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Gentrix Surgical Matrix Thick and Gentrix Surgical Matrix Extend are intended for implantation to reinforce soft tissue where weakness exists in patients requiring gastroenterological or plastic & reconstructive surgery. Reinforcement of soft tissue within gastroenterological and plastic & reconstructive surgery includes, but is not limited to, the following procedures: hernia and body wall repair, colon and rectal prolapse repair, and esophageal repair.

The Gentrix™ Surgical Matrix Thick and Gentrix™ Surgical Matrix Extend devices are composed of porcine-derived extracellular matrix scaffolds, specifically known as urinary bladder matrix. The devices are supplied in an eight-layer sheet configuration in sizes up to 30 cm x 40 cm, and packaged in double peel-open pouches. The devices are terminally sterilized using electron beam irradiation. The implantable biomaterial is a resorbable extracellular matrix scaffold that will incorporate (remodel) into the body through cellular infiltration, capillary growth, and integration by the surrounding host tissue. Animal studies have shown device resorption in approximately 240 days.

This document is a 510(k) premarket notification for a medical device called Gentrix™ Surgical Matrix Thick and Gentrix™ Surgical Matrix Extend. This device is a surgical mesh made from porcine urinary bladder matrix, intended for reinforcing soft tissue in various surgical procedures.

The information provided focuses on demonstrating "substantial equivalence" to a previously cleared predicate device (Gentrix™ Surgical Matrix 8-Layer, K162554), rather than establishing novel acceptance criteria against a clinical outcome or a new performance standard. Therefore, the concept of "acceptance criteria" in the context of an AI/ML device's performance metrics (like sensitivity, specificity, etc.) is not directly applicable here. The "reported device performance" is primarily comparative to the predicate device.

However, I can extract the types of tests performed and the general findings which serve as proof of substantial equivalence.

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

Since this is a substantial equivalence submission for a traditional medical device (surgical mesh) and not an AI/ML device, the "acceptance criteria" are not reported as specific performance metrics (like sensitivity, specificity, or AUC with threshold values). Instead, the acceptance criteria are implicitly that the new devices perform equivalently to the predicate device across various tests.

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

• Bench Testing (Biocompatibility, Mechanical, Material Characterization): Not specified in terms of sample size or data provenance. These are typically in-house laboratory tests on material samples.
• Animal Testing: A "pre-clinical porcine model" was used. The number of animals or specific details of the study are not provided. Data provenance is implied to be from a laboratory setting.
• Clinical Data: "No Clinical data was provided in support of this clearance." This implies a sample size of zero for human clinical trials.

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)

Not applicable. This submission does not involve ground truth established by experts for performance evaluation in the way an AI/ML device would. The evaluation is based on laboratory and animal tests against established scientific and engineering principles for surgical mesh materials.

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

Not applicable. There is no adjudication method described as this is not an AI/ML device or a study involving human readers/interpreters.

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 device.

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

Not applicable. This is not an AI/ML device.

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

The "ground truth" for this device's performance is based on:

• Established scientific standards for biocompatibility (e.g., ISO-10993).
• Direct measurement of physical properties (tensile strength, tear strength, stiffness, etc.) of the device material.
• Biological observations in an animal model (tissue integration, remodeling, degradation).
• Comparison to the known and accepted performance characteristics of the predicate device.

8. The sample size for the training set

Not applicable. This is not an AI/ML device, so there is no training set.

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

Not applicable. This is not an AI/ML device.

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