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Vitrea® CT Myocardial Perfusion is intended to assist a trained user for the visualization of hypo/hyper dense areas in patients with angina or with a previous myocardial infarction to assess the disease state and treatment. This software provides semi-automated heart and left ventricle segmentation and color polar maps of the myocardial tissue.

The information provided is intended to be qualitative in nature and, when used by a qualified physician, may aid in the identification of myocardial enhancement defects and the follow up of such findings.

Vitrea CT Myocardial Perfusion is a post-processing software option for the already cleared Vitrea software platform (K071331). It leverages the existing Vitrea platform functionalities such as Multi-Planar Reconstruction (MPR) images, Maximum Intensity Projections (MIP) and volume rendering.

Vitrea CT Myocardial Perfusion enables the visualization and analysis of perfusion defects in the myocardium. The software is intended for use with cardiac CT (Computed Tomography) studies to analyze cardiovascular anatomy and pathology and to assess the presence of hypo/hyper dense areas of myocardial tissue.

The software visualization tools provide semi-automated heart and Left Ventricle (LV) segmentation, and color overlay and polar maps of the myocardial tissue based on the Hounsfield attenuation (HU) values. The software displays the values associated with the generation of the Perfusion Index (PI) and Transmural Perfusion Ratio (TPR) maps. Perfusion Index (PI) is the ratio of the Mean Myocardial CT value to the LV blood pool CT value. Transmural Perfusion Ratio (TPR) is provided as a ratio per sector of the Endocardial CT value to the mean Epicardial CT value. The defect size scoring tool allows a user to delineate one or more contiguous 3D regions within the myocardium for independent size measurements. The user may observe the interpolated result as they are constructing the defect.

The software analysis tools include measurements and comparison ratios. The CT Myocardial Perfusion application allows users to load one or two volumes. In dual-volume cases, the volumes are displayed based on time. It also includes reporting tools for formatting findings and user selected areas of interest.

The provided text describes the Vitrea CT Myocardial Perfusion software, its intended use, a comparison to predicate devices, and the non-clinical tests performed for its 510(k) submission. However, it does not contain specific acceptance criteria or a study that directly proves the device meets those criteria with numerical performance metrics.

The document states that clinical studies were not required to support the safety and effectiveness of the software. Instead, it relies on design control measures, software verification and validation, and internal/external validation using phantoms and experienced users.

Therefore, providing a table of acceptance criteria and reported device performance, sample sizes for test sets, number of experts, adjudication methods, MRMC study results, standalone performance, type of ground truth, training set size, or how training set ground truth was established is not possible based on the provided text. This information is typically found in clinical study reports or detailed validation documentation, which is not present here.

Summary of available information regarding testing:

1. Table of acceptance criteria and reported device performance: Not explicitly stated with numerical performance. The document describes general quality assurance activities rather than specific performance metrics against pre-defined acceptance criteria.

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

   • Test Set Sample Size: "various phantoms and patient based CT datasets" were used for internal validation, and "experienced users" for external validation. No specific number of cases or patients is provided.
   • Data Provenance: Not specified.

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):

   • For external validation, "experienced users" evaluated the software. No specific number or qualifications are provided beyond "experienced users."

4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not mentioned.

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: No MRMC study was mentioned. The document explicitly states that "clinical studies to support safety and effectiveness of the software" were not required.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: The software aims to "assist a trained user," implying a human-in-the-loop application. No standalone algorithm performance is reported.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): For internal validation, numerical quantities were verified using "CT semi-synthetic phantoms and patient based CT datasets." For external validation, "experienced users evaluated" the software. This suggests a form of expert review or comparison to phantom-derived ground truth, but not pathology or outcomes data.

8. The sample size for the training set: Not applicable and not mentioned, as the documentation focuses on verification and validation of a software enhancement, not the development of a de novo AI algorithm that requires a separate training set. The existing Vitrea platform is leveraging cleared functionalities.

9. How the ground truth for the training set was established: Not applicable and not mentioned.

In conclusion, the document details the rigorous design control measures, software verification, and validation activities (including phantom testing and usability testing by experienced users) undertaken to ensure the software met its requirements and user needs. However, it does not present a formal study with quantitative acceptance criteria and corresponding performance data as might be found in a clinical trial or a performance validation study for a device with specific objective performance claims. The basis for clearance appears to be substantial equivalence to predicate devices and adherence to quality system regulations, rather than specific performance against numerical criteria.

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