Search Results

MRA-CMS has been developed for the objective and reproducible analysis of vessels from MRA data sets. The MRA software parameters may be used to semi-automatically determine lumen length, cross sectional parameters and percent stenosis. When interpreted by a trained physician these parameters may be useful in supporting the determination of clinical diagnoses and subsequent clinical decision making processes.

MRA-CMS can be utilized to determine lumen lengths; minimum and maximum cross sectional diameters and percent stenosis. MRA-CMS improves productivity of the clinician by semi-automating the measurement function for routine vascular measurements.

The provided text is a 510(k) summary for the MRA-CMS device. It does not contain the detailed study results, acceptance criteria, or performance data required to complete the requested table and answer many of the questions.

The submission focuses on establishing substantial equivalence to a predicate device (Vital Images, K002519 "Vitrae 2, version 2.1") and discusses general safety and effectiveness without presenting specific quantitative performance metrics beyond the device's capability to measure lumen lengths, cross-sectional diameters, and percent stenosis.

Therefore, I can only provide information based on what is available in the text. Many sections will indicate "Not provided in the text."

Here's the breakdown of the information that can be extracted:

Acceptance Criteria and Device Performance

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

• Sample size for the test set: Not provided in the text.
• Data provenance (e.g., country of origin of the data, retrospective or prospective): Not provided in the text. The document mentions "Evaluations by hospitals and literature (See Appendix F)" but does not detail the nature or source of these evaluations.

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

• Number of experts: Not provided in the text.
• Qualifications of experts: Not provided in the text.

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

• Adjudication method: Not provided in the text.

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

• MRMC study: Not provided in the text. The document refers to the device as "semi-automating the measurement function" and that the "regions-of-interest will be interpreted by the operator, who can choose to accept or reject the outlines, and then decide to use the derived data." This implies a human-in-the-loop workflow, but no comparative effectiveness study results are presented.
• Effect size: Not provided in the text.

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

• Standalone study: Not explicitly stated. The description of MRA-CMS as "semi-automating the measurement function" and requiring operator interpretation and acceptance/rejection of outlines suggests it's not purely a standalone device in its intended clinical use. No standalone performance study metrics are provided.

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

• Type of ground truth: Not provided in the text.

8. The sample size for the training set

• Sample size for the training set: Not provided in the text.

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

• Ground truth establishment for training set: Not provided in the text.

Ask a specific question about this device