AVIEW LCS is intended for the review and analysis and reporting of thoracic CT images for the purpose of 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), estimated effective diameter from the volume of 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 measured in 3D for a solid portion of the nodule. Solid 2nd Major: The length of the longest diameter of the solid part, measured in sections perpendicular to the Major axis of the nodule), VDT (Volume doubling time), Lung-RADS (classification proposed to aid with findings) and CAC score and LAA analysis. The system automatically performs the measurement, allowing lung nodules and measurements to be displayed and, also integrate with FDA certified Mevis CAD (Computer-aided detection) (K043617).

Device Description

AVIEW LCS is intended for use as diagnostic patient imaging which is intended for the review and analysis of thoracic CT images. Provides following features as semi-automatic nodule measurement (segmentation), maximal plane measure, 3D measure and volumetric measures, automatic nodules detection by integration with 3th party CAD. Also provides cancer risk based on PANCAN risk 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 is based on type, size, size change and other findings that is reported.

AI/ML Overview

The provided text does not contain detailed acceptance criteria for specific performance metrics of the AVIEW LCS device, nor does it describe a study proving the device meets particular acceptance criteria with quantitative results.

The document is a 510(k) premarket notification summary, which focuses on demonstrating substantial equivalence to a predicate device rather than providing a detailed performance study like a clinical trial.

However, based on the information provided, here's what can be extracted and inferred regarding performance and testing:

1. Table of Acceptance Criteria and Reported Device Performance

As specific quantitative acceptance criteria and detailed performance metrics are not explicitly stated in the provided text for AVIEW LCS, I cannot create a table of acceptance criteria and reported device performance. The document generally states that "the modified device passed all of the tests based on pre-determined Pass/Fail criteria" for software validation.

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

The document does not specify the sample size used for any test set or the data provenance (e.g., country of origin, retrospective/prospective). The described "Unit Test" and "System Test" are internal software validation tests rather than clinical performance studies involving patient data.

3. Number of Experts Used to Establish Ground Truth and Qualifications

The document does not mention using experts to establish ground truth for a test set. This type of information would typically be found in a clinical performance study.

4. Adjudication Method for the Test Set

The document does not describe any adjudication method for a test set. This is relevant for clinical studies where multiple readers assess cases.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

The document does not indicate that a multi-reader multi-case (MRMC) comparative effectiveness study was performed. Therefore, no effect size of human readers improving with AI vs. without AI assistance is mentioned.

6. Standalone (Algorithm Only) Performance Study

The document does not explicitly state that a standalone (algorithm only without human-in-the-loop performance) study was conducted. The "Performance Test" section refers to DICOM, integration, and thin client server compatibility reports, which are software performance tests, not clinical efficacy or diagnostic accuracy studies for the algorithm itself. The device description mentions "automatic nodules detection by integration with 3rd party CAD (Mevis Visia FDA 510k Cleared)", suggesting it leverages an already cleared CAD system for detection rather than having a new, independently evaluated detection algorithm as part of this submission.

7. Type of Ground Truth Used

The document does not specify the type of ground truth used for any performance evaluation. Again, this would be characteristic of a clinical performance study.

8. Sample Size for the Training Set

The document does not provide the sample size for any training set. This is typically relevant for AI/ML-based algorithms. The mention of "deep-learning algorithms" for lung and lobe segmentation suggests a training set was used, but its size is not disclosed.

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

The document does not explain how ground truth for any potential training set was established.

Summary of available information regarding testing:

The "Performance Data" section (8) of the 510(k) summary focuses on nonclinical performance testing and software verification and validation activities.

Nonclinical Performance Testing: The document states, "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 nonclinical testing." This indicates the submission relies on the substantial equivalence argument and internal software testing, not new clinical performance data for efficacy.
Software Verification and Validation:
- Unit Test: Conducted using Google C++ Unit Test Framework on major software components for functional, performance, and algorithm analysis.
- System Test: Conducted based on "integration Test Cases" and "Exploratory Test" to identify defects.
  - Acceptance Criteria for System Test: "Success standard of System Test is not finding 'Major', 'Moderate' defect."
  - Defect Classification:
    - Major: Impacting intended use, no workaround.
    - Moderate: UI/general quality, workaround available.
    - Minor: Not impacting intended use, not significant.
- Performance Test Reports: DICOM Test Report, Performance Test Report, Integration Test Report, Thin Client Server Compatibility Test Report.

In conclusion, the provided 510(k) summary primarily addresses software validation and verification to demonstrate substantial equivalence, rather than a clinical performance study with specific acceptance criteria related to diagnostic accuracy, reader performance, or a detailed description of ground truth establishment.

Summary

{0}------------------------------------------------

October 16, 2020

Image /page/0/Picture/1 description: The image contains the logos of the Department of Health & Human Services and the U.S. Food & Drug Administration (FDA). The Department of Health & Human Services logo is on the left, featuring a stylized symbol. To the right is the FDA logo, with the letters "FDA" in a blue square, followed by the words "U.S. FOOD & DRUG" and "ADMINISTRATION" in blue text.

Coreline Soft Co., Ltd. % Hye Yi Park Deputy General Manager Strategic Business Dept. 4,5F (Yeonnam-dong), 49, World Cup buk-ro 6-gil, Mapo-gu. Seoul 03991 REPUBLIC OF KOREA

Re: K201710

Trade/Device Name: AView LCS Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: Class II Product Code: LLZ, JAK Dated: June 22, 2020 Received: September 14, 2020

Dear Hye Yi 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 801); medical device reporting of medical device-related adverse events) (21 CFR 803) for

{1}------------------------------------------------

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.

For

Thalia T. Mills, Ph.D. Director Division of Radiological Health OHT7: Office of In Vitro Diagnostics and Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health

Enclosure

{2}------------------------------------------------

Indications for Use

510(k) Number (if known) K201710

Device Name AVIEW LCS

Indications for Use (Describe)

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

X Prescription Use (Part 21 CFR 801 Subpart D)

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

CONTINUE ON A SEPARATE PAGE IF NEEDED.

This section applies only to requirements of the Paperwork Reduction Act of 1995.

DO NOT SEND YOUR COMPLETED FORM TO THE PRA STAFF EMAIL ADDRESS BELOW.

The burden time for this collection of information is estimated to average 79 hours per response, including the time to review instructions, search existing data sources, gather and maintain the data needed and complete and review the collection of information. Send comments regarding this burden estimate or any other aspect of this information collection, including suggestions for reducing this burden, to:

Department of Health and Human Services Food and Drug Administration Office of Chief Information Officer Paperwork Reduction Act (PRA) Staff PRAStaff@fda.hhs.gov

"An agency may not conduct or sponsor, and a person is not required to respond to, a collection of information unless it displays a currently valid OMB number."

{3}------------------------------------------------

006_510(k) Summary

Image /page/3/Picture/1 description: The image shows the Coreline logo. The logo consists of a blue triangle shape on the left and the word "CORELINE" in blue on the right. The triangle shape is made up of three different shades of blue, with the darkest shade on the left and the lightest shade on the right.

{4}------------------------------------------------

510(k) Summary

SUBMITTER 1

K201710

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: 06.22.2020

2 DEVICE

Name of Device: AVIEW LCS Common or Usual Name: Image Processing Software Classification Name: System, image processing, radiological (21CFR 892.2050) Regulatory Class: II Product Code: LLZ, JAK

PREDICATE DEVICE 3

AVIEW LCS by Coreline Soft Co., Ltd. (K193220) Name of Device: AVIEW LCS Common or Usual Name: Image Processing Software Classification Name: System, image processing, radiological (21CFR 892.2050) Regulatory Class: II Product Code: LLZ, JAK

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

REFERENCE DEVICE 4

Lung Nodule Assessment and Comparison Option by Philips Medical System Nederland B.V. (K 162484)

Name of Device: Lung Nodule Assessment and Comparison Option (LNA) Common or Usual Name: Lung Nodule Assessment and Comparison Option (LNA) Classification Name: System, image processing, radiological (21CFR 892.1750) Regulatory Class: II Product Code: LLZ, JAK

{5}------------------------------------------------

AVIEW by Coreline Soft Co., Ltd. (K200714)

Name of Device: AVIEW Common or Usual Name: AVIEW Classification Name: System, image processing, radiological (21CFR 892.2050) Regulatory Class: II Product Code: LLZ, JAK

All reference devices have not been subject to a design-related recall.

DEVICEW DESCRIPTION 5

-Easy processing management
- Rule-based automatic processing server (APS) "
-Thin client service
- Connected from anywhere, anyplace, anytime. .
- . Support mobile view through various mobile device served by Ios and Android.
- Compatible with Chrome browser .
-Nodule measurement
- " Adding nodule by segmentation or by lines
- . Semi-automatic nodule measurement (segmentation)
- Maximal plane measure, 3D measure and volumetric measure. .
- י Automatic large vessel removal.
- . Provides various features calculated per each nodule
- . Fully supporting Lung-RADS workflow: US Lung-RADS and KR Lung-RADS.
- . Nodule malignancy score (PANCAN model) calculation.
- . Importing from CAD results
-CAC, LAA on LC
- Displays CAC score which was analyzed "
- . Displays LAA available which was analyzed

{6}------------------------------------------------

-Follow-up
- י Automatic retrieving the past data
- Follow-up support with nodule matching and comparison .
- . Automatic calculation of VDT (volume doubling time)
-Automatic nodule detection (CADe)
- Seamless integration with Mevis Visia (FDA 510k Cleared)
-Lungs and lobes segmentation
- Better segmentation of lungs and lobes based on deep-learning algorithms.
-Report
- י PDF report generation
- י It saves or sends the pdf report and captured images in DICOM files.
- Reports are generated using the results of all nodules nodules detected so far (Lung RADS) .
Save Result -
- . It saves the results in internal format

INDICATIONS FOR USE 6

AVIEW LCS is intended for the review and analysis and reporting of thoracic CT images for the purpose of 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), estimated effective diameter from the volume of the volume of the nodule, Mean HU (the average value of the CT pixel inside the nodule in HU), Minimum HU, Max (mass (mass calculated from the CT pixel value), and volumetric measures (Solid Major; length of the longest diameter measured in 3D for a solid portion of the nodule. Solid 2nd Major: The length of the longest diameter of the solid part, measured in sections perpendicular to the solid portion of the nodule), VDT (Volume doubling time), Lung-RADS (classification proposed to aid with findings) and CAC score and LAA analysis. The system automatically performs the measurement, allowing lung nodules and measurements to be displayed and, also integrate with FDA certified Mevis CAD (Computer-aided detection) (K043617).

COMPARISION OF TECHNOLOGICAL CHARACTERISTICS WITH 7 THE PREDICATE DEVCIE

AVIEW LCS has the same intended use and the principle of operation, and also has similar features to the predicate devices. Lung Nodule Assessment and Comparison Option (LNA) (K162484)

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 PredicateDevice	Reference Device	Reference Device
Device Name	AVIEW LCS	AVIEW LCS	Lung NoduleAssessment andComparison Option(LNA)	AVIEW
ClassificationName	System, imageProcessingRadiological	System, imageProcessingRadiological	System, imageProcessingRadiological	System, imageProcessingRadiological
RegulatoryNumber	21 CFR 892.2050	21 CFR 892.2050	21 CFR 892.2050	21 CFR 892.2050
Product Code	LLZ, JAK	LLZ, JAK	LLZ, JAK	LLZ, JAK
Review Panel	Radiology	Radiology	Radiology	Radiology
510k Number	-	K193220	K162484	K200714
Indications foruse	AVIEW LCSAVIEW LCS is intended for the review and analysis and reporting of thoracic CT images for the purpose of 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 measured in 3D for a solid portion of the nodule. Solid 2nd Major: The length 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), Lung-RADS (classification proposed to aid with findings) and CAC score and LAA analysis. The system automatically performs the measurement, allowing lung nodules and measurements to be displayed and, also integrate with FDA certified Mevis CAD (Computer-aided detection) (K043617).
	AVIEW LCSAVIEW LCS is intended for the review and analysis and reporting of thoracic CT images for the purpose of 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 measured in 3D for a solid portion of the nodule. Solid 2nd Major: The length 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, also integrate with FDA certified Mevis CAD (Computer-aided detection) (K043617).
	Lung Nodule Assessment and Comparison Option (LNA)The Lung Nodule Assessment and Comparison Option is intended for use as a diagnostic patient- imaging tool. It is intended for the review and analysis of thoracic CT images, providing quantitative and characterizing information about nodules in the lung in a single study, or over the time course of several thoracic studies. Characterizations include diameter, volume and volume over time. The system automatically performs the measurements, allowing lung nodules and measurements to be displayed.
	AVIEWAVIEW provides CT values for pulmonary tissue from CT thoracic and cardiac datasets. This software could be used to support the physician quantitatively in the diagnosis, follow up evaluation and documentation of CT lung tissue images by providing image segmentation of sub- structures in lung, lobe, airways and cardiac, registration of inspiration and expiration which could analyze quantitative information such as air trapping volume, air trapped index, and inspiration/expiration ratio. And also, volumetric and structure analysis, density evaluation and reporting tools. AVIEW is also used to store, transfer, inquire and display CT data set on premise and as cloud environment as well to allow users to connect by various environment such as mobile

{7}------------------------------------------------

{8}------------------------------------------------

course of several thoracic studies. Characterizations include nodule type, location of the noduleand measurements such as size (major axis, minor axis), estimated effective diameter from thevolume of the nodule, volume of the nodule, Mean HU(the average value of the CT pixel insidethe nodule in HU), Minimum HU, Max HU, mass(mass calculated from the CT pixel value), andvolumetric measures(Solid major; length of the longest diameter measured in 3D for solid portionof the nodule, Solid 2nd Major: The length of the longest diameter of the solid part, measured insections perpendicular to the Major axis of the solid portion of the nodule), VDT (Volumedoubling time), and Lung-RADS (classification proposed to aid with findings). The systemautomatically performs the measurement, allowing lung nodules and measurements to bedisplayed and, integrate with FDA certified Mevis CAD (Computer aided detection) (K043617).It also provides CAC analysis by segmentation of four main artery (right coronary artery, left maincoronary, left anterior descending and left circumflex artery then extracts calcium on coronaryartery to provide Agatston score, volume score and mass score by whole and each segmentedartery type. Based on the score, provides CAC risk based on age and gender.
Platform	IBM-compatible PC or PC network	IBM-compatible PC or PC network	IBM-compatible PC or PC network	IBM-compatible PC or PC network
User interface	Monitor, Mouse, Keyboard	Monitor, Mouse, Keyboard	Monitor, Mouse, Keyboard	Monitor, Mouse, Keyboard
Image InputSoures	Images can be scanned,loaded from cardreaders, or importedfrom a radiographicimaging device	Images can bescanned, loaded fromcard readers, orimported from aradiographic imagingdevice	Images can be scanned,loaded from cardreaders, or importedfrom a radiographicimaging device	Images can bescanned, loaded fromcard readers, orimported from aradiographic imagingdevice
Image format	DICOM	DICOM	DICOM	DICOM
Intended bodypart	chest	chest	chest	chest
Type of Scans	CT	CT	CT	CT
GeneralDescription	AVIEW LCSAVIEW LCS is intended for use as diagnostic patient imaging which is intended for the reviewand analysis of thoracic CT images. Provides following features as semi-automatic nodulemeasurement (segmentation), maximal plane measure, 3D measure and columetric measures,automatic nodules detection by integration with 3rd party CAD. Also provides cancer risk basedon PANCAN risk model which calculates the malignancy score based on numerical or Booleaninputs. 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 CTreporting and management recommendations that is based on type, size, size change and otherfindings that is reported.AVIEW LCSAVIEW LCS is intended for use as diagnostic patient imaging which is intended for the reviewand analysis of thoracic CT images. Provides following features as semi-automatic nodulemeasurement (segmentation), maximal plane measure, 3D measure and columetric measures,automatic nodules detection by integration with 3rd party CAD. Also provides cancer risk basedon PANCAN risk model which calculates the malignancy score based on numerical or Booleaninputs. 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 CTreporting and management recommendations that is based on type, size, size change and otherfindings that is reported.Lung Nodule Assessment and Comparison Option (LNA)The Lung Nodule Assessment and Comparison Option application is intended for use as adiagnostic patient imaging tool. It is intended for the review and analysis of thoracic CT images,

or over the time course of several thoracic studies. The system automatically performs the measurements, allowing lung nodules and measurements to be displayed. The user interface and automated tools help to determine growth patterns and compose comparative reviews. The Lung Nodule Assessment and Comparison Option application requires the user to identify a nodule and to determine the type of nodule in order to use the appropriate characterization tool. Lung Nodule Assessment and Comparison Option may be utilized in both diagnostic and screening evaluations supporting Low Dose CT Lung Cancer ScreeningAVIEW
The AVIEW is a software product which can be installed on a PC. It shows images taken with the interface from various storage devices using DICOM 3.0 which is 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 the software tools. And is intended for use as diagnostic patient imaging which is intended for the review and analysis of CT scanning. Provides following features as semi-automatic nodule management, maximal plane measure, 3D measures and columetric measures, automatic nodule detection by integration with 3rd party CAD. Also provides Brocks model which calculated 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 is based on type, size, size change and other findings that is reported. It also automatically analyzes coronary artery calcification which support user to detect cardiovascular disease in early stage and reduce the burden of medical.

	Providing ray sumimage, axial, sagittal,coronal, and obliqueplanes.	same	Providing axial,sagittal, coronal, andoblique planes	same
	Rotating to Anterior,Posterior, Left, Right,Head, and Footdirection	same	Rotating to Anterior,Posterior, Left, Right,Head, and Footdirection	same
	Providing VR (Volumerender), MIP(Maximum IntensityProjection), MinIP(Minimum IntensityProjection) image	same	Providing Average,MIP, VIP, MinIP,SurfaceMIP, Vol,Rend.	same
Key Functions	Changing the color andtransparency of the VRimage by adjusting theOTF (Opacity TransferFunction) and saving	same	Changing the color andtransparency of the VRimage	same

{9}------------------------------------------------

same

2D and 3D image

and

Segmentation of lung

comparative review

2D measurements

review

apply in the VR setting

2D and 3D image

and

Segmentation of Lungs

comparative review

measurements

review

same

{10}------------------------------------------------

Image /page/10/Picture/0 description: The image features the word "CORELINE" in a sans-serif font, with each letter rendered in a clean, white color. To the left of the text is a stylized, three-dimensional triangular shape, also in white, which adds a modern and abstract element to the logo. The background is a solid, dark blue color, providing a strong contrast that makes the white text and triangular shape stand out.

and Lobes	airway, lungs, and lung lobes
Nodule Characteristics	Nodule Characteristics
Automatic calculation of measurements for each segmented nodule Size of the Major axis and Minor axis(mm) Diameter of Major (3D), 2nd Major (3D), Major(2D), Minor(2D) (mm) Volume(mm³) Max, Min, Mean HU of the nodule((HU) Cancer probability (%)	Automatic calculation of measurements for each segmented nodule Short axis-Longest diameter perpendicular to the long axis on the slice(mm) Long Axis-Longest diameter on an axial slice(mm) Average/Max 3D/Effective diameter(mm) Volume(mm³) Mean densities(HU)
Comparison and Matching	Comparison and Matching
Comparison and matching automatic calculations between each follow-up scan and the baseline scan Doubling time in days Indicated the change of the size Auto generate Lung-RADS	Comparison and matching automatic calculations between each follow-up scan and the baseline scan Doubling time in days Percent (%) and absolute change of all numerical parameters (growth in nodule long axis, short axis, average diameter, max 3D diameter, effective diameter, volume, mean HU)
Loading multiple studies	Loading multiple studiesUp to 3 studies
Workflow Detect and Segment Comparison and Matching Results Option to integrate with 3rd party CAD which automatically detects the nodules	Workflow Detect and Segment Comparison and Matching Results Option to integrate with 3rd party CAD which

{11}------------------------------------------------

	and generate reportDisplays CAC/LAAresult analyzed byAVIEW	automaticallydetects the nodulesandgeneratereport		automaticallydetects thenodulesandgenerate report
	Supporting Low-doseCT	same	Supporting Low-doseCT	same
	Reporting resultsThe results include thefollowing.• Lung-RADS• PANCAN riskcalculator• Auto detect nodulelocation by lobe	same	Reporting resultsThe results include thefollowing.• Patient relatedinformation• Dictation Table withNodule result tableand additionalfindings• Lung-RADS• Risk Calculator	same
	Printing Option	same	Printing Option	same
Thin clientservice	Connected fromanywhere,anyplace, anytime• Supports mobileview throughvarious mobiledevices served byios and Android.• Compatible withChrome browser	-	-	same
Easy processingmanagement	Rule-based automaticprocessing server(APS)	-	-	same

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 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.

{12}------------------------------------------------

8.2.1 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.

8.2.2 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.
V Moderate defects, which are typically related to user-interface or general quality of product, while workaround is available.
く Minor defects, which are not impacting the product's intended use. Not significant.

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

8.2.3 Performance Test

DICOM Test Report for AVIEW LCS .
. Performacne test report for AVIEW LCS
AVIEW LCS Integration Test Report ●
AVIEW LCS Thin Client Server Compatibility Test Report

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 LCS 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).