present a risk for
coronary artery disease.
The HealthCCSng device analyzes
routine non-gated, non-contrast CT
studies that include the entire heart of
adult patients of age 30-85.
The device generates an exact calcium
score and a four coronary artery
calcium detection category output
representing the estimated quantity of
calcium detected together with
preview axial images of the detected

The HealthCCSng device is
intended for use as a non-
invasive post-processing
software to evaluate calcified
plaques in the coronary arteries,
which present a risk for coronary
artery disease. The software
generates an estimated coronary
artery calcium detection
category.
The HealthCCSng device analyzes
existing non-cardiac-gated CT studies
that include the heart of adult patients
above the age of 30.
The device generates a three-category
output representing the estimated


Cleared Device:
Nano-X AI Ltd. HealthCCSng
Device (K210085)

Modality
Computed tomography (CT)
Computed tomography (CT)
Same

Similar. The
inclusion criteria
are the same: in

Comparison of Technological Characteristics


both devices
algorithm is
intended to run on
non-contrast non-
gated CT scans.

Similar, the
modified
HealthCCSng
supports all the
slice thickness
range as in the
cleared device and
in addition can
support a wider
variety of scans.
The expansion of
the slice thickness
range was
validated and
performnance was
found similar to
the cleared device.

Similar, both
modified and
cleared devices
are intended for
adult population
at the age of 30
and older; the
modified device
has an upper limit
as part of product
scope focus on
relevant
population.


Deep-learning-based
segmentation of the heart

Coronary artery
calcification
quantification
method

Coronary Calcium
Detection Category and
exact detected calcium
score on side bar

Coronary Calcium Detection
Category Detected and
calcium score mark on side
bar

Similar, both
devices provide
calcium category;
both the cleared
device and the
modified device
mark the calcium
score on a side
bar; the modified
device also
provides the
detected calcium
score number as
an output, which
was validated and
was found similar
to the cleared
device.

Optional to add the results to
the report, DICOM
Secondary Capture, Insight
UI application

Similar, the
modified device
also enables the
option to add the


1) Estimated Coronary
Calcium Detection,
based on the
measurement of calcium
deposits in the coronary
arteries, precise score is
indicated besides the
arrow on the side scale
bar.
2) A corresponding
Estimated Coronary
Calcium Detection
Category, based on the
Estimated Coronary
Calcium measurements
4 categories:
0 – Zero Calcium
1-99 – Low
100-399 – Medium
≥400 - High

1) Estimated Coronary
Calcium Detection, based
on the measurement of
calcium deposits in the
coronary arteries, score is
presented as an arrow on
the side scale bar.
2) A corresponding
Estimated Coronary
Calcium Detection
Category, based on the
Estimated Coronary
Calcium measurements
3 categories:
0-99 – Low
100-399 – Medium
400 - High

Similar, both
devices provide
calcium category;
The modified
HealthCCSng
device provides a
more precise
representation of
coronary calcium
score, and
separating the
category 0 from
the other from the
‘low’ category.


JLK Tower, 5, Teheran-ro 33-gil Gangnam-gu Seoul n/a 06141 Korea,
South

Columbia Square 555 Thirteenth Street NW Washington D/C 20004
United States

Radiological computer aided triage and notification software

Radiological Computer-Assisted Triage And Notification Software


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

Predicate # Predicate Trade Name (Primary Predicate is listed first) Product Code


Device Trade Name:
Contour+(MVision Al Segmentation)

Common Name:
Medical Image Segmentation Software

Radiological Image Processing Software For Radiation Therapy

Medical Image Management And Processing System


CT Lung and Abdomen
CT Female Pelvis
CT Male Pelvis


MVision AI Segmentation (K212915)
Contour+ (MVision Al Segmentation)
Comparison

MVisionAI Segmentation is a software
system for image analysis algorithms to be
used in radiation therapy treatment
planning workflows. The system includes
processing tools for automatic contouring
of CT images using machine learning
based algorithms. The produced
segmentation templates for regions of
interest must be transferred to appropriate
image visualization systems as an initial
template for a medical professional to
visualize, review, modify and approve
prior to further use in clinical workflows.
The system creates initial contours of pre-
defined structures of common anatomical
sites, i.e. Head and Neck, Brain, Breast,
Lung and Abdomen, Male Pelvis, and
Female Pelvis in adult patients.
MVision AI Segmentation is not intended
to detect lesions or tumors. The device is
not intended for use with real-time
adaptive planning workflows.

Contour+ (MVision Al Segmentation) is
a software system for image analysis
algorithms to be used in radiation therapy
treatment planning workflows. The
system includes processing tools for
automatic contouring of CT and MR
images using machine learning based
algorithms. The produced segmentation
templates for regions of interest must be
transferred to appropriate image
visualization systems as an initial
template for a medical professional to
visualize, review, modify and approve
prior to further use in clinical workflows.
The system creates initial contours of
pre-defined structures of common
anatomical sites, i.e., Head and Neck,
Brain, Breast, Lung and Abdomen, Male
Pelvis, and Female Pelvis.
Contour+ (MVision Al Segmentation) is
not intended to detect lesions or tumors.
The device is not intended for use with
real-time adaptive planning workflows.

The following table outlines the similarities and differences between the two software versions:


Designed to be used by clinicians trained
in radiation therapy workflows.

Patients who have been prescribed
radiation therapy.

Cloud based software Application
Local (on customer premises)
installation in healthcare provider's IT
network / server

DICOM image and structure set data
transfers
TCP/IP, SCP, and HTTP (Local)
TCP/IP, SCP, and HTTPS (Cloud)

Minor changes:
Added API script to
send scans directly
from the Varian
Eclipse Treatment
Planning System;

Added support for
automatic contouring
of MR images

Machine learning-based contouring
using deep learning-based models
Does not support segmentation based
on atlas-based techniques

Same algorithms;
Updated certain
CT segmentation
models; Added 1 CT
and 2 MR models


Classification Name:
Magnetic Resonance Diagnostic Device

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

Vantage Galan 3T, MRT-3020, V10.0 with AiCE Reconstruction
Processing Unit for MR


VantageGalan3T,MRT-3020,V10.0 with AiCE Reconstruction Processing Unit

redicateDevice:Vantage Galan 3T, MRT-3020, V9.0 with AiCE Reconstruction

System Vantage Galan 3T, MRT-3020, V9.0 with AiCE

Marketed By Canon Medical Systems USA, Inc.


Vantage Galan 3T, MRT-3020, V9.0 with AiCE
Reconstruction Processing Unit for MR

Marketed By
Canon Medical Systems USA, Inc.


Item
Subject Device:
PredicateDevice:
Notes

Vantage Galan 3T, MRT-3020,
Vantage Galan 3T, MRT-3020,

with AiCE Reconstruction
with AiCE Reconstruction

Processing Unit for MR
Processing Unit for MR(K230355)

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


Allows screen access to 1st level
operating mode

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

Potential emergency
condition and means
provided for shutdown

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


1)Mean Dice(cid:116) 0.95
2) 95% CI lower bound
ofDicescores (cid:116) 0.90
3) 95% CI upper bound
ofHD95 score (cid:100) 4.0


95% CI upper bound of
VolumeError(cid:100) 5%

The results of the liver volume measurement are provided below.


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%

A detailed description of the training data is available in the Table below:


unknown: 451
(48.92%)
white: 273
(29.61%)
asian: 102
(11.06%)
black or african
american: 88
(9.54%)
american indian or
alaska native: 4
(0.43%)
native hawaiian or
pacific islander: 4
(0.43%)

2DSM were considered. Details of the dataset are reported in the table below:


Modification 1:
Support of GE
mammograms (no
re-training
required)

Modification 2:
Support of Siemens
Mammograms (re-
training required)

Modification 3:
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.

Comprehensive testing
for planned changes

Agreement testing
against the visual
assessment of 5
radiologists on GE
mammograms.

Agreement testing
against the visual
assessment of 5
radiologists on
Hologic
mammograms.
Agreement testing
against the visual
assessment of 5
radiologists on
Siemens
mammograms.

Agreement testing
against the visual
assessment of 5
radiologists on
Hologic and new
manufacturer(s)
mammograms.

Acceptance criteria
of the updated device

Quadratic kappa on
GE mammograms
superior to 0.85.
Linear kappa,
accuracy, and
density bins (A, B, C
and D) on GE

Quadratic kappa on
Siemens and
Hologic
mammograms
superior to 0.85
Linear kappa,
accuracy, and density

Quadratic kappa on
Hologic
mammograms
superior to 0.85.
Linear kappa,
accuracy, and density
bins (A, B, C and D)

development/modification and testing, and the monitoring methodology.


bins (A, B, C and D)
on Siemens and
Hologic
mammograms non-
inferior to the
comparator device
(K241561) on
Hologic
mammograms.

on Hologic
mammograms non-
inferior to the
comparator device
(K241561) on
Hologic
mammograms.

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.


Product
Marketed by
510(k) Number
Clearance Date

Aplio i900/i800/i700 Diagnostic
Ultrasound System, Software
V7.0


This study included representative images
from 50 patients selected from among
previously acquired data
• Gender: roughly equivalent number of
males and females
• Age: Ranging from 20-98 years old
• Ethnicity (Country): USA
• BMI: ranging from 16.4-71.6 kg/m2,
equally distributed across
underweight or healthy, overweight,
and obese categories
• Disease severity: normal, mildly
abnormal, moderately abnormal, and
severely abnormal categories of left
ventricle ejection fraction equivalently
represented

Images from 239 demographically diverse
patients acquired over a two-month period at
a U.S. clinical site.

A licensed sonographer selected
representative images for each of the four
evaluated chamber views (A4C/A3C/A2C/SAX)


This study included images from 50 patients
selected from among previously acquired data
• Gender: roughly equivalent number of
males and females
• Age: Ranging from 20-98 years old
• Ethnicity (Country): USA
• BMI: ranging from 16.4-71.6 kg/m2,
equally distributed across
underweight or healthy, overweight,
and obese categories
• Disease severity: normal, mildly
abnormal, moderately abnormal, and
severely abnormal categories of left
ventricle ejection fraction equivalently
represented

Ground truth was established by the median
of manual measurement results taken by
three licensed sonographers using the


This study included representative images
from 45 patients selected from among
previously acquired data
• Gender: roughly equivalent number of
known males and females*
• Age: Ranging from 36-89 years old*
• Ethnicity (Country): USA
• BMI: ranging from 18.8-71.6 kg/m2,
equally distributed across
underweight or healthy, overweight,
and obese categories
• Disease severity: normal, low severity,
and high severity categories of LVOT
velocity time integral range
equivalently represented

Ground truth was established by the median
of manual LVOT measurement results taken by
three licensed sonographers


This study included representative images
from 45 patients selected from among
previously acquired data
• Gender: roughly equivalent number of
known males and females*
• Age: Ranging from 36-89 years old*
• Ethnicity (Country): USA
• BMI: ranging from 18.8-71.6 kg/m2,
equally distributed across
underweight or healthy, overweight,
and obese categories
• Disease severity: normal, low severity,
and high severity categories of AV
velocity time integral range
equivalently represented

Ground truth was established by the median
of manual AV measurement results taken by
three licensed sonographers


GLEAMER SAS
47bis, rue des Vinaigriers
75010, Paris 10, FRANCE

Antoine Tournier
Chief Compliance Officer
Tel: 0033 6 15 81 23 45
Email: antoine.tournier@gleamer.ai
Alternate email: qara@gleamer.ai


Automated Radiological Image Processing Software


Endpoint
Metric
Mean
Lower
Upper
Acceptance criteria


Cobb angle with
the largest
curvature
(n=100)

Cobb angle with
the largest
curvature
(n=32)

Cobb angle with
the largest
curvature
(n=80)


Scintillator material: LYSO
Number of detector rings: 100
Axial FOV: 295 mm

Scintillator material: LYSO
Number of detector rings: 112
Axial FOV: 300 mm


Classification Name
Medical Image Analyzer


Device intended for use as a concurrent reading aid for
users interpreting chest radiographs

Secure cloud-based processing and delivery of chest
radiographs


MEDIASTINUM/HILA ABNORMALITY
0.922
[0.91; 0.934]

PLEURAL SPACE ABNORMALITY
0.973
[0.97; 0.975]

Table 2: AUC of the ROC Curve for ChestView US Model Predictions by ROI


High-specificity operating point
(FINDINGS)


Classification Description
21 CFR §
Product Code

Automated Radiological Image
Processing Software

Medical image management and
processing system

System, imaging, pulsed doppler,
ultrasonic


Feature
Ultrasound Workspace
TOMTEC-ARENA
EPIQ Series Diagnostic
Comparison

Version 6.0 (UWS6.0)
TTA2.50
Ultrasound System

Proposed Device
Predicate Device
Reference Device

The product is a clinical
software package
designed for review,
quantification and
reporting of structures and
function based on multi-
dimensional digital
medical data acquired with
different modalities. The
product is not intended to
be used for reading of
mammography images.

TOMTEC-ARENA
software is a clinical
software package
designed for review,
quantification and
reporting of structures and
function based on multi-
dimensional digital
medical data acquired with
different
modalities.TOMTEC-
ARENA is not intended to
be used for reading of
mammography images.

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.

Intended Use/Indications
for use of predicate and
subject device are
identical (unchanged) -
except of the product
name (bolded).
Intended Use/Indications
for use of reference device
and subject device are
similar and considered
equivalent (specifically if
compared for the clinical
use case/workflow of the
subject feature).

Indications for use of the
product are quantification
and reporting of
cardiovascular, fetal, and
abdominal structures and
function of patients with
suspected disease to
support the physician
in the diagnosis.

Indications for use of
TOMTEC-ARENA TTA2
software are quantification
and reporting of
cardiovascular, fetal,
abdominal structures and
function of patients with
suspected disease to
support the physicians in
the diagnosis

The product is intended to
be used only by licensed

Identical for predicate and
subject device -except of

Table 1: Comparison to Predicate and Reference Device for introduction of SWM onto UWS6.0


Ultrasound Workspace Version 6.0
TOMTEC-ARENA

K-number
Not available
K213544
Subject of this submission is UWS6.0

3D Auto TV software enables semi-
automated quantification of the tricuspid valve
during transesophageal echocardiography
(TEE) and transthoracic echocardiography
(TTE) examinations. It applies artificial
intelligence for model based segmentation. At
a high level, this is accomplished through
automatically derived measurements from a
segmented model of the tricuspid valve
annulus formed by the software through
model-based segmentation of the acquired
ultrasound images.

3D Auto MV (formerly named 4D MV-
ASSESSMENT) is a semi-automated
software application intended for the analysis
of Mitral Valve (MV) anatomy and function.
This application generates models of
anatomical structures of interest such as the
MV annulus, leaflets, and the closure line,
which allows for quantification of pre- and
post-operative valvular function and a
comparison of morphology.
4D CARDIO-VIEW is an advanced analysis
tool for 3D/4D echocardiography data.
Anatomical structure visualization, volume
measurements (LV and/or generic), and
specified or manual measurements are
possible for cardiac structures including, but
not limited to, the tricuspid valve. Various
tools are available for rendering that display
2- and 3-dimensional morphology and
function for defined structures.

Similar to the predicate device features.
The functionality and workflow of the 3D Auto
TV software is very similar to the 3D Auto
MV tool, where measurement parameters are
derived from models of the mitral valve (in the
case of 3D Auto MV) and tricuspid valve (in
the case of 3D Auto TV). Manual
measurements are also able to be performed
on both software applications.
Comparing 3D Auto TV to 4D CARDIO-
VIEW, both software have functionality for
quantifying the tricuspid valve. The proposed
3D Auto TV allows semi-automated
quantification, where the reference device is
fully manual. As we demonstrate high
agreement in the measurement outputs on
the same patients when quantified using the
proposed 3D Auto TV software and the
reference 4D CARDIO-VIEW application
(REF #4), there are no new questions raised
of safety or effectiveness.
The subject of this submission is introduction
of semi-automated quantification via 3D Auto
TV of UWS6.0.

For Indications for Use, Intended Use, Product Code Information, Classification please refer to Table 1.


3D surface model is created semi-
automatically using machine learning
algorithm without user interaction. User is
able to edit, accept, or reject the initial
landmark proposals of the tricuspid valve
anatomical locations.

3D Auto MV: 3D surface model is created
semi-automatically using machine learning
algorithm without user interaction. User is
able to edit, accept, or reject the initial
landmark proposals of the mitral valve
anatomical locations.
4D CARDIO-VIEW: 3D surface model is
created based on user defined anatomical
landmarks. User is able to edit the contour of
the surface model before proceeding with the
workflow.

Subject device uses identical method for
contour generation as the 3D Auto MV
application of the predicate device. The only
difference is the algorithm is trained on
tricuspid valve images, where the predicate
device was trained using mitral valve images

Semi-auto annulus results
• TV Ann Perimeter (3D)
• TV Ann Perimeter (2D)
• TV Ann Max Diam (2D)
• TV Ann Min Diam (2D)
• TV Ann Perimeter Derived Diam (2D)
• TV Ann Height (3D)
• TV Ann Area (2D)
Manual device results
• TV Ann AP Diam (2D)
• TV Ann SL Diam (2D)
• Subvalvular 5 Plane SL Diam
• Subvalvular 5 Plane AP Diam
• Supravalvular C-Shaped Perimeter
• Supravalvular AV - AoCenter Diam

3D Auto MV:
Standard MV Parameters
• AP Diameter (cm)
• AL-PM Diameter (cm)
• Sphericity Index (AP / AL-PM)
• Intertrigonal Distance (cm)
• Commissural Diameter (cm)
• D-Shaped Annulus Perimeter (cm)
• Annulus Height (cm)
• Non-planar Angle (degrees)
• Tenting Volume (cm3)
• Coaptation Depth (mm)
• Tenting Area (cm2)
• Angle AAo-AP (degrees)
• Maximum Prolapse Height (mm)
• Maximum Open Coaptation Gap (mm)
• Maximum Open Coaptation Width (mm)
• Anterior Leaflet Area (cm2)
• Posterior Leaflet Area (cm2)
• Distal Anterior Leaflet Angle (degrees)
• Posterior Leaflet Angle (degrees)
• Anterior Leaflet Length (cm)
• Posterior Leaflet Length (cm)

Similar. The proposed 3D Auto TV software
enables a subset of very similar semi-
automated measurements as the predicated
software application 3D Auto MV, only for the
tricuspid annulus.
The proposed 3D Auto TV software adds
additional TV annulus and device
measurements from those available in 4D
CARDIO-VIEW to further define the tricuspid
valve anatomy.
Both the proposed 3D Auto TV and the
predicate 4D CARDIO-VIEW software allow
manual, free-form measurements of the
valve.


• C-Shaped Annulus (cm)
2D MV Parameters
• D-Shaped Annulus Area (cm2)
• Annulus Area (cm2)
• Anterior Closure Line Length (cm)
• Posterior Closure Line Length (cm)
3D MV Parameters
• Saddle Shaped Annulus Area (cm2)
• Saddle Shaped Annulus Perimeter (cm)
• Total Open Coaptation Area (cm2)
• Anterior Closure Line Length (cm)
• Posterior Closure Line Length (cm)
4D CARDIO-VIEW:
TAVR results
• Ann-Ost left diam
• Ann-Ost right diam
• Annulus Area
• Annulus dmin
• Annulus dmax
• Ao Ring diam
• Ao SV diam
• Ao STJ diam
Volume results (not related to TV
quantification)
• EDV
• EF
• ESV
• GenVol
• Mass
• SV


The 3D Auto CFQ is a new artificial
intelligence software which will be introduced
on the Ultrasound Workspace Software
system starting with Version 6.0. The
application provides semi-automated
quantification of Mitral Regurgitation (MR)
volume and peak flow rate based on 3D color
flow images acquired during
transesophageal echocardiography (TEE)
examinations.

The Proximal Isovelocity Surface Area (PISA)
methodology can be used currently on the
predicate device to quantify valvular
regurgitation. The technique utilizes 2D/Color
and Doppler images to allow the user to make
simple, manual measurements in a cascading
fashion to allow calculation of peak flow rate
and volumetric regurgitation.
3D Auto MV is a semi-automated software
application intended for the analysis of Mitral
Valve (MV) anatomy and function. This
application generates models of anatomical
structures of interest such as the MV annulus,
leaflets, and the closure line, which allows for
quantification of pre- and post-operative
valvular function and a comparison of
morphology.

Similar. The predicate device facilitates the
quantification of mitral regurgitation volume
and peak flow rate through a group of
measurements which are performed in a
cascading fashion manually by the user
according to the Proximal Isovelocity Surface
Area (PISA) methodology. The proposed 3D
Auto CFQ software application allows the
users to quantify the same measurements for
mitral regurgitation volume and peak flow rate
but in a semi-automated workflow.
3D Auto MV feature of the predicate does not
contain functionality for quantification of mitral
regurgitation.

3D surface model is created semi-
automatically using machine learning
algorithm without user interaction. User is
able to edit, accept, or reject the initial
landmark proposals of the mitral valve
anatomical locations.

PISA: No standard contour generation
technology for the mitral valve, outside of 3D
Auto MV, included as part of the system.
3D Auto MV: 3D surface model is created
semi-automatically using machine learning

Subject device uses identical method for
contour generation as the 3D Auto MV
feature of the predicate device.


Ultrasound Workspace Version 6.0
TOMTEC-ARENA

algorithm without user interaction. User is able
to edit, accept, or reject the initial landmark
proposals of the mitral valve anatomical
locations.

The 3D Auto CFQ algorithm quantifies mitral
regurgitation volume and flow rate from
acquired 3D color flow images. The greyscale
information from these images is used to
generate a 3D model of the mitral valve,
which is used as an input along with the 3D
color data into the 3D Auto CFQ flow
algorithm. The 3D Auto CFQ algorithm uses a
fluid dynamic model of an incompressible
fluid (blood) traveling through an irregular-
shaped (i.e., nonround) orifice. In its initial
step, the algorithm generates a hypothetical
model of true blood flow velocities in the
proximal convergence zone based on all
measured Doppler velocities and the
underlying fluid dynamics model. The true
velocity model is then converted into the
corresponding apparent Doppler velocity
model (“synthetic apparent velocities”) using
ultrasound physics (projection along the axial
dimension). These synthetic velocities are
subsequently compared to the acquired
velocities in the Color Flow (CF) data set.
Based on the outcome of this comparison,
the model is updated and reiterated to get
the best fit between the acquired velocities
and the generated model. 3D Auto CFQ
determines the resulting regurgitant flow rate

PISA:
The PISA methodology uses sequential
acquisitions and manual measurements,
which are manually performed by the user:
- MR Alias Velocity (from the 2D/Color)
- MR Radius (from the 2D/Color)
- MR Vmax (from the continuous wave
doppler)
- MR VTI (from the continuous wave
doppler)
The outputs of these measurements go into
the equations for the derived measurements
including:
- Mitral Regurgitant (MR) Flow Rate
- MR Effective Regurgitant Orifice (ERO)
- MR Volume
3D Auto MV:
N/A – does not contain technology for mitral
regurgitation quantification

Similar. The PISA methodology of the
predicate device – used for quantifying MR
volume and flow rate - utilizes sequential
measurements performed by the user and is
based on assumptions including there being
a single, round, constant flow orifice during
the entire systole.
3D Auto CFQ operates using 3D color to
address the spatial complexities seen in
mitral regurgitation and was developed to
evaluate the regurgitant flow at every frame in
systole, where the PISA methodology only
assesses one frame during systole and
assumes this frame applies across systole.
The proposed 3D Auto CFQ software
application allows the users to quantify the
same measurements for mitral regurgitation
volume and peak flow rate as PISA. The
dynamic flow algorithm is the new technology
introduced in this submission. Mitral valve
model generation is identical to the 3D Auto
MV feature of the predicate device. The
dynamic flow model of the 3D Auto CFQ
software application uses this as input to
arrive at the outputs of mitral regurgitation
volume and peak flow rate. These outputs are


for this frame. This process is repeated for
each frame included in the analysis, which in
most cases includes the entire systolic cycle.
In each frame, the size and shape of the
regurgitant orifice is not assumed but is
generated by this iterative loop between the
model and the CF data.

the same as in the predicate, only the method
to arrive at the measurements differs in the
subject device.

Semi-automated measurements performed
by the 3D Auto CFQ software application:
Mitral regurgitation (MR) volume [mL];
Peak flow rate [mL/s]

PISA:
Derived measurements which the user can
obtain through the PISA methodology include:
Mitral regurgitation (MR) volume [mL];
Peak flow rate [mL/s]
3D Auto MV:
Standard MV Parameters
• AP Diameter (cm)
• AL-PM Diameter (cm)
• Sphericity Index (AP / AL-PM)
• Intertrigonal Distance (cm)
• Commissural Diameter (cm)
• D-Shaped Annulus Perimeter (cm)
• Annulus Height (cm)
• Non-planar Angle (degrees)
• Tenting Volume (cm3)
• Coaptation Depth (mm)
• Tenting Area (cm2)
• Angle AAo-AP (degrees)
• Maximum Prolapse Height (mm)
• Maximum Open Coaptation Gap (mm)
• Maximum Open Coaptation Width (mm)
• Anterior Leaflet Area (cm2)
• Posterior Leaflet Area (cm2)
• Distal Anterior Leaflet Angle (degrees)
• Posterior Leaflet Angle (degrees)
• Anterior Leaflet Length (cm)
• Posterior Leaflet Length (cm)

Similar. The measurements performed by the
proposed 3D Auto CFQ software application
can also be obtained by a user on the
predicate device using the PISA
methodology.
Substantiation of the performance of the 3D
Auto CFQ software’s regurgitant volume
output was performed by comparison to
cardiac magnetic imaging with (CMR) images
with acceptance criteria of agreement within
the limits of agreement. While the PISA
methodology is a widely accepted method for
mitral regurgitation quantification and is a
recommended method by the American
Society of Echocardiography, the outputs
from 3D Auto CFQ were compared to those
from CMR (as opposed to PISA) as the
former is considered a gold standard for
mitral regurgitation quantification.
Acceptance criteria for 3D Auto CFQ was
based on agreement with CMR being within
predefined maximum limits of agreement.


• C-Shaped Annulus (cm)
2D MV Parameters
• D-Shaped Annulus Area (cm2)
• Annulus Area (cm2)
• Anterior Closure Line Length (cm)
• Posterior Closure Line Length (cm)
3D MV Parameters
• Saddle Shaped Annulus Area (cm2)
• Saddle Shaped Annulus Perimeter (cm)
• Total Open Coaptation Area (cm2)
• Anterior Closure Line Length (cm)
• Posterior Closure Line Length (cm)

In addition to regurgitant volume, the peak
flow rate output of 3D Auto CFQ was
validated in comparison to manual PISA
method, where the correlation was very high.
3D Auto MV feature of the predicate device
facilitates anatomical measurements of the
mitral valve from the generated model of the
mitral valve but does not perform
measurements for quantifying mitral
regurgitation.


Feature
Ultrasound Workspace
TOMTEC-ARENA
EPIQ Series Diagnostic
Comparison

Version 6.0 (UWS6.0)
TTA2.50
Ultrasound System

Proposed Device
Predicate Device
Reference Device

Transducer Clinical
Application / cleared
compatibility

VeriSight ICE / Pro ICE
(Proposed Transducer)
TEE (transesophageal)
transducer.
Intended for intracardiac
and intra-luminal
visualization of cardiac and
great vessel anatomy and
physiology as well as
visualization of other
devices in the heart. The
VeriSight ICE catheter
provides 2D ultrasound
imaging capabilities, while
the VeriSight Pro ICE
catheter provides 2D
and/or 3D ultrasound
imaging capabilities.

N/A, compatibility to
VeriSight ICE / Pro ICE
has not been shown.

VeriSight ICE / Pro ICE
was introduced on EPIQ
via K202216.
TEE (transesophageal)
transducer.
Intended for intracardiac
and intra-luminal
visualization of cardiac and
great vessel anatomy and
physiology as well as
visualization of other
devices in the heart. The
VeriSight ICE catheter
provides 2D ultrasound
imaging capabilities, while
the VeriSight Pro ICE
catheter provides 2D
and/or 3D ultrasound
imaging capabilities.

Compatibility to UWS6.0 is
subject of this submission.

N/A, for TTA2
compatibility for VeriSight
ICE / Pro ICE has not
been shown.

Table 4: Comparison to Predicate and Reference Device for Compatibility to VeriSight ICE / Pro ICE Probe on UWS6.0


GE Medical Systems Israel, Functional Imaging

Regulation number
21CFR 892.1200 and 21CFR892.1750


510(k) Premarket Notification Submission


Regulation number
21CFR 892.1200 and 21CFR 892.1750


Specification/
Predicate Device:
Proposed Device:

Attribute
Omni Legend(K221932)
Omni Legend

Multiple detector ring configurations
(16, 32cm axial FOV).70 cm bore.

Multiple detector ring configurations
(16,21,32cm axial FOV).70 cm bore

Detector Unit
SiPM-based light sensor with ASIC
SiPM-based light sensor with ASIC

BGO scintillator crystals
BGO scintillator crystals

CT System
Revolution Maxima (K192686)
Revolution Maxima(K192686)

Iterative Image Reconstruction,
including Precision DL (K223212).
PET DigitalGating (DDG) also known
as MotionFree (K180318)
Enhanced AC option

IEC 60601-1 and applicable Collateral
and Particular Standards.

differences between the predicate and proposed devices.


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

6450 Ultrasound System is a general-purpose diagnostic ultrasound system, based on a mainframe platform that can be easily moved
thanks to four swivelling wheels.
audible to the human ear) for the visualization of deep structures of the body by recording the reflections or echoes of ultrasonic pulses


directed into the tissues and of the Doppler effect, i.e. the frequency-shifted ultrasound reflections produced by moving targetsI (nutseurnalalyl Use
red blood cells) in the bloodstream, to determine both direction and velocity of blood flow in the target organs.
The primary modes of operation are: B-Mode, M-Mode, Tissue Enhancement Imaging (TEI), Multi View (MView), Doppler (both PW and
CW), Color Flow Mapping (CFM), Power Doppler, Tissue Velocity Mapping (TVM), Combined modes. 6450 Ultrasound System also
manages Elastosonography (ElaXto, QElaXto, QElaXto 2D), 3D/4D and CnTI.
Several types of probes are used to cover different needs in terms of geometrical shape and frequency range.
6450 Ultrasound System can drive Phased Array, Convex Array, Linear Array, Doppler probes and Volumetric probes (Bi-Scan probes).
The control panel is equipped with a pull-out Qwerty alphanumeric keyboard that allows data entry. The touchscreen has an emulation
of the Qwerty keyboard that allows data entry and has additional controls and mode-depending keys, integrated in the touchscreen.
6450 Ultrasound System is equipped with wireless capability.
6450 Ultrasound System will be available on the market in two models with the following commercial names: MyLabE80, MyLabE85.
The difference between MyLabE80 and MyLabE85 models is only in the licenses configuration.
For both models, there is the ETC (Easy To Clean) version, having a keyboard with special controls and material, compatible with
disinfection procedures.
6450 Ultrasound System, defined herein, introduces new features and accessories listed below:
1. XStrain LA: XStrain allows clinicians to quantify endocardial velocities of contraction and relaxation and local deformation of the heart
(Strain/Strain rate). XStrain LA is an advanced processing package for the Left Atrium analysis.
2. New probe: IHX 6-25
6450 Ultrasound System employs the same fundamental technological characteristics as its predicate device cleared via K192157.

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

The multifunctional ultrasound scanner is used to collect, display and analyze ultrasound images during ultrasound imaging procedures
in combination with supported echographic probes.
Main application: Districts: Invasive access:
Cardiac Cardiac Adult, Cardiac Pediatric Transesophageal
Vascular Neonatal, Adult Cephalic, Vascular Not applicable
General Imaging Abdominal, Breast, Musculoskeletal, Intraoperative (Abdominal),
Neonatal, Pediatric, Small Organs Laparoscopic, Transrectal
(Testicles), Thyroid, Urological
Women Health OB/Fetal, Gynecology Transrectal, Transvaginal
Virtual Navigator option supports a radiological clinical ultrasound examination (first modality) by providing additional image
information from a second imaging modality. As second imaging modality it is intended any image coming from CT, MR, US, PET, XA and
NM.
The second modality provides additional security in assessing the morphology of the real time ultrasound image.
The primary modes of operation are: B-Mode, M-Mode, Tissue Enhancement Imaging (TEI), Multi View (MView), Doppler (both Pulsed
Wave (PW) and Continuous Wave (CW)), Color Flow Mapping (CFM), Power Doppler, Tissue Velocity Mapping (TVM), Combined modes,
Elastosonography, 3D/4D and CnTI.
The ultrasound scanner is suitable to be installed in professional healthcare facility environment and is designed for ultrasound
practitioners.

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

The indications for use of the 6450 Ultrasound System are the same as those of predicate device, cleared via K192157.

Technological Comparison 21 CFR 807.92(a)(6)

The new version of Esaote 6450 Ultrasound System is substantially equivalent to the predicate device 6450 Ultrasound System (cleared


Improveperformancebyreducingfalsepositive
andfalsenegativeoutputsbasedonpost-market
andreal-worlddata. Specifically,improvements
resultingfromre-trainingtheMLmodelwithnew
data.


Feature
Subject Device
Predicate Device
Comparison

System, Image
Processing,
Radiological (QIH)

System, Image
Processing,
Radiological (LLZ)


DICOM compliant
images collected in other
devices in either digitally
computed (CR) or
directly digital (DX)
formats.

Similar. The subject
device is validated to
additionally analyze other
standard image formats
and does not raise new
questions about safety or
effectiveness.

Landmark detection, user
can edit landmark

Knee detection;
Landmark detection;
Joint space detection

Similar. The subject
device is intended to be
used on the knee, hip, and
lumbar spine while the
predicate device is only
for the leg. This
difference in specific
anatomic locations does
not raise new types of
questions for safety or
effectiveness.

Measurement
Length and angle
Length and angle
Same

Similar. The subject
device requires the user
to review and edit the
device output as
necessary while the
predicate device does not
as a fully automatic
device.

Intended User
Trained Professional
Trained Professional
Same

Ortho AI is an image-
processing software
indicated to assist in
making measurements for
a total hip arthroplasty,
total knee arthroplasty,
and lumbar spine fusion
surgery.
It is intended to assist in
the measurement of x-ray
images by measuring
lengths, angles and
position of implants
relative to the bone
structures of interest,
provided that the points
of interest can be

IB Lab KOALA is a
radiological fully-
automated image
processing software
device of either computed
(CR) or directly digital
(DX)images intended to
aid medical professionals
in the measurement of
minimum joint space
width; the assessment of
the presence or absence
of sclerosis, joint space
narrowing, and
osteophytes based
OARSI criteria for these
parameters; and the
presence or absence of

The subject device
performs measurements
of lengths and angles on
hip, knee, and lumbar
spine images. The
predicate device performs
length and angle
measurements on leg
images. This difference in
specific anatomic
locations does not raise
new questions for safety
or effectiveness and
therefore does not induce
changes in the intended
use


Manufacturer
Device Name
Application Number


NeuroICH is a notification-only,
parallel workflow tool for use by
hospital networks and trained
clinicians to identify and
communicate images of
suspected ICH patients to a
specialist, independent of
standard of care workflow.
The device uses an artificial
intelligence algorithm to analyze
non-contrast CT images of the
head acquired in the acute setting
for findings suggestive of
intracranial hemorrhage (ICH) in
parallel to the ongoing standard of
care image interpretation and
notify an appropriate clinician of
these findings. Notifications
include non-diagnostic preview
images that are meant for
informational purposes only. The
device does not alter or remove
the original medical image and is
not intended to be used as a
diagnostic device. Images can be

Viz ICH is a notification-only,
parallel workflow tool for use by
hospital networks and trained
clinicians to identify and
communicate images of specific
patients to a specialist, independent
of standard of care workflow.
Viz ICH uses an artificial
intelligence algorithm to analyze
images for findings suggestive of a
prespecified clinical condition and
to notify an appropriate medical
specialist of these findings in
parallel to standard of care for
image interpretation. Identification
of suspected findings is not for
diagnostic use beyond notification.
Specifically, the device analyzes
non-contrast CT images of the brain
acquired in the acute setting, and
sends notifications to a
neurovascular or neurosurgical
specialist that a suspected
intracranial hemorrhage has been
identified and recommends review

A table comparing the key features of the subject and predicate device is provided below:


previewed through a mobile
application.
Notified clinicians are responsible
for viewing high quality images on
a diagnostic viewer per the
standard of care and engaging in
appropriate patient evaluation in
conjunction with other patient
information before making
care-related decisions. NeuroICH
is limited to analysis of imaging
data and should not be used
in-lieu of full patient evaluation or
relied upon to make or confirm
diagnosis.

of those images. Images can be
previewed through a mobile
application.
Images that are previewed through
the mobile application may be
compressed and are for
informational purposes only and not
intended for diagnostic use beyond
notification. Notified clinicians are
responsible for viewing
non-compressed images on a
diagnostic viewer and engaging in
appropriate patient evaluation and
relevant discussion with a treating
physician before making
care-related decisions or requests.
Viz ICH is limited to analysis of
imaging data and should not be
used in-lieu of full patient evaluation
or relied upon to make or confirm
diagnosis.

1. Image forwarding module
configured on site machine at
hospital end for transferring
DICOM studies.
2. Image analysis software
algorithm hosted on AWS cloud
managed by NEUROCAREAI.
3. Mobile application software
module for review of notification
and non-diagnostic images.
4. Admin panel as web application
for registration and management
of systems, sites and clinicians
accounts.

1. Image analysis software
algorithm hosted on Viz.ai’s
servers.
2. Mobile application software
module for review of notification
and non-diagnostic images.

Neurovascular or Neurosurgical
Specialist

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


DICOM Information about the
patient, study, and current image

DICOM Information about the
patient, study and current image

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

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

Preview images returned to the
Mobile application for view.


workflow early with notifications from the NeuroICH software.


510(k) Owner
Better Diagnostics AI Corp.

Raj Zaveri
Quality and Regulatory Consultant

Email: rajzaveri10@gmail.com
Phone: +91 8369438297


was changed to separate the image communication platform from the Briefcase-Triage SW. The

subject device consists of only the algorithm analysis module which can be integrated with image

communication platforms that meet the Briefcase-Triage input and output requirements.

algorithm performance, due to training the subject device on a larger data set and additional


Predicate Device
Aidoc Briefcase-Triage for PE
(K222277)

Subject Device
Aidoc Briefcase-Triage for PE

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

Briefcase-Triage is a radiological
computer- aided triage and notification
software indicated for use in the analysis
of CTPA images, in adults or transitional
adolescents aged 18 and older. The
device is intended to assist hospital
networks and appropriately trained
medical specialists in workflow triage by
flagging and communicating suspected
positive cases of Pulmonary Embolism
(PE) pathologies.
Briefcase-Triage uses an artificial
intelligence algorithm to analyze images
and highlight cases with detected findings
in parallel to the ongoing standard of care
image interpretation. The user is
presented with notifications for cases with
suspected findings. Notifications include
compressed preview images that are
meant for informational purposes only,
and not intended for diagnostic use
beyond notification. The device does not
alter the original medical image and is not
intended to be used as a diagnostic
device.
The results of Briefcase-Triage are
intended to be used in conjunction with
other patient information and based on
their professional judgment, to assist with
triage/prioritization of medical images.
Notified clinicians are responsible for
viewing full images per the standard of
care.


viewing full images per the standard of
care.

Hospital networks and appropriately
trained medical specialists

Notification-onl
y (/notification
alerts), parallel
workflow tool

No. No cases are removed from
desktop app or deprioritized

Inclusion/
Exclusion
criteria for
clinical
performance
testing

Inclusion criteria
● CTPA protocols.
● Single Energy or Dual Energy
exams
● Performed on CT scanners with
64 or greater number of detectors
● Scans performed on
adults/transitional adults ≥ 18
years of age
● Slice thickness; 0.5 mm to 3.0 mm
axial slices


Exclusion ● CTPA protocols. ● CTPA protocols.


Exclusion Criteria
● All studies that are technically
inadequate, including studies with
motion artifacts, severe metal
artifacts, sub-optimal bolus timing
or an inadequate field of view.

Artificial intelligence algorithm with
database of images.

- AHS module ( image acquisition);
- ACS module (image processing);
- Aidoc Desktop Application for
workflow integration
(Feed/Worklist (alternate names)
and non-diagnostic Image
Viewer).

- Integrated with image routing module via
image communication platform (ICP)
(image acquisition).
- Algorithm module (image processing)
- Integrated with desktop application for
workflow integration (feed and
non-diagnostic Image Viewer).


Briefcase-Triage +
Image
Communication
Platform
Time-To-Notification

Table 2. Time-to- notification comparison for Briefcase-Triage devices (Seconds)


Table 4. Frequency Distribution of Gender *


Table 5. Frequency Distribution of Manufacturer


The ScreenPoint Transpara™
system is intended for use as a
concurrent reading aid for
physicians interpreting screening
mammograms, to identify
regions suspicious for breast
cancer and assess their
likelihood of malignancy.
Output of the device includes
marks placed on suspicious soft
tissue lesions and suspicious
calcifications; region-based
scores, displayed upon the
physician’s query, indicating the

ProstatlD™ is a radiological
computer assisted detection
(CADe) and diagnostic (CADx)
software device for use in a
healthcare facility or hospital to
assist trained radiologists in the
detection, assessment and
characterization of prostate
abnormalities, including cancer
lesions using MR image data

Prostate MR AI is a plug-in
Radiological Computer Assisted
Detection and Diagnosis
Software device intended to be
used
• with a separate hosting
application
• as a concurrent reading aid
to assist radiologists in the
interpretation of a prostate
MRI examination acquired


§ 892.2090 Radiological
Computer Assisted Detection
and Diagnosis Software

Classification
Class II
Class II
Class II
Identical


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

A concurrent reading aid for
physicians interpreting prostate
MRI exams of patients presented
for high-risk screening or
diagnostic imaging, to identify
regions suspicious for prostate
cancer and assess their likelihood
of malignancy.

A concurrent reading aid for
physicians interpreting prostate
MRI examinations acquired
according to the PI-RADS
standard, to identify findings and
assess their level of suspicion.

Population of biological males
with a prostate gland undergoing
screening or clinical MRI exams.
This includes biological males of
all ages with clinical indicators
suggestive of possible prostate
cancer or with family history of
prostate cancer.

Adult men (40 years and older)
with suspected prostate cancer
undergoing prostate MRI
without prior treatment of the
prostate gland (treatment-naïve).

Equivalent –
Images
captured from
different
patient
populations
are
standardized
to be
processible by
CAD devices.

Equivalent –
Images
captured from
different
anatomical
regions are
standardized
to be
processible by
CAD devices.

physicians qualified to read
screening mammograms

Physicians qualified to read and
interpret prostate MRI exams
consistent with ACR
recommendations in the context
of PI-RADS v2

Radiologists qualified to read
prostate MRI

Equivalent –
– Users are
qualified to
read radiology
images using
CAD devices

Software that applies algorithms
for recognition of suspicious
calcifications and soft tissue
lesions to detect and
characterize findings in
radiological breast images and
provide information about the
presence, location, and
characteristics of the findings to
the user.

Software that applies algorithms
for recognition of suspicious
tissue regions in Prostate MR
images to provide information
about the presence, location, and
level of suspicion of the findings.

Equivalent –
Both predicate
and subject
devices use
algorithms to
detect findings
and provide
diagnosis.

Prostate MR AI (VA10A) Traditional 510(k) Submission


Computer aided detection
(CAD) marks to highlight
locations where the device
detected suspicious
calcifications or soft tissue
lesions. Decision support is
provided by region scores on a
scale ranging from 0-100, with
higher scores indicating a higher
level of suspicion.

ProstatID does not include a
standalone graphical user
interface. Rather, ProstatID
outputs are in DICOM format and
may be viewed on DICOM-
compliant image viewers.

Prostate MR AI does not include
a standalone graphical user
interface. Rather, it is a plug-in
device that is intended to be used
with a separate hosting
application that allows the user
to view the original case, as well
as confirm, reject, edit, or add
lesions, their contours and
Scores.

Equivalent –
The difference
between
predicate and
subject
devices is
justified by
using the
reference
device which
also does not
have UI while
it retains the
same level of
safety and
effectiveness.

Design
Software only device
Software only device
Software only device
Identical

Artificial intelligence algorithm
trained with large datasets of
biopsy proven examples of
breast cancer, benign lesions
and normal tissue.

Neural network trained on a
database of reference normal
tissues and abnormalities with
known ground truth.

Artificial intelligence algorithm
trained on a database of prostate
MR image series acquired
according to the PI-RADS
standard (non-contrast T2W and
DWI image series), and
corresponding radiological
and/or biopsy findings.

Prostate MRI image series
acquired according to the PI-
RADS standard

Equivalent –
Acquired
images are
qualified for
CAD device
processing

Medical images provided in a
DICOM format

Equivalent –
Devices all
use
standardized
image types.


• Marks placed on suspicious
soft tissue lesions and
suspicious calcifications
• Region-based scores
indicating the likelihood that
cancer is present
• Overall score indicating the
likelihoood that cancer is
present on the mammogram

• Marks locations suspicious
of lesions
• Provides region scores with
higher scores indicating a
higher level of suspicion
• Provides single exam score
that synthesizes features

• Automatically segments the
contours of the prostate gland
• Automatically segments the
parts of the prostate that belong
to the periheral zone (PZ) and
that do not belong to the
peripheral zone (non-PZ),
respectively
• Calculation of a “Suspicion
Map” that indicates lesions
suspicious for cancer
• For each detected lesion:
o Lesion contours
o Rating of severity (“Score”)
on a scale from 3 to 5 (in
steps of 1). Score is
generated by an algorithm
trained on the correlation of
prostate MRI with PI-RADS
scores provided by
radiologists and results of
lesion-targeted biopsy.
o A “Level of Suspicion”
(LoS) on a scale from 60 to
100 (in steps of 1) as a fine
granular measure of the
algorithm's suspicion for the
presence of a significant
lesion, based on training on
PI-RADS scores provided by
radiologists and results of
lesion-targeted biopsy

Equivalent –
as far as the
different
body regions
allow. PZ vs.
non-PZ is
prostate
specific and
is relevant for
PI-RADS
evaluation.
Instead of
marks for
suspicious
locations in
the image, the
subject
device
provides
lesion
contours and
a “suspicion
map”.


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

Finding level:
Scores on a continuous scale
from 0 to 1 that accompany the
overlay markings of suspicious
locations
Case level:
Suggested level of suspicion
(LoS) or overall PI-RADS exam
score

Finding level:
Rating of severity (“Score”) on a
scale from 3 to 5 (in steps of 1).
The Score is generated by an
algorithm trained on the
correlation of prostate MRI with
PI-RADS scores provided by
radiologists and results of lesion-
targeted biopsy
A “Level of Suspicion” (LoS) on
a scale from 60 to 100 (in steps
of 1) as a more granular measure
of the algorithm's suspicion for
the presence of a significant
lesion, based on training on PI-
RADS scores provided by
radiologists and results of lesion-
targeted biopsy
Prostate level (= Exam Level):
LoS derived from Finding Level
results as maximum LoS over all
findings (on a scale of 60-100 in
steps of 1), or (in the absence of
findings) as maximum of
internal Suspicion Map over
prostate segmentation (on a scale
of 1-59 in steps of 1)

Equivalent –
The
differences
between
predicate and
subject
devices can be
justified by
using the
reference
device which
apply
continuous
finding scale
and share the
same PI-
RADS LoS
exam score.

Findings are by-default
displayed when score is equal or
higher than 5.
Upon user request for findings
of score equal or less than 4.

Findings are added to post-
processed T2W image in DICOM
format as a colorized translucent
overlay to highlight locations, as
overlay scores on a continuous
scale from 0 to 1, and as a
suggested LoS or overall PI-
RADS exam score.

Upon activation of the plug-in,
findings are displayed in the
hosting workflow as
segmentations on the T2W
image series with corresponding
ratings by Scores (value range:
3-5), and as an overall exam
Score.

Equivalent –
Finding
results of both
predicate and
subject
devices can be
displayed.