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IMPRA High Porosity Grafts are indicated for use as vascular prosthesis for bypass or reconstruction of peripheral arterial blood vessels.

The IMPRA High Porosity Graft is an expanded polytetrafluoroethylene (ePTFE) vascular graft with a high porosity construction.

This is a 510(k) premarket notification for a medical device (IMPRA High Porosity Graft), not an AI/ML device. Therefore, the requested information regarding acceptance criteria, study details, expert involvement, and ground truth for an AI device is not applicable and cannot be extracted from the provided text.

The document discusses the substantial equivalence of the new device to predicate devices based on performance data. The "performance data" section (Section G) is the most relevant to your request, but it does not contain the specific information you're asking for in the context of an AI/ML study.

Here's what can be extracted from the provided text about the device's performance and testing, but it fundamentally differs from AI/ML device evaluations:

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

The document states:
"Device testing was performed on the IMPRA High Porosity Graft and compared to the results of testing performed on the IMPRA ePTFE Vascular Graft. The testing was conducted using methods recommended in ANSI/AAMI VP20-1994: Cardiovascular Implants - Vascular Prostheses and the 1993 FDA Draft Guidance. Guidance for the Preparation of Research and Marketing Applications for Vascular Graft Prostheses. The results of all testing indicated that the IMPRA High Porosity Graft is suitable for use as vascular prostheses for bypass or reconstruction of arterial blood vessels and the anticipated conditions of use imposed on the device. The results demonstrated that the IMPRA High Porosity Graft has been adequately designed to perform in a manner substantially equivalent to that of the predicate devices."

Analysis for your table format:

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

• Sample size for test set: Not specified. The document only mentions "device testing was performed."
• Data provenance: Not specified. Standardized test methods (ANSI/AAMI VP20-1994, 1993 FDA Draft Guidance) imply laboratory/bench testing, not patient data in the typical sense of AI/ML studies.

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):

• This is not applicable as it's not an AI/ML device. The "ground truth" for this type of medical device is established by physical and mechanical engineering standards, biocompatibility testing, and functional performance in a laboratory setting, not expert medical opinion on interpretative data.

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

• Not applicable. The "adjudication" in this context refers to compliance with established testing protocols and material science, not a consensus among human reviewers.

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 applicable. This is not an AI/ML diagnostic or assistive device for human readers.

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

• Not applicable. This device is a physical vascular graft, not an algorithm.

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

• The "ground truth" for this device would be defined by engineering specifications, material science properties (e.g., porosity, tensile strength, burst pressure according to the referenced standards), and successful material performance under simulated physiological conditions as determined by the ANSI/AAMI and FDA guidance documents. It is not expert consensus, pathology, or outcomes data in the AI/ML sense.

8. The sample size for the training set:

• Not applicable. This is not an AI/ML device that requires training data.

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

• Not applicable. This is not an AI/ML device that requires training data or ground truth for algorithmic training.

In summary, the provided document describes a traditional medical device (vascular graft) evaluated for substantial equivalence based on physical and mechanical testing against recognized standards and predicate devices. It does not fit the paradigm of an AI/ML device assessment.

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