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DynaMesh®-CICAT serves to support the tissue and stabilize the fascial structures of the abdominal wall. DynaMesh®-CICAT is indicated for repairing incisional hernias in all current extraperitoneal surgical techniques.

The FEG Textiltechnik Forschungs- und Entwicklungsgesellschaft mbH DynaMesh®-CICAT is a textile structure knitted from non absorbable, bio□ stable Polyvinylidene fluoride (PVDF) monofilament fiber. Polyvinylidene Fluoride (PVDF) has been used for approximately 20 years for long-term implants in cardiac and vascular surgery because of its biocompatibility and durability. PVDF is a high performance polymer material with very high material purity. The grade of Polyvinylidene Fluoride (PVDF) used is SOLEF®1008 of Solvay Solexis. The knitted mesh structure consists of uncoloured PVDF Monofilaments with a pattern of zig-zag marking stripes as visual aid to the clinician facilitating correct mesh positioning; the mesh is correctly positioned when the zig-zag stripes are in the craniocaudal direction. DynaMesh®-CICAT is supplied as a sterile, flat sheet of material without any coatings or additives. The FEG Textiltechnik's DynaMesh®-CICAT will be packed in a cardboard box. Within the cardboard box the device will be double-packed in two paper-poly pouches suitable for Ethylene Oxide sterilization; the labeled outer pouch contains the inner pouch and four adhesive labels for use on patient records.

The provided document is a 510(k) summary for the DynaMesh®-CICAT surgical mesh. It describes the device, its intended use, and its substantial equivalence to predicate devices based on non-clinical (bench) testing.

Here's an analysis of the acceptance criteria and study that proves the device meets them, based only on the provided text:

1. Table of acceptance criteria and the reported device performance

The document does not explicitly state quantitative acceptance criteria with numerical targets. Instead, it states that various bench tests were conducted "to demonstrate performance to an accepted norm and/or substantial equivalence to the predicate products." This implies the acceptance criteria were based on meeting established norms for surgical meshes or demonstrating performance comparable to the predicate devices.

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

The document does not specify the sample sizes used for each of the listed bench tests. It only states that "Various Laboratory Bench Tests have been conducted." The data provenance is from "FEG Textiltechnik Forschungs- und Entwicklungsgesellschaft mbH" in Germany, and the tests are described as non-clinical (bench tests), implying they were conducted in a laboratory setting. There is no indication of retrospective or prospective human data.

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

This information is not applicable to the provided document. The "ground truth" here refers to the physical properties of the mesh determined through engineering/mechanical testing, not human-interpreted data. Therefore, there's no mention of experts or their qualifications for establishing ground truth in this context.

4. Adjudication method for the test set

This information is not applicable. Adjudication methods are typically used when human interpretation of data (e.g., medical images) is involved and discrepancies need to be resolved. For mechanical bench tests, the measurements are generally objective and standardized.

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 such study was performed or mentioned. This document describes a surgical mesh, not an AI-powered diagnostic device.

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

No such study was performed or mentioned. This information pertains to AI algorithms, which are not relevant to this medical device.

7. The type of ground truth used

The ground truth used for the device evaluation was engineering/mechanical measurement data obtained from laboratory bench tests. These tests directly measure physical properties like burst strength, tensile strength, tear resistance, suture pullout strength, tri-elasticity, and porosity.

8. The sample size for the training set

This information is not applicable as there is no machine learning or AI algorithm involved that would require a training set. The device is a physical surgical mesh.

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

Not applicable, as there is no training set for an AI algorithm.

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