Eclipse Treatment Planning System Version

The Radiation Planning Assistant (RPA) is
used to plan radiotherapy treatments for
patients with cancers of the head and neck,
cervix, breast, and metastases to the brain. The
RPA is used to plan external beam irradiation
with photon beams using computerized
tomography (CT) images. The RPA is used to
create contours and treatment plans that the
user imports into their own Treatment Planning
System (TPS) for review, editing, and re-
calculation of the dose.
Some functions of the RPA use Eclipse
v.15.6. The RPA is not intended to be used as
a primary treatment planning system. All
automatically generated contours and plans
must be imported into the user’s own
treatment planning system for review, edit,
and final dose calculation.

The Eclipse Treatment Planning System
(Eclipse TPS) is used to plan radiotherapy
treatments for patients with malignant or
benign diseases. Eclipse TPS is used to plan
external beam irradiation with photon, electron,
and proton beams, as well as for internal
irradiation (brachytherapy) treatments.

The Radiation Planning Assistant (RPA) is a
web-based contouring and radiotherapy
treatment planning software tool that
incorporates the basic radiation planning
functions from automated contouring,
automated planning with dose optimization,
and quality control checks. The system is
intended for use for patients with cancer of the
head and neck, cervix, breast, and metastases to
the brain. The RPA system is integrated with
the Eclipse Treatment Planning System v.15.6
software cleared under K181145.

The Varian Eclipse™ Treatment Planning
System (Eclipse TPS) provides software tools
for planning the treatment of malignant or
benign diseases with radiation. Eclipse TPS is
a computer-based software device used by
trained medical professionals to design and
simulate radiation therapy treatments.
Eclipse TPS is capable of planning treatments
for external beam irradiation with photon,
electron, and proton beams, as well as for
internal irradiation (brachytherapy) treatments.


Comparison of the RPA System’s Software Functions with

Eclipse Treatment Planning System Version 15.6 (K181145)

Software
Description of Functions Available in
Differences
Similarities
Rationale for

Function
Eclipse
Substantial Equivalence

1. Organ-specific autocontouring algorithms. Eclipse
v.15.6 includes the following organ-specific
autocontouring algorithms for the following organs:
spine, lung, brain, eye, bone.
2. Expert Segmentation. Eclipse v.15.6 includes an atlas-
based contouring approach (“expert segmentation”) for
autocontouring of many structures, including:
• Head / neck region: Body, bones, brainstem,
cochlea, esophagus, eyes, mandible, oral cavity,
various lymph nodes
• Breast region: Body, heart, trachea, various
lymph nodes
• Pelvis: Body, bladder, femoral heads, pelvic
bones, rectum, spinal canal
The system calculates the anatomical points, image
features, and similarity scores of the patient image and
compares them with pre-stored expert cases. Rigid
registration is used both for initializing the deformable
registration algorithm and for displaying the expert case
and patient image in aligned preview. The
autocontouring approach depends on the selected
structures. Either the structures are heuristically
segmented from the patient image, or the structures are
generated via deformable registration and structure
propagation from the expert cases. If multiple expert
cases are used, the propagated structures from the
different atlases are fused by means of the simultaneous
truth and performance level estimation (STAPLE)
algorithm.

The RPA uses deep learning algorithms
which Eclipse does not.
Use and function: In Eclipse, the user edits
the contours prior to planning. This is the
same for complex planning in the RPA
(VMAT planning for head / neck and cervix).
It is different for simple plans, where the plan
is generated before the user reviews the
contours. If the user edits the contours in the
RPA, they will have to delete the plan as
well.

Use and function: The RPA
provides autocontouring for a
range of structures, including
most of those listed here for
Eclipse.
Performance data: The
algorithm for Expert
Segmentation in Eclipse is
very similar to the Multi-Atlas
Contouring System (MACS)
that is used to contour
structures for the chest wall
planning in the RPA.
Safety and effectiveness: Both
Eclipse and the RPA are
designed to provide contours
that the users review and edit.

Devices are Substantially
Equivalent. Both devices
provide autocontouring
functions for the same
anatomical regions. Both
devices require user edits of
contours with ‘complex plans’
prior to planning.

Automatic marker detection - Eclipse v.15.6 includes a
function (‘Calypso Beacon Detection’) to automatically
detect a specific type of marker (Calypso transponders)
on CT images.

Use and function: The Eclipse function is for
a specific type of marker that is different
from the generic markers that the RPA is
designed for.

Use and function: Both Eclipse
and the RPA can automatically
detect markers.

Devices are Substantially
Equivalent. Both devices can
automatically detect markers.

Table 2: Comparison of Functions of the Subject Device with Functions of the Predicate Device


Comparison of the RPA System’s Software Functions with the

Software
Description of Functions Available in
Differences
Similarities
Rationale for Substantial

1. Photon Optimizer (PO) algorithm. This algorithm
is used to optimize IMRT or VMAT plans based on
DVH constraints / objectives.
2. Automated Optimization Workflow. Enabling this
can automate the optimization workflow for IMRT
planning so that, after optimization, the leaf motion
calculation and final dose calculation are
automatically initiated, and the results are then
automatically saved. A similar feature exists for
VMAT plans.
3. DVH Estimation Models for RapidPlan. DVH
estimation models are created from information
extracted from a set of previous treatment plans
(called ‘treatment plans’). The estimation models
predict the DVH that is achievable from the current
treatment plan (based on the geometry in the current
plan), and also creates a set of optimization objects
that can be based on the DVH estimates or fixed
(i.e., not based on the DVH estimates).

Use and function: The main difference for
VMAT planning is that Eclipse generally
creates a plan that the user reviews, makes
edits to the optimization constraints, and
repeats the process to improve the plan
quality. The RPA uses the same
optimization tools (i.e., the tools in Eclipse),
but the optimization objectives and
constraints have been pre-set to give optimal
plans for the majority of patients. The user
is not able to easily edit the RPA VMAT
plans so, if they do not approve the plan for
clinical use, they must delete it and create
one using their own routine processes (i.e.,
in their own treatment planning system).

Use and function: The RPA
uses some Eclipse features,
including DVH Estimates for
RapidPlan and the Photon
Optimizer for optimizing
VMAT plans. The plans look
very similar.
Safety and effectiveness: Both
Eclipse and the RPA are
designed to create plans that
the users then edit and review
for clinical acceptability prior
to use.

Devices are Substantially
Equivalent. Both devices provide
autoplanning features and create
plans that the users then edit and
review for clinical acceptability
prior to use. Both devices provide
Photon Optimizer, automated
optimization workflow and DVH
estimation models.

1. Beam Angle Optimization (BAO). This tool
optimizes the number and angle of treatment beams.
It optimizes the objective function, which is
determined by DVH goals / constraints and a normal
tissue objective (which falls off with distance from
the PTV). BAO can be used for IMRT plans or as a
starting point for conformal treatment plans.
2. Collimator Angle Optimization (CAO). This
function optimizes collimator angle for each arc of a
HyperArc plan such that, whenever possible, a given
pair of MLC leaves delineates only one target in the
beam’s-eye-view.
3. Optimize collimator jaws. Adjusts the collimator
jaws to best fit the MLC leaves to the structure.
4. Use recommended jaw positions. Adjusts the
collimator jaw positions with an additional margin.
5. Optimize collimator rotation. Optimizes the
collimator rotation around a structure.

Use and function: Autoplanning in Eclipse
is mostly automation of individual tasks that
are controlled by the user. The user does
not control these tasks with the RPA.
Use and function: Review and editing of 3D
plans (cervix 4-field box, post-mastectomy
breast plans, whole brain plans) for the RPA
happens in the users’ own treatment
planning system.

Use and function: Many of the
treatment plan details in
Eclipse and RPA use functions
with similar algorithms, such
as optimizing the jaw
positions.
Safety and effectiveness: Both
Eclipse and the RPA are
designed to create plans that
the users then edit and review
for clinical acceptability prior
to use.

Devices are Substantially
Equivalent. Both devices create
plans that the users then edit and
review for clinical acceptability
prior to use through the use of AI
software. Both devices provide
Beam Angle Optimization,
Collimator Angle Optimization and
collimator jaw optimization.

510(k) Summary Radiation Planning Assistant (RPA)


Anatomical
Tissue Type(s)
Training Data Set
Test Data

3,288 patients (3,495 CT scans) who received radiation therapy at MD
Anderson Cancer Center between September 2004 and June 2018. Any
patient who received a simulation CT scan of the head/neck region in a
head -first supine position was eligible.

174 CT scans were
randomly selected from
this group (and excluded
for training) plus
qualitative evaluation 24
CT scans from an
external dataset.

160 patients who received radiation therapy at MD Anderson Cancer
Center from 2018 to 2020. Any patient who received a simulation CT
scan of the head/neck region in a head-first supine position was eligible.

Test patients were
randomly selected and
excluded from the
training set.

61 patients who received radiation therapy at MD Anderson Cancer
Center between 2010 and 2019. Any patient who received a simulation
CT scan of the head/neck region in a head-first supine position was
eligible.

These 71 cases were
randomly placed in 3
groups: training (51 pts.),
cross-validation (10 pts.)
and final test (10 pts.).

The whole brain primary segmentation models used the same models as
used for head and neck segmentation, described above, as well as an
additional vertebral body localization and segmentation model (Vertebral
Bodies model: spinal canal CNN: 1,966, VB labeling: 803, VB
segmentation: 107, from 930 MDACC patients and 355 external
patients). Patients who received spinal radiotherapy for spinal metastases
(3DCRT and VMAT) at MD Anderson, or for whom data was publicly
available (MICCAI challenge data).

Test patients were
randomly selected from
this group (and excluded
for training).

Table 3: Software Training for Anatomical Locations


1,999 patients (2,254 CT scans) who received radiation therapy at MD
Anderson from September 2004 and June 2018. Any patient who
received a simulation CT scan of the pelvic region in a head-first supine
position was eligible.

140 CT scans were
randomly selected from
this group (and excluded
for training) plus
qualitative evaluation
with 30 cervical cancer
patients from 3 centers in
S. Africa.

192 patients (316 CT scans) who were treated for locally advanced
cervical cancer between 2006 and 2020.

406 CT scans from 308 patients (UteroCervix), 250 CT scans from 201
patients (Nodal CTV), 146 CT scans from 131 patients (PAN), 490 CT
scans from 388 patients (Vagina), 487 CT scans from 388 patients
(Parametria) who received radiation therapy at MD Anderson Cancer
Center between 2006 and 2020.

Training data for GYN Liver (normal) comprised 119 patients (169 CT
scans) who had received contrast-enhanced and non-contrast CT imaging
of the liver at MD Anderson Cancer Center.

Training data for whole body (secondary for chest wall) comprised 250
patients who were treated at MD Anderson between August 2016 and
June 2021, with CT imaging in the thoracic region.


Assess the safety of using the RPA plan for normal structures for treatment
planning by comparing the number of patient plans that pass accepted
dosimetric metrics when assessed on the RPA contour with the number that
pass when assessed on the clinical contour. The difference should be 5% or
less. When there are multiple metrics for a single structure at least one
should pass this criterion.

Assess the effectiveness of the RPA plan for normal structures by
comparing the dose to RPA normal structures for RPA plans and clinical
normal structures for clinical plans. The difference in the number of RPA
plans that pass accepted dosimetric metrics and the number of clinical plans
that pass accepted dosimetric metrics should be 5% or less. When there are
multiple metrics for a single structure at least one should pass this criterion.

< 5% difference
between RPA Plan and
Clinical Plan for all
bony structures and
critical soft tissue
structures with VMAT
and 4 field box.**

Assess the effectiveness of the RPA plan for target structures by comparing
the number of RPA plans that pass accepted dosimetric metrics (e.g.,
percentage volume of the PTV receiving 95% of the prescribed dose) when
compared with clinical plans. The difference should be 5% or less. When
there are multiple metrics used to assess a single structure, at least one
coverage and one maximum criterion should pass this criterion.

< 5% difference
between RPA Plan and
Clinical Plan for all
assessed structures

Assess the geometric effectiveness of the RPA targets using recall. A low
value for this metric represents under-contouring. The 25th percentile of the
recall must be 0.7 or greater.

Assess the quality of body contouring generated by the RPA by comparing
primary and secondary body contours generated by the RPA with manual
body contours. Surface DSC (2mm) should be greater than 0.8 for 95% of
the CT scans.

Assess the ability of the RPA to accurately identify the marked isocenter.
This is achieved by comparing the automatically generated isocenters with
manually generated ones. 95% of automatically generated marked
isocenters (primary and verification approaches) should agree with
manually generated marked isocenters within 3mm in all orthogonal
directions (AP, lateral, cranial-caudal).

< 3mm difference
between RPA Plan and
Clinical Plan for all
orthogonal directions

Table 5: Summary of Statistical Results—Cervix


Criteria
Inclusion Criteria
Exclusion Criteria
Sampling Method

Test datasets were chosen
going forward in time
until sufficient data were
collected, starting with CT
scans collected on January
1, 2022. If insufficient
patient scans were found,
data collection was
restarted with January 1,
2021 (for patients treated
in 2021) and so forth, until
sufficient data was
collected.

Clear CT image of the pelvic region without
distortions.

Test datasets consisted of CT images of
patients previously treated for cervical
cancer using radiotherapy following one of
the following treatment schemes:
• 4-field box (based on bony
landmarks or soft tissue)
• VMAT

Scan was obtained with patient head-first,
supine.

The datasets included CT images, original
clinical contours of anatomic structures and
treatment targets, and the dose distributions
used for patient treatment.

Test datasets were chosen going forward in
time until sufficient data was collected,
starting with CT scans collected on January
1, 2022. If insufficient patient scans were
found, data collection could be restarted with
January 1, 2021 (for patients treated in 2021)
and so forth, until sufficient data was
collected.

Testing datasets were unique, with no
overlap with data used for model creation or
in previous validation studies.

CT scans included the manufacturer and
model of the scanner used to obtain the CT
image.


Assess the safety of use of the RPA by comparing the number of patient
plans that pass accepted dosimetric metrics when assessed on the RPA
contour with the number that pass when assessed on the clinical contour.
The difference should be 5% or less. When multiple metrics were used to
assess a single structure at least one had to pass the criteria (similar to the
manner in which doses are assessed in clinical practice).

<7% difference
between RPA Plan and
Clinical Plan for all
assessed structures.

Assess the effectiveness of use of the RPA by comparing the number of
RPA plans that pass accepted dosimetric metrics (e.g., mean dose to the
organ-at-risk) when compared with clinical plans.
The difference should be 5% or less. When multiple metrics were used to
assess a single structure, at least one should pass this criterion (similar to
the manner in which doses are assessed in clinical practice). This was
considered on a structure-by-structure basis.

<5% difference
between RPA Plan and
Clinical Plan for all
assessed structures.

Assess the quality of body contouring generated by the RPA by
comparing primary and secondary body contours generated by the RPA
with manual body contours. Surface DSC (2mm) should be greater than
0.8 for 95% of the CT scans.

Table 7: Chest Wall Summary of Statistical Results


Test datasets were chosen
going forward in time
until sufficient data was
collected, starting with CT
scans collected on January
1, 2022. If insufficient
patient scans were found,
data collection was
restarted with January 1,
2021 (for patients treated
in 2021) and so forth, until
sufficient data was
collected.

Clear CT image of the breast (thorax) region
without distortions.

Test datasets must consist of CT images of
patients previously treated for
postmastectomy breast radiotherapy
following one of the following treatment
schemes:
i. Tangent fields with supraclavicular
fields. Similar approaches,
including those that also treat the
intramammary lymph nodes are
also acceptable.

The datasets must include CT images,
original clinical contours of anatomic
structures and treatment targets, and the dose
distributions used for patient treatment.

Test datasets were chosen going forward in
time until sufficient data was collected,
starting with CT scans collected on January
1, 2022. If insufficient patient scans were
found, data collection can be restarted with
January 1, 2021 (for patients treated in 2021)
and so forth, until sufficient data was
collected.

Testing datasets must be unique, with no
overlap with data used for model creation or
in previous validation studies.

CT scan must include the manufacturer and
model of the scanner used to obtain the CT
image or recorded separately.


Assess the safety of use of RPA normal structures for treatment planning
by comparing the number of patient plans that passed accepted dosimetric
metrics (e.g., mean dose to the parotid) when assessed on the RPA
contour with the number that passed when assessed on the clinical
contour. The difference should be 5% or less. When multiple metrics
were used to assess a single structure at least one should pass this
criterion.

<5% difference
between RPA Plan and
Clinical Plan for the
majority of assessed
structures.

Assess the effectiveness of use of RPA normal structures for treatment
planning by comparing the number of RPA plans that passed accepted
dosimetric metrics (e.g., mean dose to the parotid) when compared with
clinical plans. The difference should be 5% or less. When multiple
metrics were used to assess a single structure, at least one should pass this
criterion.

<5% difference
between RPA Plan and
Clinical Plan for the
majority of assessed
structures*.

Assess the effectiveness of the RPA plan for target structures by
comparing the number of RPA plans that pass accepted dosimetric metrics
(e.g., percentage volume of the PTV receiving 95% of the prescribed
dose) when compared with clinical plans. The difference should be 5% or
less. When there are multiple metrics used to assess a single structure, at
least one coverage and one maximum criterion should pass this criterion.

<5% difference
between RPA Plan and
Clinical Plan for the
majority of assessed
criteria.

Assess the geometric effectiveness of the RPA targets using recall. A
low value for this metric represents under-contouring and a potential risk
of creating a plan that misses the target (although the user is expected to
review and edit contours). The 25th percentile of the recall must be 0.7 or
greater.

Assess the quality of body contouring generated by the RPA by
comparing body contours generated by the RPA with manual body
contours. Surface DSC (2mm) should be greater than 0.8 for 95% of the
CT scans.

Assess the ability of the RPA to accurately identify the marked isocenter.
This is achieved by comparing the automatically generated isocenters with
manually generated ones. 95% of automatically generated marked should
agree with manually generated marked isocenters within 3mm in all
orthogonal directions (AP, lateral, cranial-caudal).

<3mm difference
between RPA Plan and
Clinical Plan for all
orthogonal directions.

Table 9: Head and Neck Summary of Statistical Results


Criteria
Inclusion Criteria
Exclusion Criteria
Sampling Method

Test datasets were chosen
going forward in time
until sufficient data was
collected, starting with CT
scans collected on January
1, 2022. If insufficient
patient scans were found,
data collection was
restarted with January 1,
2021 (for patients treated
in 2021) and so forth, until
sufficient data was
collected.

Clear CT image of head and/or neck
without distortions.

Test datasets consisted of CT images of
patients previously treated for head and
neck cancer using radiotherapy following
this treatment scheme:
i. VMAT or IMRT treatments
ii. 1-3 dose levels in the prescription

Scan was obtained with patient head-first,
supine.

The datasets included CT images, original
clinical contours of anatomic structures and
treatment targets, and the dose distributions
used for patient treatment.

Test datasets were chosen going forward in
time until sufficient data was collected,
starting with CT scans collected on January
1, 2022. If insufficient patient scans were
found, data collection could be restarted
with January 1, 2021 (for patients treated in
2021) and so forth, until sufficient data was
collected.

Testing datasets were unique, with no
overlap with data used for model creation
or in previous validation studies.

CT scans included the manufacturer and
model of the scanner used to obtain the CT
image or were recorded separately.

Table 10: Head and Neck Protocol Summary


Assess the safety of using the RPA plan for normal structures by
comparing the number of patient plans that pass accepted dosimetric
metrics when assessed on the RPA contour with the number that pass
when assessed on the clinical contour. The difference should be 5% or
less. When there are multiple metrics for a single structure at least one
should pass this criterion.

<6% difference
between RPA Plan and
Clinical Plan for all
assessed structures
(Right and Left
Lens)*.

Assess the effectiveness of the RPA plan for normal structures by
comparing the number of RPA plans that pass accepted dosimetric metrics
when compared with clinical plans. The difference should be 5% or less.
When there are multiple metrics for a single structure at least one should
pass this criterion.

<9% difference
between RPA Plan and
Clinical Plan for all
assessed structures
(Right and Left
Lens)**.

Assess the effectiveness of the RPA plan for target structures by
comparing the number of RPA plans that pass accepted dosimetric metrics
(e.g., percentage volume of the brain receiving 95% of the prescribed
dose) when compared with clinical plans. The difference should be 5% or
less. When there are multiple metrics used to assess a single structure, at
least one coverage and one maximum criterion should pass this criterion.

<5% difference
between RPA Plan and
Clinical Plan for all
assessed structures.

Assess the quality of body contouring generated by the RPA by
comparing primary and secondary body contours generated by the RPA
with manual body contours. Surface DSC (2mm) should be greater than
0.8 for 95% of the CT scans.

> 0.8 difference
between RPA Plan and
Clinical Plan for all
assessments.

Assess the ability of the RPA to accurately identify the marked isocenter.
This is achieved by comparing the automatically generated isocenters with
manually generated ones. 95% of automatically generated marked
isocenters (primary and verification approaches) should agree with
manually generated marked isocenters within 3mm in all orthogonal
directions.

<3mm difference
between RPA Plan and
Clinical Plan for all
orthogonal directions.

Table 11: Whole Brain Summary of Statistical Results


Criteria
Inclusion Criteria
Exclusion Criteria
Sampling Method

Test datasets were chosen
going forward in time
until sufficient data was
collected, starting with CT
scans collected on January
1, 2022. If insufficient
patient scans were found,
data collection was
restarted with January 1,
2021 (for patients treated
in 2021) and so forth, until
sufficient data was
collected.

Clear CT image of the head/neck region
without distortions.

Test datasets consisted of CT images of
patients previously treated for whole brain
radiotherapy following one of the following
treatment schemes:
i. Opposed laterals or slight obliques.

Scan was obtained with patient head-first,
supine.

The datasets included CT images, original
clinical contours of anatomic structures and
treatment targets, and the dose distributions
used for patient treatment.

Test datasets were chosen going forward in
time until sufficient data was collected,
starting with CT scans collected on January
1, 2022. If insufficient patient scans were
found, data collection could be restarted with
January 1, 2021 (for patients treated in 2021)
and so forth, until sufficient data was
collected.

Testing datasets were unique, with no
overlap with data used for model creation or
in previous validation studies.

CT scans included the manufacturer and
model of the scanner used to obtain the CT
image.


DHT8B: Division of Radiological Imaging Devices and

Office of Product Evaluation and Quality

Center for Devices and Radiological Health


Axial3D Cloud Segmentation Service
Axial Medical Printing Limited
K221511


Axial3D Insight
Segmentation
Mimics InPrint

Device Name
Axial3D Insight
Axial3D Insight
Mimics inPrint

Automated
Radiological Image
Processing Software

Medical image
management and
processing
system

Picture archiving
and
communications
system

Different –
Updated based
on additional
processing

Axial3D Insight is
intended for use as a
cloud-based service
and image
segmentation
framework for the
transfer of DICOM
imaging information
from a medical
scanner to an output
file.

Axial3D Cloud
Segmentation
Service is
intended for use
as a cloud based
service and
image
segmentation
system for the
transfer of
DICOM imaging

Mimics inPrint is
intended for use
as a software
interface and
image
segmentation
system for the
transfer of
DICOM imaging
information from
a medical

Table 5-2 – Predicate Device Comparison: Intended Use


The Axial3D Insight
output file can be
used for the
fabrication of
physical replicas of
the output file using
additive
manufacturing
methods.
The output file or
physical replica can
be used for treatment
planning.
The output file or
physical replica can
be used for
diagnostic purposes
in the field of trauma,
orthopedic,
maxillofacial, and
cardiovascular
applications.
Axial3D Insight
should be used with
other diagnostic tools
and expert clinical
judgment.

information from
a medical
scanner to an
output file.
The Axial3D
Cloud
Segmentation
Service output
file can be used
for the fabrication
of physical
replicas of the
output file using
additive
manufacturing
methods.
The output file or
physical replica
can be used for
treatment
planning.
The physical
replica can be
used for
diagnostic
purposes in the
field of
orthopedic,
maxillofacial and
cardiovascular
applications.
Axial3D Cloud
Segmentation
Service should
be used in
conjunction with
other diagnostic
tools and expert
clinical judgment.

scanner to an
output file. It is
also used as pre-
operative
software for
treatment
planning. For this
purpose, the
Mimics inPrint
output file can be
used for the
fabrication of
physical replicas
of the output file
using traditional
or additive
manufacturing
methods.
The physical
replica can be
used for
diagnostic
purposes in the
field of
orthopedic,
maxillofacial, and
cardiovascular
applications.
Mimics inPrint
can be used for
diagnostic
purposes in the
field of
orthopedic,
maxillofacial, and
cardiovascular
applications.
Mimics inPrint
should be used in
conjunction with


other diagnostic
tools and expert
clinical
judgement.

Axial Medical
Printing Limiteds,
Axial3D Insight
provides patient-
specific 1:1 scale
replica models, either
as a digital file or as
a 3D printed physical
model.
The digital file or 3D
printed physical
model is intended to
be used in
conjunction with the
DICOM images and
expert clinical
judgement. The
applications for using
the physical 3D
printed physical
model as a
presurgical planning
tool are as follows:
Preoperative
planning of surgical
treatment options
including planning for
surgical instruments,
aiding decisions on
implants, and aiding
the surgical
treatment plan., All
planning using the
3D replica model
should be carried out

Axial3D Cloud
Segmentation
Service is
intended for use
as a cloud based
service and
image
segmentation
system for the
transfer of
DICOM imaging
information from
a medical
scanner to an
output file.
The Axial3D
Cloud
Segmentation
Service output
file can be used
for the fabrication
of physical
replicas of the
output file using
additive
manufacturing
methods.
The output file or
physical replica
can be used for
treatment
planning.
The physical
replica can be
used for

Mimics inPrint is
intended for use
as a software
interface and
image
segmentation
system for the
transfer of
DICOM imaging
information from
a medical
scanner to an
output file. It is
also used as pre-
operative
software for
treatment
planning. For this
purpose, the
Mimics inPrint
output file can be
used for the
fabrication of
physical replicas
of the output file
using traditional
or additive
manufacturing
methods. The
physical replica
can be used for
diagnostic
purposes in the
field of
orthopedic,
maxillofacial and


with the assistance
of the DICOM
images
Communication with
the surgical team to
discuss the surgical
treatment plan in
conjunction with
DICOM images
Communication with
the patient to discuss
the surgical
treatment plan in
conjunction with
DICOM images
Education tool for
surgical planning.
The 3D printed
physical model can
be used for surgical
planning in the
following
applications:
orthopedics and
trauma, maxillofacial,
and cardiovascular
surgery.

diagnostic
purposes in the
field of
orthopedic,
maxillofacial and
cardiovascular
applications.
Axial3D Cloud
Segmentation
Service should
be used in
conjunction with
other diagnostic
tools and expert
clinical judgment.

cardiovascular
applications.
Mimics inPrint
should be used in
conjunction with
other diagnostic
tools and expert
clinical
judgement.

Used in conjunction
with other diagnostic
tools and expert
clinical judgement.

Environment Hospital Hospital Hospital Equivalent


Axial3D Insight
Segmentation
Mimics InPrint


Attribute (Proposed Service (Reference Comparison

substantial
equivalence
as the output
of the
proposed
device and
predicate
devices is
equivalent.

The proposed
device uses a
subset of the
predicate
device image
modalities

A combination of
automated tools
with smart editing
tools

Combination of
automated tools
with smart editing
tools

Orthopedics /
Trauma
Cardiovascular
Cranio-
Maxillofacial

Orthopedics /
Trauma
Cardiovascular
Cranio-Maxillofacial

Region/volume
of interest
measurements
and size
measurements


Lightspeed Pro 16
Lightspeed Pro 32
Revolution CT
Optima CT660
Discovery CT750 HD

SOMATOM Definition Flash
SOMATOM Definition Edge
SOMATOM Definition AS
SOMATOM Definition AS+
SOMATOM Perspective

Table 5-5 – Imaging scanner manufacturers and models used for the validation datasets


SOMATOM Force
Sensation 16
AXIOM-Artis
Emotion 16

IQON Spectral CT
iCT 128
iCT 256
Ingenuity Core 128
Brilliance 62


The Overjet Caries Assist 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 information from the
image, patient history, or actual in
vivo clinical assessment.

Overjet Caries Assist (OCA) is a
radiological, automated, concurrent read,
computer-assisted detection (CADe)
software intended to aid in the detection
and segmentation of caries on bitewing
and periapical 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
information from the image, patient
history, or actual in vivo clinical
assessment.

Patients requiring dental services, all
sexes, 18 years of age or older

Patients requiring dental services, all
sexes, 12 years of age or older with
permanent teeth

Platform
Web - Edge, Chrome, Firefox
Web - Edge, Chrome, Firefox

User Interface
Mouse, Keyboard, Trackpad
Mouse, Keyboard, Trackpad

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

Images imported from the radiographic
device, or from the practice management
system from multiple sensor
manufacturers

Image format
jpg, png, eop, jif, dicom
jpg, png, eop, tiff, dicom


Three layers:
1 - The Network layer works
with the practice PACS or EMR
to transmit the image and meta-
data to Overjet.
2 - The decision layer processes
the image to ensure it is the correct
data type, and then annotates it via
the algorithm
3 - The presentation layer displays
the annotated image in a non-
diagnostic viewer. The dentist can
filter, display, hide, create and edit
the annotations presented.

Three layers:
1 - The Network layer works
with the practice PACS or EMR to
transmit the image and meta-data to
Overjet.
2 - The decision layer processes the
image to ensure it is the correct data
type, and then annotates it via the
algorithm
3 - The presentation layer displays
the annotated image in a non-diagnostic
viewer. The dentist can filter, display,
hide, create and edit the annotations
presented.

Digital files of bitewing radiographs
whose longer edge is greater than 500
pixel resolution.

Digital files of bitewing and periapical
radiographs whose longer edge is greater
than 500 pixel resolution.

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

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

Increase in dentist’s sensitivity of
greater than 15%


The uMR 680 system is indicated
for use as a magnetic resonance
diagnostic device (MRDD) that
produces sagittal, transverse,
coronal, and oblique cross
sectional images, and
spectroscopic images, and that
display internal anatomical
structure and/or function of the
head, body and extremities.
These images and the physical
parameters derived from the
images when interpreted by a
trained physician yield
information that may assist the
diagnosis. Contrast agents may be
used depending on the region of
interest of the scan.

The uMR 570 system is indicated
for use as a magnetic resonance
diagnostic device (MRDD) that
produces sagittal, transverse,
coronal, and oblique cross
sectional images, and
spectroscopic images, and that
display internal anatomical
structure and/or function of the
head, body and extremities.
These images and the physical
parameters derived from the
images when interpreted by a
trained physician yield
information that may assist the
diagnosis. Contrast agents may be
used depending on the region of
interest of the scan.

Table 1 Comparison of Hardware configuration


Sha
nghai United Imaging
Healthcare Co., Ltd.

Type of
Actively shielded,
OIS
Actively shielded,
O
IS

Magnet
0.45ppm @ 40cm
D
SV
0.72ppm @ 40cm
D
SV

Homogeneity
0.190ppm @ 30cm
DSV
0.420ppm @ 30cm
DSV

Shanghai United Imaging Healthcare Co., Ltd.


patient weight
Dockable Patient Table:
No
Note


Support
ECG/Respiratory/Pulse signal
triggering the scan


The homogeneity of the magnet is equal or better at typical DSVs thus the clinical
scanning of the proposed device is not limited compared to the predicate device.

More receive channels allow the proposed device to use new high-channel count and
bigger coverage receive coils.

The RF Amplifier power is just one of the influence factors to affect the B1 field,
other influence factors such as efficiency of transmitting coil, damping of
transmitting chain, the distance between coil and target location will also affect the
intensity of B1 field, and the intensity of B1 field can be adjusted by different
sequences. Generally the target B1 field is achieved by system calibration
procedures and the required RF power is always less than the maximum RF
Amplifier power output, so this difference from predicate device will not affect the
system effectiveness, and the system safety is explained in device description and
verified by the third party safety report.

Compared to the predicate device, the proposed device removes Head & Neck Coil -
16 but adds Head & Neck Coil -24. The intended use of Head & Neck Coil -24 is
equivalent to previously cleared Head & Neck Coil -16. More coil elements in the
new coil allow larger coverage for bigger patient.

Compared to the predicate device, the proposed device removes Spine Coil - 24 but
adds Spine Coil - 32. The intended use of Spine Coil - 32 is equivalent to previously
cleared Spine Coil - 24. More coil elements in the new coil allow larger coverage for
bigger patient.

Compared to the predicate device, the proposed device removes Body Array Coil-6
but adds Body Array Coil-24. The intended use of Body Array Coil-24 is equivalent
to previously cleared Body Array Coil-6. More coil elements in the new coil allow
larger coverage for bigger patient.

Compared to the predicate device, the proposed device removes Head Coil – 12 and
Head Coil – 24. The intended use of Head Coil can be overridden by Head & Neck
Coil -24, so this difference from predicate device will not affect the system
effectiveness.

Compared to the predicate device, the proposed device removes Flex Coil Large - 4
but adds Flex Coil Large - 8. The intended use of Flex Coil Large - 8 is equivalent to
previously cleared Flex Coil Large - 4. More coil elements in the new coil allow
larger coverage for bigger patient.

Compared to the predicate device, the proposed device removes Flex Coil Small - 4
but adds Flex Coil Small - 8. The intended use of Flex Coil Small - 8 is equivalent to
previously cleared Flex Coil Small - 4. More coil elements in the new coil allow
larger coverage for bigger patient.

The proposed device adds Infant Coil-24 to facilitate the exam of infant.

The intended use of SuperFlex Large - 12 is essentially identical to previously
cleared Flex Coil Large - 8. The differences are the number of channels of the coil

triggering the scan signal triggering the scan


The intended use of SuperFlex Small - 12 is essentially identical to previously
cleared Flex Coil Small - 8. The differences are the number of channels of the coil
and the material used on the surface of the coil. More coil elements in the new coil
can better cover the scanning parts and the flexible material is beneficial to wrap the
scanning parts.

The intended use of SuperFlex Body - 24 is essentially identical to previously
cleared Body Array Coil - 12. The differences are the number of channels of the coil
and the material used on the surface of the coil. More coil elements in the new coil
can better cover the scanning parts and the flexible material is beneficial to wrap the
scanning parts.

The proposed device adds Dockable Patient Table to facilitate patient transfer and
have a higher load capacity.


Non-uniformity correction is used for
correcting image intensity non-
uniformity caused by transmit field or
receive field.

Distortion correction is used for
correcting the distortion caused by the
non-linear gradient field in image
domain.

Image filter is used for denoising,
enhancement and edge smoothness.

WFI is short for water fat imaging and
separates water and fat signal according
to chemical shift effect.

Susceptibility Weighted Imaging (SWI)
uses high-pass filter to generate local
phase map, then it is multiplied onto the
magnitude data to generate SWI image.

PC combines two images with flow
encoding and without flow encoding to
achieve angiography imaging.

GETI is short for gradient echo train
imaging. It combines multi-echo images
by sum-of-square to generate hybrid
T2* contrast.

Apparent diffusion coefficient (ADC)
fits logarithm-linear least squares model
to represent water molecular diffusion
motion by DWI technique.

Table 2 Comparison of the new Application Software Features


FACT is short for fat analysis and
calculation technique and substantially
equivalent to WFI. It not only separates
water and fat signal and quantifies fat
fraction and R2* mapping according to
chemical shift effect and T2* effect.

PSIR is substantially equivalent to FFT
reconstruction and acquire real image
from two TI(time-inversion) images
which is benefit for more stable
contrast.

cDWI is substantially equivalent to
DWI and generates fitting b-value from
multiple acquisition b values.

Inline T1/T2* Map is substantially
equivalent to T1/T2* Map processed by
post-processing module. The map result
displays inline without extra operation
by post-processing module.

Inline T2 Map is substantially
equivalent to T2 Map processed by
post-processing module. The map result
displays inline without extra operation
by post-processing module.

SWI+ is substantially equivalent to SWI
and acquires multi-echo to achieve more
information than SWI.

ASL is substantially equivalent to FSE
and uses extra arterial spin labeling
preparation and imaging processing for
cerebral blood flow (CBF) imaging
without contrast agent.

FQ is substantially equivalent to GRE
and uses extra flow encoding and
imaging processing for flow
quantification.

Cardiac T1 mapping is substantially
equivalent to GRE and uses multiple TI
acquisitions with IR preparation and
imaging processing for cardiac T1
mapping.

Cardiac T2 mapping is substantially
equivalent to GRE and uses multiple
T2-prep duration preparation
acquisitions and imaging processing for
cardiac T2 mapping.

Cardiac T2* mapping is substantially
equivalent to GRE and uses multiple TE
acquisitions and imaging processing for
cardiac T2* mapping.

DeepRecon is a deep-learning based
image processing algorithm for image


de-noising and K-space-interpolation
based image super-resolution.

QScan is short for quiet scan. It doesn’t
change the sequence mechanism and
only optimizes gradient waveform to
reduce MR scan acoustic noise.

EasyScan feature allows automatic slice
positioning for Head, cardiac, c-spine, t-
spine, l-spine, shoulder, abdomen and
knee imaging. The positioning can also
be adjusted manually by user. The final
positioning effect is equivalent to
manual operation without EasyScan
feature.

Remote Assistance intends for remote
support and service.

In MR conditional implant mode，user
can set the safety conditions of the MR
conditional implant, and uMR 680
system ensure the scanning complies
with the conditions.

Liver spectroscopy is substantially
equivalent to Spectroscopy and uses
multi-echo acquisition and post-
processing instead of single echo for fat
quantification of liver.

Prostate spectroscopy is substantially
equivalent to Spectroscopy and uses
characteristic metabolites detection post
processing for prostate spectroscopy.

Breast spectroscopy is substantially
equivalent to Spectroscopy and uses
characteristic metabolites detection post
processing for breast spectroscopy.


Table a. DeepRecon American Volunteers' Demographic Distribution


DeepRecon images achieve higher
SNR compared to the images
without DeepRecon (NADR)

Uniformity difference between
DeepRecon images and NADR
images under 5%

DeepRecon images achieve 10% or
higher resolution compared to the
NADR images

Intensity difference between
DeepRecon images and NADR
images under 5%

Measurements on NADR and
DeepRecon images of same
structures, measurement difference
under 5%

Table b. The performance evaluation report criteria of DeepRecon


oncologists, and dosimetrists). This device is for prescription use by order of a physician.


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 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).

Oncospace is used to
configure and review
radiotherapy treatment plans
for a patient with malignant or
benign disease in the prostate,
thoracic, pancreas, or head &
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).

Removed
thoracic and
pancreas since
plan-matching
methodology
was removed.
Prostate, head,
and neck use the
ML models.


oncologists, and dosimetrists). oncologists, and dosimetrists).


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.

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.


1812 Ashland Ave., Suite 100K
Baltimore, MD 21205 USA


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. Comparison 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.


glands, left and right cochlea, thyroid gland, and pharyngeal constrictor muscle(s). For the head


Primary Predicate:
Aquilion Lightning
(TSX-036A/7) V10.2
with AiCE-i

JAK:
System, X-ray,
Tomography,
Computed

Reference Predicate:
Aquilion Prime SP
(TSX-303B/8) V10.2
with AiCE-i


Device Name,
Aquilion Serve
Aquilion Lightning

Model Number
(TSX-307A/1) V1.2 with AiCE-i
(TSX-036A/7) V10.2 with AiCE-i

Conventional scan (Axial Scan*)
Volume, Dynamic volume scan
Helical scan

Conventional scan (S&S, S&V)
Volume, Dynamic volume scan
Helical scan

*: S&V is not
supported
S&S is called
“Axial Scan”


Positioning:
Single
Dual
3D Landmark Scan

3D Landmark Scan
Available
Not Available

*: If 3D Landmark
Scan is set in a
scan protocol.

[Conventional scan (Axial scan)]
4-row scan: 0.5, 1, 2, 3, 4, 5, 8
mm
1-row scan: 1 mm
[Volume, Dynamic volume scan]
(80-row scan*: 0.5 mm)
40-row scan: 0.5 mm
[Helical scan]
(80-row scan*: 0.5 mm)
40-row scan: 0.5 mm and 1 mm
20-row scan: 0.5 mm
4-row scan: 0.5 mm
[3D Landmark Scan]
40-row scan: 1.0 mm

[Conventional scan (S&S, S&V)]
4-row scan: 0.5, 1, 2, 3, 4, 5, 8,
10 mm
1-row scan: 1 mm
[Volume, Dynamic volume scan]
(80-row scan*: 0.5 mm)
40-row scan: 0.5 mm and 1 mm
4-row scan: 8 mm and 10 mm
[Helical scan]
(80-row scan*: 0.5 mm)
40-row scan: 0.5 mm and 1 mm
20-row scan: 0.5 mm and 1 mm
4-row scan: 0.5 mm

Up to 30 images/s with AIDR 3D
(0.033 s/image)
Up to 50 images/s with AIDR 3D
(0.02 s/image)*1
Up to 70 images/s with AIDR 3D
(0.014 s/image)*2
Up to 100 images/s with AIDR 3D
(0.01 s/image)*3
(Depending on the scan and
reconstruction conditions)

Up to 20 images/s with AIDR 3D
(0.05 s/image)
Up to 50 images/s with AIDR 3D
(0.02 s/image) *2
(Depending on the scan and
reconstruction conditions)

*1: When the Fast
scan kit (CGS-
041A) is installed.
*2: Option
When the Fast
Image
Reconstruction kit
(CCFR-010A) is
installed.
*3: When the Fast
Image
Reconstruction kit
(CCFR-010A) and
the Fast scan kit
(CGS-041A) are
installed.


Three (3) types
･ Small
･ Large
･ SilverBeam Filter*

*Previously
cleared under
K213504
(TSX-306A)

Two cameras
mounted inside
the system at a
90-degree phase
difference.

Adaptive Iterative Dose
Reduction 3D (AIDR 3D)
AIDR 3D Enhanced
Advanced Intelligent Clear-IQ
Engine (AiCE)
Quantum Denoising Software
(QDS)

NewUX Console*
Display monitor
User Input
Data processor
Window width/level
Preset windows
Window types
ROI shape available

Available
27 inch (3840 x 2160)
Keyboard and Control Pad
(Performs scan operation and
controls voice messages)
CPU : 64-bit
Memory size: 64 Gbyte or more
Controlled and continuously
variable using the mouse
1/image
Linear only
Point, Circular

Not Available
19 inch (1280 x 1024)
Scan Keyboard
CPU : 64-bit
Memory size: 32 Gbyte or more
Controlled and continuously
variable using a speed-sensitive
rotary encoder
3/image
Linear and non-linear (6 user-
programmable), and double
windows
Point, square, free-form,
circular, polygon


CINA is a radiological computer
aided triage and notification
software indicated for use in the
analysis of (1) non-enhanced head
CT images and (2) CT
angiographies of the head. The
device is intended to assist hospital
networks and trained radiologists in
workflow triage by flagging and
communicating suspected positive
findings of (1) head CT images for
Intracranial Hemorrhage (ICH) and
(2) CT angiographies of the head
for large vessel occlusion (LVO).
CINA uses an artificial intelligence
algorithm to analyze images and
highlight cases with detected (1)
ICH or (2) LVO on a standalone
Web application in parallel to the
ongoing standard of care image
interpretation. The user is
presented with notifications for
cases with suspected ICH or LVO
findings. Notifications include
compressed preview images that
are meant for informational
purposes only, and are not intended
for diagnostic use beyond
notification. The device does not
alter the original medical image,
and it is not intended to be used as a
diagnostic device.
The results of CINA are intended to
be used in conjunction with other
patient information and based on
professional judgment to assist with
triage/prioritization of medical
images. Notified clinicians are
ultimately responsible for

Rapid NCCT Stroke is a
radiological computer aided triage
and notification software indicated
for use in the analysis of (1)
nonenhanced head CT (NCCT)
images. The device is intended to
assist hospital networks and trained
clinicians in workflow triage by
flagging and communicating
suspected positive findings of (1)
head CT images for Intracranial
Hemorrhage (ICH) and (2) NCCT
large vessel occlusion (LVO) of the
ICA and MCA-M1.
Rapid NCCT Stroke uses an
artificial intelligence algorithm to
analyze images and highlight cases
with detected (1) ICH or (2) NCCT
LVO on the Rapid server on
premise or in the cloud in parallel
to the ongoing standard of care
image interpretation. The user is
presented with notifications for
cases with suspected ICH or LVO
findings via PACS, email or mobile
device. Notifications include
compressed preview images that
are meant for informational
purposes only, and are not intended
for diagnostic use beyond
notification.
The device does not alter the
original medical image, and it is not
intended to be used as a primary
diagnostic device. The results of
Rapid NCCT Stroke are intended to
be used in conjunction with other
patient information and based on
professional judgment to assist with
triage/prioritization of medical

features of the subject and predicate devices is provided below.


images. Notified clinicians are
ultimately responsible for
reviewing full images per the
standard of care. Rapid NCCT
Stroke is for Adults only.
Cautions:
• All patients should get adequate
care for their symptoms including
CTA or MRA and/or other
appropriate care per the standard
clinical practice, irrespective of the
device output.
• The device is not intended to be a
rule-out device and for cases that
have been processed by the device
without notification for “Suspected
LVO” should not be viewed as
indicating that LVO is excluded.
All cases should undergo CTA or
MRA, per the standard stroke
workup.
Limitations:
• Rapid NCCT Stroke does not
replace the need for CTA in
ischemic stroke workup, it
provides workflow prioritization
and notification only.
• Rapid ICH has been shown to
reliably identify hemorrhages of ≥
0.4ml.
Contraindications/Exclusions/Cauti
ons:
• Patient Motion: excessive motion
leading to artifacts that make the
scan technically inadequate.
• Hemorrhagic Transformation,
Hematoma
• Very thin or no Ventricles

Input Data
NCCT (ICH) and CTA(LVO)
NCCT (ICH and LVO)

Technology
AI/ML/Neural Network
AI/ML/Neural Network

The device does not highlight or
direct a user’s attention to a specific
location in the image file.


Presentation of a preview of the
study for initial assessment not
meant for diagnostic purposes.
The device operates in parallel with
the standard of care.

Device does not mark, highlight, or
direct users’ attention to a specific
location in the original image

Two cascaded functions (ICH then
LVO) using three integrated
algorithms


Time to open in standard of
care (Minutes)

Time to notification of Rapid
NCCT Stroke (Minutes)

longer than the parallel time-to-notification of the Rapid NCCT Stroke software.


In 90% of the patients with image quality 3-5
by visual estimation it was possible to obtain
at least “Medium” quality score by LVivo IQS

93% of the above saved clips were clinically
interpretable


ITEM
Proposed Device
Predicate Device
Discussion

Rotation speed: up to
0.25s/rotation
82cm bore

40mm Detector
Material: Solid-state GOS
80 rows,
936 channels/row
Size of detector element in
Z-plane: 0.5mm

160mm Detector
Material: Solid-state GOS
320 rows,
936 channels/row
Size of detector element in
Z-plane: 0.5mm


Shanghai United Imaging He
althcare Co., Ltd.

I
TEM
Proposed Device
Predicate Device
Discussion

Anode heat capacity:
Anode heat capacity:

H
igh Voltage
80kW, 100kW(option)
100kW
Note 3

P
atient Table
Max load capacity
Max load capacity
Note 4

F
ield of View
40-600mm with extended
40-600mm with extended


Item
Proposed device
Predicate Device
Discussion

CNR(Contrast Noise Ratio) Image
Yes
Yes
Same

Water-Iodine Base Material Pair
Yes
Yes
Same

Water-Calcium Base Material Pair
Yes
Yes
Same

Calcium-Iodine Base Material Pair
Yes
Yes
Same

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

Table 2 Dual Energy comparison to Reference Devices


The detector dimension of the proposed device is shorter than that of the
predicate device. Detector rows of the proposed device is less than those of the
predicate device. The shorter detector Z-plane coverage, the longer scanning
time for CT imaging. The smaller number of rows, the less image information
obtained.
The difference did not raise new safety and effectiveness concerns.

The proposed device is configured with two different ranges of mA ranges. One
is same with the predicate device, one is smaller than the predicate device,
based on the x-ray tube hardware. Smaller mA output that induces lower ability
of x-ray penetration when scanning the object with high BMI with higher
possibility of photon starvation.
Focal spot size of the proposed device is smaller than that of the predicate
device. Smaller size is helpful for the improvement of resolution.
The differences did not raise new safety and effectiveness concerns.

The proposed device is configured with two kinds of Maximum Output Power.
One is same with the predicate device, one is smaller than the predicate device.
Smaller power, lower mA or kV level in X-ray.
The differences did not raise new safety and effectiveness concerns.

The proposed device is configured with two kinds of patient table. One is same
with the predicate device, one is with lower load capacity than the predicate
device. The two tables being a major component of the proposed device
conform to the safety standards such as IEC 60601-1 series and satisfy the
clinical use.
The difference did not raise new safety and effectiveness concerns.

Maximum slices generated per rotation of the proposed device is less than those
of the predicate device. The less slices, the longer scanning time for CT
imaging.
The difference did not raise new safety and effectiveness concerns.

The predicate device can use this function both on axial scan mode and helical
scan mode. The proposed device only can use this function on helical scan
mode.
The difference did not raise new safety and effectiveness concerns.

Virtual Non contrast Images Yes Yes Same


SIS System version
SIS System version
Comparison

SIS System is intended
for use in the viewing,
presentation and
documentation of
medical imaging,
including different
modules for image
processing, image
fusion, and
intraoperative functional
planning where the 3D
output can be used with
stereotactic image
guided surgery or other
devices for further
processing,
visualization and
localization. The device
can be used in
conjunction with other
clinical methods as an
aid in visualization and
location of the
subthalamic nuclei
(STN) and globus
pallidus externa and
interna (GPe and GPi,
respectively) in
neurological
procedures. The system
is indicated for surgical
procedures in which
anatomical structure
locations are identified
in images, including
Deep Brain Stimulation
Lead Placement.
Typical users of the SIS
Software are medical
professionals, including
but not limited to
surgeons, neurologists
and radiologists.

SIS System is an
application intended for
use in the viewing,
presentation and
documentation of
medical imaging,
including different
modules for image
processing, image
fusion, and
intraoperative functional
planning where the 3D
output can be used with
stereotactic image
guided surgery or other
devices for further
processing and
visualization. The
device can be used in
conjunction with other
clinical methods as an
aid in visualization of
the subthalamic nuclei
(STN) and globus
pallidus externa and
interna (GPe and GPi,
respectively).
Typical users of the SIS
System are medical
professionals, including
but not limited to
surgeons, neurologists
and radiologists.

Similar. Addition of
clarifying statement
(about use in medical
procedures in which
anatomical structure
locations such as STN,
GPe and GPi are
identified in images,
including deep brain
stimulation lead
placement) does not
raise different questions
of safety or
effectiveness because
predicate was already
intended for use in such
procedures and other
reference devices (e.g.,
StealthStation with
Cranial Software,
K153660) with similar
functions include this
language.

Medical professionals,
including but not limited
to surgeons,
neurologists and
radiologists.

Allows for importing
of digital imaging sets


Uses proprietary
software algorithm to
generate 3D
segmented anatomical
models from patient’s
MR scans

Allows for review and
analysis of data in 2D
and 3D formats

Performs image fusion
of datasets using
automated or manual
image matching
technique

Segments structures
in images with manual
and automated tools
and converts them
into 3D objects for
display

Creates hybrid
datasets by filing in
segmented regions
slice-by-slice on
anatomical datasets

Segmentation of CT
scan to identify
structures in relation
to those visualized on
MR

Feature to Account for
CT images with gantry
tilt

Cross-registers
images and creates 3D
(fused) model

Uses registration
methods (linear and
non-linear) by multiple
registration tools
(ANTS and ELASTIX)


Manufacturer
Device Name
Application No.


Viz LVO is a notification-only, parallel workflow
tool for use by hospital networks and trained
clinicians to identify and communicate images of
specific patients to a specialist, independent of
standard of care workflow.
Viz LVO uses an artificial intelligence algorithm to
analyze images for findings suggestive of a pre-
specified clinical condition and to notify an
appropriate medical specialist of these findings in
parallel to standard of care image interpretation.
Identification of suspected findings is not for
diagnostic use beyond notification. Specifically,
the device analyzes CT angiogram images of the
brain acquired in the acute setting, and sends
notifications to a neurovascular specialist that a
suspectedlarge vessel occlusion has been
identified and recommends review of those
images. Images can be previewed through a
mobile application. Viz LVO is intended to analyze
terminal ICA and MCA-M1 vessels for LVOs.
Images that are previewed through the mobile
application are compressed and are for
informational purposes only and not intended for
diagnostic use beyond notification. Notified
clinicians are responsible for viewing non-
compressed images on a diagnostic viewer and
engaging in appropriate patient evaluation and
relevant discussion with a treating physician
before making care-related decisions or requests.
Viz LVO is limited to analysis of imaging data and
should not be used in-lieu of full patient evaluation
or relied upon to make or confirm diagnosis.

ContaCT is a notification-only, parallel workflow
tool for use by hospital networks and trained
clinicians to identify and communicate images of
specific patients to a specialist, independent of
standard of care workflow.
ContaCT uses an artificial intelligence algorithm
to analyze images for findings suggestive of a
pre-specified clinical condition and to notify an
appropriate medical specialist of these findings in
parallel to standard of care image interpretation.
Identification of suspected findingsis not for
diagnostic use beyond notification. Specifically,
the device analyzes CT angiogram images of the
brain acquired in the acute setting, and sends
notifications to a neurovascular specialist that a
suspected large vessel occlusion has been
identified and recommends review of those
images. Images can be previewed through a
mobile application.
Images that are previewed through the mobile
application are compressed and are for
informational purposes only and not intended for
diagnostic use beyond notification. Notified
clinicians are responsible for viewing non-
compressed images on a diagnostic viewer and
engaging in appropriate patient evaluation and
relevant discussion with a treating physician
before making care-related decisions or
requests. ContaCT is limited to analysis of
imaging data and should not be used in-lieu of
full patient evaluation or relied upon to make or
confirm diagnosis.

Table 1: Substantial Equivalence Table Comparing Subject and Predicate Devices


Intended User
Neurovascular Specialist
Neurovascular Specialist

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

Initial assessment; non-diagnostic purposes

DICOM Information about the patient, study and
current image.


Brainlab AG; Olof-Palme Str.9; 81829, Munich, Germany

• Brainlab Elements Image Fusion
• Brainlab Elements Image Fusion Angio
• Brainlab Elements Contouring
• Brainlab Elements BOLD MRI Mapping
• Brainlab Elements Fibertracking

Medical image management and processing system

K212420
Brainlab Elements, Brainlab Elements Contouring (4.0), Brainlab
Elements Fibertracking (2.0), Brainlab Elements Image Fusion
(4.0), Brainlab Elements Image Fusion Angio (1.0)

K113732
iPlan (iPlan Cranial, iPlan Stereotaxy, iPlan ENT, iPlan CMF, iPlan
View, iPlan Spine)

Marc Bergenthal
Manager Regulatory Affairs
Regulatory Affairs
Phone: +49 89 99 15 68 0
Email: regulatory.affairs@brainlab.com

Sadwini Suresh
QM Consultant
Phone: +49 89 99 15 68 0
Email: regulatory.affairs@brainlab.com


Brainlab Elements, Brainlab Elements Contouring (4.5), Brainlab
Elements Fibertracking (2.0), Brainlab Elements Image Fusion (4.5),
Brainlab Elements Image Fusion Angio (1.0), Brainlab Elements BOLD
MRI Mapping (1.0)

devices. An overview of the similarities and differences can be found in the tables below:


Brainlab Elements, Brainlab Elements Contouring (4.0), Brainlab
Elements Fibertracking (2.0), Brainlab Elements Image Fusion (4.0),
Brainlab Elements Image Fusion Angio (1.0)

iPlan (iPlan Cranial, iPlan Stereotaxy, iPlan ENT, iPlan CMF, iPlan View,
iPlan Spine)


Primary Predicate Device
(Brainlab Elements Image Fusion
4.0 (K212420))

Subject Device (Brainlab
Elements Image Fusion 4.5)

Brainlab Elements Image Fusion
is an application for the co-
registration of image data within
medical procedures by using
rigid and deformable registration
methods. It is intended to align
anatomical structures between
data sets.
The device itself does not have
clinical indications.

Brainlab Elements Image
Fusion is an application for
the co-registration of image
data within medical
procedures by using rigid
and deformable registration
methods. It is intended to
align anatomical structures
between data sets.
The device itself does not
have clinical indications.

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

Brainlab Elements can be used
on hardware that fulfills the
defined minimum requirements:
- Operating System:
Windows 8.1 64bit
- Minimum 4 logical cores
- Minimum RAM: 6 GB
- Graphics: Direct X
compatible


- Minimum RAM: 6
GB
- Graphics: Direct X
compatible
- Display Resolution:
1920 x 1080 (Full HD)

DICOM 3D imaging Modalities,
e.g. CT/XT, MRI, NM/PET, OT,
are supported for automatic
fusion.
Other modalities are supported
for manual fusion (alignment)

Rigid co-
registration, rigid
image fusion

Automatic rigid co-registration
(rigid fusion) of 3D DICOM image
data: CT (incl. low-dose CT), MR,
OT (e.g. Perfusion), MR-DTI, MR-
BOLD, NM/PET
Manual rigid co-registration (rigid
fusion) of other (unknown) 3D
DICOM image data, e.g. US
(ultrasound).

Automatic rigid co-
registration (rigid fusion) of
3D DICOM image data: CT
(incl. low-dose CT), MR, OT
(e.g. Perfusion), MR-DTI,
MR-BOLD, NM/PET, US
(ultrasound).
Manual rigid co-registration
(rigid fusion) of other
(unknown) 3D DICOM
image data.

The subject device
additionally
provides
functionality to
automatically fuse
US to MR images.
Safety and efficacy
of this feature was
verified via Risk
Management and
Verification
activities.


Brainlab Elements Contouring
provides an interface with tools
and views to outline, refine,
combine and manipulate
structures in patient image data.
The generated 3D structures are
not intended to create physical
replicas used for diagnostic
purposes.


used for diagnostic
purposes.
The device itself does not
have clinical indications

The application automatically
creates segmentation objects
provided by the Universal Atlas.
Workflow relevant segmentation
objects are created automatically
or, if required by a workflow, on
a single button click.
The application also offers the
possibility to define customized
segmentation templates.

Manual Creation
and Refinement of
Objects

The application provides tools for
the manipulation of objects:
The application provides tools for
manual creation and refinement
of segmentation objects:
- SmartShaper
- Brush 3D / Erase 3D
- Brush 2D / Erase 2D
- Smart Brush
- Threshold Segmentation

The application provides tools for
the manipulation of objects:
- Copy


- Copy
- Margins
- Smoothing
- Mirroring
- Shifting and
Rotation
- Splitting
- Automatic Object
Fitting

The application provides
functionality to control the review
state of objects. In case of
leaving the application with
unreviewed semi-automatically
or automatically created objects,
a message is displayed.

It is possible to create a printable
report for an object in a platform
independent file format, giving
information about the object's
volume, its diameter according to
the Macdonald criteria and its
response evaluation criteria
(RECIST).
If multiple objects are selected
and a volumetric report is
created, it contains information
about all objects.


Lung lesion detection using marked
regions of interest (ROIs)

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

Adults with Chest Radiographs
Adults with Chest Radiographs

Digital X-rays in DICOM format
Digital X-rays in DICOM format

Information for ROI to be
marked on the duplicated
input image

Secure cloud-based processing and
delivery of outputs

Secure on-premise processing
and delivery of outputs


Characteristic
New Device
Predicate Device

AIRAscore is intended for automatic
labeling, visualization and volumetric
quantification of segmentable brain
structures from a set of MR images. This
software is intended to automate the
current manual process of identifying,
labeling and quantifying the volume of
segmentable brain structures identified
on MR images.

icobrain is intended for automatic
labeling, visualization and volumetric
quantification of segmentable brain
structures from a set of MR or NCCT
images. This software is intended to
automate the current manual process
of identifying, labeling and quantifying
the volume of segmentable brain
structures identified on MR or NCCT
images.
icobrain consists of two distinct image
processing pipelines: icobrain cross
and icobrain long.
icobrain cross is intended to provide
volumes from images acquired at a
single timepoint. icobrain long is
intended to provide changes in
volumes between two images that
were acquired on the same scanner,


with the same image acquisition
protocol and with the same contrast at
two different timepoints. The results of
icobrain cross cannot be compared
with the results of icobrain long.

 AIRAscore is a software as medical
device (SaMD) that runs on
AIRAmed internal servers (Software
as a Service - SaaS).
For sending and receiving DICOM
data dedicated interfaces are
supplied as accessory.
 Operates on off-the-shelf hardware
(multiple vendors)
 DICOM compatible
 Segmentation by machine learning
(supervised voxel classification by a
Convolutional Neuronal Network)
Input:
 T1-weighted and (optional) fluid-
attenuated inversion recovery
(FLAIR) MR images from a single
time point
Output:
 Multiple electronic report with
volumetric information of brain
structures (Encapsulated PDF
DICOM)
 Annotated DICOM images for visual
inspection by an expert (Secondary
Capture DICOM)

 Software package
 Operates on off-the-shelf hardware
(multiple vendors)
 DICOM compatible
 Segmentation by classical machine
learning and deep learning
(supervised voxel classification by a
Convolutional Neuronal Network)
Input:
 T1-weighted and fluid-attenuated
inversion recovery (FLAIR) MR
images from a single or multiple
time points
 Non-contrast CT from a single time
point
Output:
 Multiple electronic reports with
volumetric information of brain
structures and midline shift
 Annotated DICOM images

Accuracy
 Brain segmentable structure volumes
/ volume changes compared to
manually labeled ground truth
Reproducibility
 Brain segmentable structure volumes
/ volume changes compared on test-
retest images

Accuracy
 Brain segmentable structure
volumes / volume changes
compared to simulated and/or
manually labeled ground truth
Reproducibility
 Brain segmentable structure
volumes / volume changes
compared on test-retest images

Primary users of the system are
physicians with finished course of
studies, medical license and expert
knowledge in neuroanatomy and MR-
imaging of the head. The reports and
control images are looked at and
evaluated in a professional healthcare
setting (diagnostic workstation or
doctor’s office).

icobrain is used by trained
professionals in hospitals, imaging
centers or in image processing labs.

• Product Risk assessment
• Software verification tests
• Software validation tests

• Product Risk assessment
• Software verification tests
 Software validation tests


GE Medical Systems Israel, Functional Imaging


Proposed Device
Precision DL
on Omni Legend

Iterative non-ToF image
reconstruction algorithm

Deep learning-based image
processing trained to enhance non-
ToF images to have IQ performance
similar to ToF images.


Level P, 24 Campbell Street
Sydney, NSW 2000
Australia


Device Name
Annalise Enterprise CTB Triage Trauma

Radiological computer aided triage and notification software
(21CFR892.2080)


Infervision Medical Technology Co., Ltd.


Finding
Slice Thickness Range
Operating Point


Attribute
Subject BrainInsight
Predicate BrainInsight (K220815)

BrainInsight is intended for automatic labeling,
spatial measurement, and volumetric
quantification of brain structures from a set of
low-field MR images and returns annotated and
segmented images, color overlays and reports.

● Adult and pediatric (≥ 2 years) - Lateral
ventricles and midline shift applications
● Adult (≥ 18 years) - Whole brain application

Adult (≥ 18 years) - Lateral ventricles,
midline shift, and whole brain applications

● Automated measurement of brain tissue
volumes and structures of AI-reconstructed
low-field MR images
● Automatic segmentation and quantification
of brain structures of AI-reconstructed low-
field MR images using machine learning
tools

MR images are automatically sent to
BrainInsight, and processed images are
automatically returned in ~7 minutes

User Interface /
Physical
Characteristics

● No software required
● Operates in a serverless cloud environment
● User interface through PACS (multiple
vendors)

The table below compares the subject device to the predicate.


Automated internal pipeline that performs:
● segmentation
● volume calculation
● distance measurement
● numerical information display

● MRI Scanner: Hyperfine Swoop FSE MRI T1-
Gray/White Contrast, T2, T2-Fast and FLAIR
scans acquired with specified protocols
● Supports DICOM format as input

● MRI Scanner: Hyperfine Swoop FSE
MRI T1 and T2 scans acquired with
specified protocols
● Supports DICOM format as input

Provides volumetric measurements of brain
structures:
● Includes segmented color overlays and
morphometric reports
● Supports DICOM format as output of results
that can be displayed on DICOM
workstations and PACS

Automated quality control functions:
● Tissue contrast check
● Scan protocol verification
● Atlas alignment check
● Results must be reviewed by a trained
physician
● LV segmentation output quality check


Classification Name
Regulation
Product Code

Common Name: Ultrasound elastography system


VideaHealth, Inc.
179 South Street, Floor 5
Boston, MA, 02111
+1 617-340-9940
florian@videa.ai

Adam Foresman
Director of Quality & Regulatory Affairs
VideaHealth, Inc.
+1 617-340-9940
adam@videa.ai


Device Common Name:
Interproximal bone level measurement

Medical image management and processing system


Applicant
VideaHealth, Inc.
Overjet, Inc.

Device Name
Videa Perio Assist
Overjet Dental Assist

Patients ≥12 years of age with
permanent dentition present in the
radiograph

Intended User
Dentists and dental hygienists
Dentists and dental hygienists

Images imported from the
radiographic device, or from the
practice management system


Table 3: Demographic breakdown by gender


Table 4: Intraoral sensor breakdown by manufacturer


Table 5: Clinical Performance Metrics of VPA by radiographic view type and line type.


Met acceptance criteria for
sensitivity and mean
absolute error.
Specificity did not meet
acceptance criteria.

Met acceptance criteria
for all 3 metrics

Table 6: Clinical Performance Metrics of VPA by intraoral sensor manufacturer across all models.


Met acceptance
criteria for all 3
metrics

Met acceptance
criteria for sensitivity
and mean absolute
error.
Specificity did not
meet acceptance
criteria.

Table 7: Clinical Performance Metrics of VPA by patient age.


Philips Healthcare (Suzhou) Co., Ltd.
No. 258, Zhongyuan Road, Suzhou Industrial Park,
Suzhou Jiangsu, CHINA, 215024
Establishment Registration Number: 3009529630

Primary Contact
Person:
Secondary Contact
Person

Diana Xu
Associated Regulatory Affairs Manager
Phone: +86-18940060508
E-mail: diana.xu@philips.com
Erhong Wang
Senior Manager Regulatory Affairs
Phone: +86-512-67336804
E-mail: ErHong.WANG@philips.com

Classification Regulation:
21CFR 892.1750

Predicate Device:
Trade name:
Philips Incisive CT


Couch is used to position the patient. Carries the patient in
and out through the Gantry bore synchronized with the
scan.
3. Console
It is used to operate the system and monitor the scan. The
Operator console includes computer, monitor and CTBOX.
4. CT on Trailer Kit
Philips CT 3500 installed and secured on trailer requires
locking motion parts during trailer transportation and
unlocking motion parts before CT operations. CT on Trailer
Kit is used to install and secure the CT system on trailers,
trailers are provided by trailer manufactures and are not
components of the proposed Philips CT 3500.
In addition to the above components and the software
operating them, each system includes hardware and
software for data acquisition, display, manipulation, storage
and filming as well as post-processing into views other than
the original axial images.

The Philips CT 3500 is a Computed Tomography X-Ray
System intended to produce images of the head and body
by computer reconstruction of X-Ray transmission data
taken at different angles and planes. These devices may
include signal analysis and display equipment, patient and
equipment supports, components and accessories. The
Philips CT 3500 is indicated for head, whole body, cardiac
(Cardiac Calcium Scoring) and vascular X-ray Computed
Tomography applications in patients of all ages.
These scanners are intended to be used for diagnostic
imaging and for low dose CT lung cancer screening for the
early detection of lung nodules that may represent cancer*.
The screening must be performed within the established
inclusion criteria of programs / protocols that have been
approved and published by either a governmental body or
professional medical society.
*Please refer to clinical literature, including the results of the
National Lung Screening Trial (N Engl J Med 2011;
365:395-409) and subsequent literature, for further
information.


The systems comply with industry guidance and
performance standards for Computed Tomography (CT)
Equipment and Laser products (21 CFR 1020.33 and 21
CFR 1040.10, respectively).
The systems performed a comparison to the predicate
device using these technological characteristics and image
quality metrics to establish that the subject device is
substantially equivalent to the predicate device for its
intended use.
The systems pass the design verification, design validation
and consensus standards test as nonclinical tests. The
system verification is conducted against the system
requirement specifications (SRS). System verification
activities demonstrate the system meet the established
system design input requirements. System requirements
may be verified by manual test, automated test,
inspection/analysis, or any combination of the three. Non-
Clinical design validation testing covered the intended use
and commercial claims. Validation testing included workflow
validation.
The test results demonstrate that the proposed Philips CT
3500 meets the acceptance criteria and is adequate for its
intended use. Additionally, the risk management activities
show that all risks are sufficiently mitigated, that no new
risks are introduced, and that the overall residual risks are
acceptable.

The proposed Philips CT 3500 did not require clinical study
since substantial equivalence to the legally marketed
predicate device was proven with the verification/validation
testing.


Identical.
Therefore,
substantially
equivalent.

Besides installed in
hospital, the proposed
Philips CT 3500 may
also be installed on
trailer and be
transported to
designated locations for
use. And Philips CT
3500 installed on trailer
has the same intended
use as installed in
hospital.
The design, intended
use, fundamental
scientific technology
and principal
technological
components (Tube,
Generator, Detector,
gantry, patient table
and console) are same
as the proposed Philips
CT 3500 in hospital
except for the addition
of a CT on Trailer Kit to
secure the CT system
in a trailer.
CT on Trailer Kit
includes:
(cid:1068) Couch vertical lock
and horizontal lock
ASSY,
(cid:1068) UPS lock ASSY,
(cid:1068) Console lock ASSY,

Besides installed in
hospital, the proposed
Philips Incisive CT may
also be installed on
trailer and be
transported to
designated locations for
use. And Incisive CT
installed on trailer has
the same intended use
as installed in hospital.
The design, intended
use, fundamental
scientific technology
and principal
technological
components (Tube,
Generator, Detector,
gantry, patient table
and console) are same
as the Philips Incisive
CT in hospital except
for the addition of a CT
on Trailer Kit to secure
the CT system in a
trailer.
CT on Trailer Kit
includes:
(cid:1068) Gantry tilt lock
ASSY,
(cid:1068) Couch vertical lock
ASSY,
(cid:1068) Couch horizontal
lock ASSY,

The proposed
Philips CT 3500
Gantry has no tilt
function. All motion
parts can be fixed
by on trailer kit.
The design,
intended use,
fundamental
scientific
technology and
principal
technological
components are
identical to the
predicate device.
Safety and
effectiveness are
not affected.
Therefore,
demonstrating
substantial
equivalence.


(cid:1068) Isolation
Transformer lock
ASSY

(cid:1068) UPS lock Kits,
(cid:1068) Console fixation
device,
(cid:1068) Isolation
Transformer lock
Kits


The Philips CT
3500 uses the
same DMS (20mm)
as the Philips
Incisive CT to
support 64 slices.
Therefore,
demonstrating
Substantial
equivalence.

The proposed
Philips CT 3500
rotation speed
lower than Philips
Incisive CT.
Safety and
effectiveness are
not affected.


Therefore,
demonstrating
substantial
equivalence.

High resolution
mode:16 lp/cm
Standard resolution
mode: 13 lp/cm

High resolution mode:
16 lp/cm
Standard resolution
mode: 13 lp/cm

≤0.18% at 120kV,
CTDI
center
(head) ≤ 33mGy, 10mm
image thickness,
iDose4

Helical:
0.67mm – 5mm
Axial:
0.625mm – 10.0mm

Helical:
0.67mm – 5mm
Axial:
0.625mm-10.0mm


Compliance with NEMA
XR25, XR26, XR28 and
XR29

Compliance with NEMA
XR25, XR28 and XR29

Compliance with
more NEMA
standard.
Safety and
effectiveness are
not affected.
Therefore,
substantially
equivalent.


Predicate Device
Philips Incisive
CT (K212441,
K211168)

Conclusion
(Function/
User interface/
Workflow)

In 2D Viewer mode operator can
review original axial images as
acquired by the scanner.

Identical.
Therefore,
substantially
equivalent.

Use the MPR mode to view
three-plane orthogonal images.
In this mode, the three shown
planes can be easily correlated.
Three orthogonal cut planes are
shown:
• Axial Orientation


• Coronal Orientation
• Sagittal Orientation

The volume mode is used to
display CT scanner data in a full
volume image. It provides basic
tools for image editing and
generation of cine movies.

The CT Endo viewer is a review
function that allows you to
perform a general flythrough of
any suitable anatomical
structure that is filled with air or
with contrast material, including
general vessels, cardiac
vessels, the bronchus, and the
colon.

The Image Matrix parameter
sets the number of pixels that
the reconstructed image will
contain. Select 512, 768, or
1024.

Identical
Therefore,
substantially
equivalent.

O-MAR stands for orthopedic
metal artifact reduction. This
post processing capability
reduces metal induced artifacts
and is directed for large
orthopedics metals that cause
photon starvation of the rays
that pass through the metal
object.

DoseRight Index (DRI) is
according to the current scan
site and body size of the patient,
the mAs suitable for the patient
is automatically recommended,
so that the image quality can
meet the requirements of the
diagnosis, and the radiation
dose of the patient can be
reduced as far as possible.


3D-DOM combines angular and
longitudinal information to
modulate dose in three
dimensions. Personalizes dose
for each patient by automatically
suggesting tube current settings
according to the estimated
patient diameter in the scan
region. Angular dose modulation
varies the tube current during
helical scans according to
changes in patient shape
(eccentricity) and tissue
attenuation as the tube rotates.

Precise Planning can
automatically adjust the scan
range of subsequent Axial or
Helical scan series, based on
the Surview Image.

Only the name
changes.
Safety and
effectiveness
are not
affected.
Therefore,
substantially
equivalent.

Support the adjustment of
sagittal / coronal image
construction in the planned
scanning phase, and finally
obtain the adjusted tilted
multiplane image.
On the basis of Insert MPR,
surface reconstruction is carried
out by interpolation of axial
image and corresponding tilted
image is generated.

On the basis of
Insert MPR,
Added the ability
for users to tilt
the MPR image
Safety and
effectiveness
are not
affected.
Therefore,
substantially
equivalent.

OnPlan (Touch Panel)
OnPlan is a brand-new gantry
operational touch panel located
on both sides of the gantry. The
OnPlan gantry controls are used
to active the laser marker,
controls patient table


Predicate Device
Philips Incisive
CT (K212441,
K211168)

Conclusion
(Function/
User interface/
Workflow)

movements, display patient
information and images, and
conduct a new patient exam.

Precise Spine
Precise Spine application
enables the system to assist the
user to identify the lumbar disk
space automatically and
creating a batch based on the
protocol selected.

iBatch
iBatch application
enables the
system to assist
the user to identify
the lumbar disk
space
automatically and
creating a batch
based on the
protocol selected.

The Bolus tracking function
maximizes the efficiency of CT
scans that are enhanced
through the use of a contrast
agent. This is done by preceding
the Clinical scan with Locator
and Tracker scans.

Identical.
Therefore,
substantially
equivalent.

This feature enable the usage of
the injector scan trigger.

The Filming application is used
for viewing, rearranging,
windowing and zooming images
prior to sending them to be
printed.

The Worklist displays patient
information provided by the
HIS/RIS.

If the patient is from the Worklist
and the MPPS function is
enabled, feedback regarding the


study status of the patient can
be sent to the hospital HIS/RIS.

The Reporting package allows
you to create customized
reports using pre-formatted
templates.
A template is a specially
designed formatting document
that places the analytical
information and images that you
send from an application into an
organized report which can be
printed and saved.

Continuous CT (CCT) is a
scanning mode that allows the
physician to perform extended,
low-dose scans while
performing a biopsy.
The resulting images display on
a remote monitor in the scan
room, providing visual feedback
during the biopsy.

Brain Perfusion is a blood flow
imaging application that
analyzes the uptake of injected
contrast in order to determine
perfusion-related information
about one or more regions of
interest.

Dental application uses to
create true-size (life size) film
images of the mandible and
maxilla for assisting oral
surgeons in planning
implantation of prostheses.
Using a special dental planning
procedure, and the images will
be created from this scan which


can be input into the Dental
planning application.

Axial prospective gating uses an
external ECG gating system to
synchronize individual axial
scans with the patient’s
heartbeat. The ECG-triggered
scans significantly minimize
heart-motion artifacts.

The system support Parallel
workflow using Dual monitor as
below:
- main monitor: Patients, scan,
service, "show all" for scan
planning, Help.
- extend monitor: Completed,
viewers, Analysis, recon, filming,
report

Precise image reconstruction is
a recon mode where the system
uses a trained deep learning
neural network to generate
noise reduction images and
improve low contrast
detectability with reduced dose
compared with standard FBP
recon mode.

Precise Position is a camera-
based workflow designed to
assist with positioning the
patient automatically from
console or OnPlan, it can:
• automatically select patient
orientation.
• automatically set vertical
centering & positioning of the
patient to the Surview start and
end positions.
• support editing Surview start &
end range and scan direction.


Predicate Device
Philips Incisive
CT (K212441,
K211168)

Conclusion
(Function/
User interface/
Workflow)

Direct Result-With Direct Result
the user is able to choose a
desired result during scan
planning phase and get the
result for diagnosis without
further intervention.

Identical.
Therefore,
substantially
equivalent.

CT Colonoscopy (CTC)
application enables fast and
easy visualization of colon
scans, using acquired CT
images.

Vessel Analysis (VA) offers a
set of tools for general vascular
analysis. With VA the user can
easily remove bone, and extract
vessels. User also can perform
measurements such as
intraluminal diameter, cross-
sectional lumen area, length.

The Lung Nodule Analysis
(LNA) application assists the
radiologist with the detection
and quantification of pulmonary
nodules and lesions.

Dual energy Viewer is an
application for review and
analysis of CT dual-energy
scans. Users need to load CT
dual-energy scan data which is
two series with similar KV. It
provides registration function
and can generate different
weighted KV images. User can
use the tools to separate
materials.

In Precise Intervention viewer
there are several tools, they will
help you to navigate the needle
safely during the intervention.


iDose4 is an iterative
reconstruction technique that
improves image quality through
artifact prevention and
increased spatial resolution at
low dose.

The Cardiac Calcium Scoring
application is used to quantify
the buildup of calcium plaque on
the walls of the patient's
coronary arteries and other
relevant locations. The potential
calcifications are highlighted by
the application during launch.

Adaptive filters (AF) reduce
pattern noise (streaks) in non-
homogenous bodies, improving
overall image quality.

Precise Brain application for a
series of brain tissue slices that
are parallel or vertical in the
plane of the cranial CT scan.


Scintillator material: LYSO
Number of detector rings:
• 96 (uMI Panorama 28)
• 120 (uMI Panorama 35)
Axial FOV:
• 280mm (uMI Panorama 28)
• 350mm (uMI Panorama 35)

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

CT System
uCT ATLAS Astound (K223028)
uCT 780 (K172135)


liver, knee, hip, ankle,
shoulder, hand and lumbar
spine. All publications have
concluded that the work-in-
progress package and the
reconstruction algorithm can
be beneficially used for clinical
routine imaging. No cases
have been reported where the
network led to a
misinterpretation of the images
or where anatomical
information has been altered,
suppressed, or introduced. In
most cases the new algorithm
has been used to acquire
images faster and significant
time savings are reported.

The acquired datasets
represent the ground truth for
the training and validation.
Input data was retrospectively
created from the ground truth
by data manipulation and
augmentation. This process
includes further under-
sampling of the data by
discarding k-space lines,
lowering of the SNR level by
addition of noise and mirroring
of k-space data.


Predicate Device
FDA Clearance Number and Date
Manufacturer

Siemens Shenzhen
Magnetic Resonance
Ltd.

Reference Device
FDA Clearance Number and Date
Manufacturer

Table 2. Predicate devices and reference devices.


Feature
Subject Device
Predicate Device
Subject Device
Predicate Device

MAGNETOM
Amira with
software syngo
MR XA50M

MAGNETOM
Sempra with
software syngo
MR XA50M

New coils:
-Flex Large 8,
-Flex Small 8,
-Flex 8 Coil
Interface


Performance Test
Tested Hardware or Software
Source/Rationale for test

- SNR and image uniformity
measurements for coils
- Heating measurements for
coils

Guidance for Submission of
Premarket Notifications for
Magnetic Resonance
Diagnostic Devices

devices and can be reused for the subject devices:


Image Acquisition And/ Or
Optimization Guided By
Artificial Intelligence

The Caption Guidance
software is intended to
assist medical
professionals in the
acquisition of cardiac
ultrasound images.
Caption Guidance
software is an accessory
to compatible general
purpose diagnostic
ultrasound systems

The UltraSight AI
Guidance software is
intended to assist medical
professionals in the
acquisition of cardiac
ultrasound images.
UltraSight AI Guidance
software is an accessory
to compatible general
purpose diagnostic
ultrasound systems

Caption Guidance
software is indicated for
use in two-dimensional
transthoracic
echocardiography (2D-
TTE) for adult patients,
specifically in the
acquisition of the following
standard views:
Parasternal Long-Axis
(PLAX), Parasternal
Short-Axis at the Aortic
Valve (PSAX-AV),
Parasternal Short-Axis at
the Mitral Valve (PSAX-
MV), Parasternal Short-
Axis at the Papillary
Muscle (PSAX-PM),
Apical 4-Chamber (AP4),
Apical 5-Chamber (AP5),

UltraSight AI Guidance
software is indicated for
use in two-dimensional
transthoracic
echocardiography (2D-
TTE) for adult patients,
specifically in the
acquisition of the following
standard views:
Parasternal Long-Axis
(PLAX), Parasternal
Short-Axis at the Aortic
Valve (PSAX-AV),
Parasternal Short-Axis at
the Mitral Valve (PSAX-
MV), Parasternal Short-
Axis at the Papillary
Muscle (PSAX-PM),
Apical 4-Chamber (AP4),
Apical 5-Chamber (AP5),

Similar
Since the use of the
UltraSight AI Guidance
and its impact to expert
sonographers has not
been evaluated, this
users’ population is
excluded from the device’s
intended users.

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


Apical 2-Chamber (AP2),
Apical 3-Chamber (AP3),
Subcostal 4-Chamber
(SubC4), and Subcostal
Inferior Vena Cava (SC-
IVC).
The UltraSight AI
Guidance is not intended
to be used by
Sonographers.

Medical professionals
(including expert
sonographers)

Medical professionals (not
including expert
sonographers)

Substantially Equivalent:
It should be noted that
the intended users’
population of the
UltraSight AI Guidance is
slightly narrower than the
predicate and does not
include sonographers.
However, the intended
user population of the
UltraSight AI Guidance is
a subset of the broader
user population for the
predicate; thus, the
intended use and
indications are fully
encompassed within the
predicate indications.
Therefore, the first
criterion for a finding of
substantial equivalence
is satisfied.

The uSmart 3200t Plus
ultrasound system with the
3200t-compatible Terason
4V2A linear phased array
probe

Philips Lumify With S4-1
probe and Samsung Tab
S6 and S7 tablets

Substantially Equivalent:
Both the predicate device
and the proposed device
function as a software
accessory to a cleared to
market ultrasound device.
Both ultrasound devices
are cleared for the
diagnostic ultrasound
clinical application of
acquiring cardiac images

UltraSight Ltd. SECTION 5 SUMMARY Page: 5-4 of 10


of adult patients. Since
both ultrasound devices
are cleared for the
required clinical use, the
use of different ultrasound
devices does not raise
new questions of safety
and/or effectiveness.

Prescriptive Guidance:
The prescriptive guidance
feature in Caption
Guidance provides
direction to the user to
emulate how a
sonographer would
manipulate the transducer
to acquire the optimal view

Probe Guidance: The
probe guidance feature
provides graphic on-
screen instructions for
the user to emulate how
a sonographer would
manipulate the
transducer to acquire the
target cardiac view.

Substantially Equivalent:
While the user interface is
slightly different, the
functionality and type of
guidance provided to the
user will be the same.
Specifically, both devices
provide to the user
instructions on how to
manipulate the probe
(translational, tilt and
rotation guidance cues)
together with real-time
feedback on the
expected diagnostic
quality of the resulting clip
to direct the user to a
probe position that will
enable acquisition of a
diagnostic quality clip.
Hence, this difference
does not raise new
questions of safety and/or
effectiveness.

Quality Meter: a real-time
feedback from the Quality
Meter advises the user on
the expected diagnostic
quality of the resulting clip,
such that the user can
make decisions to further
optimize the quality, for
example by following the
prescriptive guidance
feature below.

Quality Bar: a real-time
quality bar providing
feedback on the clip’s
quality advises the user on
the expected diagnostic
quality of the current
image. This information
can be used by the users
to assess how close they
are to capturing a
diagnostic-quality image.

UltraSight Ltd. SECTION 5 SUMMARY Page: 5-5 of 10