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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 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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Enivo™ is indicated for use to remove surgical and bodily fluids from a closed wound for hematoma and seroma prophylaxis following plastic surgery or other general surgeries where large flaps are formed.

Enivo™ is a surgical drainage system intended for the removal of surgical and bodily fluids from a closed wound. The system can be used in both home and healthcare environments. The system includes two primary components: - A vacuum device unit that includes a single-use, portable, and battery-powered vacuum device that provides continuous operation for up to 30 days and a disposable exudate reservoir. - a removable silicone drainage catheter

The provided document is a 510(k) summary for the Enivo™ device, which is a powered suction pump. It outlines the device's intended use and compares it to a predicate device (SOMAVAC Device, K222856) to establish substantial equivalence.

Here's an analysis of the acceptance criteria and supporting studies based on the provided text:

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

The document does not provide a table with explicit acceptance criteria (e.g., minimum vacuum pressure, maximum flow rate) and corresponding measured device performance values. Instead, it lists various types of non-clinical tests that were conducted to demonstrate that "the device performs as intended" and "no new types of risk to the patent have been introduced by these differences." Without specific criteria, it's impossible to create such a table.

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

The document lists only non-clinical (bench) testing. Therefore, there is no "test set" in the context of patient data (e.g., diagnostic images, clinical samples), nor is there data provenance related to patient demographics or study design (retrospective/prospective). The tests listed are primarily engineering and performance evaluations.

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 question is not applicable. The studies conducted are non-clinical engineering and performance tests, not studies requiring expert interpretation of patient data to establish ground truth.

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

This question is not applicable. There is no "test set" in the context of patient data that would require an adjudication method.

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 question is not applicable. The Enivo™ device is a powered suction pump, not an AI-assisted diagnostic or therapeutic device. No MRMC study was conducted.

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

This question is not applicable. The Enivo™ device is a hardware device; it does not involve algorithms or AI for standalone performance evaluation in this context.

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

For the non-clinical tests conducted, the "ground truth" would be established by:

• Voluntary Standards: Compliance with recognized standards like IEC 60601-1, ISO 10993-1, ISO 20697, ASTM F1929, etc.
• Engineering Specifications: Internal design specifications for vacuum pressure, flow rate, battery life, mechanical strength, alarm thresholds, etc.
• Test Method Requirements: The specifications and procedures defined in the various ASTM and ISO standards for package integrity, sterilization, biocompatibility, etc.

8. The sample size for the training set

This question is not applicable. The Enivo™ device is not an AI/machine learning device, so there is no concept of a "training set" in this submission.

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

This question is not applicable as there is no training set mentioned or implied for this device.

Summary of Acceptance Criteria and Supporting Studies (Based on available information):

Due to the nature of the device (a powered suction pump) and the 510(k) submission type, the acceptance criteria are based on compliance with recognized consensus standards and internal engineering performance specifications rather than clinical performance metrics typically seen for diagnostic or AI-powered devices.

The document lists a comprehensive set of non-clinical tests to demonstrate substantial equivalence by showing that the device meets safety and performance requirements and does not introduce new risks compared to the predicate device. However, specific numerical acceptance criteria and reported values for each test are not detailed in this summary.

In essence, the "acceptance criteria" can be inferred as "compliance with the listed standards and satisfactory performance per internal specifications," and the "study that proves the device meets the acceptance criteria" is the entirety of the non-clinical testing performed.

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Myriad™ Particles is indicated for use in the management of the following wounds:

• · partial and full-thickness wounds
• · pressure ulcers
• venous ulcers .
• diabetic ulcers .
• chronic vascular ulcers .
• . tunneled/undermined wounds
• Surgical wounds (donor sites/grafts, post-Moh's surgery, post-laser surgery, podiatric, . wound dehiscence)
• . trauma wounds (abrasions, lacerations, partial-thickness burns, and skin tears)
• · draining wounds

Myriad™ Particles is derived from an extracellular matrix primarily composed of ovine collagen and is supplied as a sterile particulate.

The provided document is a 510(k) premarket notification for a medical device called "Myriad™ Particles." This type of submission is for demonstrating substantial equivalence to a legally marketed predicate device, rather than proving a device meets specific clinical performance acceptance criteria through the kind of study described in the prompt.

Therefore, the document does not contain the information requested regarding acceptance criteria and performance studies. The key points from the document that illustrate this are:

• No Clinical Performance Data Used for Substantial Equivalence: Section 5.6 explicitly states: "Substantial equivalence was not based on an assessment of clinical performance data." This means a human clinical study to prove performance was not conducted for this 510(k) submission.
• Focus on Substantial Equivalence through Technological Characteristics and Non-Clinical Data: The document relies on comparing the technological characteristics of Myriad™ Particles to its predicate device (Endoform™ Dermal Template) and presenting non-clinical (bench and biocompatibility) testing. The primary difference highlighted is the device presentation (powder vs. sheet format).
• No mention of AI/ML components: The device is a wound dressing, and there is no indication that it incorporates any artificial intelligence or machine learning components. Therefore, an MRMC comparative effectiveness study or standalone algorithm performance assessment would not be applicable.

In summary, the provided text does not describe a study designed to prove the device meets specific acceptance criteria in the way a clinical performance study for an AI/ML device would. It focuses on demonstrating substantial equivalence to an existing device through non-clinical means.

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Symphony™ is indicated for use in the management of the following wounds:

• · partial and full-thickness wounds
• · pressure ulcers
• venous ulcers
• · diabetic ulcers
• chronic vascular ulcers
• · tunnelled / undermined wounds
• · surgical wounds (donor sites/grafts, post-Moh's surgery, post-laser surgery, podiatric, wound dehiscence)
• · trauma wounds (abrasions, lacerations, second-degree burns, and skin tears)
• draining wounds

Symphony™ is a sterile, single use wound dressing manufactured by incorporating a layer of glycosaminoglycans between sheets of ovine forestomach-derived extracellular collagen matrix. The 4-ply rectangular devices are available in sizes up to 200 cm².

The provided text is a 510(k) summary for the device "Symphony™," a wound dressing. This document primarily focuses on demonstrating substantial equivalence to a predicate device based on material, manufacturing, and performance characteristics, rather than evaluating an AI/ML medical device. Therefore, much of the requested information about acceptance criteria, ground truth, expert adjudication, MRMC studies, and training/test set details for AI/ML models is not present in this document.

However, I can extract the information related to the device's performance and the non-clinical testing performed to establish its substantial equivalence.

Here's an analysis of the provided text, addressing the points where information is available and noting where it is not:

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

The document presents a comparison table between the Symphony™ device (Subject Device) and the predicate device (Endoform® Topical Matrix). This table implicitly shows the acceptance criteria by listing the parameters and the expected range/value for both the subject and predicate devices.

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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 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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