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Endoform™ Reconstructive Template – PLGA is intended for use as a surgical mesh to reinforce and/or repair soft tissue where weakness exists. Indications for use include the repair of hernias and/or abdominal wall defects that require the use of reinforcing material to obtain the desired surgical outcome.

Endoform™ Reconstructive Template – PLGA is a surgical mesh comprised of multiple layers of ovine-derived extracellular matrix reinforced with poly(lactic-co-Glycolic) acid (PLGA). The device design includes a range of shapes, sizes, and thicknesses in surface areas up to 400cm², to give a range of strengths as required for a particular implant procedure. Devices are terminally sterilized by ethylene oxide (EO) sterilization.

This FDA 510(k) clearance letter and supporting summary for the Endoform™ Reconstructive Template – PLGA device does not involve artificial intelligence (AI) or machine learning (ML). Therefore, many of the requested elements for AI/ML device validation are not applicable.

The device is a traditional medical device (surgical mesh) and its substantial equivalence is demonstrated through non-clinical performance data and comparison to a predicate device. There is no mention of an algorithm, AI assistance, or human readers.

However, I can extract the information relevant to its acceptance criteria and the study that proves it meets those criteria, based on the provided document.

Acceptance Criteria and Study Proof for Endoform™ Reconstructive Template – PLGA

Since this is a traditional medical device (surgical mesh) and not an AI/ML device, the concept of "acceptance criteria" is related to meeting performance specifications and demonstrating biocompatibility and safety comparable to a predicate device, rather than diagnostic accuracy metrics. The "study" refers to non-clinical testing.

Here's a breakdown based on the provided document:

1. Table of Acceptance Criteria and Reported Device Performance

The document describes the types of tests conducted and the conclusion that the device meets specifications, rather than providing specific numerical acceptance criteria and results in a table format common for AI/ML.

For this device, the "acceptance criteria" are implied by the performance characteristics demonstrated to be "substantially equivalent" to the predicate device and meeting recognized standards.

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Endoform Reconstructive Template – Non-Absorbable is intended for use as a surgical mesh to reinforce and/or repair soft tissue where weakness exists.

Endoform Reconstructive Template – Non-Absorbable is indicated for use in the repair of hernias and/or abdominal wall defects that require the use of reinforcing or bridging material to obtain the desired surgical outcome.

Endoform Reconstructive Template - Non-Absorbable is a surgical mesh manufactured by layering sheets of ovine forestomach matrix to create multi-layer configurations of devices laminated with non-resorbable polypropylene (PP) suture material in a variety of sizes for use in soft tissue reconstruction. Devices up to 400 cm² are available in thicknesses from 1- through 10- ply, and larger devices up to 1000cm2 are available in 4-, 6-, and 8-ply presentations.

This document describes the Endoform Reconstructive Template - Non-Absorbable, a surgical mesh. The submission (K181935) is a 510(k) premarket notification for a line extension to increase the maximum device size.

Here's the information about the acceptance criteria and the study that proves the device meets them, based on the provided text:

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

The document states that the performance specifications for the device have not changed and that the device meets these specifications. The specific quantitative values of these specifications are not provided in this summary.

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

• Sample size for test set: Not explicitly stated. The document refers to "Bench testing and validation" and "results of verification and validation testing" without providing specific sample numbers for each test.
• Data provenance: Not explicitly stated, but the company is Aroa Biosurgery Ltd. located in New Zealand. These would be non-clinical, laboratory-based tests.

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 device is a surgical mesh, and the testing described is non-clinical (bench testing) for physical properties, not a clinical study involving radiologists or medical image interpretation.

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

Not applicable. Adjudication methods are typically for clinical studies involving multiple reviewers/experts, which is not the case here.

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/software device, and no MRMC study was conducted.

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

Not applicable. This is a physical medical device (surgical mesh), not an algorithm.

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

For the non-clinical performance data, the "ground truth" would be established by:

• Engineering specifications and standards for mechanical strength and dimensional properties.
• Validated laboratory assays for endotoxin levels and biocompatibility (as carried over from the predicate device).

8. The sample size for the training set

Not applicable. There is no concept of a "training set" for this type of physical device testing.

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

Not applicable. There is no training set.

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Endoform® Reconstructive Template is intended for use as a surgical mesh to reinforce and/ or repair soft tissue where weakness exists. Indications for use include the repair of hernias and/or abdominal wall defects that require the use of reinforcing or bridging material to obtain the desired surgical outcome.

Endoform Reconstructive Template - Non-Absorbable is a surgical mesh manufactured by layering sheets of ovine forestomach matrix (OFM) to create 1- through 10- ply embroidered devices for soft tissue reconstruction. The device design includes thicknesses from 1- through 10- ply to give a range of strengths as required for a particular implant procedure. The construction of Endoform™ Reconstructive Template - Non-Absorbable devices includes lyophilization of single sheets of OFM followed by embroidery with polypropylene. Devices are terminally sterilized by ethylene oxide (EO) sterilization.

This document is an FDA 510(k) premarket notification decision letter for a surgical mesh device, Endoform® Reconstructive Template - Non-Absorbable. It does not describe an AI medical device or a study involving AI. Therefore, it is impossible to answer the questions about acceptance criteria and study proving an AI device meets those criteria based on the provided text.

The document discusses the substantial equivalence of the surgical mesh to a predicate device based on:

• Biocompatibility Data: Additional cytotoxicity testing, toxicological assessment, and viral inactivation assessment were performed.
• Performance Data: Biomechanical testing (uniaxial tensile strength, ball burst strength, suture retention strength) and an in-vivo study in a soft tissue reinforcement model.
• Clinical Data: No clinical data was submitted.

The provided text pertains to a physical medical device (surgical mesh) and its substantial equivalence determination, not an AI/ML medical device. Therefore, the questions about acceptance criteria for an AI device, sample sizes for AI test/training sets, experts for ground truth, adjudication methods, MRMC studies, standalone performance, and ground truth establishment for AI models are not applicable to the content of this document.

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Endoform Reconstructive Template is intended for usc as a surgical mesh to reinforce and/or repair soft tissue where weakness exists. Indications for use include the repair of hernias and/or abdominal wall defects that require the use of reinforcing or bridging material to obtain the desired surgical outcome.

The Aroa Endoform Reconstructive Template ("ERT") is a surgical mesh manufactured by layering sheets of ovine forestomach matrix (OFM) to create 1- through 10- ply embroidered devices for implant applications as part of soft tissue reconstruction. The device design includes a range of thicknesses from 1- through 10- ply to give a range of strengths as required for a particular implant procedure. The construction of ERT devices includes lyophilization of single sheets of OFM followed by embroidery with polyglycolic acid (PGA). Devices are terminally sterilized by ethylene oxide (EO) sterilization. The device has received FDA clearance (K130547) for sizes up to 200cm2.

This document is a 510(k) premarket notification for a medical device called the "Endoform® Reconstructive Template" (ERT), which is a surgical mesh. The purpose of this notification is to declare that a modified version of the ERT is substantially equivalent to a previously cleared predicate device. The only change proposed is an increase in the maximum device size.

Here's an analysis of the acceptance criteria and study information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance

2. Sample Size Used for the Test Set and Data Provenance

The document does not explicitly state specific numerical sample sizes for each test set (e.g., how many devices were tested for mechanical strength, endotoxin, etc.). It only broadly refers to "bench testing and validation testing."

• Test Set Sample Size: Not explicitly stated (e.g., number of units tested per bench test).
• Data Provenance: The studies were conducted by Aroa Biosurgery, Limited, which is based in New Zealand. The studies appear to be prospective for the modified device based on the phrase "Performance and validation testing executed based on risk analysis of the proposed change supports the substantial equivalence..."

3. Number of Experts Used to Establish Ground Truth for the Test Set and Qualifications

This information is not applicable in this context. The "acceptance criteria" here refer to engineering and manufacturing specifications (e.g., mechanical strength, sterility, dimensions) for a physical medical device. Ground truth, in the context of expert consensus, is typically relevant for diagnostic devices or those requiring human interpretation of results. For this surgical mesh, the "ground truth" is defined by the established engineering standards and specifications.

4. Adjudication Method for the Test Set

This information is not applicable. Adjudication methods (like 2+1, 3+1) are used to resolve disagreements among multiple human readers or experts when establishing a ground truth, often for image interpretation or clinical diagnosis. Since the "acceptance criteria" for this device are based on objective physical and chemical measurements (bench testing, sterility), there is no human interpretation or adjudication involved in meeting these criteria.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

No, a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not done. The document explicitly states: "No clinical data was submitted to support the safety and effectiveness of the modified Endoform Reconstructive Template." MRMC studies inherently involve human readers and clinical outcomes.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

This question is not applicable. A "standalone" performance typically refers to the performance of an algorithm or AI system without human intervention. The Endoform Reconstructive Template is a physical surgical mesh, not an algorithm or AI-powered device.

7. The Type of Ground Truth Used

The "ground truth" (or basis for acceptance) for this device's performance is based on established product specifications, engineering standards, and regulatory requirements. This includes:

• Pre-defined mechanical strength targets.
• Specified endotoxin limits.
• Dimensional tolerances.
• Sterility Assurance Level (SAL) of 10⁻⁶.
• Biocompatibility as demonstrated by the predicate device.

8. The Sample Size for the Training Set

This information is not applicable. The concept of a "training set" is relevant for machine learning or AI models. The Endoform Reconstructive Template is a physical medical device. Its development and testing involve manufacturing processes, material science, and engineering validation, not an AI training paradigm.

9. How the Ground Truth for the Training Set Was Established

This information is not applicable for the same reasons as point 8. There is no "training set" in the context of this device's development.

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Endoform™ Reconstructive Template is intended for use as a surgical mesh to reinforce and/or repair soft tissue where weakness exists. Indications for use include, but are not limited to the following procedures; hernioplasty and repair of body wall defects. The device allows reinforcement or bridging of a deficit to obtain the desired surgical outcome. Endoform™ Reconstructive Template is intended for single use only.

The Mesynthes Endoform™ Reconstructive Template (ERT) is a surgical mesh comprising either a single layer of decellularized extracellular matrix (ECM) or alternatively, multiple layers (2- to 10- layers) of ECM bonded together by dehydrothermal lamination and polyglycolic acid (PGA) suture material.

The provided text describes a 510(k) premarket notification for the Mesynthes Endoform™ Reconstructive Template surgical mesh. This type of submission relies on demonstrating substantial equivalence to a legally marketed predicate device, rather than explicit acceptance criteria and performance against those criteria in the way a novel device might.

Therefore, the information you're requesting regarding "acceptance criteria" and "study that proves the device meets the acceptance criteria" in terms of specific performance metrics, sample sizes for test sets, expert ground truth, adjudication methods, MRMC studies, or standalone algorithm performance does not apply directly to this 510(k) summary.

Instead, the submission focuses on demonstrating that the new device has "technological characteristics and substantial equivalence" to existing predicate devices.

Here's an breakdown based on the information provided, keeping in mind the nature of a 510(k) submission:

1. Table of Acceptance Criteria and Reported Device Performance

As this is a 510(k) submission based on substantial equivalence, there are no explicit "acceptance criteria" in the format of defined metrics and targets for clinical performance that the device directly "meets." Instead, the acceptance is based on demonstrating similarity to predicate devices through a series of non-clinical performance tests and animal testing.

The "performance" described is about demonstrating similarity or equivalence to predicates, rather than achieving specific quantitative clinical thresholds.

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

The document does not specify the exact sample sizes for the individual biophysical, biocompatibility, or animal tests. It only states that these tests were "performed on finished, terminally sterilized product" and in "a model of soft tissue reinforcement" for animal studies. The data provenance is implied to be from internal lab testing by Mesynthes Ltd.

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/not provided in the context of this 510(k) submission. "Ground truth" established by experts is typically relevant for studies validating diagnostic algorithms or clinical evaluations, which were not conducted here as per Section 9.

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

This information is not applicable/not provided. Adjudication methods are typically relevant for clinical studies involving human interpretation or subjective assessments, which were not part of this 510(k) submission.

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

A multi-reader multi-case (MRMC) comparative effectiveness study was not done. This type of study focuses on the impact of a device on human performance, often in diagnostic imaging, which is not relevant for a surgical mesh device.

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

This concept is not applicable to a surgical mesh device. Standalone performance refers to the accuracy of an automated system without human intervention, typically in AI/diagnostic applications.

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

For the non-clinical and animal studies, "ground truth" implicitly refers to the established scientific and engineering standards for measuring device properties (e.g., strength, biocompatibility), and histopathological or physiological assessment in animal models for tissue integration and inflammatory response. These are not typically established via expert consensus in the same way as clinical diagnostic accuracy.

8. The sample size for the training set

This information is not applicable/not provided. "Training set" is a concept related to machine learning and AI development, which is outside the scope of this medical device submission.

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

This information is not applicable/not provided for the same reasons as point 8.

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