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AI-Rad Companion Prostate MR is indicated for the processing and annotation of DICOM MR prostate images acquired in adult male populations that demonstrate indications of oncological abnormalities in the prostate.

The AI-Rad Companion Prostate MR software aims to support the radiologist and provides the following functionality:
• Viewing, analyzing, evaluating prostate MR images including DCE, ADC, T2 and DWI
• Hosting application for and provides interface to external Prostate MR AI plug-in device
• Accept/reject/edit the results generated by the plug-in software Prostate MR AI

AI-Rad Companion Prostate MR is a diagnostic aid in the interpretation of prostate MRI examinations acquired according to the PI-RADS standard.

AI-Rad Companion Prostate MR provides quantitative and qualitative information based on bi or multiparametric prostate MR DICOM images. It displays information on the segmented gland, prostate volume, and segmented lesions along with their classifications. This information can be used to support the reading and reporting of prostate MR studies, as well as the planning of prostate biopsies in the case of ultrasound guided MR-US fusion biopsies of the prostate gland.

The primary features of AI-Rad Companion Prostate MR include:
• Display of Automatic Segmentation and volume of the prostate gland as well as display of automatic segmentation, quantification and classification of lesions
• Manual Adjustment of gland and lesion segmentation and editing of lesion scores, diameter, and localization of the automated generated lesions
• Marking of new lesions
• Export of results as RTSS format for import into supporting ultrasound or fusion biopsy planning systems

Based on the provided FDA 510(k) clearance letter for AI-Rad Companion Prostate MR (K252608), there is no specific study described that proves the device meets predefined acceptance criteria for performance metrics (e.g., sensitivity, specificity, accuracy). The document primarily focuses on demonstrating substantial equivalence to a predicate device (AI-Rad Companion Prostate MR K193283) and adherence to non-clinical verification and validation standards for software development and risk management.

The document explicitly states: "No clinical tests were conducted to test the performance and functionality of the modifications introduced within AI-Rad Companion Prostate MR."

Therefore, a table of acceptance criteria and reported device performance, information about sample sizes, expert ground truth establishment, adjudication methods, multi-reader multi-case studies, standalone performance, and training set details are not available in this document as no clinical performance study for the modified device was performed.

The document emphasizes that modifications and improvements were verified and validated through non-clinical tests (software verification and validation, unit, system, and integration tests), which demonstrated conformity to industry standards and the predicate device's existing safety and effectiveness.

Here’s a breakdown of what is stated in the document regarding testing:

1. A table of acceptance criteria and the reported device performance:

• Not provided. The document does not include a table of specific clinical acceptance criteria (e.g., target sensitivity or specificity values) or reported device performance metrics against such criteria. The focus is on demonstrating that software enhancements do not adversely affect safety and effectiveness, assuming the predicate device's performance was already acceptable.

2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective):

• Not provided. Since no clinical performance study was conducted for this specific submission, details on test set sample sizes and data provenance are not presented.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g. radiologist with 10 years of experience):

• Not applicable. As no clinical study is reported, this information is not available.

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set:

• Not applicable.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

• Not done. The document explicitly states "No clinical tests were conducted."

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

• Not explicitly stated for the modified device. While the device description mentions automatic segmentation and classification, the overall context emphasizes a "diagnostic aid" that "aims to support the radiologist" and has functionality to "Accept/reject/edit the results generated by the plug-in software Prostate MR AI." This suggests an interactive workflow where standalone performance is not the primary claim for this particular submission. The separate product, "Prostate MR AI (K241770)," which performs the core AI tasks, is likely where standalone performance would be detailed, but not in this document.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

• Not applicable for this submission, as no new clinical performance study is detailed for the modified device. The original predicate device's performance would have relied on a ground truth, but that information is not part of this document.

8. The sample size for the training set:

• Not provided. Since this submission is for an updated version of an already cleared device and no new clinical performance study is detailed, the training set size for the underlying AI model (likely part of K241770 or the predicate K193283) is not included here.

9. How the ground truth for the training set was established:

• Not provided. This information would typically be detailed in the original submission for the AI algorithm (likely K241770 or K193283), not in this update focused on software enhancements and substantial equivalence.

In summary, the provided document focuses on demonstrating that the enhancements and modifications to the AI-Rad Companion Prostate MR do not adversely affect the safety and effectiveness of the existing predicate device. It relies on non-clinical software verification and validation, and substantial equivalence arguments, rather than presenting a de novo clinical performance study with new acceptance criteria and results.

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AI-Rad Companion Prostate MR is a post-processing image analysis software that assists clinicians in viewing, manipulating, analyzing and evaluating MR prostate images for US guided MR-US fusion biopsy support.

AI-Rad Companion Prostate MR aims to assist the radiologist in the preparation of MR prostate images for targeted biopsies of the prostate gland using MR-Ultrasound fusion biopsy. It allows the radiologist to communicate the location and spatial extent of lesions and the prostate volume in prostate MR images to a urologist in order to help perform biopsies.

AI-Rad Companion Prostate MR is a cloud-based image processing software that provides quantitative and qualitative information based on prostate MR DICOM images. More specifically, it provides information on the prostate volume which can be used to support the planning of prostate biopsies in the case of ultrasound guided MR-US fusion biopsies of the prostate gland. It is enabled via artificial intelligence algorithms and a cloud infrastructure.

The primary features of AI-Rad Companion Prostate MR include:

• Automatic prostate segmentation and volume estimation, with the possibility of manual adjustments
• Manual determination of location and size of lesions in a suitable user interface
• Calculation of the PSA density, based on the input of the PSA value of the patient by the clinical user
• Export in a suitable format for reading and archiving in PACS, as well as in a second format that can be imported by ultrasound systems (e.g. RTStruct), allowing the urologist to perform targeted MR-US fusion biopsy

The document provided refers to AI-Rad Companion Prostate MR and states that no clinical tests were conducted to test the performance and functionality of the modifications introduced within AI-Rad Companion Prostate MR (Page 8, Section 9. Clinical Tests). Therefore, the information requested regarding acceptance criteria and performance based on a clinical study cannot be fully provided from the given text.

However, based on the non-clinical tests and the comparison to the predicate device, here's what can be inferred and stated:

1. Table of acceptance criteria and the reported device performance

The document does not provide specific quantitative acceptance criteria or reported device performance metrics from a clinical study. It mentions non-clinical tests were conducted to assess performance claims and substantial equivalence. These tests included functionality, software validation, and bench testing (Unit, System, and Integration tests). All testable requirements in the Requirement Specifications and Risk Analysis were verified.

2. Sample size used for the test set and the data provenance

Since no clinical tests were conducted, details about a clinical test set are not available. For the non-clinical software "bench" testing, sample sizes for the test data are not explicitly stated in the provided text. The data provenance (e.g., country of origin, retrospective/prospective) for these internal tests is also not mentioned.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

The document does not mention the use of experts to establish ground truth for a clinical test set, as no clinical tests were performed. For internal software testing, the ground truth would typically be defined by design specifications and expected outputs.

4. Adjudication method for the test set

Not applicable, as no clinical test set requiring adjudication by experts is described.

5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done

No, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. The document explicitly states: "No clinical tests were conducted to test the performance and functionality of the modifications introduced within AI-Rad Companion Prostate MR." (Page 8, Section 9. Clinical Tests).

6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done

The document indicates that software "bench" testing was performed, which would be a form of standalone testing for the algorithm's functionality and performance against its requirements. However, specific results or detailed methodologies are not provided for "algorithm only" performance. The device's functionalities, such as "Automatic prostate segmentation and volume estimation," imply standalone algorithm components.

7. The type of ground truth used

For the non-clinical software testing, the ground truth would be based on the software's design specifications and expected outputs as defined by the developers (e.g., correct segmentation results against internal references, accurate volume calculations based on known inputs).

8. The sample size for the training set

The document does not mention the sample size for a training set. While the device utilizes "artificial intelligence algorithms" (Page 5), details about the training data used to develop these algorithms are not provided within this document.

9. How the ground truth for the training set was established

The document does not provide information on how the ground truth for any potential training set was established, as details about the AI algorithm's development and training are not included.

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