The software processes DI-
COM compliant image data

None – enhanced images
are viewed on existing PACS
workstations

Image Enhance-
ment Algorithm
Description

Ezra Flash software imple-
ments an image enhance-
ment algorithm using a con-
volutional neural network-
based filtering. Original im-
ages are enhanced by run-
ning through a cascade of
filter banks, where thresh-
olding and scaling operations
are applied. These filters
result in a single machine-
learning model that reduces
noise. A dedicated machine-
learningmodelisusedforthe
head and body. The pa-
rameters of the filters were
obtained through an image-
guided optimization process.

Ezra Flash software imple-
ments an image enhance-
ment algorithm using a con-
volutional neural network-
based filtering. Original im-
ages are enhanced by run-
ning through a cascade of
filter banks, where thresh-
olding and scaling operations
are applied. These filters
result in a single machine-
learning model that reduces
noise. The parameters of the
filters were obtained through
an image-guided optimiza-
tion process.

SubtleMR software imple-
ments an image enhance-
ment algorithm using con-
volutional neural network-
based filtering. Original im-
ages are enhanced by run-
ning through a cascade of
filter banks, where thresh-
olding and scaling operations
are applied. Separate neural
network-based filters are ob-
tainedfornoisereductionand
sharpness increase. The pa-
rameters of the filters were
obtained through an image-
guided optimization process.


Amit Relia, Vice President, Regulatory and Quality Affairs

1099 18th St Suite 2860, Denver CO 80202


Automated radiological image processing software

Medical image management and processing system.


ChristopheGardella
ChiefTechnicalOfficer
Tel.+003669650566
Email.christophe@brightheart.fr


Radiologicalcomputer-assisteddiagnosticsoftwarefor
lesionssuspiciousfor cancer21CFR 892.2060


Fetalultrasoundstudycontaining
thefollowingviews:4chamber,left
ventricularoutflowtract,right
ventricularoutflowtract

Suspiciousradiographicfindings
categorizedinto2groups:
● “classification”featuresare
basedontheidentificationof
morphologicalfeatureswithin
thevideoclip.
● “measurement”featuresare
basedonthedetectionand
segmentationofkeyanatomic
points

Thesoftwareautomaticallyregisters
images,andsegmentsandanalyses
selectedregionsofinterest(ROI).
Geometricparametersarecalculated
fromtheapprovedcontoursandare
fedintoafixedclassificationmodel
thathasbeenpreviouslytrainedon
datasetswithknownoutcomes.The
outputofthemodelgeneratesa
reportwhichcontainsacategorical
assessmentastowhetherthedata
areconsistentwithsignificantCAD
ornot.

Identifiablesuspiciousradiographic
findingsofthefetalheart
● overridingartery
● septaldefectatthecardiaccrux
● abnormalrelationshipofthe
outflowtracts
● enlargedcardiothoracicratio
● rightventriculartoleft
ventricularsizediscrepancy
● tricuspidvalvetomitralvalve
annularsizediscrepancy
● pulmonaryvalvetoaorticvalve
annularsizediscrepancy
● cardiacaxisdeviation


Foreachframethesoftware
evaluateswhetherthefindingsare:
present,absent,orinconclusive.
A“recordsummarytable”displays
asummaryofresultsforeachvideo
clip.An“examsummarytable”
displaysasummaryoftheresultsfor
theoverallstudy.

Categoricalassessmentasto
whetherthedataaresuggestiveofa
higherorlowerpossibilityof
significantcoronaryarterydisease
ornot


Ultrasoundimage
processingsoftware
implementingartificial
intelligenceincluding
non-adaptivemachine
learningalgorithmstrained
withclinicaldataintended
fornon-invasiveanalysisof
ultrasounddata


DeepConvolutionalNeural
Networksfor
Segmentationor
LandmarkDetection

AnatomicalSites Heart Heart,Bladder Sameassubjectdevice


Manufacturer
Nexsys Electronics Inc. dba Medweb

Regulation Name
System, Image Processing, Radiological


Feature
Lightning Viewer
OmegaAI Image Viewer
Comments

Lightning Viewer is
intended for diagnostic
purposes and to be used
as a review tool.

The OmegaAI Image Viewer
is intended for diagnostic
purposes and to be used as a
review tool.

Lossy image
compression should not
be used for primary
reading in
mammography.

Adjustment Tools:
Window level, rotate,
flip, pan, stack scroll, and
zoom.
Markup Tools:
Annotate, angle, cobb
angle, probe, Mark ROI,
and measurement.


The subject device has specialized tools for
specific use cases, such as spine labeling
and mammography tools. These tools fall
under the same general intended use to
review and navigate diagnostic images and
aiding users in visualizing a region of
interest. Thus, the inclusion of these
specialized tools do not raise any new
questions of safety and effectiveness.

Supports the following
image modalities
CR/DR/XR, CT, FL, MR,
MG, NM, US/US Echo,
PET and VL.

View all image modalities,
including CR, CT, DX, MR,
MG, NM, US, PET, RG, SC,
VL, XA, PET, and Film
Digitizer.

Both devices support a wide range of image
modalities, including CR, CT, MR, MG,
NM, US, PET, and VL. The predicate
device supports additional modalities like
DX, RG, SC, XA, and Film Digitizer. This
difference does not raise any new questions
of safety or effectiveness. The additional
modalities supported by the predicate device
do not impact the safety or effectiveness of
Lightning Viewer for its intended use cases.

A web-based software
solution that displays
images and reports from a
PACS through a zero-
footprint application
accessible via a web
browser, requiring no
installation.

Server-based software
solution that displays images
and reports from a PACS
using a zero-footprint
application (browser).
No installation is needed.

Both devices are zero-footprint and require
no installation. The subject device is web-
based, while the predicate device is server-
based. The architectural difference does not
impact the core functionality, safety, or
effectiveness of either device. Both
architectures are commonly used in medical
imaging and have established safety and
performance profiles.

Use of various
technology standards like
DICOM, DICOMweb,
WADO, Rest, HL7.

Use of various technology
standards (LDAP, SSO,
HTTPS, HTML, HL-7
Integration web services,
etc.)

Both devices utilize industry-standard
technologies for communication and data
exchange (DICOM, HL7). Each device uses
a different set of additional technologies to
support its architecture and features (e.g.,
web-based vs. server-based). These
differences do not impact the safety or
effectiveness of the devices. The different
technologies used by the devices are all
industry-standard and well-established for
their respective purposes (security,
communication, data exchange).

Supports major browsers
like Chrome and Safari.

Supports major desktop (for
diagnostic purposes) and
mobile platforms (for non-
diagnostic purposes; can be
used as a review tool) such as
Microsoft Edge, Chrome,

The predicate device supports a wider range
of platforms, including desktop and mobile
operating systems. Lightning Viewer is
designed as a web-based application and
relies on the browser's capabilities for
compatibility and rendering. This difference


Feature
Lightning Viewer
OmegaAI Image Viewer
Comments

Safari, Apple iOS, Android,
Windows and Mac devices.

does not raise new questions of safety or
effectiveness.


Primary
Predicate Device
Aquilion ONE (TSX-
308A/3) V1.4 with
PIQE Reconstruction
System

JAK:
System, X-ray,
Tomography,
Computed

Reference
Predicate Device
Aquilion ONE (TSX-
306A/3) V10.12 with
Spectral Imaging
System


Device Name,
Aquilion ONE (TSX-308A/3) V1.5
Aquilion ONE (TSX-308A/3) V1.5
Aquilion ONE (TSX-308A/3) V1.4

Model Number
with PIQE Reconstruction System

PIQE Reconstruction
System (CRRS-001A)
▪ Scan Regions
▪ Scan Type

Available
▪ Cardiac, Lung, Abdomen and pelvis
(Body)
▪ Volume scan, Dynamic volume scan,
Helical scan

Available
▪ Cardiac, Abdomen and pelvis (Body)
▪ Volume scan, Dynamic volume scan,
Helical scan

3D Landmark Scan
Available X-ray tube voltage: 120kV
Available X-ray tube voltage: 120/135kV

Option:
BODY, LUNG, BONE and CARDIAC
(Cardiac previously cleared under
K213504)

Motion Correction
Advanced Patient
Motion Correction
(APMC)
CLEAR Motion
(CSCM-001A)

Available
(Previously cleared under K213504)

and the predicate device is included below.


Common Name
Computer-Assisted Detection Device

Classification Name
Medical Image Analyzer

Primary Regulation Number
21 CFR 892.2070


Predicate Device Name
Overjet Caries Assist


Predicate Device Name
Overjet Dental Assist


Predicate
Device: Overjet
Caries Assist
(K212519)

Reference Device:
Second Opinion
(K210365)

Reference
Device: Overjet
Dental Assist
(K210187)

Manufacturer
Cube Click, Inc.
Overjet, Inc.
Pearl Inc.
Overjet, Inc.

Smile Dx® falls
under the same
regulation
(892.2070) as
primary predicate
(Overjet Caries
Assist).

Picture archiving
and
communications
system

Smile Dx® falls
under the same
regulation
(892.2070) as
predicate (Overjet
Caries Assist).

Smile Dx® has the
same primary
product MYN as
predicate (Overjet
Caries Assist) and
reference device

For technological characteristics comparison, the following table is provided:


(Second Opinion).
Additionally, Smile
Dx®’s secondary
product code LLZ is
the same as reference
device (Overjet
Dental Assist). Thus,
the subject device
has the same product
codes as the
identified predicate
and reference
devices.

Smile Dx® is a
computer-assisted
detection (CADe)
software designed
to aid dentists in
the review of
digital files of
bitewing and
periapical
radiographs of
permanent teeth.
It is intended to
aid in the
detection and
segmentation of
suspected dental
findings which
include: caries,
periapical
radiolucencies
(PARL),
restorations, and
dental anatomy.
Smile Dx® is
also intended to
aid dentists in the
measurement (in
millimeter and
percentage
measurements) of
mesial and distal
bone levels
associated with

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

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

Overjet Dental
Assist is a
radiological semi-
automated image
processing
software device
intended to aid
dental
professionals in
the measurements
of mesial and
distal bone levels
associated with
each tooth from
bitewing and
periapical
radiographs.
It should not be
used in-lieu of full
patient evaluation
or solely relied
upon to make or
confirm a
diagnosis. The
system is to be
used by trained
professionals
including, but not
limited to, dentists
and dental
hygienists.
Intended Patient
Population:

Smile Dx® has
similar indications
for use to predicate
K212519 for
detecting caries,
reference device
K210365 for
detecting PARLs,
and reference device
K210187 for
measurement of bone
levels. Thus, the
subject device
combines the
indications for use of
the three identified
predicate and
reference devices.
All three devices
share the same
intended use to
identify suspected
areas of interest in
intra-oral
radiographs.


each tooth.
The device is not
intended as a
replacement for a
complete dentist's
review or their
clinical judgment
that takes into
account other
relevant
information from
the image, patient
history, and
actual in vivo
clinical
assessment.
Smile Dx®
supports both
digital and
phosphor sensors.

The intended
patient population
of the device is
patients living in
the United States,
who are 22 years
old or older, and
that do not have
any remaining
primary teeth.
Overjet has not
evaluated the
performance of
the device on
primary dentition.

• Normal
anatomy
• Caries
• Periapical
radiolucencies
• Bone level
measurements
(mesial and
distal)
• Restorations

Caries, Margin
discrepancy,
Calculus,
Periapical
radiolucencies,
Restorations

Smile Dx® detects
caries similar to
predicate Overjet
Caries Assist
K212519.
Smile Dx® also
detects PARLs and
restorations, similar
to reference device
Second Opinion
K210365. Second
Opinion also detects
other features such as
margin discrepancy
and calculus,
however, these are
not supported by
subject device. The
absence of these
features in Smile
Dx® does not create
a new intended use.
Smile Dx® also
measures mesial and
distal bone levels,
same as reference
device Overjet


Predicate
Device: Overjet
Caries Assist
(K212519)

Reference Device:
Second Opinion
(K210365)

Reference
Device: Overjet
Dental Assist
(K210187)

Dental
professionals
including, but not
limited to, dentists
and dental
hygienists.

Smile Dx® is
intended for use by
licensed dentists,
same as all of the
identified predicate
and reference
devices. The
reference device
Overjet Dental Assist
is also intended for
use by other dental
professionals, such
as dental hygienists.
However, use of
Smile Dx® has been
limited to use by
licensed dentists
only.

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

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

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

The intended patient
population for Smile
Dx® is limited to
patients with
permanent dentition
who are at least 22
years of age. This is
identical to the
reference device
Second Opinion.
This intended patient
population age has
been supported by
use of representative
patient data in
testing.

Rx or OTC
Rx-only
Rx-only
Rx-only
Rx-only
Same

Local computer
application
(Cloud-based
installation)

The subject device is
a web-based
application, similar
to Overjet Caries
Assist and Overjet


Dental Assist. It is
compatible with
similar browsers and
is also compatible
with Safari, which is
a commonly used
browser.

The subject device is
compatible with any
operating system,
same as predicate
Overjet Caries Assist
and reference device
Overjet Dental
Assist.

Images imported
from local
computer, from a
range of
manufacturers

Images imported
from the
radiographic
device, or from
the practice
management
system, from
Carestream or
Schick sensors

Radiography
devices from a
range of
manufacturers

Images are manually
imported from the
dentist user’s local
computer into Smile
Dx®. The subject
device does not
connect to practice
management systems
like Overjet Caries
Assist and Overjet
Dental Assist.
However, this
difference does not
raise any new
questions of safety
and effectiveness.
Additionally, Smile
Dx® is compatible
with images from a
range of radiography
device


Predicate
Device: Overjet
Caries Assist
(K212519)

Reference Device:
Second Opinion
(K210365)

Reference
Device: Overjet
Dental Assist
(K210187)

user interface.
The dentist can
adjust image
settings, display
and hide the
presented
annotations.

display, hide,
create and edit
the annotations
presented.

displays it within
its user interface.
Detected features
are highlighted
with color-coded
boundary boxes
overlaid on the
original
radiograph.

device exclusively
uploads images from
the local computer.
Similarly, users of
Smile Dx® are
required to manually
upload images to the
software, whereas
the reference device
Second Opinion
automatically
uploads images.
Nevertheless, these
technological
differences do not
raise new questions
of safety and
effectiveness. The
absence of these
features in the
subject device does
not impede its ability
to fulfill its intended
use.

Utilizes computer
vision machine
learning
algorithm(s).

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

Same. Smile Dx®
utilizes computer
vision techniques,
specifically, machine
learning algorithms
to detect suspected
findings, same as the
identified predicate
and reference
devices.

Suspected
findings (i.e.,
caries, PARLs)
and
measurements
(bone levels) are
overlaid on the
original
radiograph

Caries detection
and segmentation
on radiograph
resulting in
outline of
suspected caries

Detected features
(e.g., caries,
PARLs) are
highlighted with
color-coded
boundary boxes
overlaid on the
original radiograph

The output of Smile
Dx® is similar to the
outputs of all of the
identified predicate
and reference
devices, as they all
overlay the findings
on the original
radiograph.

Contour
segmentations for
caries and
periapical

Presents
suspected carious
lesions as
segmented

The subject device
has similar marker
types to its predicate
and reference


Predicate
Device: Overjet
Caries Assist
(K212519)

Reference Device:
Second Opinion
(K210365)

Reference
Device: Overjet
Dental Assist
(K210187)

radiolucencies.
Color-coded lines
for bone levels

devices.
For suspected caries,
the subject device
creates a contour of
the suspected caries,
similar to the
predicate (Overjet
Caries Assist).
For periapical
radiolucencies, the
subject device
creates countours.
This is different to
reference device’s
(Second Opinion)
bounding boxes. The
performance and
accuracy of the
segmentations has
been supported with
appropriate
performance testing.
For bone levels, the
subject device
outputs color-coded
lines depending on
the level of measured
boneloss, similar to
reference device
Overjet Dental
Assist.

Smile Dx® is similar
to reference device
Overjet Dental Assist
in that it creates a
linear distance for
measured bone
levels.

Image Viewing
Full, Thumbnail
Full, Thumbnail
Full, Thumbnail
Full, Thumbnail
Same

Image adjustment
tools (e.g.,
brightness,
contrast, opacity,

Smile Dx® has
similar image
adjustment tools as
reference devie
Second Opinion


(e.g., contrast and
brightness). Smile
Dx® introduces a
new tool (i.e.,
opacity adjustment),
however, this does
not raise any new
questions of safety
and effectiveness and
is a common image
adjustment tool.
Smile Dx® lacks
some of the features
found in the
predicate and
reference devices
(e.g., zoom, invert,
and manual
annotation tools).
However, these tools
are not needed to
accomplish the
intended use of the
device and do not
raise new questions
of safety and
effectiveness.

• Standalone
performance
study for
pathologic feature
(i.e., caries and
periapical
radiolucency)
detection, non-
pathologic feature
detection (i.e.,
normal anatomy
and restorations)
and bone level
measurement
performance.
• Multiple-
Reader,
Multiple-Case
(MRMC) study
for pathologic
dental features

• Standalone
study for
pathologic
feature detection
performance.
• Multiple-
Reader,
Multiple-Case
(MRMC) study
for pathologic
dental features
• Analysis
included:
• Sensitivity and
specificity
evaluations
• Dice coefficient
analysis

• Standalone study
for
pathological
and non-
pathologic
feature detection
performance.
• Multiple-Reader,
Multiple-Case
(MRMC) study for
pathologic dental
features
• Analysis
included:
• wAFROC-FOM
analysis for
primary endpoints
•Determination of
the changes in
sensitivity and
change in number

• Bench testing
evaluated
precision and
recall against
labeled keypoints
within
radiographs.
• Retrospective
clinical
performance
testing that
compared
adjudicated
measurements
against Overjet
Dental Assist’s
predicted
measurements.
Analysis included

Smile Dx®
underwent similar
evaluations as
predicate and
reference devices,
following
recommendations in
2022 FDA Guidance
“Computer-Assisted
Detection Devices
Applied to Radiology
Images and
Radiology Device
Data - Premarket
Notification [510(k)]
Submissions”.


• Analysis
included:
• wAFROC
analysis for
primary endpoint
• Sensitivity and
specificity
evaluations

of false positive
dental pathologies
of a given type per
image (FPPI)


Bone Loss Measurement (Mean Absolute
Error [95% CI]

a test dataset of 352 cases collected from multiple U.S. sites. The test results were as follows:


test dataset of 200 cases collected from different U.S. sites. The test results were as follows:


specificity, thereby meeting the acceptance criteria for effective detection of caries and PARLs.


Software
CrystalVue Flow
Not Supported
Supported

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


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

IEC60601-1-2: 2020-09(4.1 Edition) , Medical electrical
equipment - Part 1-2: General requirements for basic safety and
essential performance - EMC

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

IEC TR 60601-4-2 Edition 1.0 2016-05, Medical electrical
equipment - Part 4-2: Guidance and interpretation -
Electromagnetic immunity: performance of medical electrical
equipment and medical electrical systems

AAMI / ANSI / ISO 10993-1:2018/(R)2013, Biological evaluation


of medical devices – Part 1: Evaluation and testing within a risk
management process

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

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

HERA W9/ HERA W10 Diagnostic Ultrasound Systems


Pre-determined criteria were utilized in validation tests to assess whether remote viewing and

reviewing with SonoSync matched the performance of local ultrasound systems.

Labeling materials is provided to inform users about the necessary specifications for safely and

effectively conducting remote diagnostic reviews and viewing.

the ones during training process and there is no overlap between the three.


Predicate Device (K182643) -
Segmentation Software Application as
part of IRIS 1.0 System

Intended use for providing tools for image analysis
and segmentation of kidney CT images.
The IRIS 1.0 System is intended as a medical
imaging system that allows the processing, review,
analysis, communication, and media interchange
of multi-dimensional digital images acquired from
CT imaging devices. It is also intended as software
for preoperative surgical planning, and as
software for the intraoperative display of the
aforementioned multi-dimensional digital images.
The IRIS 1.0 System Is designed for use by health
care professionals and is intended to assist the
clinician who is responsible for making all final
patient management decisions.

DIFFERENCE in Indications for use:
The machine learning enabled kidney CT
auto-segmentation tool is intended for use
for adult patients with contrast-enhanced,
axial kidney CT images with slice thickness
3mm or less.
IRISeg is intended for use by qualified
professionals.

Comparison of Indications for Use and intended Use


Description
Predicate Device (K182643) -
Subject Device

IRISeg as part of IRIS 1.0 System
IRISeg

Regulation Number
21 CFR §892.2050
21 CFR §892.2050

Product Code
Primary: LLZ
Primary: QIH; Associate: LLZ

Intended population
Adult patients
Adult patients

Intended Users
Healthcare Professionals
Qualified Professionals

The output file can be used to
render a 3D model for
preoperative surgical planning
and intraoperative display.
The output file is meant for
visual, non-diagnostic use and
shall be reviewed by clinicians
who are responsible for all final
patient management decisions.

Manual segmentation alone
Auto-segmentation followed by
manual segmentation.

Graphical user interface design.
Office setting (Segmentation
Software Application running on
a general-purpose computer)

DICOM-Compliant CT scans
Axial views, contrast enhanced

Segmentation files that can be
used to render a 3D model for
preoperative surgical planning
and intraoperative display

5 Kidney CT structures:
Parenchyma, Artery, Vein,
Collecting System and Mass

4 Kidney CT structures:
Parenchyma, Artery, Vein and
Collecting System


Various segmentation and
selection tools for manual
segmentation.

Volume rendering, 3D model
visualization, 2D slice
visualization.


Test Case
Artery DSC
Parenchyma DSC
Vein DSC
Collecting System


Software
Device is software only
Device is software only
Same

Documentation is similar
and differences are due to
updated FDA guidance.

Fibresolve is a software‐only device
that receives and analyzes lung
computed tomography (CT) imaging
data in order to provide a diagnostic
subtype classification in suspected
cases of interstitial lung disease
(ILD). The device supplements the
standard-of‐care workflow by
providing a qualitative, diagnostic
classification output of imaging
findings based on machine learning
pattern recognition, in order to
provide adjunctive information as
part of a referral pathway to an
appropriate Multidisciplinary
Discussion (MDD) or as part of an
MDD. Specifically, the tool is used
to serve as an adjunct in the
diagnosis of idiopathic pulmonary
fibrosis (IPF) prior to invasive
testing. The results of Fibresolve are
intended to be used only by
clinicians qualified in the care of
lung disease, specifically in caring
for patients with ILD, in conjunction
with the patient’s clinical history,
symptoms, and other diagnostic
tests, as well as the clinician’s
professional judgment.
The input to Fibresolve is a DICOM‐
compliant lung CT scan. Clinical
case eligibility includes the
following criteria:
Age > 22 years old.
Pulmonary symptoms suggestive of
possible ILD including IPF.

Imbio IQ-UIP is a computer-aided
software indicated for use in
passively notifying specialists
associated with interstitial lung
disease (ILD) centers of
radiological findings suggestive of
radiological usual interstitial
pneumonia (UIP) in non-contrast,
chest CT scans of adults. Imbio IQ-
UIP uses an artificial intelligence
algorithm to analyze images and
identify positive findings on a
worklist application separate from
and in parallel to the standard of
care radiological image
interpretation. Identification of
positive findings include summary
reports with a clinical guideline
reference for the definition of UIP
pattern that are meant for
informational purposes only. The
device does not alter the original
medical image and is not intended
to be used as a diagnostic device.
The results of Imbio IQ-UIP are
used to notify specialists at an ILD
center of radiological findings that
may be consistent with UIP. These
specialists are qualified clinicians
experienced in evaluating chest
CTs for ILD. Input images originate
from within the same hospital
network associated with the ILD
center. The results of Imbio IQ-UIP
are intended to be used in
conjunction with additional patient
information and based on the
user's professional judgment, to
assist with the review of medical

Similarities
• Referral software for
findings suggestive of
a pre-specified
clinical fibrotic lung
condition
• Uses artificial
intelligence to
analyze chest/lung CT
images
• Used by clinicians
qualified in the care
of lung disease
• Operates in parallel to
standard of care
workflow
• Provide qualitative
diagnostic subtype
classification for
cases suspected of
interstitial lung
disease
• 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


images. Notified clinicians are
responsible for viewing full image
series and making final clinical
determinations.

Differences:
• IQ-UIP reports
viewable on
dedicated worklist
application separate
from standard-of-
care.

The device supports referral of
findings related to fibrotic lung
diseases using machine learning,
artificial intelligence or other
image analysis algorithms.

The device operates on
radiological images of the
human body.

Anatomical Site
Lung/Chest
Lung/Chest
Same

Clinicians qualified in care of lung
disease

Adults > 22 years old and with
pulmonary symptoms suggestive of
possible ILD including IPF.

Similarities:
• Adults > 22 years old
Differences:
• Fibresolve’s patient
population is limited
to those adults with
pulmonary symptoms
suggestive of possible
ILD including IPF.
• IQ-UIP patient
population would
include the same
patient population as
those indicated for
Fibresolve but may
also include others
who have undergone a
chest CT for other
symptoms.

Does not communicate images
to patients.


Referral report viewable on
dedicated worklist application
accessible by the intended users.

IQ-UIP reports viewable on
dedicated worklist
application separate from
standard-of-care.


Data Bin
Datasets
Percentage of Total (%)

Native Hawaiian or Other Pacific Islander

Demographic data are presented in the following table.


Company Name:
Omega Medical Imaging, LLC

Address:
3400 St. Johns Parkway, Suite
1020,

Contact person:
Matthew Anderson, Director RA
/QA

Common/usual name:
Fluoroscopic/Radiographic X-ra
y sys

Classification Name:
Image-intensified Fluoroscopic
X-ray


K212336 (Predicate Device)
Soteria.AI, Model AI-100

K242488 (This Submission)
Soteria E-View, Model GI-100

The Omega Medical Imaging, LLC AI-100,
Soteria.AI (SSXI) systems with FluoroShield / CA-
100S device to provide an automated Region of
interest that reduces exposure to the patient and
operator. The System is intended for use in
Radiographic/fluoroscopic applications, including
cardiac, vascular, general
radiographic/fluoroscopic diagnostic, and
interventional x-ray imaging for General and
Pediatric Populations.

FluoroShield / CA-100S device to provide an

Image-intensified Fluoroscopic X-ray system

Classification
JAA, OWB
JAA, OWB
JAA, OWB
JAA, OWB


510(k) Cleared (Predicate
This Submission Soteria E-View

Detector Name:
Teledyne Dalsa Xineos-3030HS
Varex Azure 3131Z CXP Detector

1.1 Receptor Type
CMOS
IGZO (indium gallium zinc oxide)

1.2 Conversion Screen
Cesium Iodide
Cesium Iodide

1.3 Pixel Area – Active
29.6 cm x 29.6 cm
30.7 cm x 30.7 cm

1.4 Pixel Matrix – Active
1952 x 1952
2048 x 2048

1.6 Limiting Resolution
3.15 lp/mm
3.3 lp/mm


4. Reference Monitor Identifiers [Review Station]

5. Live Monitor Identifiers [Image Area]

5.9 Series/Image
Only Image Number
Only Image Number

5.11 Radiation Symbol
Radiation symbol during Live
Radiation symbol during Live


e.g., FL LIH, FL Loops, Spot
Replay, or Cine Replay

5.13 Detector Status
Ready/Not Ready
Ready/Not Ready

5.14 Magnification Mode
Normal, MAG 1, MAG 2
Normal, MAG 1, MAG 2

GUI [Graphic User Interface on Reference Monitor]

5.18 Close
Closes active patient
Closes active patient

5.19 NR Hi / NR Lo
Selects Noise Reduction Level
Selects Noise Reduction Level

Pulse Rates: [14 f/s default,
7.5, & 3.75 f/s]

Pulse Rates: [12.5 f/s default,
6, & 3 f/s]

Note: Image Orientation available for Acquisition Mode [from Review]

5.23 Win./Lev.
Window/Level adjustment
Window/Level adjustment

Toggles image between the
Reference and Live monitors

5.26 Zoom
Up to 2X zoom with panning
Up to 2X zoom with panning

5.28 Collimate
Invokes electronic shutters
Invokes electronic shutters


Sends image to a Windows®
compatible printer (No)

Invokes the Annotation and
Measurement function

C-ARM Specifications:
510(k) Cleared (Predicate
This Submission Soteria E-View.AI

Collimator - Longitude
Opens to full field, closes fully
Opens to full field, closes fully

Opens to full field, closes fully
(vascular), closes to mid field
(lung)

Fluoro Enable
Enables/disables Fluoro function
Enables/disables Fluoro function

Resets 5-minute alarm on high
voltage generator

Disables motion actuators and
high voltage generator

Selects field sizes: Normal, Mag
1, and Mag 2


Requests active control is 2
controllers are installed

Cardio filter select
Lung or vascular
No

DAP meter reset
Resets DAP meter outputs to 0
Resets DAP meter outputs to 0

Selects none, 0.1, 0.2, or 0.3 mm
Cu filters

Parking Control
Controls parking actuator
No

Fluoro
Enables X-ray fluoro
Enables X-ray fluoro

Fluoro loops
Enables X-ray fluoro loops
Enables X-ray fluoro loops

System Digital Display
Miscellaneous System Status
Miscellaneous System Status

Collision Sensing on FPD
Bump stop.
Bump stop.

Minimum value = 3.6 mm Al
equiv. @ 100 kV
Maximum value = 4.0 mm Al
Equiv. @ 100 kV

Dose Calibration: Maximum
Input Dose Rate

Dose Calibration: Flat Panel
Input Dose rate

Generator Function: Pulsed
Fluoro Function

Image Quality: Resolution
Up to 3.15 lp/mm
Up to 3.15 lp/mm


510(k) Cleared (Predicate
Device) K212336

Unlocks table rotate, latitude
and longitude.

Table Trendelenburg
± 15°, ± 1°
± 12°, ± 1°

Table cradle (LAO/RAO)
± 15°, ± 1°
± 12°, ± 1°

Focal Spot sizes
0.6 - 1.0 mm
0.6 – 1.2mm

H.V. Generator
510(k) Cleared (Predicate
This Submission Soteria E-View

EMD Technologies EPS High
Voltage Generator series

mA range:
Min: 5mA to Max: 1000mA
Min: 5mA to Max: 1000mA


This summary of 510(k) is being submitted in accordance with the requirements of 21 CFR 807.92.


Subject Device
Predicate Device
Comparison

Similar, the subject
device implements
artificial intelligence
including nonadaptive


Medical image management and
processing system

Regulation Number
21 CFR § 892.2050
21 CFR § 892.2050
Same.

LARALAB is a software application that
is intended to provide cardiologists,
radiologists, heart surgeons and
healthcare professionals additional
information to aid them in reading and
interpreting DICOM compliant medical
images of structures of the heart and
vessels.
LARALAB enables the user to make:
- Visualizations, assessments
and measurements (e.g.,
diameters, lengths, areas,
volumes, angles) of
structures of the heart and
vessels, including such
vascular structures relevant
as access routes in the
context of cardiovascular
procedures.

3mensio Workstation is a software
solution that is intended to provide
cardiologists, radiologists and clinical
specialists additional information to
aid them in reading and interpreting
DICOM compliant medical images of
structures of the heart and vessels.
3mensio Structural Heart enables the
user to:
- Visualize and measure
(diameters, lengths, areas,
volumes, angles) structures
of the heart and vessels
- Quantify calcium (volume,
density)
3mensio Vascular enables the
user to:
- Visualize and assess
stenosis, aneurysms and
vascular structures
- Measure the dimensions
of vessels (diameters,
lengths, areas, volumes,
angles)

While minor textual
differences exist, the
intended uses of the two
devices are otherwise the
same.

The LARALAB software enables
visualization, assessment and
measurement of cardiovascular
structures for:
- Preprocedural planning and
sizing for cardiovascular
interventions and surgery
- Postprocedural image
review
To facilitate the above, LARALAB
provides general functionality such as:
- Automatic segmentation of
cardiovascular structures
and other objects of interest
(calcifications)
- Automatic measurements
- Manual measurement and
adjustment tools
- Visualization and image

3mensio Workstation enables
visualization and measurement of
structures of the heart and vessels
for:
- Pre-operational planning
and sizing for
cardiovascular
interventions and surgery
- Postoperative evaluation
- Support of clinical
diagnosis by quantifying
dimensions in coronary
arteries
- Support of clinical
diagnosis by quantifying
calcified plaques (calcium
scoring) in the coronary
arteries
To facilitate the above, the 3mensio
Workstation provides general
functionality such as:
- Segmentation of
cardiovascular structures
- Automatic and manual
centerline detection
- Visualization and image
reconstruction
techniques: 2D review,
Volume Rendering, MPR,

Substantially the same.
Both devices are indicated
for use in preprocedural
planning and
postprocedural
assessment of structural
heart interventions.
The predicate device also
supports clinical diagnosis
by quantifying
calcifications and
quantifying dimensions in
coronary arteries. In order
to provide these functions,
the predicate device
supports a wider range of
viewing functionality (e.g.,
volume rendering and
other general visualization
and image reconstruction
techniques) than the
subject device.
The additional quantifying
function for the evaluation
of calcifications and
coronary artery
dimensions and additional
general visualization and
image reconstruction
techniques are not


reconstruction techniques:
Multiplanar Reconstruction
(MPR), Surface rendering, 4D
views
- Reporting tools

Curved MPR, Stretched
CMRP, Slabbing, MWP,
ALP, MiniP
- Measurement and
annotation tools
- Reporting tools

necessary for the subject
device to perform as
intended and not including
those functions does not
impact the performance of
the subject device or the
ability to use the subject
device as intended.

Cloud based. The LARALAB software
includes cloud-based and related
cybersecurity functionality for cloud-
based devices, including:
- User authentication
- Data encryption
(HTTPS/SSL) in transit and at
rest
- Encrypted data storage
- Third party cloud services
compliant with security
standards

Traditional client install. 3mensio is a
traditional software package, to be
installed on a specific computer.

Although the subject
device is cloud-based and
the predicate device is a
traditional software
package that needs to be
installed on a specific
computer, this difference
in application access does
not impact the intended
use or the performance of
the device, which remain
substantially equivalent.
Any risks related to
accessing the application
in the cloud that do not
exist for a specific
computer installation are
fully mitigated by the
cybersecurity functionality
of the subject device.
Therefore, these minor
differences do not raise
different questions of
safety or effectiveness.

- Import from local device
- Import from PACS

Both devices offer similar
import/upload functions.
The limited difference is
due to the cloud-based
nature of the subject
device, which requires that
patient data be uploaded,
as opposed to directly
importing data from a
PACS system, into the local
predicate device.

- CT data in DICOM format
(vendor independent)
- Upload DICOM files

- CT data in DICOM format
(vendor independent)
- Import DICOM files
- DICOM compliance for
CT, Ultrasound images

Similar. Predicate device
offer additional
functionality for ultrasound
images.

- Data de-identification before
upload (Protected Health
Information (PHI) can
completely be removed and
does not leave the client or
hospital)

Data privacy is effectively
the same between the
subject and predicate
devices. For both devices
patient data is de-
identified and no protected
health information leaves
the facility (either because
it is removed before the
data is uploaded, as in the
subject device, or because


the data remains on site, as
in the predicate device).

- Study list overview
- Deleting
- Search
- Sorting
- Export

Automatic processing generating:
- Volumetric segmentations of
cardiovascular structures
based on deterministic Deep
Learning algorithms
- Measurements (e.g. splines,
distances, angulation,
volumes)
- Assessments containing
Automatic Pre-calculated
views

Automatic segmentation toolset:
- Automatic segmentations
- Automatic centerline

Both devices include
automated segmentation
functionality and both
devices include the option
for the physician to review
the segmentation. There
are slight differences
between the underlying
automatic analysis
concepts between the
devices. Specifically, the
subject device provides
the user with pre-
calculated
segmentations/measurem
ents/assessments, which
the user can
review/adjust/approve.
Alternatively, the predicate
device includes automated
and manual steps.
However, in both cases,
the type of information
outputted by the device is
identical.

- Length measurement
- Spline/diameter
measurement
- Angle Measurement
- Volume measurements
- Zoom / Pan / Rotation /
Windowing tools
- Markers / Annotation tool
- C-arm angulation calculation

- Length measurement
- Spline/diameter
measurement
- Angle measurement
- Volume measurements
- Zoom / Pan / Rotation /
Windowing tools
- Markers / Annotation tool
- C-Arm angulation
calculation
Additional tools for vascular
assessment:
- Calcium scoring for
assessment of calcium in
the aortic root
- Calcium scoring for
assessment of calcium in
the coronary arteries
- Segmentation and analysis
of coronary artery tree
centerline

Similar. Predicate device
offers additional
functionality for coronary
artery assessment.

2D
- Multiplanar Reconstruction
(MPR)
- Coloured overlays (of
segmented objects)

2D
- Multiplanar
Reconstruction (MPR)
- Maximum intensity
projection (MIP)

Similar. Predicate device
offers additional
functionality for image
assessment.


- Minimum-intensity
projection (MinIP)
- AveIP
- Curved (CPR) cross-
curved, stretched Planar
Reformation
3D
- MIP volume rendering
- Color volume rendering
- Grayscale volume
rendering

- Case Planning results, incl.:
- Measurements
- Screenshots
- Assessments


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

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

ultrasound system and its applications comply with the following FDA-recognized standards.


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

IEC TR 60601-4-2 Edition 1.0 2016-05, Medical electrical equipment -
Part 4-2: Guidance and interpretation - Electromagnetic immunity:
performance of medical electrical equipment and medical electrical
systems

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

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

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


Primary Predicate
Second Opinion
K210365

Manufacturer
Pearl Inc.
Pearl Inc.
Overjet, Inc.

Dental CADe to aid in
dental radiograph review
by HCP

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


radiographs of permanent teeth
in patients 12 years of age or
older as a second reader.

from the image, patient history, or
actual in vivo clinical assessment.

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

Automated, concurrent-read,
CADe software that utilizes
machine learning

Detection of radiological dental
findings: 5 restorations
(crowns, bridges, implants, root
canals, fillings), 4 pathologies
(caries, margin discrepancy,
calculus, periapical
radiolucency) using bounding
boxes.

Detection and segmentation of
caries using polygons.

bitewing and periapical account other relevant information


Lesion size on abnormal images (percent of image pixels)

Table 2 - Summary of image characteristics.


syngo Dynamics VA41D
syngo Dynamics VA40F

syngo Dynamics is a multimodality, vendor
agnostic Cardiology image and information
system intended for medical image management
and processing that provides capabilities relating
to the review and digital processing of medical
images.
syngo Dynamics supports clinicians by providing
post image processing functions for image
manipulation, and/or quantification that are
intended for use in the interpretation and analysis
of medical images for disease detection,
diagnosis, and/or patient management within the
healthcare institution’s network.
syngo Dynamics is not intended to be used for
display or diagnosis of digital mammography
images in the U.S.

syngo Dynamics is a multimodality, vendor
agnostic Cardiology image and information
system intended for medical image management
and processing that provides capabilities relating
to the review and digital processing of medical
images.
syngo Dynamics supports clinicians by providing
post image processing functions for image
manipulation, and/or quantification that are
intended for use in the interpretation and analysis
of medical images for disease detection,
diagnosis, and/or patient management within the
healthcare institution’s network.
syngo Dynamics is not intended to be used for
displaying or diagnosis of digital mammography
images in the U.S.


Architecture Client-server Client-server Identical

• US
• XA
• DX
• CT
• MR
• SC
• NM
• PT
• ECG

• Standalone medical
device including a
DICOM Server
• Integrated model within
an Electronic Health
Record (EHR) System
with a DICOM Archive
• Multimodality
Cardiovascular
(MMCV) deployment
with native support of
2D/3D CT/MR image
types

Within the network, the
following communication
protocols are used:
• TCP/IP: for
communication and
transport
• DICOM and HL7 at
application level
• HTTP for
communication and
transport of images,
MP4s and thumbnails

Within the network, the
following communication
protocols are used:
• TCP/IP for
communication and
transport
• DICOM and HL7 at
application level
• HTTP(S) for
communication and
transport of images,
MP4s and thumbnails

Lossless compression with
compression factor 2 to 3
and lossy compression
(JPEG and MP4) with
higher compression rate.


• Window/Leveling
• Edge Enhancement
• Digital Subtraction
• Multiplanar
reconstruction (MPR)
• Maximum and
Minimum Intensity
Projection (MIP/MinIP)
• Volume Rendering
Technique (VRT)
• Gamma Correction
• Manual and semi-
automated calculation
for left ventricular
ejection fraction (Auto
EF, updated)

• Window/Leveling
• Edge Enhancement
• Digital Subtraction
• Multiplanar
reconstruction (MPR)
• Maximum and
Minimum Intensity
Projection (MIP/MinIP)
• Volume Rendering
Technique (VRT)
• Gamma Correction
• Manual and semi-
automated calculation
for left ventricular
ejection fraction (Auto
EF)

Enhanced. Rationale is
provided below this
table.

• Pixel Size Evaluation
• Distance line
• Angle
• volume

• Pixel Size Evaluation
• Distance line
• Angle
• Volume

Ability to interface with a
third-party rules engine
(BizTalk), where rules are
configured by the end
customer to determine
clinical relevance of
selected observations.
Customers identify and
store selected patient data.
Orchestrations provide a
trigger to pull in previously
stored relevant data for a
given study.

• Customizable DICOM
Structured Reporting
• Collaborative reporting
• Web reporting

• Customizable DICOM
Structured Reporting
• Collaborative reporting
• Remote reporting


syngo Dynamics VA41D
syngo Dynamics VA40F

Access
strategies for
imaging and
reporting

• Workplace (thick
client)- access for
reading and reporting.
• Remote Workplace
(MP4 image display
with access to full
DICOM image for
US/XA and full
DICOM image for
CT/MR) – access for
reading and reporting
• WebViewer – (Web
Client with MP4 Image
display) – Access for
review only

• Workplace (thick
client) – access for
reading and reporting.
• Remote Workplace
(MP4 image display
with access to full
DICOM image for
US/XA and full
DICOM image for
CT/MR) – access for
reading and reporting.
• WebViewer- (Web
Client with MP4 Image
display) – Access for
review only

Yes –Through the Common
Login and Web Viewer,
images can be viewed on
mobile devices,
WebViewer, supports iOS
and Android devices, but
are non-diagnostic use.

Provide long term archive
and retrieve of DICOM
studies to/from either VNA
(Vendor Neutral Archive)
or HSM (Hierarchical
Storage Management)
archiving Systems.

Software-only option for
server Workstation:
software only (HW is not
part of the medical device,
but needs to meet
recommended requirements
as specified by syngo
Dynamics)

Provides virtualization of
server and client machines


Server:
Microsoft Windows server
2016 Standard edition (64
bit)
Microsoft Windows Server
2019 Standard Edition (64
Bit)
Client Software: Microsoft
Windows 10 x64 version
1803 or greater
Portal Website Host:
Microsoft Windows Server
2016 Standard edition (64-
bit), Microsoft Windows
Server 2019 Standard
edition (64-bit)

• The use of syngo
Dynamics VA41D
server/workplace in the
context of
cardiovascular
configuration.
• EHR/EHS Integrated
configuration with
syngo Dynamics server.
• Multi-modality
cardiovascular
configuration with
native/syngo server and
syngo Dynamics
workplace with
native/syngo
components.

• The use of syngo
Dynamics VA40F
server/workplace in the
context of
cardiovascular
configuration.
• EHR/EHS Integrated
configuration with
syngo Dynamics server.
• Multi-modality
cardiovascular
configuration with
native/syngo server and
syngo Dynamics
workplace with
native/syngo
components.


Modification Group #1:
Re-training Auto EF ML-
DSF with additional data

Labeling will be updated in accordance
with the authorized PCCP to provide
users with current information regarding
the device’s re-training process and
performance capabilities

Modification Group #2:
Optimizations of the Auto
EF ML-DSF core
algorithms

Modification Group #3:
Auto EF ML-DSF with
contrast support

Performance testing will be
repeated using the same test
methods and acceptance criteria
as that used in syngo Dynamics
VA41D. Performance testing
will be expanded to include
contrast cases.

Labeling will be updated in accordance
with the authorized PCCP to provide
users with current information regarding
the device’s capabilities with expanded
input images including contrast.

Summary Predetermined Modifications for Auto EF


Applicant
DeepEcho
Sonio
Samsung Medison Co.

Biometry Assist feature in
the V8 ultrasound system

892.1550 - Accessory to
Ultrasonic Pulsed
Doppler Imaging
System
892.1560 - Accessory to
Ultrasonic Pulsed Echo
Imaging System
892.2050 - Medical
Image Management and
Processing System

892.1550 - Ultrasonic
Pulsed Doppler Imaging
System
892.1560 - Ultrasonic
Pulsed Echo Imaging
System
892.1570 - Diagnostic
Ultrasound Transducer

Qualified and trained
healthcare professionals
including radiologists,
obstetricians,
sonographers,
OB/GYNs, maternal
and fetal medicine
specialists (MFM
specialists), and fetal
surgeons

Qualified and trained
healthcare professionals in
a professional prenatal
ultrasound imaging
environment, including
sonographers, MFMs,
OB/GYNs, and fetal
surgeons

Appropriately trained
healthcare professionals
qualified for direct use of
medical devices

Pregnant patients aged
18 years and older,
from 14 to 41 weeks of
gestation

Pregnant patients across
Trimester 1, Trimester 2,
and Trimester 3, from 11
weeks to 37 weeks of
gestation

Table 1: Comparator Table for Subject and Predicate Devices


Cephalic view,
Abdominal view,
Femoral view

Transthalamic view,
Transventricular view,
Transcerebellar view, Four
chambers, Profile or
Nuchal translucency,
Crown rump length,
Sagittal spine, Abdominal
circumference, Long bone,
Upper lip, nose, and
nostrils, Left ventricular
outflow tract, Right
ventricular outflow tract

8 views recommended by
the ISUOG and AIUM for
biometric measurements
and heart assessment.

Femur Length (FL),
Abdominal
circumference (AC),
Amniotic Fluid
Pocket’s Depth, Head
circumference (HC),
Biparietal Diameter
(BPD) Estimated Fetal
Weight (EFW),
Estimated Gestational
Age (EGA)

Length measurement (FL,
BPD)
Ellipse measurement (AC,
HC)
Nuchal Translucency

Images labeled with
correct views, caliper
placement suggestion
and measurement for
circumference and
distance for metrics
such as HC, BPD, FL,
AC, and examination
reports

Images labeled with
correct views, quality
criteria identified as
"Verified" when detected
and "Not verified" when
not detected

Images labeled with correct
view
Caliper placement
suggestion and
measurement for
circumference, distance and
Nuchal Translucency
Editable examination report
accessible on the console

Provides real-time
identification of views
and suggestions for
caliper placement.

Primarily focused on
verifying the quality
criteria of detected views,
ensuring that all required
views are captured
according to standardized
protocols

Available on the Samsung
V8 for automated view
recognition and
measurement.


Artificial Intelligence
for biometric
measurement
computations

Artificial Intelligence for
lecture of biometrics and
colorimetry for 3D and
Doppler

Deep learning-based
recognition algorithm

Cloud-based standalone
software accessible
from various devices,
offering flexibility and
ease of integration into
different clinical
environments

A SaaS solution with edge
software requiring
installation on a server
connected to the
ultrasound machine


Point Estimate
95% CI
Point Estimate
95% CI

Table 2: Primary Endpoints #1 - #4 Results


Table 3: Primary Endpoints #5 and #6 Results


Table 5:
V
iew Identifica
tion Primary End
point by BMI
Subgroups and
Per Anato
mical
View


Manufacturer PearlInc. PearlInc. Overjet,Inc.

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


Second Opinion PC is a
computer aided detection
("CADe”) software to aid
dentists in the detection of
periapical radiolucencies
by drawing bounding
polygons to highlight the
suspected region of
interest.
It is designed to aid dental
health professionals to
review periapical
radiographs of permanent
teeth in patients 12 years
of age or older as a second
reader.

SecondOpinionisacomputer
aideddetection("CADe”)
softwaretoidentifyandmark
regionsinrelationtosuspected
dentalfindingswhichinclude
Caries,Discrepancyatthe
marginofanexisting
restoration,Calculus,Periapical
radiolucency,Crown(metal,
includingzirconia&non-metal),
Filling(metal&non-metal),
Rootcanal,Bridgeand
Implants.
Itisdesignedtoaiddental
healthprofessionalstoreview
bitewingandperiapical
radiographsofpermanentteeth
inpatients12yearsofageor
olderasasecondreader.

OverjetPeriapicalRadiolucency
(PARL)Assistisaradiological,
automated,concurrentread
computer-assisteddetection
softwareintendedtoaidinthe
detectionofperiapicalradiolucencies
onpermanentteethcapturedon
periapicalradiographs.Thedevice
providesadditionalaidforthedentist
touseintheiridentificationof
periapicalradiolucency.Thedevice
isnotintendedasareplacementfor
acompletedentist’sreviewortheir
clinicaljudgmentthatconsidersother
relevantinformationfromtheimage
orpatienthistory.Thesystemisto
beusedbyprofessionallytrained
andlicenseddentists.
TheOverjetPeriapicalRadiolucency
Assistsoftwareisindicatedforuse
onpatients12yearsofageorolder.

Utilizescomputervision
neuralnetworkalgorithms,
developedfrom
open-sourcemodelsusing
supervisedmachine
learningtechniques

Utilizescomputervisionneural
networkalgorithms,developed
fromopen-sourcemodels
usingsupervisedmachine
learningtechniques

Detectionofradiologicaldental
findings:5restorations
(crowns,bridges,implants,root
canals,fillings),4pathologies
(caries,margindiscrepancy,
calculus,periapical
radiolucency)usingbounding
boxes.


Automated Radiological Image Processing Software


510(k) Submitter/Holder
Smart Soft Healthcare AD

Medical image management and processing system


Applicant
ScanDiags AG
Smart Soft Healthcare AD

Device Name
ScanDiags Ortho L-Spine MR-Q
CoLumbo

Radiological images: MRI
(Standardized images used as input)

Study Type
(anatomical area
of interest)

• Lumbar spine vertebral body
area
• Lumbar spine intervertebral disc
area
• Foraminal area segmentation
• Spinal canal area
For all segmented areas the area in mm2
is calculated

• Vertebral body area
• Intervertebral disc area
• Foraminal stenosis clearance size
• Dural sac area and stenotic ratio

• Vertebral body heights (anterior,
middle, posterior)
• Vertebral body derived
measurements:
o Height ratios

• Vertebral body height (anterior,
middle, posterior)
• Disc height (anterior, middle,
posterior)
• Spinal canal anteroposterior
diameter

Spine MR-Q) to the predicate device (CoLumbo, K220497).


o Angle
o Biconcave height losses
• Intervertebral disc heights
(anterior, middle, posterior)
• Spinal canal anteroposterior and
mediolateral diameters

Report:
A Measurement Result PDF-report sent
back to the PACS, which is reviewed,
revised and approved by radiologist and
contains cropped versions of the original
MRI images, with an overlay on top of the
cropped images to highlight the
segmented anatomic structures and
applied measurements and tables
displaying quantitative data of the
anatomic areas of interest.

Report:
Export of measurement results to a written
report for user's review, revise and
approval.

The ScanDiags Ortho L-Spine MR-Q
Software is HIPAA Compliant by
preventing unauthorized access (only
authenticated and authorized users can
access DICOM data and preliminary
Measurement Results in built-in
ScanDiags DICOM Viewer), encrypting
data in transfer (both DICOM-TLS, SSL
certificates in use). The DICOM data
transferred to and processed by
ScanDiags Ortho L-Spine MR-Q Software
only temporarily stores the data until it is
either approved or rejected by the
intended user. The vulnerability
assessment and penetration testing
demonstrates satisfactory security
performance.

Smart Soft Healthcare conforms to the
cybersecurity requirements by
implementing a process of
preventing unauthorized access,
modifications, misuse or denial of use, or
the unauthorized use of
information that is stored, accessed or
transferred from a medical device to an
external recipient. The
vulnerability assessment and penetration
testing demonstrates satisfactory security
performance.

Patients aged ≥ 18 are considered to be
valid input.

Supervised Deep Convolutional Neural
Network (DCNN), both for classification
(image-to-class) to and segmentation
(image-to-image) model architectures

Deep Convolutional Image-to-Image
Neural Network


Mean intraclass correlation coefficient (ICC) of measurements (heights, diameters and areas) for

lumbar vertebrae, discs, neuroforamina and the thecal sac.

Intervertebral Disc
Area
0.92 [0.87 - 0.94]

Anteroposterior Diameter
0.92 [0.90 - 0.94]

Mediolateral Diameter
0.86 [0.83 - 0.88]

The device successfully passed the primary ICC acceptance criteria across all structures.


Table 8: Mean DICE scores for lumbar vertebrae, discs, neuroforamina and the thecal sac.

The device successfully passes the secondary DICE acceptance criteria across all structures.


Table 9: Mean absolute error (MAE) of measurements (heights, diameters and areas) for lumbar

vertebrae, discs, neuroforamina and the thecal sac.

The device successfully passes the co-secondary MAE acceptance criteria across all structures.


Intervertebral Disc
Anterior Height [mm]
1.1

Thecal Sac
Anteroposterior Diameter [mm]
0.81


Application
Function name
Proposed device
Predicate Device
Remark

Functional Substantially
Equivalent (Note 1)


Pulmonary lobes Segmentation
Yes
Yes
Same

Airway Tree Extraction and Editing
Yes
Yes
Same


Application
Function Name
Proposed device
Predicate Device
Remark

Brain Perfusion
Motion Correction
Yes
Yes
Same

Time-density curve analysis
Yes
Yes
Same

Symmetric ROI and ROI Template
Yes
Yes
Same


Cardiac function Assessment
Yes
Yes
Same


Calcium Scoring
Calcium sites segmentation
Yes
Yes
Same


Dynamic Analysis
Motion correction
Yes
Yes
Same

Data Loading and 3D/4D Display
Yes
Yes
Same


Liver Evaluation
Phase Selection
Yes
Yes
Same

Rib Segmentation and manual correction
Yes
Yes
Same

Vascular Territories Computation and
visualization


Dual Energy
Mono Energetic Image
Yes
Yes
Same

CNR(Contrast Noise Ratio) Image
Yes
Yes
Same

Base Material Images: Including Water-Iodine,
Water-Calcium, Calcium-Iodine, Uric acid-
Calcium, Water-HAP, Liver-Fat Base Material
Pair image.

Effective Atomic Number Images
 Component analysis of kidney stones,
uric acid stones or non-uric acid stones
 Component analysis of joint gout, uric
acid gout or non-uric acid gout

Virtual Non contrast Images
Yes
Yes
Same


Application
Function name
Proposed device
Predicate Device
Remark

Dental Application
Defining the Reference Plane
Yes
Yes
Same

Save, Report, Print(True size printing)
Yes
Yes
Same


Colon Segmentation and Centerline Calculate

Colon editing and Center Line editing
Yes
Yes
Same

Polyps’ Quantitative Calculation and Analysis


Functional Substantially
Equivalent (Note 1)

Vessel and centerlines Extraction
Yes
Yes
Same

Semi-automatic vessel extraction
Yes
Yes
Same

Vascular Measurement and vascular stenosis
analysis


Lung Nodule
Marking Nodules
Yes
Yes
Same

Measurement for the segmented nodule
Yes
Yes
Same


Vessel analysis:
 Bone removal
 Vessel and centerlines Extraction
 Semi-automatic vessel extraction
 Vascular Measurement and vascular -
stenosis analysis
 Hyper Realistic Rendering

Heart Analysis:
 Multi-Phase Loading
 Hyper Realistic Rendering
 Heart Chamber Segmentation
 Coronary Artery Extraction
 Editing Tools
 Centerline Extraction
 Stenosis Analysis
 Plaque Analysis
 Cardiac function Assessment

Fusion Review:
 The Combined Display of Heart and
Vessels tissue

TAVR Evaluation:
 Automatic Aortic annulus location and
manually correction
 Automatic Coronary ostia Location and
manually correction
 Multi-parameter Calculation


Functional
Substantially
Equivalent（Note 2）

Functional
Substantially
Equivalent（Note 3）

Functional
Substantially
Equivalent（Note 4）

Functional
Substantially
Equivalent（Note 5）


Validation Type
Algorithm
Acceptance Criteria


Anatomical variation
With anatomical variation
56

information of distribution was as follows:


Global performance (Dice Similarity Coefficient)


Subgroup
Distribution
Lung segmentation
Airway segmentation


Anatomical variation
With anatomical variation
28


Anatomical variation
With anatomical variation
53


Dice
Hepatic portal vein segmentation
0.89


Anatomical variation
With anatomical variation
50


Anatomical variation
With anatomical variation
51


Liver
Hepatic artery
Hepatic portal
Hepatic vein

Subgroup
Distribution
segmentati
segmentation
vein segmentation
segmentation


LunitInc.
4-8F,374,Gangnam-daero,Gangnam-gu,
Seoul,06241,RepublicofKorea
Tel:+82-2-2138-0827
FAX:+82-2-6919-2702

HyungtakHarryHan
Sr.RegulatoryAffairsSpecialist
Email:hhan@lunit.io
SuminChung
Sr.RegulatoryAffairsSpecialist
Email:sumin.chung@lunit.io


Radiological Computer Assisted Detection/Diagnosis Software For Suspicious
LesionsForCancer


LunitINSIGHTDBTisacomputer-assisted
detectionanddiagnosis(CADe/x)software
intendedtobeusedconcurrentlyby
interpretingphysicianstoaidinthedetection
andcharacterizationofsuspectedlesionsfor
breastcancerindigitalbreasttomosynthesis
(DBT)examsfromcompatibleDBTsystems.
Throughtheanalysis,theregionsofsoft
tissuelesionsandcalcificationsaremarked
withanabnormalityscoreindicatingthe
likelihoodofthepresenceofmalignancyfor
eachlesion.LunitINSIGHTDBTusesscreening
mammogramsofthefemalepopulation.
LunitINSIGHTDBTisnotintendedasa
replacementforacompleteinterpreting
physician’sreviewortheirclinicaljudgment
thattakesintoaccountotherrelevant
informationfromtheimageorpatienthistory.


Feature
Proposed device:
Predicate device:
Comments

Radiological Computer
Assisted
Detection/Diagnosis
Software

Regulation number
21 CFR 892.2090
21 CFR 892.2090

Classification Panel
Radiology
Radiology

QP-Prostate® CAD is a
Computed Aided
Detection and
Diagnosis
(CADe/CADx) image
processing software
that automatically
detects and identifies
suspected lesions in the
prostate gland based
on bi-parametric
prostate MRI. The
software is intended to
be used as a
concurrent read by
clinicians with proper
training in a clinical
setting as an aid for
interpreting prostate
MRI studies. The
results can be
displayed in a variety of
DICOM outputs,
including identified
suspected regions of
abnormalities marked
as an overlay onto
source MR images. The
output can be displayed
on third-party DICOM
workstations and
Picture Archive and
Communication
Systems (PACS).
Patient management

ProstatIDTM 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
with the following
indications for use.
ProstatID analyzes T2W,
DWI and ADC MRI data.
ProstatID does not
include DCE images in
its analysis.
ProstatID software is
intended for use as a
concurrent reading aid
for physicians
interpreting
prostate MRI exams of
patients presented for
high-risk screening or
diagnostic imaging, from
compatible MRI
systems, to identify
regions suspicious for
prostate cancer and
assess their likelihood of
malignancy.
Outputs of the device
include the volume of the
prostate and locations,
as well as the extent of
suspect lesions, with

Substantially
equivalent. Minor
differences in outputs,
exist, but both devices
are CADe/x devices
that characterize
prostate abnormalities
on MR image data.
The differences do not
raise different
questions of safety
and effectiveness.

predicate device ProstatIDTM (Bot Image, Inc.)


decisions should not be
based solely on the
results of QP-Prostate®
CAD.

index scores indicating
the likelihood that cancer
is present, as well as an
exam score by way of
PI-RADS interpretation
suggestion. "Extent of
suspect lesions" refers to
both the assessment of
the boundary of a
particular abnormality,
as well as identification
of multiple abnormalities.
In cases where multiple
abnormalities are
present, ProstatlD can
be used to assess each
abnormality
independently.
Outputs of this device
should be interpreted
with all available MR
data consistent with
ACR clinical
recommendations
(e.g., dynamic contract
enhanced images if
available) in context of
PI-RADs v2, and in
conjunction with bi-
parametric
MRI acquired with either
surface or endorectal
MRI accessory coils
from compatible MRI
systems. Analysis by
ProstatlD
is not intended as a
replacement for
interpreting prostate
abnormalities using MR
image data consistent
with clinical
recommendations
(including DCE); nor
should patient
management decisions
be made solely on the
basis of ProstatlD.

QP-Prostate® CAD is
intended to be used by
physicians with proper
training, including
radiologists, urologists
and any physician
qualified to read and
interpret prostate MRI
consistent with ACR
recommendations in the
context of PI-RADS.

Intended users of
ProstatlD are physicians
qualified to read and
interpret prostate MRI
exams consistent with
ACR recommendations
in the context of PI-
RADS v2.


Patients above 40
years with prostate MR
imaging.

The device is intended to
be used in the
population of biological
adult males with a
prostate gland
undergoing screening or
clinical MRI exams. This
includes biological males
with clinical indicators
suggestive of possible
prostate cancer or
with family history of
prostate cancer.

Identification of location
of suspicious lesions,
with two suspicion
levels of clinically
significant prostate
cancer, moderate or
high

Extent and location of
identified suspected
lesions, assigned to a
level of suspicion (0-1).
A suggested level of
suspicion or overall PI-
RADS exam score.

Substantially
equivalent. While
minor differences exist
in that QP-Prostate
provides two suspicion
levels, while ProstatID
assigns a level of
suspicion on a scale of
0-1, the intended use
of the devices remain
the same.
Furthermore, the
safety and
effectiveness of QP-
Prostate are supported
through performance
assessments and do
not raise different
questions of safety
and effectiveness.

DICOM compatibility
DICOM-in DICOM-out
DICOM-in DICOM-out
Same

T2W and DWI series,
DCE is not included for
analysis

T2W, DWI and ADC MRI
data, DCE is not
included for analysis

Substantially similar.
While QP-Prostate
takes a subset of the
input data used in the
predicate device. This
difference does not
raise different
questions of safety
and effectiveness.

AI-based, safety and
effectiveness are
supported
through performance
assessments.

The software is
intended to be used as
a concurrent read by
clinicians with proper
training in a clinical
setting as an aid for
interpreting prostate
MRI studies. Patient
management decisions
should not be based
solely on the results of
QP-Prostate® CAD.

ProstatID software is
intended for use as a
concurrent reading aid.
Analysis by ProstatlD is
not intended as a
replacement for
interpreting prostate
abnormalities using MR
image data consistent
with clinical
recommendations
(including DCE); nor


Feature
Proposed device:
Predicate device:
Comments

should patient
management decisions
be made solely on the
basis of ProstatlD.


(high suspicion marker, any biopsy source)

(high and moderate suspicion markers, any

Table 2: Summary of the standalone performance testing for QP-Prostate® CAD.


261 Madison Avenue, 9th Floor
New York, NY 10016

Alan Nelson
Chief Technology Officer, Radformation


AutoContour, AutoContouring, AutoContour Agent,
AutoContour Cloud Server

Medical image management and processing system


Table 3: Technological Characteristics
AutoContour Model RADAC V4 vs. AutoContour Model RADAC V3 (K230685)

CTorMRinputforcontouringor
registration/fusion.
PET/CTinputforregistration/fusiononly.
DICOMRTSTRUCTandREGISTRATION
forinput.
(Minordifferences)

Nobuilt-inreporting,supportsexporting
DICOMRTSTRUCT,REGISTRATION
andDOSEfiles.
(Minordifferences)


Regionsand CT orM Rinputforcontouringof CT orMRinputforcontouringof

Volumesof ana tomi calregions:HeadandNeck, ana tomicalregions:HeadandNeck,

interest(ROI) Tho rax, AbdomenandPelvis. Tho rax,AbdomenandPelvis.

adformation, Inc
.
AutoContour - 510(k) Submis


● VB_T05
● VB_T06
● VB_T07
● VB_T08
● VB_T09
● VB_T10
● VB_T11
● VB_T12
● Ventricle_L
● Ventricle_R
MRModels:
● A_Pud_Int_L
● A_Pud_Int_R
● Bladder
● Bladder_Trigone
● Brain
● Brainstem
● Cerebellum
● Colon_Sigmoid
● External_Pelvis
● Eye_L
● Eye_R
● Femur_L
● Femur_R
● Glnd_Prostate
● Hippocampus_L
● Hippocampus_R
● Hypo_True
● Hypothalamus
● Lens_L
● Lens_R
● NVB_L
● NVB_R
● OpticChiasm
● OpticNrv_L
● OpticNrv_R
● OpticTract_L
● OpticTract_R
● PenileBulb
● Pituitary
● Prostate
● Rectal_Spacer
● Rectum
● SeminalVes
● SpinalCord_Cerv
● Urethra


For CT Structure models large, medium and small structures resulted in

a mean DSC of 0.92+/-0.06, 0.85+/-0.09, and 0.81+/-0.12 respectively. A full summary of

the CT structure DSC is available below:

volume structures (eg. Gallbladder, Duodenum) and 0.5 for Small structures (eg.


Table 4: CT Training Data Results for AutoContour Model RADAC V4

the CT structure DSC is available below:


Table 5: CT External Clinical Dataset References

structure guidelines used for structure model training were added to the image sets.


primarily of glioblastoma and astrocytoma patients.

Images were acquired on either a GE Signa HDxT (3T) or Siemens Skyra (3T) scanner

45 testing image sets and were acquired from the Cancer Imaging Archive GLIS-RT


Table 7: MR Initial Testing Dataset References

open source datasets, and one institution within the United States.


models, a mean training DSC of 0.96+/-0.03 was found for large models, 0.84+/-0.07 for

medium models, 0.74+/- 0.09 for small models.

(NRG/RTOG) guidelines as appropriate by three clinically experienced experts


Table 8: MR Training Data Results for AutoContour Model RADAC V4

medium models, 0.74+/- 0.09 for small models.


Table 9: MR External Clinical Dataset References

Nyholm, Tufve, Stina Svensson, Sebastian Andersson, Joakim Jonsson,
Maja Sohlin, Christian Gustafsson, Elisabeth Kjellén, et al. 2018. “MR
and CT Data with Multi Observer Delineations of Organs in the Pelvic

Area - Part of the Gold Atlas Project.” Medical Physics 12 (10): 3218–21.

accuracy of the models on image sets acquired that were unique to the training datasets.


resolution between 0.94 mm, and acquisition parameters of TR=5.98ms, TE=96.8s. Data

for testing of the MR Pelvis structure models were acquired from 2 publicly available

datasets, which contained images of patients with prostate or rectal cancer, as well as 1

dataset shared from 2 institutions utilizing an MR Linac.

DSC values were calculated between ground truth contour data and AutoContour

structures and rated on the same DSC passing criteria as was used for the training DSC

validation. All structures passed the minimum DSC criteria for small, medium, and large

Additionally, the qualitative clinical appropriateness of AutoContour structures generated

on these scans was graded by clinical experts. Autocontour structures were graded on a

scale from 1 to 5 where 5 refers to contour requiring no additional edits, and 1 refers to a

score in which full manual re-contour of the structure would be required. An average

score >= 3 was used to determine whether a structure model would ultimately be

beneficial clinically. An average rating of 4.6 was found across all MR structure models

demonstrating that only minor edits would be required in order to make the structure


Table 10: MR External Reviewer Results for AutoContour Model RADAC V4


Device Name
AI-Rad Companion Organs RT
AI-Rad Companion Organs RT

AI-Rad Companion Organs RT is
a post-processing software
intended to automatically contour
DICOM CT and MR pre-defined
structures using deep-learning-
based algorithms.
Contours that are generated by AI-
Rad Companion Organs RT may
be used as input for clinical
workflows including external
beam radiation therapy treatment

raise different questions of the safety and effectiveness.


planning. AI-Rad Companion
Organs RT must be used in
conjunction with appropriate
software such as Treatment
Planning Systems and Interactive
Contouring applications, to
review, edit, and accept contours
generated by AI-Rad Companion
Organs RT.
The outputs of AI-Rad Companion
Organs RT are intended to be used
by trained medical professionals.
The software is not intended to
automatically detect or contour
lesions

Segmentation of
Organ at Risk in the
Anatomic Regions

CT: Head & Neck, Thorax,
Abdomen & Pelvis
Head & Neck lymph nodes
(203 OAR)
MR: Pelvis (9 OAR)

CT: Head & Neck, Thorax,
Abdomen & Pelvis
Head & Neck lymph nodes
(166 OAR)
MR: Pelvis (9 OAR)

No Limitation on scanner model
for CT. Siemens Healthineers’
data only for MR. DICOM
compliance required.

No Limitation on TPS model,
DICOM compliance required.

Contraindications
Adult use only
Adult use only

AI-Rad Companion Organs RT is
designed for use only in adult
populations.
AI-Rad Companion Organs RT is
designed for any patient for whom
relevant modality scans are
available.


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

Limited to patients previously
selected for Radiation Therapy.

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

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

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

Contour
visualization and
editing feature

AI-Rad Companion Organs RT
provides basic result preview of
automatic segmentation results,
and no editing feature of the
automatic segmented contour.

MR: The algorithm is unchanged
from the predicate and is separate
from the CT algorithm therefore
the performance is unchanged
from the predicate.
CT: The target performance was
validated using 579 cases
distributed to four cohorts.
Both: To objectively evaluate the
target performance, the DICE
coefficient, the absolute symmetric
surface distance (ASSD) and the
fail rate was evaluated. The

MR: The target performance was
validated using 66 cases to
validate the overall performance of
the MR contouring.
CT: The target performance was
validated using 414 cases
distributed to three cohorts.
Both: To objectively evaluate the
target performance, the DICE
coefficient, the absolute symmetric
surface distance (ASSD) and the
fail rate was evaluated. The
segmentation performance of the


segmentation performance of the
subject was equivalent to the
overall performance compared to
the predicate, reference device and
comparable literature & devices.

User Interface –
Results Preview
(Confirmation)

Basic visualization functionality of
original data and generated
contours

Results send to Confirmation UI &
Optional bypassing of
Confirmation UI to TPS

Design to be used by trained
clinicians.


Medical Devices –
Application of usability
engineering to medical
devices

FDA recognized Consensus Standards listed in Table 2.


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

Digital Imaging and
Communications in
Medicine (DICOM) Set

Medical devices – symbols
to be used with information
to be supplied by the
manufacturer – Part 1:
General Requirements

Health software – Part 1:
General requirements for
product safety

Health software and Health
IT system safety
effectiveness and security

Medical devices –
Information to be supplied
by the manufacturer


Validation Testing Subject
Acceptance Criteria

• All the organs segmented in the predicate
device are also segmented in the subject
device
• The average (AVG) Dice score difference
between the subject and predicate device
is smaller than 3%


Table 3: Acceptance Criteria of AIRC Organs RT VA50


Table 3: Performance summary of the subject device CT contouring


able 4: Detail
ed P
erformance ev
aluatio
n of the
new org
a
ns in th
e su
bject dev
ice

(Data origin)
So
uth/Nort
h
Ameri
ca: 1
63


Head & Neck: 24
Thorax &
Abdomen: 20
Pelvis: 29

Head & Neck: 50
Thorax: 81
Abdomen: 115
Pelvis: 55

Table 5: Validation Testing Data Information for new OARs


Organ Group
No. of Training
No. of Validation

Table 5: Validation Testing Data Information based on Cohort


Device Name
Oncospace
Oncospace
Identical

510(k) Owner
Oncospace, Inc.
Oncospace, Inc.

System, Planning, Radiation
Therapy Treatment

Oncospace is used to configure
and review radiotherapy treatment
plans for a patient with malignant
or benign disease in the head and
neck, thoracic, abdominal, and
pelvic regions. It allows for set up
of radiotherapy treatment
protocols, association of a
potential treatment plan with the
protocol(s), submission of a dose
prescription and achievable
dosimetric goals to a treatment
planning system, and review of
the treatment plan. It is intended
for use by qualified, trained
radiation therapy professionals
(such as medical physicists,
oncologists, and dosimetrists).

Oncospace is used to configure
and review radiotherapy treatment
plans for a patient with malignant
or benign disease in the prostate,
head, and neck regions. It allows
for set up of radiotherapy
treatment protocols, association of
a potential treatment plan with the
protocol(s), submission of a dose
prescription and achievable
dosimetric goals to a treatment
planning system, and review of
the treatment plan. It is intended
for use by qualified, trained
radiation therapy professionals
(such as medical physicists,
oncologists, and dosimetrists).
This device is for prescription use
by order of a physician.

Substantially
Equivalent
Added thoracic
and abdominal
regions, added
gynecological
sites to expand
the prostate
reference to the
pelvic region.

Note: The subject device algorithms, and any future algorithm updates, are locked prior to clinical use.


This device is for prescription use
by order of a physician.

Client-Server (Clinic-provided
client machines, cloud Windows
servers controlled by Oncospace)

Connected to or
Controlling of
Radiation
Delivery Devices

Medical professionals, including
but not limited to, radiation
oncologists, medical physicists or
physicians.

There are no demographic,
regional, or cultural limitations
for patients. It is up to the user to
determine if the system can be
used for a patient.

Head and neck
Thoracic
Abdominal
Pelvic
The thoracic, abdominal, and
gynecological regions have been
added using the same machine
learning methods as in the
predicate device.

New:
Gynecologic,
thoracic, and
abdominal organs
Identical: Head
and neck, prostate

The system can be used in a
hospital environment or in a
doctor’s office.

Yes. Import existing plans from
third-party systems to compare
dose objectives against templates.


Yes. Factory-default plans with
dose goals exist and users can
configure a dose template.

Yes. Regions of interest are
matched as the study is opened in
the device. Users can adjust or
match to more available regions
of interest.

Yes. Comparisons can be done
between more than one selected
treatment plan. Dose is based on
calculated dose and curated, gold-
standard treatment plans.

Yes. Display, pan, zoom, scroll,
windowing, viewport layout.

Calculate and
Display Dose
Volume
Histograms

Dose
Summation/
Treatment-Over-
Time Data

Yes. Contains features for review
of isodose lines, review of DVHs,
dose comparison and dose
summation.

Yes. Can export the selected plan
for review and setup by a
dosimetrist.
Oncospace does not export a final
plan, it will not export to a record-
and-verify system.


Development (Training/Tuning)
and Internal Performance Testing
Dataset (randomly split 80/20)

1145 treatment plans for patients
who received radiation therapy for
HNC at Johns Hopkins University
between 2008-2019.
Plans were required to exhibit 90%
target coverage.
10% of the plans were single-
target and 90% were SIB (19% 2-
target, 51% 3-target, 20% 4-
target).
96% of plans had a total
prescribed dose >= 60 Gy, 4% had
a total prescribed dose < 60 Gy.

Dataset A: 265 patients who
received radiation therapy
for HNC at Institution_2.
Plans were required to
exhibit 90% target coverage.
11% of the plans were
single-target and 89% were
SIB (3% 2-target, 41% 3-
target, 45% 4-target). 98% of
plans had a total prescribed
dose >= 60 Gy, 2% had a
total prescribed dose < 60
Gy.

18 patients who received
radiation therapy for HNC at
JHU between 2021-2022. This
included plans with 1-4 target
dose levels, 10 to 48 fractions,
in a variety of anatomical
locations: lip, larynx, base of
tongue, parotid, nasopharynx,
scalp, neck, etc. HN was
clinically validated in a previous
510k submission.

medical record such that technique information could not be linked.


The dataset contained 35% IMRT,
27% VMAT, 15% tomotherapy, 2%
3D conformal, and 22%
unspecified plans.

Dataset B: 27 patients who
received radiation therapy
for HNC at Institution_3.
Plans were required to
exhibit 90% target coverage.
All plans had 3 targets and
total prescribed dose >= 60
Gy.

1623 treatment plans (1437 lung
and 186 esophagus) for patients
who received radiation therapy for
thoracic cancer at Johns Hopkins
University between 2008-2019.
Plans were required to exhibit 92%
target coverage.
82% of plans had a total
prescribed dose >= 45 Gy, 18%
had a total prescribed dose < 45
Gy.
57% of plans had conventional
fractionation (dose per fraction
<2.3Gy) and 43% were hypo-
fractionated plans.

20 patients (14 lung and 6
esophagus) who received
radiation therapy at JHU
between 2021-2024. This
included targets in multiple
locations within the lungs and
esophagus, including single-
target, SIB, and multi-phase
courses, treated with
conventional- and hypo-
fractionation, and SBRT.

712 treatment plans for patients
who received radiation therapy for
pancreatic cancer at Johns
Hopkins University between 2008-
2019, and 69 treatment plans
from patients who received
radiation therapy for liver cancer
at Montefiore Einstein
Comprehensive Cancer Center.
Plans were required to exhibit 85%
target coverage.
3% of plans had conventional
fractionation (dose per fraction

17 patients (11 pancreas and 6
liver) who received radiation
therapy for at JHU between
2021-2024. This included
single-target and SIB courses,
treated with conventional- and
hypo-fractionation and SBRT.


<2.3Gy) and 97% were hypo-
fractionated plans.

1785 treatment plans (1662
prostate and 123 gynecological)
for patients who received
radiation therapy for pelvic cancer
at Johns Hopkins University
between 2008-2019.
Plans were required to exhibit 94%
target coverage.
98% of plans had conventional
fractionation (dose per fraction
<2.3Gy) and 2% were hypo-
fractionated plans.
37% of plans had at least one
phase with a nodal PTV, and 63%
did not.
The Prostate dataset used in the
Pelvis model contained 15% IMRT,
46% VMAT, 14% tomotherapy,
and 25% unspecified plans.

40 patients who received
radiation therapy for
prostate cancer at
Institution_3. Plans were
required to exhibit 94%
target coverage. All plans
had conventional
fractionation.

17 patients (12 prostate and 5
gynecological) who received
radiation therapy at JHU
between 2021-2024. This
included single-target and SIB
courses, treated with
conventional- and hypo-
fractionation and SBRT.
Prostate was clinically validated
in previous 510k submission.


Measurement [units]
Description
Application

Length between two points, for both
curved lines (splines) and straight lines,
including the diameter (including min,
max, average) resulting from closed
splines and depth

Diameter & depth of cardiovascular
structures of interest

The perimeter of a contour (closed spline)

Perimeter of cardiovascular structures of
interest

Area of cardiovascular structures of interest

Signal intensity [HU]
(modality CT) / Intensity
[unitless] (modality MR)

Modality CT: Hounsfield value (in
Hounsfield Units, HU) of the underlying
pixels
Modality MR: Intensity / shade of grey
(high, intermediate, low) of underlying
pixels

Intensity of pixels in cardiovascular
structures of interest

Volume of cardiovascular structures of
interest

Location in the x-, y-, and z-planes of a
point

Coordinates of points of interest on a 3D
rendering, for export purposes

Mass of cardiovascular structures of interest

The displacement vector represents the
position of a point with respect to the
position of that point in the reference (end
diastole) phase.

Strain within cardiovascular structures of
interest (e.g., myocardium)

Industry-standard measure for coronary
calcium based on volume and intensity of
calcified plaque

For assessing overall calcified plaque
burden in coronary arteries.

The angle of an object/structure of
interest

The narrowing of a vessel in area or
diameter compared to a normal reference
location

For measuring an abnormal narrowing in an
artery

The velocity of moving objects within
contour(s)

Velocity within cardiovascular structures of
interest (e.g., blood flow)

Strain is a measure of the deformation in
shape and dimension of the heart muscle
during the cardiac cycle.


Derivative of strain with respect to time

Strain within cardiovascular structures of
interest, as above

Trigger time elapsed from the first phase
till the phase where the peak strain has
been reached.

The difference in rotation between the
apical and basal slices divided by the
apical and basal slices. Note
circumferential displacement represents
an angle.

LV/RV cavity volume at the phase
defined as the ED

LV/RV cavity volume at the phase
defined as the ES

Stroke volume is the volume of blood
pumped out of the LV/RV during each
cardiac contraction and is represented by
the difference of EDV and ESV.

Ejection fraction is measured as a
percentage of the total amount of blood in
LV/RV that is pumped out with each
cardiac cycle. It is calculated by dividing
the SV by EDV.

Cardiac output is the amount of blood
pumped by the heart in a minute and is
calculated by multiplying the SV with
heart rate per minute.

Cardiac index is a hemodynamic
parameter that relates the CO from LV in
one minute to BSA and is obtained by
dividing the CO by BSA.

LV myocardial mass at the phase defined
as the ED and is calculated by multiplying
the myocardial volume in ED phase with
myocardial density (1.05 g/ml).

LV myocardial mass at the phase defined
as the ES and is calculated by multiplying
the myocardial volume in ES phase with
myocardial density (1.05 g/ml).

Surface area of the patient body used in
medical indicators or assessments


cvi42 is intended to be used by qualified medical professionals for viewing, post-processing and quantitative evaluation of cardiovascular magnetic resonance (MR) images and cardiovascular computed tomography (CT) images in a Digital Imaging

and Communications in Medicine Standard format, for the purpose of obtaining diagnostic information as part of a comprehensive diagnostic decision-making process

cvi42 is intended to be used for viewing, post-processing, qualitative and quantitative evaluation of cardiovascular magnetic resonance (MR) images and computed tomography (CT) images in a Digital Imaging and Communications in Medicine

• Importing cardiac MR & CT Images in DICOM format.

• Supporting clinical diagnostics by qualitative analysis of cardiac MR & CT images using display functionality such as panning, windowing, zooming, navigation through series/slices and phases, 3D reconstruction of images including

multiplanar reconstructions of the images.

• Supporting clinical diagnostics by quantitative measurement of the heart and adjacent vessels in cardiac MR & CT images, specifically signal intensity, distance, area, volume, and mass.

• Supporting clinical diagnostics by using area and volume for measuring cardiac function and derived parameters cardiac output and cardiac index in long axis and short axis cardiac MR & CT images.

• Flow quantifications based on velocity encoded cardiac MR images (including two and four dimensional flow analysis).

• Strain analysis of cardiac MR images by providing measurements of 2D LV myocardial function (displacement, velocity, strain, strain rate, time to peak, and torsion).

• Supporting clinical diagnostics of cardiac CT images including quantitative measurements of calcified plaques in the coronary arteries (calcium scoring), specifically Agatston and volume and mass calcium scores, visualization and

quantitative measurement of heart structures including coronaries, femoral, aortic, and mitral valves.

• Evaluating CT and MR images of blood vessels. Combining digital image processing and visualization tools such as multiplanar reconstruction (MPR), thin/thick maximum intensity projection (MIP), inverted MIP thin/thick, volume

rendering technique (VRT), curved planar reformation (CPR), processing tools such as bone removal (based on both single energy and dual energy) table removal and evaluation tools (vessel centerline calculation, lumen calculation,

stenosis calculation) and reporting tools (lesion location, lesion characteristics) and key images. The software package is designed to support the physician in confirming the presence or absence of physician identified lesion in blood

vessels and evaluation, documentation and follow up of any such lesions.

cvi42 shall be used by qualified medical professionals, experienced in examining and evaluating cardiovascular MR or CT images, for the purpose of obtaining diagnostic information as part of a comprehensive diagnostic decision-making process.

cvi42 is a software application that can be used as a stand-alone product or in a networked environment.

The target population for cvi42 and its manual workflows is not restricted; however, cvi42’s semi-automated machine learning algorithms, included in the MR Function and CORE CT modules, are intended for an adult population. Further, image

acquisition by a cardiac MR or CT scanner may limit the use of the software for certain sectors of the general public.

cvi42 shall not be used to view or analyze images of any part of the body except the cardiac images acquired from a cardiovascular magnetic resonance or computed tomography scanner.

Table 2. Subject Device Intended Use / Indications for Use


Primary Predicate
Predicate
Predicate
Predicate
Predicate
Predicate

Manufactured by Circle
Manufactured by Circle
Manufactured by Circle
Manufactured by Circle
Manufactured by Circle
Manufactured by Circle

Viewing, post-processing,
qualitative and quantitative
evaluation of cardiovascular MR
images in DICOM format.

Viewing, post-processing, qualitative
and quantitative evaluation of
cardiovascular CT images in DICOM
format.

Viewing, post-processing, qualitative
and quantitative evaluation of blood
vessels and cardiovascular MR and
CT images in DICOM format.

The Cardiac CT Function Software
Application is intended for qualitative
and quantitative evaluation of
cardiovascular CT images in a DICOM
Standard format, to calculate and
display cardiac function metrics (e.g.,
end diastolic volume, end systolic
volume, stroke volume, ejection fraction,
cardiac output, cardiac index, and LV
myocardial mass).

qualitative and quantitative
and quantitative evaluation of
and quantitative evaluation of blood
and quantitative evaluation of blood
Application is intended for qualitative
Application is intended for qualitative

evaluation of cardiovascular MR
cardiovascular CT images in DICOM
vessels and cardiovascular MR and
vessels and cardiovascular MR and
and quantitative evaluation of
and quantitative evaluation of

images in DICOM format.
format.
CT images in DICOM format.
CT images in DICOM format.
cardiovascular MR images in a
cardiovascular CT images in a DICOM

DICOM Standard format. As
Standard format, to calculate and

perquisite, the user confirms
display cardiac function metrics (e.g.,

endocardial and epicardial contours in
end diastolic volume, end systolic

tracks features over the cardiac cycle
cardiac output, cardiac index, and LV

and computed 2D myocardial
myocardial mass).

ct42 is intended to be used for viewing,
post-processing and quantitative
evaluation of cardiovascular computed
tomography (CT) images in a Digital
Imaging and Communications in
Medicine (DICOM) Standard format.
It enables:
• Importing Cardiac CT Images in
DICOM format
• Supporting clinical diagnostics by
qualitative analysis of the cardiac CT
images using display functionality
such as panning, windowing,
zooming, navigation through
series/slices and phases, 3D
reconstruction of images including
multi-lanner reconstructions of the
images.
• Supporting clinical diagnostics by
quantitative measurement of the heart
and adjacent vessels in cardiac CT
images, specifically distance, area,
volume and mass
• Supporting clinical diagnostics by
using area and volume measurements
for measuring LV function and derived
parameters cardiac output and cardiac
index in long axis and short axis
cardiac CT images.

The Myocardial Strain Software
Application is intended for qualitative
and quantitative evaluation of
cardiovascular magnetic resonance
(CMR) images. It provides
measurements of 2D LV myocardial
function (displacement, velocity,
strain, strain rate, time to peak, and
torsion); these measurements are
used by qualified medical
professionals, experiences in
examining and evaluating CMR
images, for the purpose of obtaining
diagnostic information for patients with
suspected heart disease as part of a
comprehensive diagnostic decision-
making process.

The Cardiac CT Function Software
Application is indicated to be use with
multi-phase, multi-slice cardiovascular
CT angiography images to assist
qualified medical professionals in
assessing and evaluating cardiac
function. CT Function includes manual
and semi-automatic heart segmentation
of 2 chambers (LV and RV) and
calculation of cardiac function metrics
including end diastolic volume, end
systolic volume, stroke volume, ejection
fraction, cardiac output, cardiac index,
and LV myocardial mass.

viewing, post-processing and
image analysis software package add-
viewing, post-processing, qualitative
Application is intended for qualitative

quantitative evaluation of
on for evaluating CT and MR images
and quantitative evaluation of
and quantitative evaluation of

cardiovascular magnetic resonance
of blood vessels. Combining digital
cardiovascular magnetic resonance
cardiovascular magnetic resonance

(MR) images in a Digital Imaging
image processing and visualization
(MR) and computed tomography (CT)
(CMR) images. It provides

and Communications in Medicine
tools such as multiplanar
images in a Digital Imaging and
measurements of 2D LV myocardial

(DICOM) Standard format.
reconstruction (MPR), thin/think
Communications in Medicine (DICOM)
function (displacement, velocity,

maximum intensity projection (MIP)
Standard format.
strain, strain rate, time to peak, and

It enables;
thin and think, inverted MIP thin and
torsion); these measurements are

• Importing Cardiac MR Images in
think, volume rendering technique
It enables a set of tools to assist
used by qualified medical

DICOM format
(VRT), curved planner reformation,
physicians in qualitative assessment
professionals, experiences in

• Supporting clinical diagnostics by
processing tools such as bone
of cardiac images and quantitative
examining and evaluating CMR

qualitative analysis of the cardiac
removal (based on both single energy
measurements of the heart and
images, for the purpose of obtaining

functionality such as panning,
evaluation tools (vessel centerline
scoring; and to confirm the presence
suspected heart disease as part of a

windowing, zooming, navigation
calculation, lumen calculation,
or absence of physician-identified
comprehensive diagnostic decision-

through series/slices and phases.
stenosis calculation) and reporting
lesion in blood vessels.
making process.

• Supporting clinical diagnostics by
tools (lesion location, lesion

quantitative measurement of the
characteristics) and key images), the
The target population for cvi42 Auto’s

heart and adjacent vessels in
software package is designed to
manual workflows is not restricted;

cardiac MR images, specifically
support the physician in conforming
however, cvi42 Auto’s semi-

distance, area, volume and mass
the presence or absence of physician
automated machine learning

• Supporting clinical diagnostics by
identified lesion in blood vessels and
algorithms are intended for an adult

using area and volume
evaluation, documentation and follow
population.

measurements for measuring LV
up of any such lesions.

function and derived parameters
cvi42 Auto shall be used only for

cardiac output and cardiac index in
It shall be used by qualified medical
cardiac images acquired from an MR

long axis and short axis cardiac MR
professionals, experienced in
or CT scanner. It shall be used by

images.
examining and evaluating
qualified medical professionals,

• Flow quantifications based on
cardiovascular CT or MR images, for
experienced in examining and

velocity encodes images
the purpose of obtaining diagnostic
evaluating cardiovascular MR or CT

Table 3. Predicate Device Intended Use / Indications for Use