AVIEW 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 of CT lung tissue images by providing image segmentation of sub-structures in lung, lobe, airways and cardiac, registration and expiration which could analyze quantitative information such as 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 devices and chrome browser. 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 nodule, 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 solid portion of the nodule, Solid 2nd Major: 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 CAC analysis by segmentation of four main artery (right coronary artery, left main coronary, left anterior descending and left circumflex artery then extracts calcium on coronary artery to provide Agatston score, volume score and mass score by whole and each segmented artery type. Based on the score, provides CAC risk based on age and gender.

Device Description

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.

AI/ML Overview

The provided FDA 510(k) summary for the AVIEW 2.0 device (K200714) primarily focuses on establishing substantial equivalence to a predicate device (AVIEW K171199, among others) rather than presenting a detailed clinical study demonstrating its performance against specific acceptance criteria.

However, based on the nonclinical performance testing section and the overall description, we can infer some aspects and present the available information regarding the device's capabilities and how it was tested. It is important to note that explicit acceptance criteria and detailed clinical study results are not fully elaborated in the provided text. 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."

Here's a breakdown of the requested information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document does not explicitly state "acceptance criteria" with numerical or performance targets. Instead, it describes general validation methods and "performance tests" that were conducted to ensure functionality and reliability. The "Reported Device Performance" here refers to the successful completion or validation of these functions.

Feature/Function	Acceptance Criteria (Inferred from Validation)	Reported Device Performance (as per 510(k) Summary)
Software Functionality & Reliability	Absence of 'Major' or 'Moderate' defects.	All tests passed based on pre-determined Pass/Fail criteria. No 'Major' or 'Moderate' defects found during System Test. Minor defects, if any, did not impact intended use.
Unit Test (Major Software Components)	Functional test conditions, performance test conditions, algorithm analysis met.	Performed using Google C++ Unit Test Framework; included functional, performance, and algorithm analysis for image processing. Implied successful completion.
System Test	No 'Major' or 'Moderate' defects identified.	Conducted by installing software to hardware with recommended specifications. New errors from 'Exploratory Test' were managed. Successfully passed as no 'Major' or 'Moderate' defects were found.
Specific Performance Tests	(Implied: Accurate, reliable, and consistent output)
Auto Lung & Lobe Segmentation	(Implied: Accurate segmentation)	Performed. The device features "Fully automatic lung/lobe segmentation using deep-learning algorithms."
Airway Segmentation	(Implied: Accurate segmentation)	Performed. The device features "Fully automatic airway segmentation using deep-learning algorithms."
Nodule Matching Experiment Using Lung Registration	(Implied: Accurate nodule matching and registration)	Performed. The device features "Follow-up support with nodule matching and comparison."
Validation on DVF Size Optimization with Sub-sampling	(Implied: Optimized DVF size with sub-sampling)	Performed.
Semi-automatic Nodule Segmentation	(Implied: Accurate segmentation)	Performed. The device features "semi-automatic nodule management" and "semi-automatic nodule measurement (segmentation)."
Brock Model (PANCAN) Calculation	(Implied: Accurate malignancy score calculation)	Performed. The device "provides Brocks model which calculated the malignancy score based on numerical or Boolean inputs" and "PANCAN risk calculator."
VDT Calculation	(Implied: Accurate volume doubling time calculation)	Performed. The device offers "Automatic calculation of VDT (volume doubling time)."
Lung RADS Calculation	(Implied: Accurate Lung-RADS categorization)	Performed. The device "automatically categorize Lung-RADS score" and integrates with "Lung-RADS (classification proposed to aid with findings)."
Validation LAA Analysis	(Implied: Accurate LAA analysis)	Performed. The device features "LAA analysis (LAA-950HU for INSP, LAA-856HU for EXP), LAA size analysis (D-Slope), and true 3D analysis of LAA cluster sizes."
Reliability Test for Airway Wall Measurement	(Implied: Reliable airway wall thickness measurement)	Performed. The device offers "Precise airway wall thickness measurement" and "Robust measurement using IBHB (Integral-Based Half-BAND) method" and "Precise AWT-Pi10 calculation."
CAC Performance (Coronary Artery Calcification)	(Implied: Accurate Agatston, volume, mass scores, and segmentation)	Performed. The device "automatically analyzes coronary artery calcification," "Extracts calcium on coronary artery to provide Agatston score, volume score and mass score," and "Automatically segments calcium area of coronary artery based on deep learning... Segments and provides overlay of four main artery." Also "Provides CAC risk based on age and gender."
Air Trapping Analysis	(Implied: Accurate air trapping analysis)	Performed. The device features "Air-trapping analysis using INSP/EXP registration."
INSP/EXP Registration	(Implied: Accurate non-rigid elastic registration)	Performed. The device features "Fully automatic INSP/EXP registration (non-rigid elastic) algorithm."

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

The 510(k) summary does not specify the sample size used for the test set(s) used in the performance evaluation, nor does it detail the data provenance (e.g., country of origin, retrospective or prospective). It simply mentions "software verification and validation" and "nonclinical performance testing."

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

The document does not provide information on the number of experts used to establish ground truth or their specific qualifications for any of the nonclinical or performance tests mentioned. Given that no clinical study was performed, it is unlikely that medical experts were involved in establishing ground truth for a test set in the conventional sense for clinical performance.

4. Adjudication Method

No information is provided regarding an adjudication method. Since the document states no clinical study was conducted, adjudication by multiple experts would not have been applicable for a clinical performance evaluation.

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

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not reported. The document explicitly 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." Therefore, there is no mention of an effect size for human readers with or without AI assistance.

6. Standalone Performance Study

Yes, a standalone (algorithm only without human-in-the-loop) performance evaluation was conducted, implied by the "Nonclinical Performance Testing" and "Software Verification and Validation" sections. The "Performance Test" section specifically lists several automatic and semi-automatic functions (e.g., "Auto Lung & Lobe Segmentation," "Airway Segmentation," "CAC Performance") that were tested for the device's inherent capability.

7. Type of Ground Truth Used

The document does not explicitly state the type of ground truth used for each specific performance test. For software components involving segmentation, it is common to use expert-annotated images (manual segmentation by experts) as ground truth for a quantitative comparison. For calculations like Agatston score, or VDT, the ground truth would likely be mathematical computations based on established formulas or reference standards applied to the segmented regions. However, this is inferred, not explicitly stated.

8. Sample Size for the Training Set

The document does not specify the sample size for any training set. It mentions the use of "deep-learning algorithms" for segmentation, which implies a training phase, but details about the training data are absent.

9. How Ground Truth for the Training Set Was Established

The document does not specify how the ground truth for any training set was established. While deep learning is mentioned for certain segmentation tasks, the methodology for creating the labeled training data is not detailed.

Summary

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September 17, 2020

Image /page/0/Picture/1 description: The image contains the logos of the Department of Health and Human Services (HHS) and the Food and Drug Administration (FDA). The HHS logo is a circular seal with an emblem in the center, while the FDA logo features the letters "FDA" in a blue square, followed by the words "U.S. FOOD & DRUG 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, Republic of Korea

Re: K200714

Trade/Device Name: AVIEW Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: Class II Product Code: LLZ, JAK

Dear Hye Yi Park:

The Food and Drug Administration (FDA) is sending this letter to notify you of an administrative change related to your previous substantial equivalence (SE) determination letter dated August 26, 2020. Specifically, FDA is updating this SE Letter for a typographical error in the trade name as an administrative correction.

Please note that the 510(k) submission was not re-reviewed. For questions regarding this letter please contact Thalia T. Mills, OHT7: Office of In Vitro Diagnostics and Radiological Health, 301-796-6641, thalia.mills@fda.hhs.gov.

Sincerely,

Michael D. O'Hara 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

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August 26, 2020

Image /page/1/Picture/1 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 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 03991 REPUBLIC OF KOREA

Re: K200714

Trade/Device Name: AVIEW 2.0 Regulation Number: 21 CFR 892.2050 Regulation Name: Picture archiving and communications system Regulatory Class: Class II Product Code: LLZ, JAK Dated: July 17, 2020 Received: July 20, 2020

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 mav, 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

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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 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 (OS) 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,

Michael D. O'Hara For

Enclosure

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Indications for Use

510(k) Number (if known) K200714

Device Name AVIEW

Indications for Use (Describe)

A VIEW 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 of CT lung tissue images by providing image segmentation of sub-structures in lung, lobe, airways and cardiac, registration and expiration which could analyze quantitative information such as 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 devices and chrome browser. 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 nodule, 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 solid portion of the nodule, Solid 2nd Major: 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 CAC analysis by segmentation of four main artery (right coronary artery, left main coronary, left anterior descending and left circumflex artery then extracts calcium on coronary artery to provide Agatston score, volume score and mass score by whole and each segmented artery type. Based on the score, provides CAC risk based on age and gender.

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)
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K200714

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: 03.13.2020

2 DEVICE

Name of Device: AVIEW 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 by Coraline Soft Co., Ltd. (K171199)

Name of Device: AVIEW Common or Usual Name: Image Processing 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

Imbio CT Lung Density Analysis Software by Imbio LLC (K141069) Name of Device: Imbio CT Lung Density Analysis Software Common or Usual Name: Software Accessory to a Computed Tomography Device Classification Name: System, X-ray tomography, Computed (21CFR 892.1750) Regulatory Class: II Product Code: JAK

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AVIEW LCS by Coraline 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

AI-Rad Companion (Cardiovascular) by Siemens Medical Solutions USA, Inc. (K183268) Name of Device: AI-Rad Companion (Cardiovascular) Common or Usual Name: AI-Rad Companion (Cardiovascular) Classification Name: Computed tomography x-ray system (21CFR 892.1750) Regulatory Class: II Product Code: JAK, LLZ

Calcium Scoring by Siemens Medical Solutions, Inc. (K990426) Name of Device: Calcium Scoring Common or Usual Name: Calcium Scoring Classification Name: System, X-ray tomography, Computed (21CFR 892.1750) Regulatory Class: II Product Code: JAK

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

5 DEVICEW DESCRIPTION

Fully automatic pre-processing .
- Fully automatic lung/lobe segmentation using deep-learning algorithms. •
- . Fully automatic airway segmentation using deep-learning algorithms.
- Fully automatic INSP/EXP registration (non-rigid elastic) algorithm. ●
COPD analysis ●

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. LAA analysis (LAA-950HU for INSP, LAA-856HU for EXP)
. LAA size analysis (D-Slope)
- The world-first true 3D analysis of LAA cluster sizes. •
. Precise airway wall thickness measurement
- . Robust measurement using IBHB (Integral-Based Half-BAND) method.
- Precise AWT-Pi10 calculation from 10 samples per each branch .
Air-trapping analysis using INSP/EXP registration
. PRM analysis using INSP/EXP registration (Not available in US)
. Unique pulmonary vessel analysis method (Lobar-pealing method)
Easy and comprehensive UI ●
- Multiple database management
- Comprehensive dynamic bull's eye chart and tables. .
- Web-based access to analysis results, including 3D rendering (Thin-client technology) .
- . PDF report generation
Interoperability ●
- DICOM 3.0 COMPLIANT: C-STORE, C-FIND, C-MOVE and C-ECHO .
- Resulting images and report can be transferred to PACS through DICOM connection
Thin client service
- Connected from anywhere, anyplace, anytime. .
- . Supports mobile view through various mobile devices served by iOS and Android.
- . Compatible with Chrome browser
Research-support ●
- 1000+ feature values are exporting for radiomics research. ●
- . All the segmentation masks are stored in open format (such as Analyze or NifTi)
Easy processing management ●
- Rule-based automatic processing server (APS) ●
  - . Scaling
Nodule Management ●
- Adding nodule by segmentation or by lines. ●
- Semi-automatic nodule measurement (segmentation)
- . Maximal plane measure, 3D measure and volumetric measure.
- . 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.
Follow-up ●
- Automatic retrieving the past data .
- Follow-up support with nodule matching and comparison
- . Automatic calculation of VDT (volume doubling time)
Lungs, Lobes and Airway segmentation
- Better segmentation of lungs, lobes and airway based on deep-learning algorithms.
· Automatic nodule detection (CADe)
- Seamless integration with Mevis Visia (FDA 510(k) Cleared) .
· Coronary Artery Calcification
- Extracts calcium coronary artery and provide Agatston Score, Volume Score and Mass score. .
- Automatically segments calcium area of coronary artery based on deep learning

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. Segments and provides overlay of four main artery (right coronary artery, left main coronary, left anteriordescending, and left circumflex artery) and myocardium
. Provides CAC risk based on age and gender.
· Report
- PDF report generation •
- . It saves or sends the pdf report and captured images in DICOM files.
- . Reports are generated using the results of all nodules detected so far (Lung RADS)
. Save Result
- It saves the results in internal format ●

INDICATIONS FOR USE 6

AVIEW 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 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 devices and chrome browser. 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 nodule, volume of the nodule, Mean HU(the average value of the CT pixel inside the nodule in HU), Minimum HU, Max HU, mass calculated from the CT pixel value), and volumetric measures(Solid major; length of the longest diameter measured in 3D for 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), 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 CAC analysis by segmentation of four main artery (right coronary artery, left anterior descending and left circumflex artery then extracts calcium on coronary artery to provide Agatston score, volume score by whole and each segmented artery type. Based on the score, provides CAC risk based on age and gender.

COMPARISION OF TECHNOLOGICAL CHARACTERISTICS WITH 7 THE PREDICATE DEVICE

AVIEW has the same intended use and the principle of operation and has similar features to the predicate devices. AVIEW (K171199)

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	Reference Device	Reference Device	RegulatoryNumber	21 CFR 892.2050	21 CFR 892.2050	21 CFR 892.1750	21 CFR 892.2050	21 CFR 892.1750	21 CFR 892.1750		Keyboard	Keyboard	Keyboard	Keyboard	Keyboard	Keyboard
Device Name	AVIEW 2.0	AVIEW	Imbio CT LungDensity AnalysisSoftware	AVIEW LCS	AI-RadCompanion(Cardiovascular)	Calcium Scoring	Product Code	LLZ, JAK	LLZ	JAK	LLZ, JAK	JAK	JAK	Image InputSources	Images can be scanned,loaded from cardreaders, or importedfrom a radiographicimaging device	Images can bescanned, loadedfrom card readers, orimported from aradiographicimaging device	Images can be scanned,loaded from cardreaders, or importedfrom a radiographicimaging device	Images can bescanned, loaded fromcard readers, orimported from aradiographic imagingdevice	Images can bescanned, loadedfrom card readers, orimported from aradiographicimaging device	Images can bescanned, loadedfrom card readers, orimported from aradiographic imaging device
ClassificationName	System, imageProcessing Radiological	System, imageProcessingRadiological	Computed Tomographyx-ray system	System, imageProcessingRadiological	ComputedTomography x-raysystem	ComputedTomography x-raysystem	Review Panel	Radiology	Radiology	Radiology	Radiology	Radiology	Radiology	Image format	DICOM	DICOM	DICOM	DICOM	DICOM	DICOM
510k Number	-	K171199	K141069	K193220	K183268	K990426	ImageMeasurementTools	Ruler (line and 3D),Tapeline (curve, polyand3D), Angle (3-point,4point, and 3D), pixelvalues, area of ROI(rectangle, circle,ellipse), volume	Ruler (line and 3D),Tapeline (curve,poly and3D), Angle(3-point, 4point, and3D), pixelvalues, area of ROI(rectangle, circle,ellipse), volume		Ruler (line and 3D),Tapeline (curve, polyand3D), Angle (3-point, 4point, and 3D),pixel values, area ofROI (rectangle, circle,ellipse), volume
Indications foruse	AVIEW 2.0AVIEW provides CT values for pulmonary tissue from CT thoracic and cardiac datasets. This software could be used to support the physicianquantitatively in the diagnosis, follow up evaluation and documentation of CT lung tissue images by providing image segmentation of sub-structures inlung, lobe, airways and cardiac, registration of inspiration and expiration which could analyze air trapping on lung, 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 aswell to allow users to connect by various environment such as mobile devices and chrome browser. 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 (majoraxis, minor axis), estimated effective diameter from the volume 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), and volumetric measures(Solid major; length of the longestdiameter measured in 3D for solid portion of the nodule, Solid 2nd Major: The length of the longest diameter of the solid part, measured in sectionsperpendicular to the Major axis of the solid portion of the nodule), VDT (Volume doubling time), and Lung-RADS (classification proposed to aid withfindings). The system automatically performs the measurement, allowing lung nodules and measurements to be displayed and, integrate with FDAcertified Mevis CAD (Computer aided detection) (K043617). It also provides CAC analysis by segmentation of four main artery (right coronary artery,left main coronary, left anterior descending and left circumflex artery then extracts calcium on coronary artery to provide Agatston score, volume scoreand mass score by whole and each segmented artery type. Based on the score, provides CAC risk based on age and gender.AVIEWAVEIW provides CT values for pulmonary tissue from CT thoracic datasets. This software can be used to support the physician quantitatively in thediagnosis, followup evaluation and documentation of CT lung tissue images by providing image segmentation of sub-structures in the left and right lung(e.g., the five lobes and airway), volumetric and structural analysis, density evaluations and reporting tools. AVIEW is also used to store, transfer, inquireand display CT data sets. AVEIW is not meant for primary image Interpretation in mammography.Imbio CT Lung Density Analysis SoftwareThe Imbio CT Lung Density Analysis Software provides reproducible CT values for pulmonary tissue, which is essential for providing quantitativesupport for diagnosis follow up examinations. The Imbio CT Lung Density Analysis Software can be used to support the physician in the diagnosis anddocumentation of pulmonary tissue images (e.g., abnormalities) from CT thoracic datasets. Three-D segmentation and isolation of sub-compartments,volumetric analysis, density evaluation, and reporting tools are provided.AVEIW 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 singlestudy, 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 CTpixel inside the nodule in HU), Minimum HU, Max HU, mass(mass calculated from the CT pixel value), and volumetric measures (Solid Major, lengthof 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, measuredin sections perpendicular to the Major axis of the solid portion of the nodule), VDT(Volume doubling time), and Lung-RADS (classification proposedto aid with findings). The system automatically performs the measurement, allowing lung nodules and measurements to be displayed and, also integratewith FDA certified Mevis CAD (Computer-aided detection) (K043617)AI-Rad Companion (Cardiovascular)Al-Rad Companion (Cardiovascular) is processing software that provides quantitative and qualitative analysis from previously acquired ComputedTomography DICOM images to support radiologists and physicians from emergency medicine, specialty care, urgent care, and general practice in theevaluation and assessment of cardiovascular disease.It provides the following functionality:· Segmentation and volume measurement of the heart· Quantification of the total calcium volume in the coronary arteries· Segmentation of the aorta· Measurement of maximum diameters of the aorta at typical landmarks· Threshold-based highlighting of enlarged diametersThe software has been validated for non-cardiac chest CT data with filtered backprojection reconstruction from Siemens Helathineers, GE Healthcare,Philips, and Toshiba/Canon, Additionally, the calcium detection feature has been validated on non-cardiac chest CT data with iterative reconstructionform Siemens Healthineers.Only DICOM images of adult patients are considered to be valid input.Calcium ScoringFrom user specified sets of CT cardiac images, Calcium Scoring can be used to;· Allow the user to interactively indicate regions of detected calcification· To allow the user to allocate each detected region to one of several coronary arteries· To estimate algorithmically a score for the amount of detected calcification in each allocated artery· To prepare reports including reports including calcium score data, Imagery, ECG traces, Comparison of scroe to cited literature and additionalrelevant information.The calcium-scoring package is a diagnostic tool that can be used to evaluate the calcified plaques in the coronary arteries, which is a risk factor forcoronary artery disease. Calcium scoring may be used to monitor the progression or regression overtime of the amount or volume of calcium in thecoronary arteries, which may be related to the prognosis of a cardiac attack.							Image viewing	Axial, sagittal, andcoronal image, obliqueslice, cube view	Axial, sagittal, andcoronal image,oblique slice, cubeview		Axial, sagittal, andcoronal image, obliqueslice, cube view
Platform	IBM-compatible PC orPC network	IBM-compatible PCor PC network	IBM-compatible PC orPC network	IBM-compatible PC orPC network	IBM-compatible PCor PC network	IBM-compatible PCor PC network	Imagemanipulation	Panning, rotating,zooming, windowing,inverting, Coloring,Oblique, Note (textoverlay), Coloring	Panning, rotating,zooming, windowing,inverting, Coloring,Oblique, Note (textoverlay), Coloring		Panning, rotating,zooming, windowing,Coloring, Oblique,Note (textoverlay), Coloring
GeneralDescription	AVIEW 2.0The AVIEW is a software product which can be installed on a PC. It shows images taken with the interface from various storage devices using DICOM3.0 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 analysisof CT scanning. Provides following features as semi-automatic nodule management, maximal plane measure, 3D measures and volumetric measures,automatic nodule detection by integration with 3rd party CAD. Also provides Brocks model which calculated the malignancy score based on numericalor Boolean inputs. Follow up support with automated nodule matching and automatically categorize Lung-RADS score which is a quality assurance tooldesigned to standardize lung cancer screening CT reporting and management recommendations that is based on type, size, size change and other findingsthat is reported. It also automatically analyzes coronary artery calcification which support user to detect cardiovascular disease in early stage and reducethe burden of medical.AVIEWThe AVIEW is a software product which can be installed on a PC. It shows images taken with the interface from various storage devices using DICOM3.0 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.Imbio CT Lung Density Analysis SoftwareThe Imbio CT Lung Density Analysis Software (Imbio LDA) IS A SET OF IMAGE POST-PROCESSING ALGORITHMS THAT PERFORM IAMGESEGMENTATION, REGISTRATION, THRESHOLDING, AND CLASSIFICATION ON ct images of juman lungs.The algorithms within the Imbio CT Lung Density Analysis Software are combined into a single command-line or through scripting. The Imbio CT LungDensity Analysis Software program performs segmentation, then registration, then thresholding and classification. The program reads in DICOMdatasets, processes the data, then writes output DICOM files to a specified directory.The Imbio CT Lung Density Analysis Software is a command-line software application that analyzed DICOM CT Lung images datasets and generatedreports and DICOM output that show the lungs segmented and overlaid with colorpcodings representing the results of its thresholding and classificationrules. It has simple file management functions for input and output, and separate modules that implement the CT image-processing algorithms. ImbioCT Lung Density Analysis Software does not interface directly with any CT or data collection equipment; instead the software imports data filespreviously generated by such equipment.AVIEW LCSAVIEW LCS is intended for use as diagnostic patient imaging which is intended for the review and analysis of thoracic CT images. Provides followingfeatures as semi-automatic nodule measurement (segmentation), maximal plane measure, 3D measure and volumetric measures, automatic noduledetection by integration with 3rd party CAD. Also provide cancer risk based on PANCAN risk model which calculated the malignancy score based onnumerical or Boolean inputs. Follow up support with automated nodule matching and automatically categorize Lung-RADS score which is a qualityassurance tool designed to standardize lung cancer screening CT reporting and management recommendations that is based on type, size, size changeand other findings that is reported.AI-Rad Companion (Cardiovascular)In general, AI-Rad Companion (Cardiovascular) is a software only image post-processing application that uses deep learning algorithms to post-processCT data of the thorax. As an update to the previously cleared devices, the following modifications have been made;
	1) Modified indication for Use Statement2) Support of software AI-Rad Companion CT VA10Aa) heart segmentation including measurement (modified)b) calcium detection based on deep learning algorithm (modified)

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Coreline

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	d) AHA landmarks for labeling and diameter measurement of the aorta, including threshold-based aorta diameter classification (modified)3) subject device claims listThe subject device AI-Rad Companion (Cardiovascular) is an image processing software that utilizes deep learning algorithms to provide quantitative and qualitative analysis from previously acquired Computed Tomography DICOM image to support radiologists and physicians from emergency medicine, specialty care, urgent care, and general practice in the evaluation and assessment of disease of the thorax. The subject device support the following device specific functionality.
	Segmentation and volume measurement of heartIdentification and measurement of volume with high Hounsfield values- related to coronary calcificationSegmentation of the aorta determination of 9 Landmarks.Computation of cross-sectional MPRs at the 9 landmarks and their maximum diameterMeasurement of maximum diameters of the aorta at typical landmakrs.Threshold-based classification of diameters into different categories
	Calcium ScoringCalcium Scoring is a software package running on the 3Dvirtuoso workstation that allows the user to mark regions of detected calcification in CT cardiac images, to assign each region to a coronary artery, and to calculate the Agatston score and other information from the identified pixels. Film and paper reports of the results can also be prepared. Calcium Scoring is also a cost-effective alternative to Electron Beam CT (EBCT), since it produces calcium scores that correlated to the EBCT's gold standard, but at a much lower cost.
DICOM	This receives DICOM data from CT by DICOM communicationConducts DICOM data communication with PACS. It also imports DICOM file directly, saves by using export function.	This receives DICOM data from CT by DICOM communicationConducts DICOM data communication with PACS. It also imports DICOM file directly, saves by using export function.	Retrieve image data over the network via DICOM	This receives DICOM data from CT by DICOM communicationConducts DICOM data communication with PACS. It also imports DICOM file directly, saves by using export function.	Retrieve image data over the network via DICOM	Retrieve image data over the network via DICOM
	Fully automatic lungs, lobes and airways segmentation using deep-learning algorithms	Semi-automatic segmentation of lungs, lobes and airways.
	Semi-automatic segmentation of lungs, lobes and airways.
	Visualization of multi-planar reconstructed (MPR) images and 3D rendered images, with color-defined Hounsfield Unit (HU) ranges.	Visualization of multi-planar reconstructed (MPR) images and 3D rendered images, with color-defined Hounsfield Unit (HU) ranges.
Lung AnalysisFunctions	Calculation of LAA (Lower Attenuation Area) index with HU density histogram. Volume measurements and percentile index	Calculation of LAA (Lower Attenuation Area) index with HU density histogram. Volume measurements and percentile index
	Calculation of LAA cluster size distribution with D-slope	Calculation of LAA cluster size distribution with D-slope
	Graphical visualization of the above quantification results for reporting	Graphical visualization of the above quantification results for reporting
	Export of quantification results to CSV tables	Export of quantification results to CSV tables
	Visualization of LAA% for each of 5 lobes	Visualization of LAA% for each of 5 lobes
	Measurements of the airway branches, such as, lumen area and wall area	Measurements of the airway branches, such as, lumen area and wall area

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	Analyzes Air TrappingIndex by registration ofinspiration andexpiration data. Couldcompare both IN/EXafter the registration	Imbio providessegmentation of lungand automatiedregistration ofinspiration andexpiration image part toclassify the analysis bythresholding the CTdata.It also provides aninterctive visualliztionof the registered pairs toanalyze low-densitycluster (air trap) andairway analysis.Uses advanced image
	Fully automaticINSP/EXP registration(non-rigid elastic)algorithm.	processing techniquesto spatially "register"two CT image of thelungs.
	Fully automaticlung/lobe segmentationusing deep-learningalgorithms		same
	Automatic calculation ofmeasurements for eachsegmented nodule· Size of the Major axisand Minor axis(mm)· Diameter of Major(3D), 2nd Major(3D), Major(2D),Minor(2D) (mm)· Volume(mm³)· Max, Min, Mean HUof the nodule((HU)Cancer probability (%)		same
LungCancerScreening	Comparison andmatching automaticcalculations betweeneach follow-up scan andthe baseline scan· Doubling time indays· Indicated the changeof the sizeAuto generate Lung-RADS		Same
	Loading multiple studies		Same
	Workflow· Detect and Segment· Comparison andMatching· ResultsOption to integrate with3rd party CAD whichautomatically detects thenodules and generatereport		Same
	Supporting Low-doseCT		Same
	Reporting resultsThe results include thefollowing;· Lung-RADS· PANCAN riskcalculator· Auto detect nodulelocation by lobe		Same

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Image /page/12/Picture/0 description: The image shows the word "CORELINE" in white text on a dark blue background. To the left of the word is a triangular shape that is also white. The triangular shape is made up of three lines that are connected at the corners.

Cardiac (CAC)	Extracting Calcium onCoronary Artery andprovides Agatston score,volume score and massscore.	-	-	Extracting Calciumon Coronary Arteryand providesAgatston score andvolume score	evaluation anddocumentation ofcalcified coronarylesions, calculationof the Agatstonequivalentscore
	Automatically segmentscalcium area of coronaryartery based on deeplearning.		-	Calcium Detectiondeep learning-basedalgorithm

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.

-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.
Moderate defects, which are typically related to user-interface or general quality of product, while workaround is available.
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
- · Auto Lung & Lobe Segmentation
- Airway Segmentation .
- Nodule Matching Experiment Using Lung Registration .
- Validation on DVF Size Optimization with Sub-sampling ●
- Semi-automatic Nodule Segmentation

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Brock Model (ask PANCAN) Calculation .
VDT Calculation .
. Lung RADS Calculation
Validation LAA Analysis ●
Validation LAA Size Analysis ●
Size analysis algorithm of LAA clusters ●
Lung Registration
Reliability Test for Airway wall Measurement
CAC Performance ●
Air Trapping Analysis .

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 described in this submission is 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).