(245 days)
Yes
The device description explicitly states that the device "utilizes machine and deep learning algorithms".
No
The device is image processing software intended to support clinicians in the evaluation and assessment of cardiovascular diseases by providing quantitative and qualitative analysis from previously acquired CT images. It does not directly manage or treat a patient's condition.
Yes
The intended use of the device is to provide "quantitative and qualitative analysis from previously acquired Computed Tomography DICOM images to support radiologists and physicians... in the evaluation and assessment of cardiovascular diseases," which directly indicates a diagnostic purpose.
Yes
The device is described as "image processing software" and its functionality is entirely based on analyzing previously acquired DICOM images. The description focuses on software enhancements and deployment options (cloud and edge), with no mention of accompanying hardware components required for its operation beyond the input images themselves.
Based on the provided information, this device is not an In Vitro Diagnostic (IVD).
Here's why:
- IVDs are used to examine specimens derived from the human body. The intended use and device description clearly state that AI-Rad Companion (Cardiovascular) processes previously acquired Computed Tomography DICOM images. These are medical images, not biological specimens like blood, urine, or tissue.
- The functionality described is image processing and analysis. The software performs tasks like segmentation, volume measurement, quantification of calcium, and diameter measurements on the CT images. These are all related to interpreting medical images, not analyzing biological samples.
- The intended use is to support clinicians in the evaluation and assessment of cardiovascular diseases based on imaging data. This aligns with the purpose of medical image analysis software, not IVDs which provide information about a patient's health status through the examination of specimens.
Therefore, while this device is a medical device used in the diagnosis and assessment of cardiovascular conditions, it falls under the category of medical image processing software, not an In Vitro Diagnostic.
No
The letter does not explicitly state that the FDA has reviewed, approved, or cleared a PCCP for this specific device.
Intended Use / Indications for Use
AI-Rad Companion (Cardiovascular) is image processing software that provides quantitative and qualitative analysis from previously acquired Computed Tomography DICOM images to support radiologists and physicians from emergency medicine, specialty care, urgent care, and general practice in the evaluation and assessment of cardiovascular diseases.
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 diameters
The software has been validated for non-cardiac chest CT data with filtered backprojection reconstruction from Siemens Healthineers, GE Healthcare, Philips, and Toshiba/Canon. Additionally, the calcium detection feature has been validated on non-cardiac chest CT data with iterative reconstruction from Siemens Healthineers.
Only DICOM images of adult patients are considered to be valid input.
Product codes
JAK, QIH
Device Description
AI-Rad Companion (Cardiovascular) SW version VA20 is an enhancement to the previously cleared device AI-Rad Companion (Cardiovascular) K183268 that utilizes machine and deep learning algorithms to provide quantitative and qualitative analysis to computed tomography DICOM images to support qualified clinicians in the evaluation and assessment of cardiovascular diseases.
As an update to the previously cleared device, the following modifications have been made:
Segmentation of Aorta – Performance Improvement
Although the structure of the underlying neural network has not changed in the subject device of this submission, the performance was enhanced over the previously cleared device by adding training data (re-use of existing annotations + 267 additional annotations).
Aorta diameter measurements - Maximum Diameter Ascending, Descending Aorta
In the previously cleared device diameter measurements of the aorta were performed at nine predefined locations according to the AHA guidelines.
As an enhancement to the previously cleared device and subject of this submission are aorta diameter measurements at the locations of the maximum diameter of the ascending and the descending aorta.
Visualization of aorta's VRT and as cross-sectional MPRs - Maximum Diameter Ascending, Descending Aorta
In the previously cleared device visualization VRT and cross-sectional MPRs were provided at nine predefined locations according to the AHA guidelines.
As an enhancement to the previously cleared device, such visualization of the maximum diameter of the ascending and descending aorta were added to the subject of this submission.
Categorization of diameter measurements - Maximum Diameter Ascending, Descending Aorta
In the previously cleared device categorization of diameter measurements was performed at locations according to the AHA guidelines.
With the subject of this submission, the categorization of diameter measurements was extended to locations of the maximum diameter of the ascending and descending aorta.
Individual Confirmation of Aorta Findings
For the measurements of the aorta, only all the measurements could be accepted or declined in the predicate device.
Within the scope of this submission the concept of individual accept, decline-possibility was introduced to all aorta measurements.
Structured DICOM Report (DICOM TID 1500)
In the predicate device, the system would produce results in form of quantitative, structured and textual reports and would generate DICOM Secondary Capture images which would be forwarded to PACS reading and reporting systems.
Within the scope of this submission, the system supports an alternative, digital output format for the same results. For this purpose, a DICOM Structured Report is generated which is both human and machine readable and, therefore, will support, e.g., a transfer of the results into the clinical report more efficiently. The DICOM Structured Report is compliant to the TID1500 format for applicable content.
Cloud and Edge Deployment
Another enhancement provided within this submission is the existing cloud deployment in an on-premise deployment known as an edge deployment. The system remains hosted in the teamplay digital health platform and remains driven by the AI-Rad Companion Engine; however, with the edge deployment the processing of clinical data and the generation of results is performed within the customer environment. This system remains fully connected to the cloud for monitoring and maintenance of the system from a remote setup. At the time of this submission this feature has been cleared in submission K213706 (AI-Rad Companion Brain MR VA40) and is unchanged within this subject device.
Mentions image processing
AI-Rad Companion (Cardiovascular) is image processing software that provides quantitative and qualitative analysis from previously acquired Computed Tomography DICOM images to support radiologists and physicians from emergency medicine, specialty care, urgent care, and general practice in the evaluation and assessment of cardiovascular diseases.
Mentions AI, DNN, or ML
AI-Rad Companion (Cardiovascular) SW version VA20 is an enhancement to the previously cleared device AI-Rad Companion (Cardiovascular) K183260 that utilizes machine and deep learning algorithms to provide quantitative and qualitative analysis to computed tomography DICOM images to support qualified clinicians in the evaluation and assessment of cardiovascular diseases.
Calcium Detection with deep learning-based algorithm
Landmark Detection with deep learning-based algorithms, 9 AHA positions
Aorta Segmentation with deep learning-based algorithm with improved performance by adding training data (+ 267 additional annotations)
Input Imaging Modality
Computed Tomography DICOM images
Anatomical Site
Cardiovascular, heart, coronary arteries, aorta
Indicated Patient Age Range
Adult patients
Intended User / Care Setting
Radiologists and physicians from emergency medicine, specialty care, urgent care, and general practice.
Description of the training set, sample size, data source, and annotation protocol
Although the structure of the underlying neural network has not changed in the subject device of this submission, the performance was enhanced over the previously cleared device by adding training data (re-use of existing annotations + 267 additional annotations).
Description of the test set, sample size, data source, and annotation protocol
The performance of the aorta segmentation module has been validated in a representative retrospective clinical cohort (N=315).
The accuracy of the aortic diameter measurements was validated in a representative retrospective clinical cohort (N=193, including 50% of the cases with dilated aorta and 9% of the cases with aortic aneurysm). The test data has been chosen to be representative for the intended population consists of a cohort of consecutive patients undergoing Chest CT exams for varying indications in addition to a cohort at increased risk for incidental findings particularly in the cardiovascular domain, due to the screening nature of the examination.
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
The performance of the aorta segmentation module has been validated in a representative retrospective clinical cohort (N=315) and has shown substantially equivalent performance to the predicate device. For the subject device, average DICE (± std. dev) coefficient was 0.924 (± 0.046), v., 0.910 (± 0.066) for predicate device. Consistent performance has been observed for all relevant subgroups including device manufacturers, slice thickness, patient sex and age, and comorbidities.
The accuracy of the aortic diameter measurements was validated in a representative retrospective clinical cohort (N=193, including 50% of the cases with dilated aorta and 9% of the cases with aortic aneurysm). The evaluation included Bland Altman analysis, in particular detailed analysis of error and bias of individual subgroups.
With respect to the diameter measurements at the nine predefined locations, the predicate device yielded a bias within ±1.8 mm (95%-CI: [1.5 mm. 2.1 mm]) and mean absolute error (MAE) to be ≤2.4 mm (95%-CI: [2.1 mm, 2.6 mm]). For the subject device the bias was within ±1.5 mm (95%-CI: [0.9 mm, 2.0 mm]) and MAE ≤2.2 mm (95%-CI: [1.8 mm, 2.6 mm]).
Wirth respect to the diameter measurements at the location of maximum ascending and maximum descending aorta, respectively, inter-reader variability was assessed, and 95%-limits of agreement (LoAs) were established at ±3.51 mm. 91.9% of the measurements provided by the subject device were found to lie within the LoA, with a bias within ±1.5 mm (95%-CI: [1.2 mm, 1.8 mm]) and MAE ≤1.8 mm (95%-CI: [1.44 mm, 2.23 mm]).
For all diameter measurements consistent performance has been observed for all relevant subgroups including device manufacturers, slice thickness, patient sex and age, and comorbidities. In summary, all performance criteria have been fulfilled and the validation demonstrated substantially equivalent performance to the predicate device.
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
Average DICE (± std. dev) coefficient was 0.924 (± 0.046) for the subject device.
Bias for diameter measurements at nine predefined locations: ±1.5 mm (95%-CI: [0.9 mm, 2.0 mm])
MAE for diameter measurements at nine predefined locations: ≤2.2 mm (95%-CI: [1.8 mm, 2.6 mm])
95%-limits of agreement (LoAs) for maximum ascending and maximum descending aorta diameter: ±3.51 mm.
91.9% of measurements within LoA.
Bias for maximum ascending and maximum descending aorta diameter: ±1.5 mm (95%-CI: [1.2 mm, 1.8 mm])
MAE for maximum ascending and maximum descending aorta diameter: ≤1.8 mm (95%-CI: [1.44 mm, 2.23 mm])
Predicate Device(s)
Reference Device(s)
Predetermined Change Control Plan (PCCP) - All Relevant Information
Not Found.
§ 892.1750 Computed tomography x-ray system.
(a)
Identification. A computed tomography x-ray system is a diagnostic x-ray system intended to produce cross-sectional images of the body by computer reconstruction of x-ray transmission data from the same axial plane taken at different angles. This generic type of device may include signal analysis and display equipment, patient and equipment supports, component parts, and accessories.(b)
Classification. Class II.
0
April 6, 2023
Siemens Medical Solutions U.S.A. % Alexandra Fink Sr. Manager, Regulatory Affairs 40 Liberty Blvd. MALVERN PA 19355
Re: K222360
Trade/Device Name: AI-Rad Companion (Cardiovascular) Regulation Number: 21 CFR 892.1750 Regulation Name: Computed Tomography X-Ray System Regulatory Class: Class II Product Code: JAK, QIH Dated: February 17, 2023 Received: March 7, 2023
Dear Alexandra Fink:
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 devices or postmarketing safety reporting (21 CFR 4, Subpart B) for combination products (see
1
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 medical devices and radiation-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,
Lu Jiang
Lu Jiang, Ph.D. Assistant Director Diagnostic X-Ray Systems Team DHT8B: Division of Imaging Devices and Electronic Products OHT8: Office of Radiological Health Office of Product Evaluation and Quality Center for Devices and Radiological Health
Enclosure
2
Image /page/2/Picture/0 description: The image contains the logo for Siemens Healthineers. The word "SIEMENS" is written in teal, and the word "Healthineers" is written in orange below it. To the right of the words is a graphic of several orange dots arranged in a circular pattern.
DEPARTMENT OF HEALTH AND HUMAN SERVICES Food and Drug Administration
Indications for Use
Form Approved: OMB No. 0910-0120 Expiration Date: 06/30/2023 See PRA Statement below.
510(k) Number (if known)
K22360
Device Name
AI-Rad Compaion (Cardiovascular)
| Indications for Use (Describe) | |
|---|---|
| -------------------------------- | -- |
Indications for Use (Describe)
AI-Rad Companion (Cardiovascular) is image processing software that provides quantitative and qualitative analysis from previously acquired Computed Tomography DICOM images to support radiologists and physicians from emergency medicine, specialty care, urgent care, and general practice in the evaluation and assessment of cardiovascular diseases.
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 diameters
The software has been validated for non-cardiac chest CT data with filtered backprojection reconstruction from Siemens Healthineers, GE Healthcare, Philips, and Toshiba/Canon. Additionally, the calcium detection feature has been validated on non-cardiac chest CT data with iterative reconstruction from Siemens Healthineers.
Only DICOM images of adult patients are considered to be valid input.
Type of Use (Select one or both, as applicable)
| Prescription Use (Part 21 CFR 801 Subpart D) | Over-The-Counter Use (21 CFR 801 Subpart C) |
|---|---|
| -------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------- |
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."
FORM FDA 3881 (6/20)
Page 1 of 1
PSC Publishing Sarvious (301) 443-6740 EF
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Image /page/3/Picture/0 description: The image contains the logo for Siemens Healthineers. The word "SIEMENS" is written in teal, and the word "Healthineers" is written in orange below it. To the right of the words is a graphic of orange dots arranged in a circular pattern.
510(k) SUMMARY K222360 FOR AI-RAD COMPANION (Cardiovascular) SW Version VA20
Submitted by: Siemens Medical Solutions USA, Inc. 40 Liberty Boulevard Malvern, PA 19355 Date Prepared: July, 26th 2022
This summary of 510(k) safety and effectiveness information is being submitted in accordance with the requirements of Safe Medical Devices Act of 1990 and 21 CFR §807.92.
| 1. Submitter | |
|---|---|
| Importer/Distributor | Siemens Medical Solutions USA, Inc. |
| 40 Liberty Boulevard | |
| Malvern, PA 19355 | |
| Mail Code: 65-1A | |
| Registration Number: 2240869 | |
| Manufacturing Site | Siemens Healthcare GmbH |
| Henkestrasse 127 | |
| Erlangen, Germany 91052 | |
| Registration Number: 3002808157 |
2. Contact Person
Alexandra Fink Senior Manager, Regulatory Affairs Siemens Healthcare GmbH Hartmannstrasse 16 Erlangen, Germany 91052 Email: alexandra.fink@siemens-healthineers.com
3. Device Name and Classification
| Product Name: | AI-Rad Companion (Cardiovascular) |
|---|---|
| Trade Name: | AI-Rad Companion (Cardiovascular) |
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Image /page/4/Picture/0 description: The image shows the logo for Siemens Healthineers. The word "SIEMENS" is written in teal, and the word "Healthineers" is written in orange. To the right of the words is a graphic of orange dots arranged in a circular pattern.
| Classification Name: | System, X-Ray, Tomography, Computed |
|---|---|
| Classification Panel: | Radiology |
| CFR Section: | 21 CFR §892.1750 |
| Secondary CFR Section: | 21 CFR §892.2050 |
| Device Class: | Class II |
| Product Code: | JAK |
| Secondary Product Code: | QIH |
4. Predicate Device
| Product Name: | AI-Rad Companion (Cardiovascular) |
|---|---|
| Propriety Trade Name: | AI-Rad Companion (Cardiovascular) |
| 510(k) Number: | K183268 |
| Clearance Date: | September 10, 2019 |
| Classification Name: | System, X-Ray, Tomography, Computed |
| Classification Panel: | Radiology |
| CFR Section: | 21 CFR §892.1750 |
| Secondary CFR Section: | 21 CFR §892.2050 |
| Device Class: | Class II |
| Primary Product Code: | JAK |
| Secondary Product Code: | LLZ |
| Recall Information: | N/A |
5. Indications for Use
AI-Rad Companion (Cardiovascular) is image processing software that provides quantitative and qualitative analysis from previously acquired Computed Tomography DICOM images to support radiologists and physicians from emergency medicine, specialty care, urgent care, and general practice in the evaluation and assessment of cardiovascular diseases.
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 diameters
The software has been validated for non-cardiac chest CT data with filtered backprojection reconstruction from Siemens Healthineers, GE Healthcare, Philips, and Toshiba/Canon. Additionally, the calcium detection feature has been validated on non-cardiac chest CT data with iterative reconstruction from Siemens Healthineers.
Only DICOM images of adult patients are considered to be valid input.
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Image /page/5/Picture/0 description: The image shows the logo for Siemens Healthineers. The word "SIEMENS" is written in teal, and the word "Healthineers" is written in orange below it. To the right of the words is a graphic of orange dots arranged in a circular pattern.
6. Device Description
AI-Rad Companion (Cardiovascular) SW version VA20 is an enhancement to the previously cleared device AI-Rad Companion (Cardiovascular) K183268 that utilizes machine and deep learning algorithms to provide quantitative and qualitative analysis to computed tomography DICOM images to support qualified clinicians in the evaluation and assessment of cardiovascular diseases.
As an update to the previously cleared device, the following modifications have been made:
Segmentation of Aorta – Performance Improvement
Although the structure of the underlying neural network has not changed in the subject device of this submission, the performance was enhanced over the previously cleared device by adding training data (re-use of existing annotations + 267 additional annotations).
Aorta diameter measurements - Maximum Diameter Ascending, Descending Aorta
In the previously cleared device diameter measurements of the aorta were performed at nine predefined locations according to the AHA guidelines.
As an enhancement to the previously cleared device and subject of this submission are aorta diameter measurements at the locations of the maximum diameter of the ascending and the descending aorta.
Visualization of aorta's VRT and as cross-sectional MPRs - Maximum Diameter Ascending, Descending Aorta
In the previously cleared device visualization VRT and cross-sectional MPRs were provided at nine predefined locations according to the AHA guidelines.
As an enhancement to the previously cleared device, such visualization of the maximum diameter of the ascending and descending aorta were added to the subject of this submission.
Categorization of diameter measurements - Maximum Diameter Ascending, Descending Aorta
In the previously cleared device categorization of diameter measurements was performed at locations according to the AHA guidelines.
With the subject of this submission, the categorization of diameter measurements was extended to locations of the maximum diameter of the ascending and descending aorta.
Individual Confirmation of Aorta Findings
For the measurements of the aorta, only all the measurements could be accepted or declined in the predicate device.
Within the scope of this submission the concept of individual accept, decline-possibility was introduced to all aorta measurements.
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Image /page/6/Picture/0 description: The image contains the logo for Siemens Healthineers. The word "SIEMENS" is written in teal, and the word "Healthineers" is written in orange below it. To the right of the words is a graphic of orange dots.
Structured DICOM Report (DICOM TID 1500)
In the predicate device, the system would produce results in form of quantitative, structured and textual reports and would generate DICOM Secondary Capture images which would be forwarded to PACS reading and reporting systems.
Within the scope of this submission, the system supports an alternative, digital output format for the same results. For this purpose, a DICOM Structured Report is generated which is both human and machine readable and, therefore, will support, e.g., a transfer of the results into the clinical report more efficiently. The DICOM Structured Report is compliant to the TID1500 format for applicable content.
Cloud and Edge Deployment
Another enhancement provided within this submission is the existing cloud deployment in an on-premise deployment known as an edge deployment. The system remains hosted in the teamplay digital health platform and remains driven by the AI-Rad Companion Engine; however, with the edge deployment the processing of clinical data and the generation of results is performed within the customer environment. This system remains fully connected to the cloud for monitoring and maintenance of the system from a remote setup. At the time of this submission this feature has been cleared in submission K213706 (AI-Rad Companion Brain MR VA40) and is unchanged within this subject device.
Image /page/6/Figure/6 description: The image shows a diagram of the Al-Rad Companion on Edge system. The diagram illustrates the flow of data between the cloud, edge, and on-premise components. The system includes components such as the teamplay Cloud, teamplay Edge, Edge TP Connector, Data Filtering and Analysis, and PACS/TPS. The diagram also shows the different types of data that are sent between the components, such as entitlements, runtime config data, and log data.
Figure 1 Illustration of the edge deployment for AI-Rad Companion
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Image /page/7/Picture/0 description: The image contains the logo for Siemens Healthineers. The word "SIEMENS" is written in teal, and the word "Healthineers" is written in orange below it. To the right of the words is a graphic of orange dots.
7. Technological Characteristics
The comparison between the above referenced predicate device is listed at a high-level in the following Table 1.
| Feature | Subject Device
AI-Rad Companion
(Cardiovascular)
VA20 | Predicate Device
AI-Rad Companion
(Cardiovascular)
(K183268) | Result |
|------------------------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------|-----------------------------------------------------------------------------|
| Modality | CT | CT | Identical |
| Segmentation of
heart | AI-based Heart
Segmentation | AI-based Heart
Segmentation | Identical |
| Detection of
coronary
calcium &
quantification of
coronary
calcium volume | Calcium Detection with
deep learning-based
algorithm | Calcium Detection with
deep learning-based
algorithm | Identical |
| Visualization of
heart and of
calcium | Color overlay of MPR
and VRT with
evaluation results | Color overlay of MPR
and VRT with
evaluation results | Identical |
| Detection of
aortic
landmarks | Landmark Detection
with deep learning-
based algorithms, 9
AHA positions | Landmark Detection
with deep learning-
based algorithms, 9
AHA positions | Identical |
| Segmentation of
aorta | Aorta Segmentation
with deep learning-
based algorithm with
improved performance
by adding training data
(+ 267 additional
annotations) | Aorta Segmentation
with deep learning-
based algorithm | Modified: improved
performance of the
algorithm |
| Aorta diameter
measurements | Aorta diameter
measurements at nine
predefined locations
according to the AHA
guidelines and at the
locations of the | Threshold-based
classification of
diameters into different
categories | Modified: maximum
diameter of ascending
and descending aorta
added |
| | maximum diameter of
the ascending and
descending aorta | | |
| Visualization of
aorta's VRT and
as cross-
sectional MPRs | Visualization VRT and
cross-sectional MPRs at
nine predefined
locations according to
the AHA guidelines and
of the maximum
diameter of ascending
and descending aorta | Visualization VRT and
cross-sectional MPRs at
nine predefined
locations according to
the AHA guidelines | Modified:
maximum diameter of
ascending and
descending aorta added |
| Categorization
of diameter
measurements | Categorization of
diameter measurements
at locations according
to the AHA guidelines
and at locations of the
maximum diameter of
ascending and
descending aorta | Categorization of
diameter measurements
at locations according
to the AHA guidelines | Modified:
maximum diameter of
ascending and
descending aorta added |
| Reports | Results in form of
quantitative, structured
and textual reports, and
DICOM Secondary
Capture as well as
DICOM Structured
Report (TID 1500) | Results in form of
quantitative, structured
and textual reports, and
DICOM Secondary
Capture | Modified: format of
DICOM report changed |
| Deployment | Cloud and Edge (on-
premise) deployments | Cloud deployment | Modified: edge
deployment added |
Table 1 Comparison of technological characteristics
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Image /page/8/Picture/0 description: The image shows the Siemens Healthineers logo. The word "SIEMENS" is in teal, and the word "Healthineers" is in orange. To the right of the words is a graphic of orange dots arranged in a circular pattern.
8. Nonclinical Tests
Non-clinical tests were conducted to test the functionality of AI-Rad Companion (Cardiovascular). Software validation and bench testing have been conducted to assess the performance claims as well as the claim of substantial equivalence to the predicate device.
AI-Rad Companion has been tested to meet the requirements of conformity to multiple industry standards. Non-clinical performance testing demonstrates that AI-Rad Companion (Cardiovascular) complies with the FDA guidance document, "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices" (May 11, 2005) as well as with the following FDA recognized Consensus Standards listed in Table 2 below.
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Image /page/9/Picture/0 description: The image shows the logo for Siemens Healthineers. The word "SIEMENS" is written in teal, and the word "Healthineers" is written in orange below it. To the right of the words is a graphic of orange dots arranged in a circular pattern.
Table 2 Voluntary Conformance Standards
| Recognition
Number | Product
Area | Title of Standard | Reference
Number and
Date | Standards
Development
Organization |
|-----------------------|--------------------------|------------------------------------------------------------------------------------------------------------|---------------------------------|------------------------------------------|
| 5-114 | General | Medical Devices – Application of usability engineering to medical devices [including Corrigendum 1 (2016)] | 62366-1:
2015-02 | IEC |
| 5-125 | General | Medical Devices – application of risk management to medical devices | 14971:2019 | ISO |
| 13-79 | Software/
Informatics | Medical device software – software life cycle processes [Including Amendment 1 (2016)] | 62304:
2006/A1:2016 | AAMI
ANSI
IEC |
| 12-300 | Radiology | Digital Imaging and Communications in Medicine (DICOM) Set | PS 3.1 – 3.20
(2016) | NEMA |
Verification and Validation
Software documentation for a Moderate Level of Concern software, per FDA's Guidance Document "Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices" issued on May 11, 2005, is also included as part of this submission. The performance data demonstrates continued conformance with special controls for medical devices containing software. Non-clinical tests (unit, integration and system) were conducted on the subject device during product development. In Summary all performance criteria have been fulfilled.
Siemens Healthineers adheres to the cybersecurity requirements as defined the FDA Guidance "Content of Premarket Submission for Management of Cybersecurity in Medical Devices: Guidance for Industry and Food and Drug Administration Staff" (October 2, 2014) by implementing a process of preventing unauthorized access, modifications, misuse or denial of use, or the unauthorized use of information that is stored, accessed, or transferred from a medical device to an external recipient.
9. Performance Software Validation
To validate the novel and updated features of the AI-Rad Companion (Cardiovascular) from the clinical perspective, the following algorithms underwent a scientific evaluation:
- -Performance of aorta segmentation
- -Aorta diameter measurements at the nine predefined landmarks and at location of maximum ascending and maximum descending aorta, respectively.
The results of clinical data-based software validation for the subject device AI-Rad Companion Cardiovascular demonstrated equivalent performance in comparison to the predicate device.
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In more detail, the performance of the aorta segmentation module has been validated in a representative retrospective clinical cohort (N=315) and has shown substantially equivalent performance to the predicate device. For the subject device, average DICE (± std. dev) coefficient was 0.924 (± 0.046), v., 0.910 (± 0.066) for predicate device. Consistent performance has been observed for all relevant subgroups including device manufacturers, slice thickness, patient sex and age, and comorbidities.
The accuracy of the aortic diameter measurements was validated in a representative retrospective clinical cohort (N=193, including 50% of the cases with dilated aorta and 9% of the cases with aortic aneurysm). The test data has been chosen to be representative for the intended population consists of a cohort of consecutive patients undergoing Chest CT exams for varying indications in addition to a cohort at increased risk for incidental findings particularly in the cardiovascular domain, due to the screening nature of the examination. The evaluation included Bland Altman analysis, in particular detailed analysis of error and bias of individual subgroups.
With respect to the diameter measurements at the nine predefined locations, the predicate device yielded a bias within ±1.8 mm (95%-CI: [1.5 mm. 2.1 mm]) and mean absolute error (MAE) to be ≤2.4 mm (95%-CI: [2.1 mm, 2.6 mm]). For the subject device the bias was within ±1.5 mm (95%-CI: [0.9 mm, 2.0 mm]) and MAE ≤2.2 mm (95%-CI: [1.8 mm, 2.6 mm]).
Wirth respect to the diameter measurements at the location of maximum ascending and maximum descending aorta, respectively, inter-reader variability was assessed, and 95%-limits of agreement (LoAs) were established at ±3.51 mm. 91.9% of the measurements provided by the subject device were found to lie within the LoA, with a bias within ±1.5 mm (95%-CI: [1.2 mm, 1.8 mm]) and MAE ≤1.8 mm (95%-CI: [1.44 mm, 2.23 mm]).
For all diameter measurements consistent performance has been observed for all relevant subgroups including device manufacturers, slice thickness, patient sex and age, and comorbidities. In summary, all performance criteria have been fulfilled and the validation demonstrated substantially equivalent performance to the predicate device.
Summary Performance data
AI-Rad Companion (Cardiovascular) was tested and found to be safe and effective for intended users, uses and use environments through the design control verification and validation process and clinical data-based software validation. The Human Factor Usability Validation showed that Human factors are addressed in the system test according to the operator's manual and in clinical use tests with customer report and feedback form. Customer employees are adequately trained in the use of this equipment.
10. Clinical Tests
No clinical tests were conducted to test the performance and functionality of the modifications introduced within AI-Rad Companion (Cardiovascular). Verification and validation of the enhancements and improvements have been performed and these modifications have been validated for their intended use. The data from these activities were used to support the subject device and the substantial equivalence argument.
No animal testing has been performed on the subject device.
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Safety and Effectiveness 11.
The device labeling contains instructions for use and any necessary cautions and warnings to ensure safe and effective use of the device.
Risk management is ensured via ISO 14971:2019 compliance to identify and provide mitigation of potential hazards in a product risk analysis early in the design phase and continuously throughout the development of the product. These risks are controlled via measures realized during software development, testing and product labeling.
Substantial Equivalence and Conclusion 12.
AI-Rad Companion (Cardiovascular) is substantially equivalent to the follow predicate device (Table 3).
Table 3 Predicate device for AI-Rad Companion (Cardiovascular)
| Predicate Device | FDA Clearance
Number | FDA Clearance
Date | Main Product Code |
|--------------------------------------|-------------------------|-----------------------|-------------------|
| AI-Rad Companion
(Cardiovascular) | K183268 | September 10, 2019 | JAK |
AI-Rad Companion (Cardiovascular) has the same intended use and technical characteristics compared to the predicate device, AI-Rad Companion (Cardiovascular) [K183268], with respect to the software features, functionalities and core algorithms. The enhancements and improvements provided in AI-Rad Companion (Cardiovascular) increase the clinical utility and reduce the complexity of the imaging workflow for the clinical user. The conclusions from all verification and validation data suggest that these enhancements are equivalent with respect to safety and effectiveness of the predicate device. These modifications do not change the intended use of the product. Siemens is of the opinion that AI-Rad Companion (Cardiovascular) is substantially equivalent to the currently marketed predicate device.