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The Biodesign Nipple Reconstruction Cylinder is intended for implantation to reinforce soft tissue where weakness exists, in plastic and reconstructive surgery of the nipple. The cylinder is supplied sterile and is intended for one-time use.

The Biodesign Nipple Reconstruction Cylinder is composed of a bioabsorbable, extracellular collagen matrix (Small Intestinal Submucosa, SIS). The SIS material is identical to the predicates SurgiSIS® Mesh (K980431, K062696), SIS Plastic Surgery Matrix (K034039), and SIS Facial Implant (K050246, K070738) all manufactured by Cook Biotech Incorporated. The Biodesign Nipple Reconstruction Cylinder is a rolled SIS mesh and available in sizes from 0.7 cm in diameter and 1.0 cm to 2.5 cm in length. The cylinder is a scaffold which becomes infiltrated by the host cells during the body's natural repair process. The device is implanted using a skin flap procedure that prevents migration of the device. A PET marking template (Class I, 21 CFR 888.4800) and silicone (35A durometer) nipple shield (Class I, 21 CFR 880.5630 ) to be placed over the cylinder post-operatively, are included with the device. The use of the Biodesign Nipple Recosntruction Cylinder, an off-the-shelf graft, is advantageous in that a donor site is no longer necessary.

Here's a breakdown of the acceptance criteria and study information for the Biodesign® Nipple Reconstruction Cylinder, based on the provided 510(k) summary:

This device's submission is for substantial equivalence to existing predicate devices, not for a de novo marketing authorization. Therefore, the "acceptance criteria" are not defined as specific performance thresholds, but rather the demonstration that the new device performs similarly to
its predicates across various tests, without raising new questions of safety or effectiveness.

1. Table of Acceptance Criteria and Reported Device Performance

Since this is a substantial equivalence submission, the "acceptance criteria" are implied to be performance comparable to the predicate devices. The reported device performance is presented as demonstrating this comparability.

2. Sample Sizes and Data Provenance

• Bench Testing: The sample sizes for suture retention strength and ultimate tensile strength are not specified. The tests were performed on "finished, terminally sterilized SurgiSIS® mesh" which forms the device.
• Biocompatibility Testing: The sample sizes for each specific biocompatibility test are not specified. The tests were performed on "sterilized SurgiSIS Mesh."
• Animal Testing: The sample size is not explicitly stated beyond "an animal study" in "a guinea pig model." It is implied to include multiple animals to assess performance over 5 months.
  • Data Provenance: The study was an animal study, likely conducted in a controlled laboratory setting. The country of origin is not specified but presumed to be within the Cook Biotech research facilities or contracted labs. The data is prospective within the context of the animal study.
• Clinical Testing:
  • Sample Size: 2 case studies and anecdotal evidence of 186 device implants (totaling 188 implants).
  • Data Provenance: The document does not specify the country of origin. The data appears to be retrospective (anecdotal evidence from past implants) and possibly some prospective observation for the "2 case studies."

3. Number of Experts and Qualifications for Ground Truth for Test Set

This device's submission relies on demonstrating substantial equivalence to already approved predicate devices. Thus, there isn't a "test set" in the traditional sense of a diagnostic algorithm where expert ground truth is established for novel readings.

• For the clinical testing, the "ground truth" implicitly comes from the clinical outcomes and observations made by the surgeons/clinicians performing the implants and follow-ups. The number of experts and their specific qualifications are not reported. Their assessment of "substantially equivalent to its predicates in its application" is based on their clinical experience.

4. Adjudication Method for the Test Set

Given the nature of the submission (substantial equivalence for a physical implant), there is no mention of an adjudication method in the context of expert review of data from a "test set" for a diagnostic algorithm. The clinical "data" comprises case studies and anecdotal evidence from implants managed by various clinicians.

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

No MRMC comparative effectiveness study was done or reported. This type of study is typical for diagnostic AI devices, not for assessing the substantial equivalence of a physical implant. The focus here is on the material, design, and performance characteristics compared to predicates.

6. Standalone Performance Study

This concept of "standalone performance" typically applies to diagnostic algorithms operating independently. Since this is a physical implant, it doesn't have a "standalone" algorithm-only performance. Its performance is assessed through its material properties, biological interaction (in animals), and clinical outcomes (in humans).

7. Type of Ground Truth Used

• Bench Testing: The "ground truth" is based on objective mechanical measurements (suture retention strength, ultimate tensile strength) and comparison to established predicate device performance or industry standards.
• Biocompatibility Testing: The "ground truth" is adherence to ISO 10993-1 standards for various biological responses.
• Animal Testing: The "ground truth" is histopathological analysis and observation of tissue response (minimal inflammation, increased soft tissue volume) in the guinea pig model, compared to expected healthy tissue response and the known behavior of SIS material.
• Clinical Testing: The "ground truth" is based on clinical outcomes, observations, and anecdotal evidence from patients who received the implant. This includes assessment of its ability to reinforce soft tissue in nipple reconstruction, functional outcomes, and reported complications. This is closer to outcomes data and expert clinical assessment rather than a single objective "ground truth" like pathology for a diagnostic image.

8. Sample Size for the Training Set

This submission does not involve a machine learning algorithm, so there is no "training set" in the context of AI. The development of the device (implant) relies on established knowledge of SIS material, previous predicate devices, and pre-clinical/clinical testing.

9. How Ground Truth for the Training Set was Established

As there is no training set for an AI model, this question is not applicable. The underlying "knowledge base" for the device's design and expected performance comes from decades of research and clinical use of SIS extracellular matrix material.

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The COOK® Urological Graft is for implantation to reinforce soft tissues where weakness exists in the urological anatomy, including temporary wound or solid organ support in the kidney. The Urological Graft is supplied sterile and intended for one-time use.

The COOK® Urological Graft is a bioabsorbable, extracellular collagen matrix that is identical to the predicates SURGIS Mesh (K980431) and SURGISIS® Sling (K992159), also manufactured by COOK Biotech Incorporated, and to Vicryl Mesh bag (K051701), manufactured by Ethicon. The device is manufactured from porcine small intestinal submucosa (SIS), packaged in a lyophilized (dried) state and supplied sterile in a sealed double pouch system.

The provided text describes a 510(k) submission for the COOK® Urological Graft and does not contain information about acceptance criteria or a study proving the device meets said criteria in the way typically found for AI/ML medical devices (e.g., performance metrics like sensitivity, specificity, AUC).

Instead, this document focuses on demonstrating substantial equivalence to existing legally marketed predicate devices, which is the cornerstone of the 510(k) pathway. The study mentioned refers to the type of testing performed to prove this equivalence, rather than a performance study against specific acceptance criteria for a novel AI/ML algorithm.

Therefore, the requested information cannot be fully provided as the context is different from what the prompt anticipates for AI/ML device studies.

However, I can extract what is relevant to the prompt, even if it's not a direct match to the AI/ML framework:

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

This document does not define specific "acceptance criteria" in terms of quantitative performance metrics (like sensitivity, specificity, or AUC) that an AI/ML model would need to meet. For a 510(k) submission of a traditional medical device like the COOK® Urological Graft, the primary "acceptance criterion" is substantial equivalence to predicate devices.

Reported Device Performance (as it relates to substantial equivalence):

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 mentions "bench, animal, biocompatibility and clinical testing" to establish equivalence. However, it does not provide details on:

• The specific sample sizes used for these tests.
• The data provenance (e.g., country of origin, retrospective/prospective nature) for any clinical data.

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 is not applicable as the device is a physical surgical graft, not an AI/ML diagnostic or prognostic tool that requires expert-established ground truth on a test set. The "ground truth" for demonstrating equivalence would be derived from the performance and characteristics of the predicate devices and the results of the specific engineering, animal, and clinical tests performed on the COOK® Urological Graft itself.

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

Not applicable for a physical medical device submission demonstrating substantial equivalence. Adjudication methods are typically relevant for human interpretation or AI/ML output assessment where discrepancies might arise.

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 graft, not an AI-assisted diagnostic tool, so MRMC studies or human reader improvement with AI are not relevant.

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

Not applicable. The device is a physical surgical graft, not an algorithm.

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

For this type of device, the "ground truth" for demonstrating substantial equivalence would be based on:

• Material properties data: Bench testing results on tensile strength, bioabsorption rates, pore size, etc.
• Biocompatibility data: Standardized tests for cytotoxicity, sensitization, irritation, etc., according to ISO standards.
• Animal study data: In vivo performance in terms of tissue integration, host response, strength, and degradation over time.
• Clinical safety and performance data (if collected): Surgical outcomes, adverse event rates, and efficacy in repairing or reinforcing tissues, compared to predicates. This data would be against established clinical endpoints and observations from healthcare professionals and patient outcomes.

8. The sample size for the training set

Not applicable. This is not an AI/ML device that uses a "training set."

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

Not applicable. This is not an AI/ML device, so there is no training set or ground truth in that context.

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FortaGen is intended to be used for implantation to reinforce soft tissue including, but not limited to: defects of the abdominal and thoracic wall, muscle flap reinforcement, rectal and vaginal prolapse, reconstruction of the pelvic floor, hernias, suture-line reinforcement and reconstructive procedures. The device is intended for one-time use.

FortaGen consists of a multi-laminate sheet predominantly of Type I porcine collagen. The device is supplied in sheet form in sizes ranging from 5 x 5 cm to 12 x 36 cm in sterile double layer peelable packaging.

The provided text describes a medical device called FortaGen™ Surgical Mesh and its clearance by the FDA based on substantial equivalence to predicate devices. However, the information provided does not contain details about specific acceptance criteria, a study proving the device meets those criteria, or a detailed breakdown of performance data against specific metrics.

The document states:

• "FortaGen was subjected to a panel of tests to assess biocompatibility, integrity, and performance. The device passed the requirements of all tests." This is a general statement that tests were conducted and passed, but no specific criteria, results, or study details are provided.
• The FDA letter confirms that the device is "substantially equivalent" to legally marketed predicate devices, which implies that it meets the safety and efficacy standards demonstrated by those predicates. However, it doesn't detail what specific performance metrics constitute substantial equivalence or how FortaGen™'s performance was directly compared against them in a structured study report.

Therefore, I cannot populate the requested table or answer most of the specific questions about the study design as the information is not present in the provided text.

Based on the available information, here's what can be extracted:

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

   Acceptance Criteria	Reported Device Performance
   Biocompatibility requirements	Device passed all tests
   Integrity requirements	Device passed all tests
   Performance requirements	Device passed all tests
   Substantial Equivalence to predicate devices (GraftPatch (K970561) and Surgisis (K980431))	Determined to be substantially equivalent by FDA

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

   • Sample Size: Not specified.
   • Data Provenance: Not specified (e.g., country of origin, retrospective/prospective). The document only states "FortaGen was subjected to a panel of tests."

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

   • Not specified. The document does not describe a process involving experts establishing ground truth for a test set. This type of information is typically relevant for diagnostic devices or AI-assisted systems, which this surgical mesh is not.

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

   • Not applicable/Not specified. Adjudication methods are typically used in clinical studies with human interpretation, which is not described here for the device's technical assessment.

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-assisted diagnostic or imaging device. Therefore, an MRMC study comparing human readers with/without AI assistance would not be performed for this product.

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

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

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

   • For the device's performance tests (biocompatibility, integrity, performance), the ground truth would be established by validated test methods and established standards/specifications for medical devices, rather than expert consensus on diagnostic images or pathology. The document does not specify the exact methods or standards used for these tests.

8. The sample size for the training set:

   • Not applicable. This is a physical surgical mesh, not an AI model that requires a training set.

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

   • Not applicable. This is a physical surgical mesh, not an AI model.

In summary, the provided text indicates that the FortaGen™ Surgical Mesh passed a panel of tests for biocompatibility, integrity, and performance and was deemed substantially equivalent to predicate devices by the FDA. However, it does not offer the granular detail requested about specific acceptance criteria values, study designs, sample sizes, or methods for establishing ground truth, which are more typically provided for diagnostic devices or those involving interpretation of data.

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The Surgisis® Sling is intended for implantation to reinforce soft tissues where weakness exists in the urological, gynecological and gastroenterological anatomy including but not limited to the following procedures: transvaginal repair of stress urinary incontinence, such as pubourethral support and bladder support, and transabdominal repair of apical vaginal prolapse, colon and rectal prolapse, and sacrocolposuspension. By providing pubourethral support, the sling may be used for the treatment of urinary incontinence resulting from urethral hypermobility or intrinsic sphincter deficiency. The device is supplied sterile and is intended for one-time use.

The Surgisis® Sling is supplied in sheet form in sizes ranging from 20 cm2 to 140 cm2. The device is packaged in sterile, sealed double pouches.

This document is a 510(k) Summary for the Surgisis® Sling, a surgical mesh device. It does not provide information about acceptance criteria or a study proving that the device meets such criteria in terms of performance metrics like sensitivity, specificity, or any other quantitative measures typically associated with AI/ML device evaluations.

The document focuses on demonstrating substantial equivalence to predicate devices based on:

• Intended Use: The Surgisis® Sling has the same intended use as its predicates (K980431, K954665, K980483, K963226).
• Technological Characteristics: The device is stated to have the same technological characteristics as the predicate devices.
• Testing for Biocompatibility, Integrity, and Performance: The document states that the Surgisis® Sling "passed the requirements of all tests" in these areas. However, it does not specify what these requirements or performance metrics were, nor does it provide the results of these tests in a detailed manner.

Therefore, I cannot provide the requested information for an AI/ML device as this document pertains to a traditional medical device (surgical mesh) where the evaluation criteria are different. The concept of "acceptance criteria" in this context refers to meeting the standards of biocompatibility, integrity, and equivalent performance to existing devices, rather than statistical performance metrics for an AI algorithm.

Summary of what can be extracted, and what cannot:

1. Table of acceptance criteria and reported device performance:

   • Acceptance Criteria (Implied): Biocompatibility, Integrity, Performance (in relation to predicate devices).
   • Reported Device Performance: "The Surgisis® Sling passed the requirements of all tests." No specific quantitative performance metrics are provided.

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

   • Not applicable/Not provided. The document refers to "tests" on the device itself (e.g., material properties), not a "test set" of patient data for an algorithm.

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

   • Not applicable/Not provided. Ground truth in the context of an AI/ML device would involve annotations by experts on medical data. This document doesn't involve that.

4. Adjudication method:

   • Not applicable/Not provided.

5. Multi-reader multi-case (MRMC) comparative effectiveness study:

   • Not applicable/Not performed. This is for evaluating AI assistance to human readers.

6. Standalone (algorithm only) performance:

   • Not applicable/Not performed. This device is not an algorithm.

7. Type of ground truth used:

   • Not applicable in the AI/ML sense. The "ground truth" for this device would be established engineering and biological standards for surgical mesh materials.

8. Sample size for the training set:

   • Not applicable/Not provided. This document describes a physical medical device, not an AI algorithm.

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

   • Not applicable.

In conclusion, the provided document describes a premarket notification (510(k)) for a conventional surgical mesh, focusing on substantial equivalence to existing devices. It does not contain the type of information related to acceptance criteria, test sets, ground truth, or study designs that would be relevant for an AI/ML medical device.

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