(115 days)
Yes
The summary explicitly mentions "Better segmentation of lungs and lobes based on deep-learning algorithms," which is a type of machine learning.
No
The device is described as a diagnostic tool for reviewing and analyzing thoracic CT images for characterizing lung nodules, not for direct treatment or therapy.
Yes
The device is intended for the "review and analysis and reporting of thoracic CT images for the purpose of characterizing nodules in the lung," and is described as "diagnostic patient imaging," directly indicating its role in diagnosis.
Yes
The device description and performance studies focus entirely on software functionalities, algorithms, and testing. There is no mention of any hardware components being part of the device itself, only the software being installed on hardware with recommended system specifications.
Based on the provided information, this device is not an IVD (In Vitro Diagnostic).
Here's why:
- IVD Definition: In Vitro Diagnostics are tests performed on samples taken from the human body, such as blood, urine, or tissue, to detect diseases, conditions, or infections.
- Device Function: The AVIEW LCS is a software device that analyzes and processes medical images (CT scans) of the lungs. It does not perform any tests on biological samples.
- Intended Use: The intended use clearly states it's for the "review and analysis and reporting of thoracic CT images." This is image analysis, not in vitro testing.
Therefore, the AVIEW LCS falls under the category of medical imaging software or a picture archiving and communication system (PACS) component, not an In Vitro Diagnostic device.
No
The letter does not explicitly state that the FDA has reviewed and approved or cleared a PCCP for this specific device. The 'Control Plan Authorized (PCCP) and relevant text' section is marked "Not Found".
Intended Use / Indications for Use
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).
Product codes (comma separated list FDA assigned to the subject device)
LLZ, JAK
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.
- -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
- -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
Mentions image processing
Yes
Mentions AI, DNN, or ML
Yes
Input Imaging Modality
CT
Anatomical Site
chest
Indicated Patient Age Range
Not Found
Intended User / Care Setting
Not Found
Description of the training set, sample size, data source, and annotation protocol
Not Found
Description of the test set, sample size, data source, and annotation protocol
Not Found
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
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.
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 are not impacting the product's intended use. Not significant. Success standard of System Test is not finding 'Major', 'Moderate' defect.
Performance Test: DICOM Test Report for AVIEW LCS; Performance test report for AVIEW LCS; AVIEW LCS Integration Test Report; AVIEW LCS Thin Client Server Compatibility Test Report.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
Not Found
Predicate Device(s): If the device was cleared using the 510(k) pathway, identify the Predicate Device(s) K/DEN number used to claim substantial equivalence and list them here in a comma separated list exactly as they appear in the text. List the primary predicate first in the list.
Reference Device(s): Identify the Reference Device(s) K/DEN number and list them here in a comma separated list exactly as they appear in the text.
Predetermined Change Control Plan (PCCP) - All Relevant Information for the subject device only (e.g. presence / absence, what scope was granted / cleared under the PCCP, any restrictions, etc).
Not Found
§ 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).
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)
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).
| 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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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
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
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.
- -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 Predicate
Device | Reference Device | Reference Device |
|------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------|-------------------------------------------------------------|---------------------------------------------|
| Device Name | AVIEW LCS | AVIEW LCS | Lung Nodule
Assessment and
Comparison Option
(LNA) | AVIEW |
| Classification
Name | System, image
Processing
Radiological | System, image
Processing
Radiological | System, image
Processing
Radiological | System, image
Processing
Radiological |
| Regulatory
Number | 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 for
use | AVIEW LCS
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, 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 LCS
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, 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. | | | |
| | AVIEW
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 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 nodule
and measurements such as size (major axis, minor 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 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, 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. | ||||
|---|---|---|---|---|
| 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 Input | ||||
| Soures | Images can be scanned, | |||
| loaded from card | ||||
| readers, or imported | ||||
| from a radiographic | ||||
| imaging device | Images can be | |||
| scanned, loaded from | ||||
| card readers, or | ||||
| imported from a | ||||
| radiographic imaging | ||||
| device | Images can be scanned, | |||
| loaded from card | ||||
| readers, or imported | ||||
| from a radiographic | ||||
| imaging device | Images can be | |||
| scanned, loaded from | ||||
| card readers, or | ||||
| imported from a | ||||
| radiographic imaging | ||||
| device | ||||
| Image format | DICOM | DICOM | DICOM | DICOM |
| Intended body | ||||
| part | chest | chest | chest | chest |
| Type of Scans | CT | CT | CT | CT |
| General | ||||
| Description | AVIEW LCS | |||
| 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 columetric measures, | ||||
| automatic nodules detection by integration with 3rd 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. | ||||
| AVIEW LCS | ||||
| 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 columetric measures, | ||||
| automatic nodules detection by integration with 3rd 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. | ||||
| Lung Nodule Assessment and Comparison Option (LNA) | ||||
| The Lung Nodule Assessment and Comparison Option application is intended for use as a | ||||
| diagnostic 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 Screening | ||||
| AVIEW | ||||
| 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 sum | ||||
| image, axial, sagittal, | ||||
| coronal, and oblique | ||||
| planes. | same | Providing axial, | ||
| sagittal, coronal, and | ||||
| oblique planes | same | |||
| Rotating to Anterior, | ||||
| Posterior, Left, Right, | ||||
| Head, and Foot | ||||
| direction | same | Rotating to Anterior, | ||
| Posterior, Left, Right, | ||||
| Head, and Foot | ||||
| direction | same | |||
| Providing VR (Volume | ||||
| render), MIP | ||||
| (Maximum Intensity | ||||
| Projection), MinIP | ||||
| (Minimum Intensity | ||||
| Projection) image | same | Providing Average, | ||
| MIP, VIP, MinIP, | ||||
| SurfaceMIP, Vol, | ||||
| Rend. | same | |||
| Key Functions | Changing the color and | |||
| transparency of the VR | ||||
| image by adjusting the | ||||
| OTF (Opacity Transfer | ||||
| Function) and saving | same | Changing the color and | ||
| transparency of the VR | ||||
| image | same |
9
same
same
same
same
2D and 3D image
and
Segmentation of lung
comparative review
2D measurements
3D
review
2D
apply in the VR setting
2D and 3D image
and
and
Segmentation of Lungs
comparative review
measurements
3D
3D
review
2D
2D
same
same
same
same
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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 studies |
| Up 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 |
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| | and generate report
Displays CAC/LAA
result analyzed by
AVIEW | automatically
detects the nodules
and
generate
report | | automatically
detects the
nodules
and
generate report |
|-------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|-------------------------------------------------------------------|
| | Supporting Low-dose
CT | same | Supporting Low-dose
CT | same |
| | Reporting results
The results include the
following.
• Lung-RADS
• PANCAN risk
calculator
• Auto detect nodule
location by lobe | same | Reporting results
The results include the
following.
• Patient related
information
• Dictation Table with
Nodule result table
and additional
findings
• Lung-RADS
• Risk Calculator | same |
| | Printing Option | same | Printing Option | same |
| Thin client
service | Connected from
anywhere,
anyplace, anytime
• Supports mobile
view through
various mobile
devices served by
ios and Android.
• Compatible with
Chrome browser | - | - | same |
| Easy processing
management | Rule-based automatic
processing 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.
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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.