AVIEW CAC provides quantitative analysis of calcified plaques in the coronary arteries using non-contrast non-gated Chest CT scans. It enables the calculation of the Agatston score for coronary artery calcification, segmenting and evaluating the right coronary artery and left coronary artery. Also provide risk stratification based on calcium score, gender, and age, offering percentile-based risk categories by established guidelines. Designed for healthcare professionals, including radiologists and cardiologists, AVIEW CAC supports storing, inquiring, and displaying CT data sets on-premises, facilitating access through mobile devices and Chrome browsers. AVIEW CAC analyzes existing noncontrast/non-gated Chest CT studies that include the heart of adult patients above the age of 40. Also, the device's use should be limited to CT scans acquired on General Electric (GE) or its subsidiaries (e.g., GE Healthcare) equipment. Use of the device with CT scans from other manufacturers has not been validated or recommended.

Device Description

The AVIEW CAC is a software product that can be installed on a PC. It shows images taken with the interface from various storage devices using DICOM 3.0, the digital image and communication standard in medicine. It also offers functions such as reading, manipulation, analyzing, post-processing, saving, and sending images by using software tools. And is intended for use as a quantitative analysis of CT scanning. It also provides a calcium score by automatically analyzing coronary arteries from the segmented arteries.

AI/ML Overview

The provided text describes the acceptance criteria and the study conducted for the AVIEW CAC device.

Here's the breakdown of the information requested:

1. Table of Acceptance Criteria and Reported Device Performance

The acceptance criteria for the quantitative analysis of calcified plaques is primarily based on the Intraclass Correlation Coefficient (ICC) of the Agatston score against a ground truth and a predicate device.

Acceptance Criteria	Reported Device Performance (AVIEW CAC vs. Ground Truth)	Reported Device Performance (AVIEW CAC vs. Predicate Device)
P-value > 0.8 for ICC (implied target for strong agreement)	Agatston Score ICC (95% CI):	Agatston Score ICC (95% CI):
	Total: 0.896 (0.857, 0.925)	Total: 0.939 (0.916, 0.956)
	LCA: 0.927 (0.899, 0.947)	LCA: 0.955 (0.938, 0.968)
	RCA: 0.840 (0.778, 0.884)	RCA: 0.887 (0.844, 0.918)
All p-values < 0.001 (indicating statistical significance of correlation)	All reported p-values are <.001	All reported p-values are <.001
Correlation coefficient between AVIEW CAC automatic analysis and Agatston scores calculated from heart CT should be over 90%	Correlation coefficient between AVIEW CAC automatic analysis results of the chest CT based on the heart CT and the Agatston scores was over 90%.	Not applicable

Note: The acceptance criterion for ICC is implied by the p-value requirement ">0.8", which usually signifies a strong correlation. The reported ICC values are all above this implied threshold.

2. Sample Size Used for the Test Set and Data Provenance

Test Set Sample Size:
- 150 CSCT (gated) cases
- 150 Chest CT (non-gated) cases
- Additionally, 280 datasets collected from multiple institutions were used for a separate "MI functionality test report" which also evaluated correlation.
Data Provenance: The document does not explicitly state the country of origin. The test cases were derived from "multiple institutions". It is implied to be retrospective as the device analyzes "existing" non-contrast/non-gated chest CT studies.

3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

The document does not specify the number of experts used or their detailed qualifications (e.g., "radiologist with 10 years of experience") for establishing the ground truth.

4. Adjudication Method for the Test Set

The document does not explicitly describe an adjudication method (such as 2+1, 3+1) for establishing the ground truth. It simply refers to "ground truth" without detailing its consensus process.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, If So, What Was the Effect Size of How Much Human Readers Improve with AI vs. Without AI Assistance

A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. The study focuses on the standalone performance of the algorithm against a defined ground truth and comparison against a predicate device, not on human reader performance with or without AI assistance.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

Yes, a standalone performance study was done. The performance data section explicitly states, "we evaluated the agreement in A coronary calcium scoring between the subject device and the ground truth" and "the correlation coefficient A between the AVIEW CAC automatic analysis results of the chest CT based on the heart CT and the Agatston scores was over 90%". This indicates the algorithm's performance without human intervention.

7. The Type of Ground Truth Used

The ground truth used was Agatston scores for coronary artery calcification. The document does not specify if this ground truth was established by expert consensus of human readers, pathology, or outcomes data. However, the comparison is made to "Ground Truth" for Agatston Score measurements, which implies a highly reliable, perhaps manually derived or reference Agatston score.

8. The Sample Size for the Training Set

The document does not provide the sample size for the training set. It only mentions the test set sizes.

9. How the Ground Truth for the Training Set Was Established

The document does not describe how the ground truth for the training set was established. It only refers to deep learning for automatic segmentation but does not detail the process for creating the ground truth data used to train the deep learning model.

Summary

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March 29, 2024

Image /page/0/Picture/1 description: The image shows 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 blue square is the text "U.S. FOOD & DRUG ADMINISTRATION" in blue.

Coreline Soft Co., Ltd. Hyeyi Park Deputy General Manager/Strategic Business Dept. 4, 5F (Yeonnam-dong), 49 World Cup buk-ro 6-gil, MAPO-GU SEOUL, KOREA, SOUTH

Re: K233211

Trade/Device Name: AVIEW CAC Regulation Number: 21 CFR 892.2050 Regulation Name: Medical Image Management And Processing System Regulatory Class: Class II Product Code: QIH, JAK Dated: February 23, 2024 Received: February 26, 2024

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 (the 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 available at https://www.accessdata.fda.gov/scripts/cdrb/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.

Additional information about changes that may require a new premarket notification are provided in the FDA guidance documents entitled "Deciding When to Submit a 510(k) for a Change to an Existing Device" (https://www.fda.gov/media/99812/download) and "Deciding When to Submit a 510(k) for a Software Change to an Existing Device" (https://www.fda.gov/media/99785/download).

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Your device is also subject to, among other requirements, the Quality System (OS) regulation (21 CFR Part 820), which includes, but is not limited to, 21 CFR 820.30, Design controls; 21 CFR 820.90, Nonconforming product; and 21 CFR 820.100, Corrective and preventive action. Please note that regardless of whether a change requires premarket review, the QS regulation requires device manufacturers to review and approve changes to device design and production (21 CFR 820.30 and 21 CFR 820.70) and document changes and approvals in the device master record (21 CFR 820.181).

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 801); medical device reporting of medical device-related adverse events) (21 CFR Part 803) for devices or postmarketing safety reporting (21 CFR Part 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 Part 4, Subpart A) for combination products; and, if applicable, the electronic product radiation control provisions (Sections 531-542 of the Act); 21 CFR Parts 1000-1050.

Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21 CFR 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,

Samuel for

Jessica Lamb, Ph.D. Assistant Director Imaging Software Team DHT8B: Division of Radiological Imaging Devices and Electronic Products OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health

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Indications for Use

510(k) Number (if known) K233211

Device Name AVIEW CAC

Indications for Use (Describe)

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

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: 03.28.2024

2 DEVICE

Name of Device: AVIEW CAC Common or Usual Name: Image Processing Software Classification Name: Medical Image Management and Processing System (21CFR 892.2050) Regulatory Class: II Product Code: QIH, JAK

PREDICATE DEVICE 3

AVIEW by Coraline Soft Co., Ltd. (K214036)

Name of Device: AVIEW Common or Usual Name: Image Processing Software Classification Name: Medical Image Management and Processing System (21CFR 892.2050) Regulatory Class: II Product Code: QIH, JAK

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

REFERENCE DEVICE 4

HealthCCSng by Zebra Medical Vision Ltd.(K210085)

Name of Device: HealthCCSng Common or Usual Name: Image Processing Software Classification Name: Medical Image Management and Processing System (21CFR 892.1750) Regulatory Class: II Product Code: JAK

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DEVICE DESCRIPTION 5

INDICATIONS FOR USE 6

AVIEW CAC provides quantitative analysis of calcified plaques in the coronary arteries using non-contrast/non-gated Chest CT scans. It enables the calculation of the Agatston score for coronary artery calcification, segmenting and evaluating the right coronary artery and left coronary artery. Also provide risk stratification based on calcium sore, gender, and age, offering percentile-based risk categories by established guidelines. Designed for healthcare professionals, including radiologists, AVIEW CAC supports storing, transferring, inquiring, and displaying CT data sets on-premises, facilitating access through mobile devices and Chrome browsers. AVEW CAC analyzes existing non-contrast/non-gated Chest CT studies that include the heart of adult patients above the age of 40. Also, the device's use should be limited to CT scans acquired on General Electric (GE) or its subsidiaries (e.g., GE Healthcare) equipment. Use of the device with CT scans from other manufacturers has not been validated or recommended.

COMPARISION OF TECHNOLOGICAL CHARACTERISTICS WITH 7 THE PREDICATE DEVCIE

AVIEW CAC has the same intended use and the principle of operation and has similar features to the predicate devices. AVIEW (K214036)

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	Predicate Device	Reference Device
Device Name	AVIEW CAC	AVIEW	HealthCCSng
Classification Name	Medical ImageManagement andProcessing System	Medical ImageManagement andProcessing System	Medical ImageManagement andProcessing System
Regulatory Number	21 CFR 892.2050	21 CFR 892.2050	21 CFR 892.1750
Product Code	QIH, JAK	QIH, JAK	JAK
Review Panel	Radiology	Radiology	Radiology
510k Number	-	K214036	K210085
Indications for use	AVIEW CAC	AVIEW CAC provides quantitative analysis of calcified plaques in the coronary arteries
	using non-contrast/non-gated Chest CT scans. It enables the calculation of the Agatston
	score for coronary artery calcification, segmenting and evaluating the right coronary artery
	and left coronary artery. Also provide risk stratification based on calcium score, gender,
	and age, offering percentile-based risk categories by established guidelines. Designed for
	healthcare professionals, including radiologists and cardiologists, AVIEW CAC supports

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storing, transferring, inquiring, and displaying CT data sets on-premises, facilitating
access through mobile devices and Chrome browsers. AVIEW CAC analyzes existing non-
contrast/non-gated Chest CT studies that include the heart of adult patients above the age
of 40. Also, the device's use should be limited to CT scans acquired on General Electric
(GE) or its subsidiaries (e.g., GE Healthcare) equipment. Use of the device with CT scans
from other manufacturers has not been validated or recommended.

AVIEW

AVIEW provides CT values for pulmonary tissue from CT thoracic and cardiac datasets. This software can be used to support the physician providing quantitative analysis of CT images by image segmentation of sub-structures in the lung, lobe, airways, fissures completeness, cardiac, density evaluation, and reporting tools. AVIEW is also used to store, transfer, inquire and display CT data set on-premises and as a cloud environment to allow users to connect by various environments such as mobile devices and Chrome browsers. Converts the sharp kernel to soft kernel for quantitative analysis of segmenting low attenuation areas of the lung. Characterizing nodules in the lung in a single study or over the time course of several thoracic studies. Characterizations include nodule type, location of the nodule, and measurements such as size (major axis, minor axis), estimated effective diameter from the volume of the nodule, the volume of the nodule, Mean HU(the average value of the CT pixel inside the nodule in HU), Minimum HU, Max HU, mass(mass calculated from the CT pixel value), and volumetric measures(Solid major; length of the longest diameter measure in 3D for a solid portion of the nodule, Solid 2nd Major: The size of the longest diameter of the solid part, measured in sections perpendicular to the Major axis of the solid portion of the nodule), VDT (Volume doubling time), and Lung-RADS (classification proposed to aid with findings.). The system automatically performs the measurement, allowing lung nodules and measurements to be displayed and, integrate with FDA certified Mevis CAD (Computer aided detection) (K043617). It also provides the Agatston score, volume score, and mass score by the whole and each artery by segmenting four main arteries (right coronary artery, left main coronary, left anterior descending, and left circumflex artery). Based on the calcium score provides CAC risk based on age and gender. The device is indicated for adult patients only. HealthCCSng

The HealthCCSng device is intended for use as a non-invasive post-processing software to evaluate calcified plaques in the coronary arteries, which present a risk for coronary artery disease. The software generates an estimated coronary artery calcium detection category.

The HealthCCSng device analyzes existing non-cardiac-gated CT studies that include the heart of adult patients above the age of 30. The device generates a threecategory output representing the estimated quantity of calcium detected together with preview axial images of the detected calcium meant for informational purposes only. The device output will be available to the radiologist as part of their standard workflow. The HealthCCSng results are not intended to be used on a stand-alone basis for risk attribution, clinical decision-making or otherwise preclude clinical assessment of CT studies

General Description	AVIEW CAC
	The AVIEW CAC is a software product that can be installed on a PC. It shows images
	taken with the interface from various storage devices using DICOM 3.0, the digital image
	and communication standard in medicine. It also offers functions such as reading,
	manipulation, analyzing, post-processing, saving, and sending images by using software
	tools. And is intended for use as a quantitative analysis of CT scanning. It also provides a
	calcium score by automatically analyzing coronary arteries from the segmented arteries.

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	AVIEW	HealthCCSng
	The AVIEW is a software product that can be installed on a PC. It shows images taken with the interface from various storage devices using DICOM 3.0, the digital image and communication standard in medicine. It also offers functions such as reading, manipulation, analyzing, post-processing, saving, and sending images by using software tools. And is intended for use as a quantitative analysis of CT scanning. It provides the following features such as segmentation of lung, lobe, airway, fissure completeness, semi-automatic nodule management, maximal plane measure, 3D measures and volumetric measures, automatic nodule detection by integration with 3rd party CAD. It also provides the Brocks model, which calculates the malignancy score based on numerical or Boolean inputs. Follow-up support with automated nodule matching and automatically categorize Lung-RADS score, which is a quality assurance tool designed to standardize lung cancer screening CT reporting and management recommendations that are based on type, size, size change, and other findings that are reported. It also provides a calcium score by automatically analyzing coronary arteries from the segmented arteries	HealthCCSng product is a software device that automatically estimates the coronary artery calcium category from non-cardiac-gated adult CT scans. The product is aimed to leverage the high utilization of CT scans in the medical care environment (both inpatient and outpatient), including lung cancer screening programs, in order to automatically detect calcification in the coronary arteries of patients in an opportunistic manner.Zebra's HealthCCSng product analyzes cases using an artificial intelligence algorithm for the automated detection and estimation of coronary calcium and outputs a result for review by the radiologist. The device works in parallel to and in conjunction with the standard of care workflow. The final diagnosis is made by the radiologist after reviewing the scan independently of the software. The device is intended for use by the radiologists as a non-diagnostic analysis software in conjunction with additional patient information and professional judgment.HealthCCSng receives a non-cardiac-gated CT study from the storage application, Zebra's Imaging Analytics Platform (IMA). For each CT study received, the software shall validate there is at least one compliant series in which the entire heart is present, and perform an analysis. For each compliant study, the software shall output:1. Estimated Coronary Calcium Detection, based on the measurement of calcium deposits in the coronary arteries.2. A corresponding Estimated Coronary Calcium Detection Category, based on the Estimated Coronary Calcium measurement.
Platform	IBM-compatible PC or PC network	same
User Interface	Monitor, Mouse, Keyboard	same
Image Input Sources	Images can be scanned, loaded from card readers, or imported from a radiographic imaging device	same
Image format	DICOM	same	same
Image Measurement Tools	Ruler (line and 3D),Tapeline (curve, poly and3D), Angle (3-point, 4point, and 3D), pixel values, area of ROI (rectangle, circle, ellipse), volume	same
Image viewing	Axial, sagittal, and coronalimage, oblique slice, cubeview	same
Image manipulation	Panning, rotating, zooming,windowing,inverting,Coloring, Oblique, Note(textoverlay), Coloring	same
DICOM	This receives DICOM datafrom CT byDICOMcommunicationConductsDICOMdatacommunication with PACS.It also imports DICOM filedirectly, saves by usingexport function.	same
CAC	ExtractingCalcium onCoronaryArtery andprovides Agatston score.	Extracting Calcium onCoronary Artery andprovides Agatston score,volume score and massscore.	Agatston equivalent CACrisk category, based on theAgatston method
	Automatically segments thecalcium area of the coronaryartery based ondeeplearning.	same	Not applicable
Contrast	Non-contrast	Non-contrast	Non-contrast
Supported CT scan	Non-contrast/non-gatedChest CT	Cardiac CT	Non-Cardiac gated CT scan
Guideline and RiskPercentile	MAYO-1999SCCT/STR-2016UserCustomAMJ-2001MESA-2006	MAYO-1999SCCT/STR-2016
Thin client service	Connectedfromanywhere, anyplace,anytime.Supports mobile viewthrough various mobiledevices served by iosand Android.Comparable with Chromebrowser	same
Easy processingmanagement	Rule-basedautomaticprocessing server (APS)	same

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PERFORMANCE DATA 8

8.1 Nonclinical Performance Testing

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

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device. The substantial equivalence of the device is supported by the non-clinical testing.

8.2 Software Verification and Validation

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 to hardware 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.

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

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

Regression Test
Regression test aims to ensure the quality and stability of the product by reconfirming the proper functioning of existing features through the selection of either all or specific test cases that have been previously executed.
Performance Test -
- . Performance test on Chest CT
  - This test comprised two distinct components. First, we evaluated the agreement in A coronary calcium scoring between the subject device and the ground truth. Second, we investigated the concordance in coronary calcium scoring between the subject device and the predicate device. We used a total of 150 CSCT (gated) cases and a total of 150 Chest CT (non-gated) cases and assess the performance of AVIEW CAC in measuring coronary calcium using the Agatston Score on non-contrast chest CT scans. Also, the device's performance was validated with GE CT.
    - Ground Truth Predicate ICC (95% CI) p-value(>0.8) ICC (95% CI) p-value(>0.8) Total Total 0.896(0.857,0.925) <.001 0.939(0.916,0.956) <.001 (n=150) LCA 0.927(0.899,0.947) 0.955(0.938,0.968) <.001 <.001 RCA 0.840(0.778,0.884) 0.887(0.844,0.918) <.001 <.001
    - · Performance testing results

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MI functionality test report .
- Using the 280 datasets collected from multiple institutions, the correlation coefficient A between the AVIEW CAC automatic analysis results of the chest CT based on the heart CT and the Agatston scores was over 90%, indicating reliability in evaluating Agatston scores for chest CT images.

CONCLUSIONS 9

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 safe and effective. Therefore, it is our opinion that the AVIEW CAC described in this substantially equivalent to the predicate device.

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).