Search Results

Ask a specific question about this device

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.

Ask a specific question about this device