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Endoform Dental Membrane is specifically intended for use in extraction sockets and soft tissue grafting. The device contains and prevents migration of guided bone regeneration graft material and prevents loss of alveolar height and ridge following tooth extraction. The device is provided sterile and intended for one-time use.

Endoform Dental Membrane is an ovine derived bioabsorbable extracellular matrix intended for application in dental and periodontal procedures. The device is composed of non-cross linked and non-reconstituted collagen. The device is supplied sterile in a variety of sizes and thicknesses which may be trimmed by a licensed dentist or oral surgeon to meet individual patient needs.

The provided text describes the non-clinical testing performed on the Endoform Dental Membrane to demonstrate its safety and performance. However, it does not include information about acceptance criteria for all the tests, nor does it detail a study that defines "device performance" in terms of clinical or comparative effectiveness against specific criteria in the way you've outlined.

Based on the available text, here's a breakdown of the information that is present, and what is not:

1. Table of Acceptance Criteria and Reported Device Performance

Note: The document details numerous non-clinical tests. For many, it states that the device "met the pre-defined specification" or "meets the specification," but it often does not explicitly list the numerical acceptance criteria in this summary. The table below compiles the criteria where they are explicitly mentioned.

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

The document describes several non-clinical tests but does not explicitly state the specific numerical sample sizes for each test set. It mentions "All EDM devices" or "all samples" in some contexts.

For the Animal Performance Testing:

• Sample Size (Test Set): Not explicitly stated how many animals were used, but it was an ovine (sheep) defect model study using "selected timepoints (week 4, 8 and 16)".
• Data Provenance: Prospective animal study conducted in an ovine (sheep) defect model. The country of origin is not specified, but the applicant's address is New Zealand.

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

This information is not provided in the document. The non-clinical tests described rely on validated laboratory methods and specifications, which are based on scientific standards rather than expert consensus on a test set in the way clinical diagnostic devices might.

For the animal study, the assessment criteria (resorption, cellular infiltration, inflammatory response, retention of bone grafting material, hard tissue infill) would likely be evaluated by veterinarians or pathologists, but the number and qualifications of these experts are not mentioned.

4. Adjudication Method for the Test Set

This information is not provided as the document focuses on laboratory and animal study results rather than human-read test sets.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

No. A MRMC comparative effectiveness study was not performed or described. The document explicitly states: "Clinical data was not required to demonstrate substantial equivalence."

6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study

Not applicable. This device is a bioabsorbable extracellular matrix (Endoform Dental Membrane), not an AI algorithm. Therefore, "standalone algorithm" performance is not relevant.

7. Type of Ground Truth Used

The "ground truth" for the various tests conducted for the Endoform Dental Membrane is based on:

• Validated Test Methods: For biochemical content (collagen, GAG, DNA), physical properties (moisture, DSC, permeability, suture retention, modulus, thickness), residual substances (Tx-100, EDTA, PAA), bioburden, endotoxin, and shelf-life. These are quantitative measurements against predefined specifications.
• Standards Compliance: For biocompatibility (ISO 10993 series), sterilization (ISO 11135), and packaging (ASTM standards).
• Histopathological and Macroscopic Assessment: For the animal performance study, evaluating resorption, cellular infiltration, inflammatory response, and bone graft retention based on examinations at specific time points. This likely involves expert evaluation of tissue samples, but it's not "expert consensus" on a diagnostic task, rather assessment of biological outcomes compared to a reference device.
• "Critically sized" defects: The animal study also demonstrated that untreated controls did not completely regenerate bone, indicating the defects were appropriately sized for evaluating the device's performance.

8. Sample Size for the Training Set

Not applicable. This device is a physical medical device, not an AI algorithm. Therefore, there is no "training set."

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

Not applicable. As above, there is no training set for this type of device.

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Endoform Restella is for implantation to reinforce soft tissue where weakness exists in patients requiring soft tissue repair or reinforcement in plastic and reconstructive surgery. The device is supplied sterile and is intended for one-time use.

Endoform Restella is a surgical mesh manufactured by layering sheets of ovine forestomach matrix to create multi-layer configurations of devices laminated with absorbable polyglycolic acid (PGA) and non-absorbable polypropylene (PP) suture material for use in plastic and reconstructive surgery. The 3-ply devices are available in sizes up to 400 cm² in arced rectangle, contour, and oval shapes.

The provided text is a 510(k) summary for the medical device "Endoform Restella." This document describes the device, its intended use, and how it demonstrates substantial equivalence to a predicate device for FDA clearance.

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

1. Table of Acceptance Criteria and Reported Device Performance

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

The document does not specify the exact sample sizes (e.g., number of devices, number of tests performed) for the bench testing.
The data provenance is from non-clinical bench testing. The text does not provide country of origin or whether it's retrospective or prospective, though bench testing is inherently prospective in nature.

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

This information is not provided in the document. Bench testing typically relies on predefined engineering specifications rather than expert consensus on a 'ground truth' in the same way clinical data would.

4. Adjudication method for the test set

This information is not applicable/not provided. Adjudication methods are typically relevant for human-interpreted data (e.g., imaging studies, clinical endpoints), not for objective bench test results like mechanical strength or endotoxin levels.

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, a multi-reader multi-case (MRMC) comparative effectiveness study was not done. This device is a surgical mesh; the concept of "human readers" and "AI assistance" is not relevant to its type of evaluation.

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

This question is not applicable to this medical device. The "Endoform Restella" is a physical surgical mesh, not an algorithm or AI performing a task. Its performance is evaluated through physical and material properties, not by an algorithm's output.

7. The type of ground truth used

The ground truth used for the non-clinical performance evaluation was based on product specifications and the characteristics of the predicate device. The device was deemed acceptable if it met these predefined specifications and demonstrated equivalence in key properties to the legally marketed predicate.

8. The sample size for the training set

This information is not applicable/not provided. The "Endoform Restella" is a physical device, not a machine learning algorithm that requires a "training set."

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

This question is not applicable to this medical device.

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Endoform® Plastics and Reconstructive Matrix is for implantation to reinforce soft tissue where weakness exists in patients requiring soft tissue repair or reinforcement in plastic and reconstructive surgery. The device is supplied sterile and is intended for one-time use.

Endoform® Plastics and Reconstructive Matrix is an advanced collagen matrix comprised of natural >70%, non-reconstituted collagen. Endoform® Plastics and Reconstructive Matrix is designed to be fixed, via sutures, staples or tacks to the surrounding tissue, at the discretion of the attending physician for applications in plastic and reconstructive surgery. For example, the device can be surgically implanted to reinforce damaged or ruptured soft tissue membranes and reinforce muscle flaps. The device is supplied sterile and dry in a variety of sizes and thicknesses, which can be trimmed by surgeons to meet the individual patient's needs. Endoform® Plastics and Reconstructive Matrix is laminated via a proprietary process termed 'lug lamination', which is a physical means of fabricating the devices, such that the individual sheets of the device are physically bonded to one another as opposed to using embroidery to sew the laminate of collagen matrix sheets.

The provided text describes a 510(k) premarket notification for a medical device (Endoform® Plastics and Reconstructive Matrix) and primarily focuses on proving its substantial equivalence to legally marketed predicate devices. This type of submission relies on demonstrating that the new device is as safe and effective as a predicate device, rather than proving de novo safety and efficacy through extensive clinical trials for novel devices.

Therefore, the information you've requested about acceptance criteria, efficacy studies, expert adjudication, MRMC studies, standalone algorithm performance, and training set details are not applicable in the context of this 510(k) submission as it is not a study proving the device meets acceptance criteria for a novel AI/software medical device.

The "acceptance criteria" presented here are in the context of bench testing and biocompatibility, not "device performance" in the sense of diagnostic accuracy or clinical outcomes that typically require such detailed study methodologies.

Let's break down what is available in the provided document, and then explain why the requested information is absent.

1. Table of acceptance criteria and reported device performance (based on the provided text):

The document does not explicitly present acceptance criteria in a quantitative table with corresponding "reported device performance" in the way one would for a diagnostic or AI device's clinical performance. Instead, it describes bench tests performed to demonstrate that the device meets "all product specifications for the intended use." The "acceptance criteria" for these tests would be the pre-defined product specifications, which are not detailed numerically in this summary.

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

• Sample Size: The document does not specify the sample sizes used for each of the bench tests mentioned (tensile strength, suture retention, etc.).
• Data Provenance: Not applicable in the context of this submission. The tests are bench tests of the manufactured device, not retrospective or prospective clinical data from human patients.

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

• Not applicable. Ground truth, in the sense of clinical diagnoses or outcomes, is not being established for bench tests of a surgical mesh. The "truth" for these tests are the physical/material properties of the device itself.

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

• Not applicable. This concept is for clinical or image-based studies where human readers might disagree. Bench tests rely on standardized measurement methods.

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 device is a surgical mesh, not an AI or diagnostic tool. No MRMC study was performed or required.

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

• Not applicable. This device is a surgical mesh, not an algorithm.

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

• For the bench tests, the "ground truth" refers to the established physical and chemical properties measured according to standardized methods. For biocompatibility, it's assessed against ISO 10993-1 standards and by leveraging the established safety of a reference device. For the overall submission, the "ground truth" for substantial equivalence relies on the regulatory approval and safety profile of the predicate device.

8. The sample size for the training set:

• Not applicable. There is no AI model or algorithm being trained for this device.

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

• Not applicable. There is no training set for this device.

Explanation of the 510(k) Process and Why This Information is Absent:

The document is a 510(k) Pre-Market Notification. For a device submitted under a 510(k), the primary goal is to demonstrate "substantial equivalence" to a legally marketed predicate device. This means the device is as safe and effective as another legally marketed device, and does not raise new questions of safety and effectiveness.

• No De Novo Clinical Efficacy Study: The document explicitly states: "There was no clinical testing required to support the indications for use as they are equivalent to the predicate device." This is a key characteristic of the 510(k) pathway for devices like surgical meshes that are considered "well-understood" and have similar predicate devices.
• Focus on Bench Testing and Biocompatibility: The "performance testing" described is confined to bench tests (tensile strength, suture retention, etc.) and biocompatibility. These tests confirm that the manufacturing process is consistent and that the material properties are similar to the predicate, and that the material does not pose new biological risks.
• Leveraging Predicate Device Data: The safety and performance of the proposed device are "based on the in vivo performance of the predicate and reference devices." This means the FDA relies on the existing track record and regulatory history of the predicate devices rather than requiring new, extensive clinical trials for the new device.
• Not an AI/Software Device: The concepts of "multi-reader multi-case studies," "standalone algorithm performance," "training set," and "adjudication methods" are typically relevant for Software as a Medical Device (SaMD) or AI-powered devices where the performance criterion is diagnostic accuracy, image interpretation, or clinical decision support. The Endoform® Plastics and Reconstructive Matrix is a physical surgical mesh, not a software product.

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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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