Predicate Devices

Reference Devices

AI/ML (Artificial Intelligence / Machine Learning)

Yes
The device description and intended use explicitly state that the device uses "deep-learning-based auto-segmented organs" and mentions "Deep learning contouring". Deep learning is a subset of machine learning.

Therapeutic

No
The device aids in treatment planning by segmenting organs, but it does not directly treat, diagnose, cure, or prevent disease.

Diagnostic

No

The device is intended for generating contours of organs for radiation oncology treatment planning, not for diagnosing diseases or conditions.

SaMD (Software as a Medical Device)

Yes

The device description explicitly states "This software could be used..." and details its functions as software-based processes (deep learning contouring, generating RT-DICOM, rule-based pre-processing, receiving/sending/exporting data) without mentioning any associated hardware components that are part of the medical device itself.

IVD (In Vitro Diagnostic)

Based on the provided information, this device is not an In Vitro Diagnostic (IVD).

Here's why:

IVDs are used to examine specimens derived from the human body. The intended use and device description clearly state that this device processes CT images, which are medical images of the body, not specimens taken from the body (like blood, urine, tissue, etc.).
The purpose of this device is to assist in medical image analysis and treatment planning. It provides auto-segmented contours from CT images for use in radiation oncology treatment planning or other applications where segmented anatomical structures are needed. This is a function related to medical imaging and treatment, not laboratory testing of biological samples.

The device falls under the category of medical image processing software, specifically for segmentation in the context of radiation therapy planning.

PCCP (Predetermined Change Control Plan) Authorized

No
The letter does not explicitly state that the FDA has reviewed and approved or cleared a PCCP for this device, nor does it reference any related section 515C(b)(1) as a clearance for PCCP.

Overview

Intended Use / Indications for Use

AVIEW RT ACS provides deep-learning-based auto-segmented organs and generates contours in RT-DICOM format from CT images which could be used as an initial contour for the clinicians to approve and edit by the radiation oncology department for treatment planning or other professions where a segmented mask of organs is needed.

a. Deep learning contouring from four body parts (Head & Neck, Breast, Abdomen, and Pelvis)
b. Generates RT-DICOM structure of contoured organs
c. Rule-based auto pre-processing

Receive/Send/Export medical images and DICOM data

Note that the Breast (Both right and left lung, Heart) were validated with non-contrast CT. Head & Neck (Both right and left Eyes, Brain and Mandible), Abdomen (Both right and Liver), and Pelvis (Both right and left Femur and Bladder) were validated with Contrast CT only.

Product codes

QKB

Device Description

The AVIEW RT ACS provides deep-learning-based auto-segmented organs and generates contours in RT-DICOM format from CT images. This software could be used by the radiation oncology department planning, or other professions where a segmented mask of organs is needed.

Deep learning contouring: it can automatically contour the organ-at-risk (OARs) from four body parts (Head ● & Neck, Breast, Abdomen, and Pelvis)
. Generates RT-DICOM structure of contoured organs
. Rule-based auto pre-processing

Receive/Send/Export medical images and DICOM data

Mentions image processing

Unit Test -
Conducting Unit Test using Google C++ Unit Test Framework on major software components identified by software development team. List of Unit Test includes Functional test condition for software component unit, Performance test condition, and part of algorithm analysis for image processing algorithm.

Mentions AI, DNN, or ML

AVIEW RT ACS provides deep-learning-based auto-segmented organs and generates contours in RT-DICOM format from CT images which could be used as an initial contour for the clinicians to approve and edit by the radiation oncology department for treatment planning or other professions where a segmented mask of organs is needed.

Input Imaging Modality

CT images

Anatomical Site

Head & Neck, Breast, Abdomen, Pelvis

Indicated Patient Age Range

20-89 years.

Intended User / Care Setting

radiation oncology department for treatment planning or other professions where a segmented mask of organs is needed.

Description of the training set, sample size, data source, and annotation protocol

Not Found

Description of the test set, sample size, data source, and annotation protocol

The data set information used in the test is 120cases (each 60cases) including both Korean and U.S, Gender: F 70, M 50, Age: 20-89 years. The TCIA data was constructed with various ethnics (White, Black, Asian, Hispanic, Latino, African, American, etc.), the result can be obtained by performing generalization without performance difference according to ethnic

Breast (Both right and left lung, Heart) were validated with non-contrast and contrast CT.
A Head & Neck(Both right and left Eyes, Brain and Mandible), Abdomen(Both right and left Kidney and Liver), and Pelvis(Both right and left Femur and Bladder) were validated with Contrast CT only.

Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)

Performance Test -
Compare Standalone Performacne Test
The purpose of this test is to compare and verify the AVIEW RT ACS performance and the performance of the predicate device. The test process involves generating a robust gold standard. Three radiation oncology physicians segmented the organs to be used for validation. There were 3 experts, all trained by the "The Korean Society for Radiation Oncology", board-certified by the "Ministry of Health and Welfare", with a range of 9-21 years of experience in radiotherapy to participate in this test. The experts were attending assistant professors (n=2), and professors (n=1) from three institutions. First, the 1 expert manually delineated the organs. Second, segmentation results generated by 1 expert are sequentially edited by 2 experts. In the editing process, the first expert makes corrections, and the result is received by another expert completes the gold standard by finalizing it. This process was performed by a panel of three radiation oncology physicians' experiences. And the results of auto-segmentation of gold-standard and AVIEW RT ACS and auto-segmentation of predicate device are analyzed and evaluated using DSC and 95% HD, respectively. The data set information used in the test is 120cases (each 60cases) including both Korean and U.S, Gender: F 70, M 50, Age: 20-89 years. The TCIA data was constructed with various ethnics (White, Black, Asian, Hispanic, Latino, African, American, etc.), the result can be obtained by performing generalization without performance difference according to ethnic.

Key results are provided in Table 1 DSC for each organ, Table 2. 95% HD (mm) for each organ, and subsequent tables for sub-group analysis per population, vendor, slice thickness and kernel.

Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)

DSC and 95% HD

Predicate Device(s)

K182624

Reference Device(s)

K191928

Predetermined Change Control Plan (PCCP) - All Relevant Information

Not Found

Regulation Number and Section

§ 892.2050 Medical image management and processing system.

(a)
Identification. A medical image management and processing system is a device that provides one or more capabilities relating to the review and digital processing of medical images for the purposes of interpretation by a trained practitioner of disease detection, diagnosis, or patient management. The software components may provide advanced or complex image processing functions for image manipulation, enhancement, or quantification that are intended for use in the interpretation and analysis of medical images. Advanced image manipulation functions may include image segmentation, multimodality image registration, or 3D visualization. Complex quantitative functions may include semi-automated measurements or time-series measurements.(b)
Classification. Class II (special controls; voluntary standards—Digital Imaging and Communications in Medicine (DICOM) Std., Joint Photographic Experts Group (JPEG) Std., Society of Motion Picture and Television Engineers (SMPTE) Test Pattern).

Summary

0

Image /page/0/Picture/0 description: The image contains the logo of the U.S. Food and Drug Administration (FDA). On the left is the Department of Health & Human Services logo. To the right of that is the FDA logo, which is a blue square with the letters "FDA" in white. To the right of the FDA logo is the text "U.S. FOOD & DRUG ADMINISTRATION" in blue.

Coreline Soft Co., Ltd. % Hyeyi Park RA Manager 4,5F (Yeonnam-dong), 49, World Cup buk-ro-6-gil, Mapo-gu. Seoul. 03991 REPUBLIC OF KOREA

November 10, 2022

Re: K220408

Trade/Device Name: AVIEW RT ACS Regulation Number: 21 CFR 892.2050 Regulation Name: Medical image management and processing system Regulatory Class: Class II Product Code: QKB Dated: October 7, 2022 Received: October 11, 2022

Dear Hyeyi Park:

We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Federal Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. Although this letter refers to your product as a device, please be aware that some cleared products may instead be combination products. The 510(k) Premarket Notification Database located at https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpmn/pmn.cfm identifies combination product submissions. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration. Please note: CDRH does not evaluate information related to contract liability warranties. We remind you, however, that device labeling must be truthful and not misleading.

If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to additional controls. Existing major regulations affecting your device can be found in the Code of Federal Regulations, Title 21, Parts 800 to 898. In addition, FDA may publish further announcements concerning your device in the Federal Register.

Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Part

1

801); medical device reporting of medical device-related adverse events) (21 CFR 803) for devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see https://www.fda.gov/combination-products/guidance-regulatory-information/postmarketing-safety-reportingcombination-products); good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820) for devices or current good manufacturing practices (21 CFR 4. Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR 1000-1050.

Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR Part 807.97). For questions regarding the reporting of adverse events under the MDR regulation (21 CFR Part 803), please go to https://www.fda.gov/medical-device-safety/medical-device-reportingmdr-how-report-medical-device-problems.

For comprehensive regulatory information about mediation-emitting products, including information about labeling regulations, please see Device Advice (https://www.fda.gov/medicaldevices/device-advice-comprehensive-regulatory-assistance) and CDRH Learn (https://www.fda.gov/training-and-continuing-education/cdrh-learn). Additionally, you may contact the Division of Industry and Consumer Education (DICE) to ask a question about a specific regulatory topic. See the DICE website (https://www.fda.gov/medical-device-advice-comprehensive-regulatoryassistance/contact-us-division-industry-and-consumer-education-dice) for more information or contact DICE by email (DICE@fda.hhs.gov) or phone (1-800-638-2041 or 301-796-7100).

Sincerely,

Julie Sullivan -S

Julie Sullivan, Ph.D. Director DHT8C: Division of Radiological Imaging and Radiation Therapy Devices OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health

Enclosure

2

Indications for Use

510(k) Number (if known) K220408

Device Name AVIEW RT ACS

Indications for Use (Describe)

AVIEW RT ACS provides deep-learning-based auto-segmented organs and generates contours in RT-DICOM format from CT images which could be used as an mittal contour for the clinicians to approve and edit by the radiation oncology department for treatment planning or other professions where a segmented mask of organs is needed.

a. Deep learning contouring from four body parts (Head & Neck, Breast, Abdomen, and Pelvis)
b. Generates RT-DICOM structure of contoured organs
c. Rule-based auto pre-processing

Receive/Send/Export medical images and DICOM data

Note that the Breast (Both right and left lung, Heart) were validated with non-contrast CT. Head & Neck (Both right and left Eyes, Brain and Mandible), Abdomen (Both right and Liver), and Pelvis (Both right and left Femur and Bladder) were validated with Contrast CT only.

Type of Use (Select one or both, as applicable)

Prescription Use (Part 21 CFR 801 Subpart D)

Over-The-Counter Use (21 CFR 801 Subpart C)

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510(k) Summary

K220408

SUBMITTER 1

Coreline Soft Co., Ltd. 4,5F (Yeonnam-dong), 49 World Cup buk-ro 6-gil, Mapo-gu, Seoul, 03991, Republic of Korea.

Phone: 82.2.517.7321 Fax: 82.2.571.7324

Contact Person: hyeyi. Park Date Prepared: 02.10.2022

2 DEVICE

Name of Device: AVIEW RT ACS Common or Usual Name: Medical Imaging Software Classification Name: Radiological Image Processing Software For Radiation Therapy (21CFR 892.2050) Regulatory Class: II Product Code: QKB

PREDICATE DEVICE 3

MIM-MRT Dosimetry by MIM Software Inc. (K182624)

Name of Device: MIM-MRT Dosimetry Common or Usual Name: Medical Imaging Software Classification Name: System, image processing, radiological (21CFR 892.2050) Regulatory Class: II Product Code: LLZ

This predicate has not been subject to a design-related recall

REFERENCE DEVICE 4

AccuContour™ by Xiamen Manteia Technology LTD. (K191928)

Name of Device: AccuContour™ Common or Usual Name: Medical Imaging Software Classification Name: Radiological Image Processing Software For Radiation Therapy (21CFR 892.2050) Regulatory Class: II Product Code: QKB

4

This reference device has not been subject to a design-related recall

5 DEVICE DESCRIPTION

The AVIEW RT ACS provides deep-learning-based auto-segmented organs and generates contours in RT-DICOM format from CT images. This software could be used by the radiation oncology department planning, or other professions where a segmented mask of organs is needed.

Deep learning contouring: it can automatically contour the organ-at-risk (OARs) from four body parts (Head ● & Neck, Breast, Abdomen, and Pelvis)
. Generates RT-DICOM structure of contoured organs
. Rule-based auto pre-processing

Receive/Send/Export medical images and DICOM data

INDICATIONS FOR USE 6

AVIEW RT ACS provides deep-learning-based auto-segmented organs and generates contours in RT-DICOM format from CT images which could be used as an initial contour for the clinicians to approve and edit by the radiation oncology department for treatment planning or other professions where a segmented mask of organs is needed.

a. Deep learning contouring from four body parts (Head & Neck, Breast, Abdomen, and Pelvis)
Generates RT-DICOM structure of contoured organs b.
c. Rule-based auto pre-processing

Receive/Send/Export medical images and DICOM data

Note that the Breast (Both right and left lung, Heart) were validated with non-contrast CT. Head & Neck (Both right and left Eyes, Brain, and Mandible), Abdomen (Both right and Liver), and Pelvis (Both right and left Femur and Bladder) were validated with Contrast CT only.

5

COMPARISION OF TECHNOLOGICAL CHARACTERISTICS WITH 8 THE PREDICATE DEVCIE

AVIEW RT ACS has the same intended use and the principle of operation and has similar features to the predicate devices.

There might be slight differences in features and menu, but these differences between the predicate device and the proposed device are not so significant since they do not raise any new or potential safety risks to the user or patient and questions of safety or effectiveness. Based on the results of software validation and verification tests, we conclude that the proposed device is substantially equivalent to the predicate devices.

Characteristic	Subject Device	Primary Predicate Device	Reference Device
Device Name	AVIEW RT ACS	MIM-MRT Dosimetry	AccuContour
Classification Name	Radiological
Image
Processing Software For
Radiation Therapy	Radiological
Image Processing
System	Radiological
Image
Processing Software For
Radiation Therapy
Regulatory Number	21 CFR 892.2050	21 CFR 892.2050	21 CFR 892.2050
Product Code	QKB	LLZ	QKB
Review Panel	Radiology	Radiology	Radiology
510k Number	-	K182624	K191928
Indications for use	AVIEW RT ACS
	AVIEW RT ACS provides deep-learning-based auto-segmented organs and generates
contours in RT-DICOM format from CT images which could be used as an initial contour
for the clinicians to approve and edit by the radiation oncology department for treatment
planning or other professions where a segmented mask of organs is needed.
a. Deep learning contouring from four body parts (Head & Neck, Breast, Abdomen,
and Pelvis)
	b. Generates RT-DICOM structure of contoured organs
c. Rule-based auto pre-processing
Receive/Send/Export medical images and DICOM data
Note that the Breast (Both right and left lung, Heart) were validated with non-contrast and
	contrast CT. Head & Neck (Both right and left Eyes, Brain and Mandible), Abdomen (Both
right and left Kidney and Liver), and Pelvis (Both right and left Femur and Bladder) were
validated with Contrast CT only.
	MIM-MRT Dosimetry
	MIM software is used by trained medical professionals as a tool to aid in evaluation and
information management of digital medical images. The medical image modalities include,
but are not limited to, CT, MRI, CR, DX, MG, US, SPECT, PET and XA as supported by
ACR/NEMA DICOM 3.0. MIM assists in the following indications:
	• Receive, transmit, store, retrieve, display, print, and process medical images and DICOM
objects.
	• Create, display and print reports from medical images.
	• Registration, fusion display, and review of medical images for diagnosis, treatment
evaluation, and treatment planning.
	• Evaluation of cardiac left ventricular function and perfusion, including left ventricular
enddiastolic volume, end-systolic volume, and ejection fraction.
	• Localization and definition of objects such as tumors and normal tissues in medical
images.
	• Creation, transformation, and modification of contours for applications including, but
not limited to, quantitative analysis, aiding adaptive therapy, transferring contours to
radiation therapy treatment planning systems, and archiving contours for patient follow-

6

| | up and management.
• Quantitative and statistical analysis of PET/SPECT brain scans by comparing to other
registered PET/SPECT brain scans.
• Planning and evaluation of permanent implant brachytherapy procedures (not including
radioactive microspheres).
• Calculating absorbed radiation dose as a result of administering radionuclide.
• When using device clinically, the user should only use FDA approved radiopharmaceuticals.
If using with unapproved ones, this device should only be used for research purposes. |
|---------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| | Lossy compressed mammographic images and digitized film screen images must not be
reviewed for primary image interpretations. Images that are printed to film must be printed
using an FDA-approved printer for the diagnosis of digital mammography images.
Mammographic images must be viewed on a display system that has been cleared by the
FDA for the diagnosis of digital mammography images. The software is not to be used for
mammography CAD. |
| | AccuContour
It is used by radiation oncology department to register multimodality images and segment |
| | (non-contrast) CT images, to generate needed information for treatment planning,
treatment evaluation and treatment adaptation. |
| | AVIEW RT ACS |
| | The AVIEW RT ACS provides deep-learning-based auto-segmented organs and generates |
| | contours in RT-DICOM format from CT images. This software could be used by the radiation
oncology department for treatment planning, or other professions where a segmented mask |
| | of organs is needed. |
| | • Deep learning contouring: it can automatically contour the organ-at-risk (OARS) |
| | from four body parts (Head & Neck, Breast, Abdomen, and Pelvis) |
| | • Generates RT-DICOM structure of contoured organs |
| | • Rule-based auto pre-processing |
| | Receive/Send/Export medical images and DICOM data |
| | MIM-MRT Dosimetry |
| | MIM - MRT Dosimetry extends features of MIM SurePlan. It is designed for use in medical |
| | imaging and operates on both Windows and Mac computer systems. MIM - MRT Dosimetry
extends the functionality of the MIM - Y90 Dosimetry (K172218) software and utilizes |
| | functionality of MIM -SPECTRA Quant (K180815). Both of these are predicates for this |
| | submission. The following functions have been added to allow calculations of absorbed dose |
| | as a result of administering a radionuclide. |
| General Description | • Allows for quantification of planar images |
| | • Allows for calculation of time-integrated activity coefficients |
| | • Allows for voxel-based dose calculation of radionuclides |
| | • Allows for correction of dose for tissue density |
| | Accu Contour |
| | The proposed device, AccuContourTM, is a standalone software which is used by radiation
oncology department to register multimodality images and segment (non-contrast) CT |
| | images, to generate needed information for treatment planning, treatment evaluation and |
| | treatment adaptation. |
| | The product has two image process functions: |
| | (1) Deep learning contouring: it can automatically contour the organ-at-risk, including head |
| | and neck, |
| | thorax, abdomen and pelvis (for both male and female), |
| | (2) Automatic Registration, and |
| | (3) Manual Contour.
It also has the following general functions: |
| | Receive/Send/Export medical images and DICOM data |

7

| | • Patient management.
• Review of processed images. | | |
|----------------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
| | Open and save of files. | | |
| Operating System
Image format | Windows
DICOM | Windows and MAC system
DICOM | Windows
DICOM |
| Data
Communications | Receive, transmit, store,
retrieve and process medical
images and DICOM objects | Receive, transmit, store,
retrieve, display, print, and
process medical images and
DICOM objects. | Receive, add/edit/delete,
transmit, input/export,
medical images and DICOM
data |
| Algorithm | Deep Learning | Atlas-based | Deep Learning |
| Compatible
Modality | CT Images | Non-Contrast CT | Non-Contrast CT |
| Segmentation of
Organ | Head & Neck, Breast,
Abdomen, Pelvis | Head & Neck, Breast,
Abdomen, Pelvis | Head & Neck, Thorax,
Abdomen & Pelvis |
| Automated
workflow | Automatically processes
input image data contour
organs and DICOM sends
generated RT Structure set | Creation, transformation,
and modification of contours
for applications including,
but not limited to,
quantitative analysis, aiding
adaptive therapy, transferring
contours to radiation therapy
treatment planning systems,
and archiving contours for
patient follow-up and
management | AccuContour automatically
processes input image data |
| Data anonymization | Replaces the patient's name
and ID with user defined
prefix and suffixes and IDs
and strips the birth date,
referring physician name,
and any private DICOM tags
that exist. | Replaces the patient's name
and ID with randomized
generic names and IDs and
strips the birth date, referring
physician name, and any
private DICOM tags that
exist. | No information publicly
available. |
| Target Population | Any patient type for whom
scanned with CT modality
images and segment CT
images are available. | Any patient type for whom
relevant modalities such as
CT and MR, as supported by
ACR/NEMA DICOM 3.0. | Any patient type for whom
Relevant multimodality
images and segment (non-
contrast) CT images are
available. |
| Segmentation
Performance | The segmentation
performance was validated
multi-race and multi-vendor
using datasets from South
Korea and the USA using
four major vendors (GE,
Siemens, Toshiba and
Phillips). The segmentation
accuracy is evaluated using
DICE coefficient | Contour Evaluation: Atlas-
based segmentation studies
have shown the accuracy of
multi-atlas segmentation
with an overall average dice
similarity index of 0.81 for
the contours tested: right and
left lung, trachea, heart, and
esophagus | The segmentation
performance was validated
using datasets from China
and the USA using three
major vendors (GE, Siemens
and Phillips). The
segmentation accuracy is
evaluated using DICE
coefficient |

8

PERFORMANCE DATA 9

9.1 Handware and software verification and Validation

This Medical device is not new; therefore, a clinical study was not considered necessary prior to release. Additionally, there was no clinical testing required to support the medical device as the indications for use is equivalent to the predicate device. The substantial equivalence of the device is supported by the non-clinical testing

Verification, validation, and testing activities were conducted to establish the performance, functionality and reliability characteristics of the modified device passed all of the tests based on pre-determined Pass/Fail criteria.

Unit Test -
Conducting Unit Test using Google C++ Unit Test Framework on major software components identified by software development team. List of Unit Test includes Functional test condition for software component unit, Performance test condition, and part of algorithm analysis for image processing algorithm.
System Test -
In accordance with the document 'integration Test Cases' discussed in advanced by software development team and test team, test is conducted by installing software with recommended system specification. Despite Test case recognized in advance was not in existence. New software error discovered by 'Exploratory Test' conducted by test team will be registered and managed as new test case after discussion between development team and test team.

Discovered software error will be classified into 3 categories as severity and managed.

V Major defects, which are impacting the product's intended use and no workaround is available.
Moderate defects, which are typically related to user-interface or general quality of product, while workaround is available.
く Minor defects, which aren't impacting the product's intended use. Not significant.

Success standard of System Test is not finding 'Major', 'Moderate' defect.

Performance Test -
- · DICOM Test Report
- · DICOM Conformance Statement
- · Thin Client Server Compatibility Test Report
- Compare Standalone Performacne Test
  - The purpose of this test is to compare and verify the AVIEW RT ACS performance and the performance of the predicate device. The test process involves generating a robust gold standard. Three radiation oncology physicians segmented the organs to be used for validation. There were 3 experts, all trained by the "The Korean Society for Radiation Oncology", board-certified by the "Ministry of Health and Welfare", with a range of 9-21 years of experience in radiotherapy to participate in this test. The experts were attending assistant professors (n=2), and professors (n=1) from three institutions. First, the 1 expert manually delineated the organs. Second, segmentation results generated by 1 expert are sequentially edited by 2 experts. In the editing process, the first expert makes corrections, and the result is received by another expert completes the gold standard by finalizing it. This process was performed by a panel of three radiation oncology physicians' experiences. And the results of auto-segmentation of gold-standard and AVIEW RT ACS and auto-segmentation of predicate device are analyzed and evaluated using

9

DSC and 95% HD, respectively. The data set information used in the test is 120cases (each 60cases) including both Korean and U.S, Gender: F 70, M 50, Age: 20-89 years. The TCIA data was constructed with various ethnics (White, Black, Asian, Hispanic, Latino, African, American, etc.), the result can be obtained by performing generalization without performance difference according to ethnic

Breast (Both right and left lung, Heart) were validated with non-contrast and contrast CT.
A Head & Neck(Both right and left Eyes, Brain and Mandible), Abdomen(Both right and left Kidney and Liver), and Pelvis(Both right and left Femur and Bladder) were validated with Contrast CT only.
DSC and 95% HD(mm) for
- ◆ Total DSC & HD analysis.

Table 1 DSC for each oragn
Part	Organ	AVIEW	Predicate device	Difference
Head&
Neck	Brain (25)	0.97 ± 0.01(0.97, 0.98)	0.96 ± 0.01 (0.96, 0.96)	0.01
	Rt. Eye (25)	0.79 ± 0.10 (0.75, 0.83)	0.80 ± 0.06 (0.77, 0.82)	-0.01
	Lt. eye (25)	0.72 ± 0.12 (0.67, 0.76)	0.76 ± 0.12 (0.72, 0.81)	-0.04
	Mandible (25)	0.90 ± 0.05 (0.89, 0.93)	0.83 ± 0.07 (0.80, 0.86)	0.07
Breast	Heart (32)	0.94 ± 0.03 (0.93, 0.95)	0.78 ± 1.20 (0.70, 8.56)	0.16
	Rt. Lung (31)	0.98 ± 0.01 (0.97, 0.98)	0.96 ± 0.02 (0.95, 0.97)	0.02
	Lt. Lung (31)	0.97 ± 0.02 (0.96, 0.98)	0.96 ± 0.03 (0.95, 0.97)	0.01
Abdom
en	Liver (26)	0.96 ± 0.01 (0.96, 0.97)	0.87 ± 0.06 (0.85, 0.90)	0.09
	Rt. Kidney (26)	0.90 ± 0.03 (0.89, 0.91)	0.75 ± 0.18 (0.68, 0.82)	0.15
	Lt. kidney (26)	0.90 ± 0.05 (0.88, 0.92)	0.79 ± 0.12 (0.75, 0.84)	0.11
Pelvis	Bladder (35)	0.88 ± 0.14 (0.84, 0.93)	0.52 ± 0.26 (0.44, 0.60)	0.36
	Rt. Femur head
(37)	0.87 ± 0.14 (0.83, 0.90)	0.58 ± 0.11 (0.54, 0.61)	0.29
	Lt. Femur head
(37)	0.86 ± 0.10 (0.83, 0.90)	0.55 ± 0.11(0.51, 0.58)	0.31

Table 2. 95% HD (mm) for each oragn ●

Part	Organ	AVIEW	Predicate device	Difference
Head&
Neck	Brain (25)	6.92 ± 20.46 (-1.1, 14.94)	4.61 ± 2.17 (3.76, 5.46)	2.31
	Rt. Eye (25)	3.68 ± 1.50 (3.09, 4.27)	4.38 ± 1.36 (3.85, 4.91)	-0.70
	Lt. eye (25)	6.38 ± 11.11 (2.03, 10.74)	7.74 ± 10.83 (3.50, 11.99)	-1.36
	Mandible (25)	2.01 ± 1.23 (1.53, 2.49)	24.00 ± 93.61 (-12.69, 60.70)	-21.99
Breast	Heart (32)	6.19 ± 4.21 (4.73, 7.65)	18.90 ± 5.09 (17.14, 20.67)	-12.71
	Rt. Lung (31)	2.88 ± 1.67 (2.30, 3.47)	7.03 ± 2.94 (6.00, 8.06)	-4.14
	Lt. Lung (31)	4.97 ± 13.49 (0.22, 9.72)	4.83 ± 6.21 (2.64, 7.02)	0.14
Abdom
en	Liver (26)	7.17 ± 12.07 (2.54, 11.81)	24.62 ± 15.16 (18.79, 30.44)	-17.44
	Rt. Kidney (26)	6.84 ± 9.14 (3.33, 10.35)	14.63 ± 13.07 (9.60, 19.65)	-7.79

10

| | Lt. kidney (26) | $5.34 \pm 4.30$
(3.69, 6.99) | $15.18 \pm 10.71$ (11.06,
19.26) | -9.84 |
|--------|------------------------|------------------------------------|-------------------------------------|--------|
| Pelvis | Bladder (35) | $10.55 \pm 20.56$
(3.74, 17.36) | $30.48 \pm 22.76$ (22.94,
38.02) | -19.93 |
| | Rt. Femur head
(37) | $10.02 \pm 8.94$ (7.10,
12.93) | $43.65 \pm 30.38$ (33.72,
53.57) | -33.63 |
| | Lt. Femur head
(37) | $11.75 \pm 12.42$ (7.64,
15.86) | $46.14 \pm 24.84$ (37.91,
54.37) | -34.39 |

DSC and 95% HD(mm) were obtained by race, vendors, slice thickness and kernel for sub-group analysis.

				◆ Dice Similarity Coefficient Comparison (DSC)
--	--	--	--	------------------------------------------------	--	--

					Table 3. DSC for Korean Population each organ.
--	--	--	--	--	------------------------------------------------	--	--

Part	Organ	AVIEW	Predicate device	Difference
Head&
Neck	Brain (10)	0.97 ± 0.01 (0.97, 0.98)	0.96 ± 0.01 (0.95, 0.96)	0.01
	Rt. Eye (10)	0.81 ± 0.07 (0.76, 0.86)	0.80 ± 0.07 (0.76, 0.84)	0.01
	Lt. eye (10)	0.77 ± 0.09 (0.71, 0.82)	0.79 ± 0.06 (0.75, 0.83)	-0.02
	Mandible (10)	0.90 ± 0.03 (0.89, 0.93)	0.81 ± 0.09 (0.76, 0.87)	0.09
Breast	Heart (21)	0.95 ± 0.02 (0.94, 0.96)	0.81 ± 0.10 (0.76, 0.85)	0.14
	Rt. Lung (21)	0.97 ± 0.01 (0.97, 0.98)	0.96 ± 0.02 (0.95, 0.97)	0.01
	Lt. Lung (21)	0.96 ± 0.02 (0.96, 0.97)	0.95 ± 0.03 (0.94, 0.97)	0.01
Abdom
en	Liver (10)	0.95 ± 0.01 (0.94, 0.96)	0.88 ± 0.08 (0.83, 0.93)	0.07
	Rt. Kidney (10)	0.89 ± 0.03 (0.87, 0.91)	0.75 ± 0.24 (0.60, 0.90)	0.14
	Lt. kidney (10)	0.88 ± 0.06 (0.84, 0.92)	0.80 ± 0.16 (0.70, 0.90)	0.08
Pelvis	Bladder (17)	0.92 ± 0.07 (0.89, 0.95)	0.47 ± 0.27 (0.34, 0.59)	0.45
	Rt. Femur head
(19)	0.88 ± 0.07 (0.84, 0.91)	0.56 ± 0.11 (0.51, 0.61)	0.32
	Lt. Femur head
(19)	0.87 ± 0.78 (0.84, 0.91)	0.52 ± 0.13 (0.46, 0.58)	0.35

Table 4. DSC for U.S Population each organ. ●

Part	Organ	AVIEW	Predicate device	Difference
Head& Neck	Brain (15)	0.97 ± 0.01 (0.96, 0.98)	0.96 ± 0.01 (0.96, 0.97)	0.01
	Rt. Eye (15)	0.78 ± 0.12 (0.72, 0.84)	0.80 ± 0.06 (0.77, 0.83)	-0.02
	Lt. eye (15)	0.68 ± 0.13 (0.62 ± 0.75)	0.75 ± 0.14 (0.68, 0.82)	-0.07
	Mandible (15)	0.91 ± 0.06 (0.88, 0.94)	0.84 ± 0.06 (0.81, 0.87)	0.07
Breast	Heart (11)	0.93 ± 0.04 (0.90, 0.95)	0.71 ± 0.09 (0.65, 0.76)	0.22
	Rt. Lung (10)	0.98 ± 0.0 (0.98, 0.99)	0.96 ± 0.01 (0.96, 0.97)	0.02
	Lt. Lung (10)	0.97 ± 0.03 (0.95, 0.99)	0.96 ± 0.03 (0.95, 0.98)	-0.01
Abdom en	Liver (16)	0.97 ± 0.01 (0.96, 0.97)	0.87 ± 0.05 (0.85, 0.90)	1.0
	Rt. Kidney (16)	0.91 ± 0.01 (0.91, 0.92)	0.75 ± 0.14 (0.68, 0.82)	0.16

11

	Lt. kidney (16)	0.91 ± 0.02 (0.90, 0.92)	0.79 ± 0.09 (0.74, 0.83)	0.12
Pelvis	Bladder (18)	0.85 ± 0.19 (0.76, 0.94)	0.58 ± 0.22 (0.48, 0.69)	0.27
	Rt. Femur head
(18)	0.80 ± 0.12 (0.80,0.91)	0.60 ± 0.10 (0.55,0.65)	0.20
	Lt. Femur head
(18)	0.85 ± 0.13 (0.79 ±
0.91)	0.57 ± 0.09 (0.53, 0.62)	0.27

� Hausdorff Distance Comparison (95% HD)

Part	Organ	AVIEW	Predicate device	Difference
Head&
Neck	Brain (10)	13.19 ± 32.27 (6.81, 33.19)	4.33 ± 1.33 (3.51, 5.16)	8.86
	Rt. Eye (10)	3.18 ± 1.01 (2.55, 3.81)	4.14 ± 1.36 (3.30, 4.99)	-0.96
	Lt. eye (10)	3.53 ± 1.40 (2.66, 4.40)	5.22 ± 2.33 (3.78, 6.66)	-1.69
	Mandible
(10)	2.02 ± 0.53 (1.69, 2.35)	6.15 ± 5.71 (2.61, 9.69)	-4.13
Breast	Heart (21)	5.24 ± 2.57 (4.15, 6.34)	18.16 ± 4.72 (16.14, 20.18)	-12.92
	Rt. Lung
(21)	3.41 ± 1.76 (2.66, 4.16)	6.87 ± 3.19 (5.50, 8.23)	-3.46
	Lt. Lung
(21)	2.79 ± 0.52 (2.57, 3.01)	3.24 ± 0.96 (2.83, 3.65)	-0.45
Abdom
en	Liver (10)	4.29 ± 1.50 (3.26, 5.22)	21.14 ± 17.22 (10.46, 31.81)	-16.85
	Rt. Kidney
(10)	4.74 ± 1.77 (3.65, 5.84)	15.24 ± 17.44 (4.43, 26.05)	-10.49
	Lt. kidney
(10)	6.24 ± 3.35 (2.30, 10.18)	12.34 ± 10.54 (5.80, 18.87)	-6.10
Pelvis	Bladder (17)	4.90 ± 6.03 (2.19, 7.61)	33.96 ± 26.33 (22.13, 45.80)	-29.06
	Rt. Femur
head (19)	9.52 ± 6.64 (6.61, 12.43)	41.34 ± 8.74 (37.51, 45.17)	-31.82
	Lt. Femur
head (19)	9.93 ± 6.83 (6.94, 12.92)	49.19 ± 32.97 (34.73, 63.64)	-39.26

Table 6. 95% HD (mm) for U.S Population each organ ●

Part	Organ	AVIEW	Predicate device	Difference
Head&
Neck	Brain (15)	$2.74 \pm 1.09 (2.19, 3.29)$	$4.79 \pm 2.62 (3.47, 6.12)$	-2.05
	Rt. Eye (15)	$4.01 \pm 1.71 (3.15, 4.87)$	$4.53 \pm 1.38 (3.84, 5.23)$	-0.52
	Lt. eye (15)	$8.29 \pm 14.16 (1.12, 15.45)$	$9.42 \pm 13.78 (2.45, 16.40)$	-1.13
	Mandible (15)	$2.00 \pm 1.56 (1.21, 2.79)$	$35.91 \pm 120.91 (-25.28, 97.10)$	-33.91
Breast	Heart (11)	$8.00 \pm 6.03 (4.43, 11.56)$	$20.31 \pm 5.71 (16.94, 23.69)$	-12.31
	Rt. Lung (10)	$1.78 \pm 0.66 (1.36, 2.19)$	$7.37 \pm 2.43 (5.86, 8.88)$	-5.59
	Lt. Lung (10)	$9.56 \pm 23.90 (-5.25, 24.97)$	$8.18 \pm 10.41 (1.72, 14.63)$	1.38
Abdomen	Liver (16)	$8.98 \pm 15.24 (1.51, 16.45)$	$26.79 \pm 13.86 (20.00, 33.58)$	-17.81
en	Rt. Kidney (16)	$8.15 \pm 11.51 (3.61, 5.94)$	$14.25 \pm 10.08 (9.31, 19.19)$	-6.10
	Lt. kidney (16)	$4.77 \pm 2.38 (3.61, 5.94)$	$16.96 \pm 10.75 (11.69, 22.22)$	-12.19

12


Bladder (18)	$17.37 \pm 28.73 (3.29, 31.44)$	$27.01 \pm 18.47 (17.96, 36.06)$	-9.64
Rt. Femur head (18)	$10.57 \pm 11.16 (5.10, 16.04)$	$46.09 \pm 43.22 (24.91, 67.27)$	-35.52
Lt. Femur head (18)	$13.91 \pm 16.86 (5.38, 22.44)$	$42.52 \pm 8.23 (38.35, 46.68)$	-28.61

◆ DSC & 95% HD (mm) Comparison by vendors, slice thickness and kernel

Part	Organ	AVIEW	Predicate device	Difference
Head&
Neck	Brain (4)	0.97 ± 0.01 (0.97, 0.98)	0.96 ± 0.0 (0.96, 0.97)	0.01
	Rt. Eye (4)	0.85 ± 0.05 (0.80, 0.90)	0.77 ± 0.05 (0.72, 0.82)	0.08
	Lt. eye (4)	0.78 ± 0.04 (0.71, 0.86)	0.77 ± 0.05 (0.72, 0.82)	0.01
	Mandible (4)	0.91 ± 0.04 (0.87, 0.94)	0.81 ± 0.13 (0.68, 0.94)	0.10
Breast	Heart (9)	0.94 ± 0.02 (0.93, 0.96)	0.75 ± 0.10 (0.69, 0.82)	0.19
	Rt. Lung (9)	0.97 ± 0.01 (0.96, 0.98)	0.95 ± 0.02 (0.94, 0.97)	-0.02
	Lt. Lung (9)	0.96 ± 0.02 (0.95, 0.97)	0.95 ± 0.02 (0.94, 0.97)	0.01
Abdomen	Liver (16)	0.96 ± 0.01 (0.96, 0.97)	0.86 ± 0.06 (0.84, 0.89)	0.10
	Rt. Kidney (16)	0.91 ± 0.02 (0.90, 0.92)	0.77 ± 0.12 (0.72, 0.83)	0.14
	Lt. kidney (16)	0.91 ± 0.03 (0.89, 0.92)	0.78 ± 0.08 (0.74, 0.82)	0.13
Pelvis	Bladder (18)	0.90 ± 0.07 (0.87, 0.93)	0.55 ± 0.27 (0.42, 0.67)	0.35
	Rt. Femur head (19)	0.90 ± 0.06 (0.87, 0.93)	0.56 ± 0.10 (0.51, 0.60)	0.34
	Lt. Femur head (19)	0.89 ± 0.09 (0.85, 0.93)	0.53 ± 0.13 (0.47, 0.58)	0.36

● Table 7. DSC for organ by SIEMENS vendors.

● Table 8. 95% HD (mm) for each organ by SIEMENS vendors.

Part	Organ	AVIEW	Predicate device	Difference
Head&
Neck	Brain (4)	28.16 ± 51.23 (-22.04,
78.36)	3.28 ± 0.45 (2.84, 3.72)	24.88
	Rt. Eye (4)	2.77 ± 0.37 (2.42, 3.13)	4.75 ± 1.50 (3.29, 6.22)	-1.98
	Lt. eye (4)	3.26 ± 0.53 (2.74, 3.78)	5.30 ± 2.18 (3.16 ± 7.44)	-2.04
	Mandible (4)	1.91 ± 0.51 (1.42, 2.41)	5.04 ± 4.11 (1.01, 9.08)	-3.13
Breast	Heart (9)	5.92 ± 2.97 (3.98, 7.86)	20.17 ± 3.52 (17.86, 22.47)	-14.25
	Rt. Lung (9)	2.73 ± 0.61 (2.33, 3.13)	7.30 ± 2.63 (5.58, 9.02)	-4.58
	Lt. Lung (9)	2.97 ± 0.26 (2.80, 3.14)	3.63 ± 1.25 (2.81, 4.45)	-0.65
Abdomen	Liver (16)	9.10 ± 15.19 (1.66, 16.55)	29.04 ± 14.54 (21.92, 36.16)	-19.93
	Rt. Kidney (16)	8.40 ± 11.42 (2.81, 14.00)	15.54 ± 9.83 (10.73, 20.36)	-7.14
	Lt. kidney (16)	5.47 ± 3.29 (3.86, 7.08)	18.94 ± 10.02 (14.03, 23.85)	-13.47
Pelvis	Bladder (18)	7.04 ± 9.22 (2.65, 11.42)	23.99 ± 17.93 (15.71, 32.27)	-16.95
	Rt. Femur head (19)	8.01 ± 6.47 (5.10, 10.92)	50.42 ± 3.59 (32.13, 68.71)	-42.41
	Lt. Femur head (19)	8.57 ± 7.05 (5.40, 11.74)	41.98 ± 9.27 (37.70, 46.27)	-33.41

Table 9. DSC for each oragn by GE vendors ●

Part	Organ	AVIEW	Predicate device	Difference
Head&
Neck	Brain (2)	$0.96 \pm 0.01 (0.96, 0.97)$	$0.97 \pm 0.0 (0.96, 0.97)$	-0.01
	Rt. Eye (2)	$0.70 \pm 0.08 (0.64, 0.76)$	$0.81 \pm 0.04 (0.78, 0.84)$	-0.11
	Lt. eye (2)	$0.61 \pm 0.12 (0.53, 0.69)$	$0.78 \pm 0.06 (0.74, 0.81)$	-0.17
	Mandible (2)	$0.88 \pm 0.07 (0.83, 0.93)$	$0.81 \pm 0.06 (0.65, 0.76)$	0.07

13

Breast	Heart (12)	0.93 ± 0.04 (0.90, 0.95)	0.71 ± 0.09 (0.65, 0.76)	0.22
	Rt. Lung (12)	0.98 ± 0.0 (0.98, 0.99)	0.96 ± 0.01 (0.96, 0.97)	0.02
	Lt. Lung (12)	0.97±0.03 (0.95, 0.99)	0.96 ± 0.03 (0.95, 0.98)	0.01
	Abdomen	Liver (3)	0.97	0.85
Rt. Kidney (3)		0.91	0.50	0.41
Lt. kidney (3)		0.89	0.88	0.01
Pelvis	Bladder (9)	0.72 ± 0.31 (0.45, 1.0)	0.52 ± 0.25 (0.31, 0.74)	0.20
	Rt. Femur head (9)	0.84 ± 0.13 (0.73, 0.95)	0.60 ± 0.12 (0.49, 0.71)	0.24
	Lt. Femur head (9)	0.81±0.15 (0.68, 0.94)	0.56±0.11 (0.46, 0.65)	0.25

● Table 10. 95% HD (mm) for each oragn by GE vendors

Table 10. 95% HD (mm) for each oragn by GE vendors
Part	Organ	AVIEW	Predicate device	Difference
Head&
Neck	Brain (2)	3.37 ± 1.12 (2.60, 4.14)	4.01 ± 0.77 (3.48, 4.55)	-0.64
	Rt. Eye (2)	5.18 ± 1.16 (4.37, 5.98)	4.57 ± 1.37 (3.62, 5.52)	0.61
	Lt. eye (2)	5.63 ± 1.06 (4.89, 6.36)	6.27 ± 3.77 (3.66, 8.89)	-0.64
	Mandible (2)	2.64 ± 1.93 (1.30, 3.97)	64.50 ± 165.04 (16.94, 23.69)	-61.86
Breast	Heart (12)	8.00 ± 6.03 (4.43, 11.56)	20.31 ± 5.71 (16.94, 23.69)	-12.31
	Rt. Lung (12)	1.78 ± 0.66 (1.36, 2.19)	7.37 ± 2.43 (5.86, 8.88)	-5.59
	Lt. Lung (12)	9.56 ± 23.90 (-5.25, 24.37)	8.18 ± 10.41 (1.72, 14.63)	-1.38
Abdomen	Liver (3)	3.27	32.82	-29.55
	Rt. Kidney (3)	3.27	5.88	-2.61
	Lt. kidney (3)	3.27	6.55	-3.28
Pelvis	Bladder (9)	14.13 ± 11.93 (3.68, 24.59)	36.66 ± 31.09 (9.40, 63.91)	-22.53
	Rt. Femur head (9)	10.68 ± 9.53 (2.33, 19.04)	32.41 ± 12.58 (21.93, 43.44)	-21.73
	Lt. Femur head (9)	19.93 ± 22.34 (0.35, 39.51)	44.61 ± 11.01 (34.96, 54.26)	-24.68

● Table 11. DSC for each organ by PHILIPS vendors

Part	Organ	AVIEW	Predicate device	Difference
Head&
Neck	Brain (11)	0.98 ± 0.01 (0.97, 0.98)	0.96 ± 0.01
(0.95, 0.96)	0.02
	Rt. Eye (11)	0.83 ± 0.09 (0.77, 0.88)	0.81 ± 0.07 (0.77, 0.86)	0.02
	Lt. eye (11)	0.74 ± 0.10 (0.69, 0.80)	0.76 ± 0.17 (0.67, 0.85)	0.02
	Mandible (11)	0.93 ± 0.03 (0.91, 0.94)	0.85 ± 0.06 (0.82, 0.89)	0.08
Breast	Heart	N/A	N/A
	Rt. Lung	N/A	N/A
	Lt. Lung	N/A	N/A
Abdom
en	Liver (6)	0.95 ± 0.02 (0.94, 0.97)	0.89 ± 0.08 (0.83, 0.95)	0.06
	Rt. Kidney (6)	0.88 ± 0.04 (0.85, 0.91)	0.67 ± 0.30 (0.43, 0.90)	0.21
	Lt. kidney (6)	0.87 ± 0.07 (0.81, 0.93)	0.75 ± 0.19 (0.59, 0.90)	0.12
Pelvis	Bladder (4)	0.88 ± 0.05 (0.83, 0.93)	0.31 ± 0.18 (0.14, 0.48)	0.57

14

core:line

| Rt. Femur

head (4)	$0.79 \pm 0.16$ (0.63, 0.94)	$0.64 \pm 0.15$ (0.50, 0.79)	0.15
Lt. Femur
head (4)	$0.77 \pm 0.14$ (0.63, 0.90)	$0.63 \pm 0.13$ (0.50, 0.75)	0.14

Table 12. 95% HD (mm) for each organ by PHILIPS vendors. ●

Part	Organ	AVIEW	Predicate device	Difference
Head&
Neck	Brain (11)	2.57 ± 0.85 (2.07, 3.08)	5.30 ± 2.94 (3.56, 7.04)	-2.73
	Rt. Eye (11)	3.11 ± 1.31 (2.34, 3.88)	3.97 ± 1.43 (3.12, 4.81)	-0.86
	Lt. eye (11)	8.80 ± 16.77 (-1.10,18.71)	9.96 ± 16.13 (0.43, 19.49)	-1.16
	Mandible
(11)	1.72 ± 0.67 (1.33, 2.12)	5.18 ± 5.27 (2.06, 8.29)	-3.46
Breast	Heart	N/A	N/A
	Rt. Lung	N/A	N/A
	Lt. Lung	N/A	N/A
Abdomen	Liver (6)	4.18 ± 1.95 (2.62, 5.74)	18.06 ± 15.21 (5.89, 30.24)	-13.88
en	Rt. Kidney
(6)	4.54 ± 1.78 (3.12, 5.96)	17.55 ± 22.23 (-0.24, 35.34)	-13.01
	Lt. kidney
(6)	6.30 ± 7.42 (0.36, 12.24)	11.38 ± 11.62 (2.07, 20.68)	-5.08
Pelvis	Bladder (4)	8.72 ± 5.85 (2.10, 15.34)	38.68 ± 8.49 (29.07, 48.29)	-29.96
	Rt. Femur
head (4)	14.44 ± 18.68 (-6.70,
35.58)	24.39 ± 23.29 (-1.96, 50.75)	-9.95
	Lt. Femur
head (4)	54.37 ± 59.01 (-12.40,
121.14)	37.60 ± 5.32 (31.58, 43.61)	16.77

● Table 13. DSC for each organ by TOSHIBA vendors

Part	Organ	AVIEW	Predicate device	Difference
Head&
Neck	Brain (2)	0.96 ± 0.02 (0.93, 0.99)	0.95 ± 0.01 (0.94, 0.97)	0.01
	Rt. Eye (2)	0.86 ± 0.05 (0.78, 0.93)	0.75 ± 0.03 (0.71, 0.79)	0.11
	Lt. eye (2)	0.84 ± 0.06 (0.76, 0.93)	0.74 ± 0.03 (0.70, 0.77)	0.10
	Mandible (2)	0.94 ± 0.0 (0.93, 0.94)	0.85 ± 0.01 (0.84, 0.86)	0.09
Breast	Heart (12)	0.95 ± 0.02 (0.94, 0.96)	0.85 ± 0.09 (0.80, 0.90)	0.10
	Rt. Lung
(12)	0.97 ± 0.01 (0.96, 0.98)	0.96 ± 0.02 (0.95, 0.97)	0.01
	Lt. Lung
(12)	0.97 ± 0.01 (0.96, 0.98)	0.95 ± 0.04 (0.93, 0.98)	0.02
Abdom
en	Liver (3)	0.95 ± 0.01 (0.94, 0.96)	0.92 ± 0.04 (0.87, 0.97)	0.03
	Rt. Kidney
(3)	0.92 ± 0.02 (0.90, 0.94)	0.89 ± 0.04 (0.84, 0.94)	0.03
	Lt. kidney
(3)	0.93 ± 0.03 (0.90, 0.96)	0.91 ± 0.04 (0.86, 0.96)	0.02
Pelvis	Bladder (9)	0.95 ± 0.02 (0.93, 0.96)	0.52 ± 0.26 (0.35, 0.69)	0.43
	Rt. Femur
head (9)	0.85 ± 0.10 (0.78, 0.91)	0.56 ± 0.09 (0.50, 0.62)	0.29
	Lt. Femur
head (9)	0.88 ± 0.07 (0.84, 0.92)	0.58 ± 0.08 (0.53, 0.63)	0.30

● Table 14. 95% HD (mm) for each organ by TOSHIBA vendors.

Part	Organ	AVIEW	Predicate device	Difference
Head&Neck	Brain (2)	$2.53 \pm 2.08 (-0.36, 5.41)$	$5.86 \pm 1.89 (3.24, 8.48)$	-3.33
	Rt. Eye (2)	$2.62 \pm 0.40 (2.06, 3.18)$	$5.10 \pm 0.26 (4.73, 5.46)$	-2.48
	Lt. eye (2)	$2.35 \pm 0.79 (1.26, 3.44)$	$6.31 \pm 0.44 (5.70, 6.93)$	-3.96
	Mandible (2)	$1.28 \pm 0.31 (0.85, 1.71)$	$3.50 \pm 0.57 (2.71, 4.28)$	-2.22
Breast	Heart (12)	$4.74 \pm 2.22 (3.48, 5.99)$	$16.66 \pm 5.07 (13.79, 19.53)$	-11.92

15

| | Rt. Lung
(12) | $3.93 \pm 2.16 (2.71, 5.15)$ | $6.54 \pm 3.63 (4.48, 8.59)$ | -2.61 |
|---------|-----------------------|---------------------------------|----------------------------------|--------|
| | Lt. Lung
(12) | $2.65 \pm 0.62 (2.30, 3.00)$ | $2.94 \pm 0.55 (2.63, 3.25)$ | -0.29 |
| Abdomen | Liver (3) | $4.17 \pm 1.36 (2.63, 5.74)$ | $11.39 \pm 11.38 (-1.48, 24.27)$ | -7.22 |
| en | Rt. Kidney
(3) | $4.30 \pm 2.32 (1.68, 6.91)$ | $6.81 \pm 3.43 (2.94, 10.69)$ | -2.51 |
| | Lt. kidney
(3) | $3.39 \pm 1.05 (2.20, 4.47)$ | $5.59 \pm 3.12 (2.06, 9.12)$ | -2.2 |
| Pelvis | Bladder (9) | $3.80 \pm 1.03 (3.13, 4.47)$ | $36.27 \pm 29.82 (16.79, 55.76)$ | -32.47 |
| | Rt. Femur
head (9) | $12.40 \pm 9.95 (5.90, 18.90)$ | $42.77 \pm 7.46 (37.89, 47.64)$ | -30.37 |
| | Lt. Femur
head (9) | $11.57 \pm 10.16 (4.94, 18.21)$ | $42.54 \pm 6.74 (38.13, 46.94)$ | -30.37 |

● Table 15. DSC for each organ by ≥1, ≤2 slice thickness

Part	Organ	AVIEW	Predicate device	Difference
Head&
Neck	Brain (9)	0.97 ± 0.01 (0.96, 0.98)	0.96 ± 0.01 (0.95, 0.96)	0.01
	Rt. Eye (9)	0.86 ± 0.07 (0.78, 0.87)	0.80 ± 0.06 (0.76, 0.84)	0.06
	Lt. eye (9)	0.79 ± 0.08 (0.74, 0.84)	0.80 ± 0.06 (0.76, 0.84)	-0.01
	Mandible (9)	0.91 ± 0.03 (0.89, 0.93)	0.81 ± 0.09 (0.75, 0.87)	0.1
Breast	Heart (1)	0.93	0.69	0.24
	Rt. Lung (1)	0.98	0.97	0.01
	Lt. Lung (1)	0.97	0.97	0.00
Abdomen	Liver (5)	0.97 ± 0.01 (0.95, 0.98)	0.88 ± 0.02 (0.86, 0.91)	0.09
	Rt. Kidney (5)	0.90 ± 0.01 (0.87, 0.93)	0.76 ± 0.17 (0.61, 0.91)	0.14
	Lt. kidney (5)	0.88 ± 0.08 (0.80, 0.95)	0.86 ± 0.08 (0.79, 0.93)	0.02
Pelvis	Bladder (3)	0.88 ± 0.06 (0.81, 0.95)	0.05 ± 0.24 (0.24, 0.77)	0.38
	Rt. Femur head (3)	0.76 ± 0.10 (0.88, 0.65)	0.71 ± 0.08 (0.59, 0.82)	0.05
	Lt. Femur head (3)	0.71 ± 0.02 (0.69, 0.74)	0.72 ± 0.03 (0.68, 0.75)	-0.01

. Table 16. 95% HD (mm) for each organ by ≥1, ≤2 slice thickness

Part	Organ	AVIEW	Predicate device	Difference
Head&Neck	Brain (9)	$14.24 \pm 34.04 (-8.0, 36.48)$	$4.48 \pm 1.39 (3.55, 5.36)$	9.76
	Rt. Eye (9)	$3.15 \pm 1.06 (2.46, 3.84)$	$4.23 \pm 1.32 (3.37, 5.09)$	-1.08
	Lt. eye (9)	$3.58 \pm 1.60 (2.54, 4.63)$	$5.57 \pm 3.64 (3.29, 8.04)$	-1.99
	Mandible (9)	$1.93 \pm 0.60 (1.53, 2.32)$	$6.06 \pm 5.98 (2.15, 9.97)$	-4.13
Breast	Heart (1)	8	15.93	-7.93
	Rt. Lung (1)	2	5.33	-3.33
	Lt. Lung (1)	2	2.18	-0.18
Abdomen	Liver (5)	$14.72 \pm 25.47 (-7.61, 37.05)$	$30.88 \pm 19.29 (13.97, 47.79)$	-16.16
	Rt. Kidney (5)	$13.10 \pm 17.17 (-1.95, 28.15)$	$18.69 \pm 15.09 (5.46, 31.91)$	-5.59
	Lt. kidney (5)	$7.50 \pm 7.90 (0.58, 14.42)$	$13.08 \pm 9.35 (4.88, 21.27)$	-5.58
Pelvis	Bladder (3)	$10.11 \pm 6.48 (1.13, 19.09)$	$33.06 \pm 9.55 (46.29, 19.82)$	-22.95
	Rt. Femur head (3)	$16.16 \pm 16.74 (-7.04, 39.36)$	$16.27 \pm 21.85 (-14.01, 46.56)$	-0.11
	Lt. Femur head (3)	$73.29 \pm 64.05 (-15.48, 162.06)$	$34.0 \pm 8.21 (22.62, 45.38)$	39.29

16

Part	Organ	AVIEW	Predicate device	Difference
Head&
Neck	Brain (9)	0.98 ± 0.01 (0.97, 0.98)	0.96 ± 0.01 (0.95, 0.96)	0.02
	Rt. Eye (9)	0.84 ± 0.08 (0.79, 0.90)	0.79 ± 0.08 (0.74, 0.84)	0.05
	Lt. eye (9)	0.74 ± 0.1 (0.67, 0.80)	0.72 ± 0.18 (0.61, 0.84)	0.02
	Mandible (9)	0.94 ± 0.03 (0.92, 0.96)	0.88 ± 0.03 (0.85, 0.90)	0.06
Breast	Heart (20)	0.95 ± 0.02 (0.94, 0.96)	0.81 ± 0.10 (0.77, 0.86)	0.14
	Rt. Lung (20)	0.97 ± 0.01 (0.97, 0.98)	0.96 ± 0.02 (0.95, 0.97)	0.01
	Lt. Lung (20)	0.97 ± 0.02 (0.96, 0.97)	0.95 ± 0.03 (0.94, 0.97)	0.02
Abdomen	Liver (15)	0.96 ± 0.01 (0.95, 0.96)	0.88 ± 0.07 (0.84, 0.92)	0.08
	Rt. Kidney (15)	0.90 ± 0.02 (0.89, 0.92)	0.75 ± 0.02 (0.65, 0.85)	0.15
en	Lt. kidney (15)	0.91 ± 0.04 (0.89, 0.92)	0.78 ± 0.13 (0.71, 0.85)	0.13
Pelvis	Bladder (24)	0.89 ± 0.16 (0.83, 0.95)	0.48 ± 0.28 (0.37, 0.59)	0.41
	Rt. Femur head (24)	0.88 ± 0.09 (0.84, 0.91)	0.57 ± 0.10 (0.53, 0.61)	0.31
	Lt. Femur head (24)	0.88 ± 0.09 (0.84, 0.91)	0.54 ± 0.12 (0.50, 0.59)	0.34

. Table 17. DSC for each organ by >2, ≤3 slice thickness

● Table 18. 95% HD (mm) for each organ by >2, ≤3 slice thickness

Part	Organ	AVIEW	Predicate device	Difference
Head&
Neck	Brain (9)	2.29 ± 0.67 (1.85, 2.73)	5.28 ± 3.29 (3.13, 7.43)	-2.99
	Rt. Eye (9)	2.91 ± 1.12 (2.18, 3.64)	4.56 ± 1.58 (3.53, 5.60)	-1.65
	Lt. eye (9)	9.77 ± 18.56 (-2.35, 21.9)	11.80 ± 17.47 (0.38, 23.21)	-2.03
	Mandible (9)	1.45 ± 0.51 (1.11, 1.79)	3.71 ± 1.71 (2.59, 4.82)	-2.26
Breast	Heart (20)	5.11 ± 2.56 (3.99, 6.23)	18.12 ± 4.84 (16.0, 20.24)	-13.01
	Rt. Lung (20)	3.48 ± 1.77 (2.71, 4.26)	6.94 ± 3.25 (5.52, 8.67)	-3.46
	Lt. Lung (20)	2.83 ± 0.50 (2.61, 3.04)	3.29 ± 0.95 (2.87, 3.70)	-0.46
Abdomen	Liver (15)	3.99 ± 1.51 (3.22, 4.75)	20.99 ± 16.1 (12.85, 29.14)	-17
	Rt. Kidney (15)	3.99 ± 1.16 (3.40, 4.57)	13.43 ± 14.1 (6.32, 20.55)	-9.44
	Lt. kidney (15)	4.35 ± 2.85 (2.91, 5.79)	14.46 ± 10.63 (9.08, 19.83)	-10.11
Pelvis	Bladder (24)	6.81 ± 8.68 (3.34, 10.29)	30.16 ± 24.80 (20.02, 40.30)	-23.35
	Rt. Femur head (24)	10.01 ± 8.79 (6.63, 13.39)	41.54 ± 8.85 (38.07, 45.01)	-31.53
	Lt. Femur head (24)	10.51 ± 9.74 (6.76, 14.25)	41.95 ± 8.57 (38.59, 45.31)	-31.44

| | | | | | | Table 19. DSC for each oragan. by >3. 3, ≤4 slice thickness ●

Part	Organ	AVIEW	Predicate device	Difference
Head&
Neck	Brain (7)	3.45 ± 1.18 (2.58, 4.33)	3.94 ± 0.80 (3.35, 4.54)	-0.49
	Rt. Eye (7)	5.35 ± 1.15 (4.5, 6.2)	4.32 ± 1.27 (3.38, 5.27)	1.03
	Lt. eye (7)	5.63 ± 1.15 (4.78, 6.48)	5.2 ± 2.41 (3.41, 6.98)	0.43
	Mandible (7)	2.83 ± 2.0 (1.36, 4.31)	73.16 ± 176.29 (-57.43,
203.76)	-70.33
Breast	Heart (10)	8.13 ± 6.34 (4.2, 12.06)	19.84 ± 5.79 (16.25, 23.43)	-11.71
	Rt. Lung
(10)	1.61 ± 0.43 (1.33, 1.89)	7.37 ± 2.43 (5.86, 8.88)	-5.76
	Lt. Lung
(10)	10.26 ± 25.24 (-6.23,
26.75)	8.18 ± 10.41 (1.72, 14.63)	2.08
Abdom
en	Liver (1)	3.27	32.82	-29.55
	Rt. Kidney
(1)	3.27	5.88	-2.61
	Lt. kidney
(1)	3.27	6.55	-3.28
Pelvis	Bladder (2)	18.16 ± 14.90 (-2.49,
38.81)	68.99 ± 15.60 (47.37, 90.61)	-50.83
	Rt. Femur
head (2)	14.21 ± 10.85 (-0.82,
29.24)	19.92 ± 4.20 (14.11, 25.74)	-5.71
	Lt. Femur
head (2)	32.33 ± 36.47 (-18.22,
82.87)	50.32 ± 16.58 (27.34, 73.29)	-17.99

● Table 21. DSC for each oragan. by >4, ≤5slice thickness

Part	Organ	AVIEW	Predicate device	Difference
Head&
Neck	Brain	N/A	N/A
	Rt. Eye	N/A	N/A
	Lt. eye	N/A	N/A
	Mandible	N/A	N/A
Breast	Heart (1)	0.82	0.81	0.01
	Rt. Lung	N/A	N/A
	Lt. Lung	N/A	N/A
Abdomen	Liver (5)	0.96 ± 0.0 (0.96, 0.97)	0.84 ± 0.04 (0.81, 0.87)	0.12
	Rt. Kidney
(5)	0.91 ± 0.02 (0.89, 0.92)	0.72 ± 0.16 (0.57, 0.86)	0.19
	Lt. kidney
(5)	0.91 ± 0.01 (0.89, 0.92)	0.74 ± 0.08 (0.67, 0.81)	0.17
	Pelvis	Bladder (6)	0.91 ± 0.09 (0.84, 0.98)	0.69 ± 0.12 (0.59, 0.78)
Rt. Femur
head (6)		0.90 ± 0.06 (0.85, 0.95)	0.55 ± 0.06 (0.50, 0.60)	0.35
Lt. Femur
head (6)		0.90 ± 0.05 (0.86, 0.95)	0.55 ± 0.05 (0.51, 0.59)	0.35

● Table 22. 95% HD (mm) for each oragan. by >4, ≤5 slice thickness

18

Part	Organ	AVIEW	Predicate device	Difference
Head&
Neck	Brain	N/A	N/A
	Rt. Eye	N/A	N/A
	Lt. eye	N/A	N/A
	Mandible	N/A	N/A
Breast	Heart (1)	6.68	25	-18.32

	Rt. Lung	N/A	N/A
	Lt. Lung	N/A	N/A
Abdom
en	Liver (5)	9.97 ± 11.42 (-0.04, 19.98)	27.57 ± 5.71 (22.57, 32.58)	-17.6
	Rt. Kidney
(5)	9.86 ± 11.31 (-0.05, 19.77)	15.91 ± 10.03 (7.12, 24.70)	6.05
	Lt. kidney
(5)	6.56 ± 3.48 (3.51, 9.60)	21.18 ± 12.75 (10.0, 32.36)	-14.62
Pelvis	Bladder (6)	5.1 ± 3.86 (2.01, 8.19)	19.33 ± 6.58 (14.06, 24.60)	-14.23
	Rt. Femur
head (6)	9.07 ± 8.89 (1.96, 16.19)	42.35 ± 5.09 (38.28, 46.42)	-33.28
	Lt. Femur
head (6)	8.71 ± 9.21 (1.35, 16.08)	42.84 ± 4.11 (36.55, 46.13)	-34.13

. Table 23. DSC for each oragan. By soft kernel

Part	Organ	AVIEW	Predicate device	Difference
Head&
Neck	Brain (12)	0.97 ± 0.01 (0.96, 0.98)	0.96 ± 0.01 (0.95, 0.96)	0.01
	Rt. Eye (12)	0.82 ± 0.09 (0.77, 0.88)	0.78 ± 0.06 (0.75, 0.82)	0.04
	Lt. eye (12)	0.73 ± 0.14 (0.65, 0.81)	0.73 ± 0.15 (0.64, 0.81)	0.00
	Mandible
(12)	0.92 ± 0.05 (0.89, 0.95)	0.85 ± 0.06 (0.82, 0.89)	0.07
Breast	Heart (17)	0.95 ± 0.02 (0.94, 0.95)	0.80 ± 0.12 (0.75, 0.86)	0.15
	Rt. Lung
(17)	0.98 ± 0.01 (0.97, 0.98)	0.96 ± 0.01 (0.96, 0.97)	0.02
	Lt. Lung
(17)	0.97 ± 0.01 (0.97, 0.98)	0.96 ± 0.03 (0.94, 0.97)	0.01
Abdomen	Liver (4)	0.96 ± 0.01 (0.94, 0.97)	0.88 ± 0.08 (0.80, 0.96)	0.08
	Rt. Kidney
(4)	0.92 ± 0.02 (0.91, 0.94)	0.80 ± 0.17 (0.64, 0.97)	0.12
	Lt. kidney
(4)	0.93 ± 0.02 (0.91, 0.96)	0.85 ± 0.12 (0.73, 0.97)	0.08
Pelvis	Bladder (15)	0.91 ± 0.08 (0.87, 0.95)	0.47 ± 0.25 (0.34, 0.59)	0.44
	Rt. Femur
head (14)	0.83 ± 0.11 (0.77, 0.89)	0.61 ± 0.12 (0.55, 0.67)	0.22
	Lt. Femur
head (14)	0.84 ± 0.10 (0.79, 0.89)	0.58 ± 0.09 (0.53, 0.63)	0.26

. Table 24. 95% HD (mm) for each oragan. By soft kernel

Part	Organ	AVIEW	Predicate device	Difference
Head&
Neck	Brain (12)	$2.84 \pm 1.40 (2.05, 3.63)$	$5.44 \pm 2.87 (3.82, 7.07)$	-2.60
	Rt. Eye (12)	$3.29 \pm 1.50 (2.44, 4.14)$	$4.58 \pm 1.21 (3.89, 5.26)$	-1.29
	Lt. eye (12)	$8.28 \pm 16.10 (-0.83, 17.39)$	$10.15 \pm 15.15 (1.58, 18.72)$	-1.87
	Mandible
(12)	$1.96 \pm 1.72 (0.98, 2.93)$	$4.28 \pm 3.05 (2.56, 6.00)$	-2.32
Breast	Heart (17)	$6.43 \pm 5.29 (3.91, 8.94)$	$18.13 \pm 5.42 (15.56, 20.71)$	-11.70
	Rt. Lung
(17)	$3.34 \pm 2.14 (2.29, 4.39)$	$6.53 \pm 3.20 (4.96, 8.10)$	-3.19
	Lt. Lung
(17)	$2.45 \pm 0.76 (2.07, 2.82)$	$3.05 \pm 0.57 (2.77, 3.33)$	-0.60
Abdom	Liver (4)	$3.75 \pm 1.40 (2.38, 5.12)$	$18.46 \pm 16.92 (1.88, 35.04)$	-14.71

19

| en | Rt. Kidney
(4) | $3.88 \pm 2.06$ (1.86, 5.90) | $6.61 \pm 2.83$ (3.84, 9.38) | -2.73 |
|--------|------------------------|----------------------------------|----------------------------------|--------|
| | Lt. kidney
(4) | $3.17 \pm 0.97$ (2.21, 4.12) | $5.86 \pm 2.60$ (3.31, 8.40) | -2.69 |
| Pelvis | Bladder (15) | $14.83 \pm 30.69$ (-1.24, 30.91) | $38.59 \pm 24.31$ (25.85, 51.33) | -23.76 |
| | Rt. Femur
head (14) | $12.42 \pm 11.32$ (6.27, 18.57) | $36.54 \pm 15.01$ (28.38, 44.70) | -24.12 |
| | Lt. Femur
head (14) | $12.94 \pm 12.92$ (5.62, 20.25) | $41.20 \pm 6.61$ (37.46, 44.94) | -28.26 |

● Table 25. DSC for each oragan. By standard kernel

Part	Organ	AVIEW	Predicate device	Difference
Head&
Neck	Brain (4)	0.97 ± 0.01 (0.96, 0.98)	0.96 ± 0.00 (0.96, 0.97)	0.01
	Rt. Eye (4)	0.67 ± 0.11 (0.57, 0.77)	0.79 ± 0.03 (0.76, 0.81)	-0.12
	Lt. eye (4)	0.62 ± 0.13 (0.49, 0.74)	0.76 ± 0.04 (0.73, 0.80)	-0.14
	Mandible (4)	0.92 ± 0.04 (0.88, 0.96)	0.82 ± 0.03 (0.79, 0.85)	0.10
Breast	Heart (6)	0.92 ± 0.05 (0.88, 0.96)	0.70 ± 0.07 (0.64, 0.76)	0.22
	Rt. Lung (6)	0.99 ± 0.00 (0.98, 0.99)	0.96 ± 0.01 (0.95, 0.97)	0.03
	Lt. Lung (6)	0.96 ± 0.05 (0.92, 1.00)	0.95 ± 0.03 (0.92, 0.98)	0.01
Abdomen	Liver (1)	0.97	0.85	0.12
	Rt. Kidney (1)	0.91	0.50	0.41
	Lt. kidney (1)	0.89	0.88	0.01
Pelvis	Bladder (4)	0.73 ± 0.36 (0.38, 1.09)	0.59 ± 0.22 (0.37, 0.81)	0.14
	Rt. Femur head (4)	0.84 ± 0.14 (0.70, 0.99)	0.56 ± 0.07 (0.49, 0.63)	0.28
	Lt. Femur head (4)	0.81 ± 0.17 (0.64, 0.98)	0.53 ± 0.11 (0.43, 0.63)	0.28

● Table 26. 95% HD (mm) for each oragan. By standard kernel

Part	Organ	AVIEW	Predicate device	Difference
Head&
Neck	Brain (4)	2.82 ± 0.63 (2.21, 3.44)	3.96 ± 0.54 (3.43, 4.48)	-1.14
	Rt. Eye (4)	5.48 ± 1.25 (4.26, 6.70)	5.06 ± 1.62 (3.47, 6.65)	0.42
	Lt. eye (4)	5.77 ± 1.19 (4.60, 6.94)	7.67 ± 5.05 (2.72, 12.62)	1.90
	Mandible (4)	1.90 ± 0.83 (1.09, 2.71)	5.14 ± 3.19 (2.01, 8.26)	-3.24
Breast	Heart (6)	5.93 ± 2.43 (3.99, 7.87)	19.18 ± 6.49 (13.99, 24.38)	-13.25
	Rt. Lung (6)	1.91 ± 0.78 (1.29, 2.53)	7.94 ± 2.82 (5.68, 10.20)	-6.03
	Lt. Lung (6)	14.70 ± 30.79 (-9.94,
39.34)	11.38 ± 12.80 (1.14, 21.63)	3.32
Abdomen	Liver (1)	3.27	32.82	-29.55
	Rt. Kidney (1)	3.27	5.88	-2.61
	Lt. kidney (1)	3.27	6.55	-3.28
Pelvis	Bladder (4)	10.49 ± 10.06 (0.63, 20.36)	31.33 ± 33.16 (-1.17, 63.83)	-20.84
	Rt. Femur head (4)	11.72 ± 10.67 (1.26, 22.18)	36.28 ± 10.56 (25.93, 46.62)	-24.56
	Lt. Femur head (4)	23.28 ± 24.30 (-0.54,
47.10)	46.11 ± 12.11 (34.24, 57.98)	-22.83

● Table 27. DSC for each oragan. By medium kernel

Part	Organ	AVIEW	Predicate device	Difference
Head&	Brain (4)	0.97 ± 0.01 (0.97, 0.98)	0.96 ± 0.00 (0.96, 0.97)	0.01

20

Neck	Rt. Eye (4)	$0.85 \pm 0.05 (0.80, 0.90)$	$0.77 \pm 0.05 (0.72, 0.82)$	0.08
	Lt. eye (4)	$0.78 \pm 0.08 (0.71, 0.86)$	$0.77 \pm 0.05 (0.72, 0.82)$	0.01
	Mandible (4)	$0.91 \pm 0.04 (0.87, 0.94)$	$0.81 \pm 0.13 (0.68, 0.94)$	0.10
Breast	Heart (9)	$0.94 \pm 0.02 (0.93, 0.96)$	$0.75 \pm 0.10 (0.69, 0.82)$	0.19
	Rt. Lung (9)	$0.97 \pm 0.01 (0.96, 0.98)$	$0.95 \pm 0.02 (0.94, 0.97)$	0.02
	Lt. Lung (9)	$0.96 \pm 0.02 (0.95, 0.97)$	$0.95 \pm 0.02 (0.94, 0.97)$	0.01
Abdomen	Liver (16)	$0.96 \pm 0.01 (0.96, 0.97)$	$0.86 \pm 0.06 (0.84, 0.89)$	0.10
en	Rt. Kidney
(16)	$0.91 \pm 0.02 (0.90, 0.92)$	$0.77 \pm 0.12 (0.72, 0.83)$	0.14
	Lt. kidney
(16)	$0.91 \pm 0.03 (0.89, 0.92)$	$0.78 \pm 0.08 (0.74, 0.82)$	0.13
Pelvis	Bladder (17)	$0.90 \pm 0.07 (0.87, 0.93)$	$0.55 \pm 0.27 (0.42, 0.67)$	0.35
	Rt. Femur
head (19)	$0.90 \pm 0.06 (0.87, 0.93)$	$0.56 \pm 0.10 (0.51, 0.61)$	0.34
	Lt. Femur
head (19)	$0.89 \pm 0.09 (0.85, 0.93)$	$0.53 \pm 0.13 (0.47, 0.58)$	0.36

● Table 28. 95% HD (mm) for each oragan. By medium kernel

Part	Organ	AVIEW	Predicate device	Difference
Head&
Neck	Brain (4)	28.16 ± 51.23 (-22.04,
78.36)	3.28 ± 0.45 (2.84, 3.72)	24.88
	Rt. Eye (4)	2.77 ± 0.37 (2.42, 3.13)	4.75 ± 1.50 (3.29, 6.22)	-1.98
	Lt. eye (4)	3.26 ± 0.53 (2.74, 3.78)	5.30 ± 2.18 (3.16, 7.44)	-2.04
	Mandible (4)	1.91 ± 0.51 (1.42, 2.41)	5.04 ± 4.11 (1.01, 9.08)	-3.13
Breast	Heart (9)	5.92 ± 2.97 (3.98, 7.86)	20.17 ± 3.52 (17.86, 22.47)	-14.25
Abdom
en	Rt. Lung (9)	2.73 ± 0.61 (2.33, 3.13)	7.30 ± 2.63 (5.58, 9.02)	-4.57
	Lt. Lung (9)	2.97 ± 0.26 (2.80, 3.14)	3.63 ± 1.25 (2.81, 4.45)	-0.66
	Liver (16)	9.10 ± 15.19 (1.66, 16.55)	29.04 ± 14.54 (21.92, 36.16)	-19.94
Abdom
en	Rt. Kidney (16)	8.40 ± 11.42 (2.81, 14.00)	15.54 ± 9.83 (10.73, 20.36)	-7.14
	Lt. kidney (16)	5.47 ± 3.29 (3.86, 7.08)	18.94 ± 10.02 (14.03, 23.85)	-13.47
	Pelvis	Bladder (17)	7.04 ± 9.22 (2.65, 11.42)	23.99 ± 17.93 (15.71, 32.27)
Rt. Femur head (19)		8.01 ± 6.47 (5.10, 10.92)	50.42 ± 39.59 (32.13, 38.71)	-42.41
Lt. Femur head (19)		8.57 ± 7.05 (5.40, 11.74)	41.98 ± 9.27 (37.7, 46.27)	-33.41

. Table 29. DSC for each oragan. By sharp kernel

Part	Organ	AVIEW	Predicate device	Difference
Head&
Neck	Brain (5)	0.97 ± 0.01 (0.96, 0.98)	0.96 ± 0.01 (0.96, 0.97)	0.01
	Rt. Eye (5)	0.77 ± 0.07 (0.70, 0.83)	0.87 ± 0.04 (0.84, 0.91)	-0.10
	Lt. eye (5)	0.71 ± 0.07 (0.65, 0.77)	0.85 ± 0.05 (0.81, 0.90)	-0.14
	Mandible (5)	0.88 ± 0.06 (0.83, 0.93)	0.80 ± 0.07 (0.74, 0.86)	0.08
Breast	Heart	N/A	N/A	N/A
	Rt. Lung	N/A	N/A	N/A
	Lt. Lung	N/A	N/A	N/A
Abdomen	Liver (5)	0.95 ± 0.02 (0.93, 0.96)	0.91 ± 0.06 (0.86, 0.96)	0.04
	Rt. Kidney (5)	0.87 ± 0.03 (0.84, 0.90)	0.69 ± 0.32 (0.40, 0.97)	0.18
	Lt. kidney (5)	0.86 ± 0.07 (0.79, 0.92)	0.76 ± 0.21 (0.58, 0.95)	0.10
Pelvis	Bladder	N/A	N/A	N/A
	Rt. Femur head	N/A	N/A	N/A
	Lt. Femur	N/A	N/A	N/A

21

	head
--	------	--	--	--

Table 30. 95% HD (mm) for each oragan. By sharp kernel ●

Part	Organ	AVIEW	Predicate device	Difference
Head&
Neck	Brain (5)	3.00 ± 0.42 (2.64, 3.37)	4.20 ± 0.87 (3.44, 4.96)	-1.20
	Rt. Eye (5)	3.90 ± 1.24 (2.81, 4.99)	3.05 ± 0.68 (2.45, 3.65)	0.85
	Lt. eye (5)	4.83 ± 1.50 (3.52, 6.14)	3.97 ± 2.85 (1.47, 6.47)	-0.86
	Mandible (5)	2.30 ± 0.41 (1.94, 2.66)	101.61 ± 207.65 (-80.40,
283.61)	-99.31
Breast	Heart	N/A	N/A
	Rt. Lung	N/A	N/A
	Lt. Lung	N/A	N/A
Abdomen	Liver (5)	4.52 ± 1.97 (2.79, 6.25)	13.74 ± 12.22 (3.03, 24.45)	-9.22
	Rt. Kidney (5)	4.92 ± 1.69 (3.44, 6.40)	19.86 ± 24.04 (-1.21, 40.93)	-14.94
	Lt. kidney (5)	7.06 ± 8.03 (0.02. 14.20)	12.32 ± 12.74 (1.16, 23.48)	-5.26
Pelvis	Bladder	N/A	N/A
	Rt. Femur head	N/A	N/A
	Lt. Femur head	N/A	N/A

There are organs that aren' available in a certain range or vendor which the value was input as N/A

◆ Number of samples for each analysis

each part	Head & Neck	Breast	Abdomen	Pelvis	Total
N	25	32	26	27	120
Each part by organs	Head & Neck	Breast	Abdomen	Pelvis	Total
N	100	94	78	109	120
Each vendor	SIEMENS	GE	PHILIPS	TOSHIBA	Total
N	48	25	21	26	120
each slice thickness (mm)	≥1, ≤2	>2, ≤3	>3, ≤4	>4, ≤5	Total
N	18	70	20	12	120
Each kernel	SOFT	STANDARD	MEDIUM	SHARP	Total
N	47	15	48	20	120

Table 31.

10 CONCLUSIONS

The new device and predicate device are substantially equivalent in the areas of technical characteristics, general functions, application, and intended use. The new device does not introduce a fundamentally new scientific technology, and the nonclinical tests demonstrate that the device is as safe and as effective as the predicate. Therefore, it is our opinion that the AVIEW RT ACS described in this submission is substantially equivalent to the predicate device.