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The proposed Surgical Fabrics are implants which are intended to reinforce soft tissue where weakness exists for the urological, gynecological and gastroenterological anatomy inclusive but not limited to the following procedures: pubourethral support, urethral and vaginal prolapse repair. colon and rectal prolapse repair. reconstruction of the pelvic floor, bladder support, and sacro- colposuspension.

The Surgical Fabrics are woven or knitted from polymer fibers, and precut into patches for soft tissue reinforcement in surgical repair procedures.

This document (K963226) describes a 510(k) premarket notification for "Surgical Fabrics" by Boston Scientific Corporation, submitted in 1996. This submission is for a medical device that predates the widespread use of AI in medical imaging and diagnostics. As such, the provided text does not contain information about acceptance criteria or studies related to AI performance, digital image analysis, or ground truth establishment in a way that aligns with the questions posed.

The document discusses the substantial equivalence of the proposed surgical fabrics to existing predicate devices based on product testing related to their physical performance characteristics for soft tissue reinforcement.

Therefore, an answer based on the provided input for questions 1-9 would be:

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

• The document refers to product testing comparing the proposed devices to predicate devices, stating: "The results indicate that the proposed devices are Substantially Equivalent to the predicate devices in terms of performance characteristics tested."
• However, specific acceptance criteria (e.g., tensile strength thresholds, biocompatibility metrics) and the detailed reported performance values are not provided in this summary. The summary only asserts substantial equivalence based on these tests.

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

• This information is not provided in the summary. The type of "product testing" mentioned would typically involve material science and mechanical testing, not clinical studies with "test sets" in the context of AI.

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 concept is not applicable to the device described. "Ground truth" in the context of expert consensus is relevant for diagnostic or AI-assisted devices interpreting imagery or data. This device is a surgical implant (fabric).

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

• This concept is not applicable to the device described.

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

• This concept is not applicable to the device described. This device is a surgical fabric, not an AI or imaging diagnostic tool.

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

• This concept is not applicable to the device described.

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

• This concept is not applicable in the AI sense. For a surgical fabric, "ground truth" would relate to its physical properties meeting historical standards or established safety benchmarks, not expert interpretation of data.

8. The sample size for the training set

• This concept is not applicable to the device described. There is no AI model or "training set" mentioned or implied.

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

• This concept is not applicable to the device described.

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