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The T-Line® Hernia Mesh is indicated for the reinforcement of soft tissue where weakness exists for the repair of ventral hernias performed via an open onlay or sublay approach in adults (greater than 21 years of age).

The T-Line® Hernia Mesh is manufactured by knitting and heat pressing standard medical grade polypropylene monofilament yarn using wellestablished standard processes that are used to manufacture other commercially available hernia meshes. Mesh extensions are used to apply the device to the abdominal wall. The extensions of the T-Line® Hernia Meshare incorporated directly into the mesh body. The mesh design incorporatescontinuous, uninterrupted, seamless extensions from the mesh body to facilitate mesh securement to tissue. After knitting, needles are swaged onto the ends of the extensions to allow the extensions to be sewn into the abdominal fascia by surgeons akin to how sutures are sewn into fascia.

The provided text describes a 510(k) premarket notification for the T-Line Hernia Mesh and does not include information about an AI/ML powered medical device. Therefore, I cannot answer the questions about acceptance criteria, study details, expert qualifications, or comparative effectiveness as these are not relevant to the provided content.

The document discusses the substantial equivalence of the T-Line Hernia Mesh to a predicate device, focusing on an expansion in its Indications for Use to include an open sublay approach. It details performance testing conducted on an animal model to support this expanded indication for use.

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T-LINE™ HERNIA MESH is indicated for the reinforcement of soft tissue where weakness exists for the repair of ventral hernias performed via an open onlay approach.

The T-Line Hernia Mesh is manufactured by knitting and heat pressing standard medical grade polypropylene monofilament yarn using wellestablished standard processes that are used to manufacture other commercially available hernia meshes. Mesh extensions are used to apply the device to the abdominal wall. The extensions of the T-Line Hernia Mesh are incorporated directly into the mesh body. The mesh design incorporates continuous, uninterrupted, seamless extensions from the mesh body to facilitate mesh securement to tissue. After knitting, needles are swaqed onto the ends of the extensions to allow the extensions to be sewn into the abdominal fascia by surgeons akin to how sutures are sewn into fascia.

This is an FDA 510(k) summary for the T-Line Hernia Mesh, which is a medical device. As such, the concept of "acceptance criteria" and "study that proves the device meets the acceptance criteria" in the context of an AI/ML device focusing on metrics like sensitivity, specificity, AUC, and expert adjudication, does not directly apply here. This document describes the equivalence of a conventional medical device (surgical mesh) to a predicate device, based on material properties, design, and biological response in animal models, not on AI/ML performance.

However, I can interpret your request in the context of device performance and safety acceptance for this type of medical device, and extract the relevant information provided:

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

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

• Sample Size: The document states "All animals" were evaluated, referring to the porcine model. A specific number of animals is not provided.
• Data Provenance: In vivo testing performed in a "simulated use porcine model." The country of origin is not specified but it's an animal model, not human data. This was a prospective study to evaluate the device in an animal model.

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

• This information is not explicitly provided. Histological evaluations and scoring would typically be performed by trained pathologists or veterinary surgeons, but the number or specific qualifications are absent.

4. Adjudication method for the test set:

• Not applicable/Not specified for this type of device and study. The evaluation likely involved comparative histological assessment and observation, not a human consensus process for classification.

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. This is not an AI/ML device. Therefore, an MRMC study comparing human readers with and without AI assistance was not conducted.

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

• No. This is not an AI/ML device.

7. The type of ground truth used:

• The "ground truth" for the performance evaluation in this context was established through histological evaluations (inflammation, bioincorporation, fibrosis, cellular populations), gross findings (in a simulated use porcine model), and clinical observations (body weights, clinical pathology parameters) over a 6-month post-operative period, compared against a 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" in that sense. The device design was informed by "design inputs; including procedural characteristics and requirements, clinical input from physicians, review of predicate device characteristics and labeling, user interface considerations, relevant external standards, and outputs from the company's risk management process."

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

• Not applicable. As noted above, there isn't a "training set" for an AI/ML model. The design and specifications were derived from various inputs, including existing predicate device characteristics, clinical needs, and risk management rather than a labeled dataset in the AI sense.

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REXLENE is indicated for use in general soft tissue approximation and/or ligation, including use in ophthalmic procedures, but not for use in cardiovascular or neural tissue.

REXLENE is a sterilized nonabsorbable monofilament surgical suture made out of polypropylene used in general soft tissue approximation and/or ligation with or without needle made out of Stainless Steel STS 304.

REXLENE suture is a nonabsorbable, sterile surgical monofilament suture composed of polypropylene. REXLENE sutures are not coated. The sutures are dyed blue to enhance visibility in tissue.

REXLENE suture meets all requirements established by the United States Pharmacopoeia (U.S.P.) for nonabsorbable surgical suture. Available suture size is as below. - Dyed suture blue ([Phthalocyaninato (2-)] Copper): USP 8-0 ~ USP 1

The provided text is a 510(k) Premarket Notification from the FDA for a surgical suture device named REXLENE. It does not contain information about acceptance criteria for a device's performance, nor does it describe a study proving a device meets such criteria in terms of AI or software performance metrics.

Instead, the document focuses on demonstrating that the REXLENE suture is "substantially equivalent" to already legally marketed predicate devices, primarily WG-Surgical Sutures with Needle (K080684) and PROLENE™ Polypropylene Nonabsorbable Suture (K133356). The "acceptance criteria" referred to in this document are compliance with established regulatory standards for surgical sutures.

Here's a breakdown of the information that is available, reframed to address your request as much as possible, and highlighting what is not present:

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

The document outlines compliance with specific USP (United States Pharmacopoeia) and ISO standards for surgical sutures as the "acceptance criteria" for the REXLENE device, and states that the device meets these.

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 document. The document mentions "Non clinical tests were conducted," but does not detail the sample sizes for these tests, or the specific provenance of any data beyond the manufacturer being in Korea.

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 information is not applicable and not provided. The device is a surgical suture, not a diagnostic imaging device or AI-driven system that would require expert consensus for ground truth establishment. The "ground truth" here is compliance with scientific and regulatory standards as measured through laboratory testing.

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

This information is not applicable and not provided. Adjudication methods like 2+1 or 3+1 are typically used in clinical studies or expert reviews to resolve discrepancies in diagnoses or assessments, particularly for AI/CAD devices. This document deals with laboratory testing against physical and biological standards.

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 information is not applicable and not provided. REXLENE is a surgical suture, not an AI or CAD (Computer-Aided Detection) system. MRMC studies are used to evaluate the performance of diagnostic tools (often involving AI) with human readers.

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

This information is not applicable and not provided. REXLENE is a physical medical device (suture), not an algorithm or software.

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

For the non-clinical tests, the "ground truth" is defined by the specifications and requirements set forth in the US Pharmacopoeia (USP) and ISO 10993 standards. For example, the device must meet specific diameter ranges as defined in USP .

8. The sample size for the training set

This information is not applicable and not provided. Training sets are relevant for AI/machine learning models, which this device is not.

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

This information is not applicable and not provided for the same reason as point 8.

In summary, the provided document is a regulatory submission for a surgical suture and outlines its compliance with established physical and biological standards. It does not describe an AI or software device and therefore lacks the information requested regarding AI acceptance criteria, study design, expert involvement, or data sets for AI development.

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