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The ACell UBM Surgical Mesh ML and MLPlus are intended for implantation to reinforce soft tissue where weakness exists in urological, gynecological, and gastroenterological anatomy including, but not limited to the following procedures: pubourethral support, urethral and vaginal prolapse repair, colon and rectal prolapse repair, reconstruction of the pelvic floor, bladder support, tissue repair, sacrocolposuspension, hernia and body wall repair, and esophageal repair. By providing pubourethral support, the ACell surgical mesh may be used for the treatment of urinary incontinence resulting from urethral hypermobility and intrinsic sphincter deficiency. The device is intended for one-time use.

The ACell UBM Surgical Mesh ML and MLPlus are composed of porcine collagen and are supplied sterile in sizes ranging from 16 cm² to 14x20 cm.

The provided text describes a 510(k) premarket notification for the ACell UBM Surgical Mesh ML and MLPlus. This document focuses on the regulatory clearance process for a medical device and does not contain information about a study proving device performance against specific acceptance criteria in the way you've outlined for an AI/ML medical device.

The main points from the document regarding "tests" are:

• Discussion of tests and test results: "The ACell Surgical Mesh ML and MLPlus were subjected to a number of tests to assess the biocompatibility and the performance of the materials. They passed the requirements of all tests and were shown to be safe and effective as surgical mesh devices as indicated."

This is a very general statement and does not provide specific acceptance criteria, reported performance metrics, or details of a study design that would fit the questions about AI/ML device performance.

Therefore, I cannot populate the requested table and answer many of your specific questions because the provided text is about a traditional medical device (surgical mesh) and its 510(k) clearance, not an AI/ML device and its performance study.

Here's why the questions cannot be answered from the provided text:

1. Table of acceptance criteria and reported device performance: The document states "passed the requirements of all tests" but does not detail what those tests were, what their specific acceptance criteria were, or the quantitative performance metrics achieved by the device.
2. Sample size, data provenance: Not applicable as no such studies demonstrating AI/ML performance are described.
3. Number of experts, qualifications: Not applicable. The "tests" likely refer to material science, biocompatibility, and mechanical property tests, not expert-reviewed output.
4. Adjudication method: Not applicable.
5. MRMC comparative effectiveness study: Not applicable. This device is a surgical mesh, not an AI assisting human readers.
6. Standalone performance: Not applicable.
7. Type of ground truth: Not applicable.
8. Sample size for training set: Not applicable.
9. Ground truth for training set: Not applicable.

In summary, the provided document is a 510(k) summary for a physical surgical mesh product. It details regulatory information, intended use, and general statements about passing safety and performance tests, but it does not contain the kind of detailed study information (especially concerning AI/ML performance, ground truth, expert review, sample sizes, etc.) that your questions are designed to extract.

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The ACell UBM Surgical Mesh is intended for implantation to reinforce soft tissues. The device is intended for one-time use.

The ACell UBM Surgical Mesh is composed of porcine collagen and is supplied sterile in single sheet sizes ranging from 16 cm squared to 360 cm squared.

Here's an analysis of the provided text regarding the ACell UBM Surgical Mesh, focusing on acceptance criteria and supporting studies:

This document is a 510(k) Premarket Notification summary for the ACell UBM Surgical Mesh. It largely focuses on demonstrating substantial equivalence to predicate devices rather than providing detailed acceptance criteria or results from a rigorous clinical study.

1. Table of Acceptance Criteria and Reported Device Performance

Based on the provided text, specific quantitative acceptance criteria are not explicitly stated. The document broadly claims that the device "passed the requirements of all tests and was shown to be safe and effective." Without specific metrics (e.g., tensile strength, biocompatibility indices, degradation rates), a table of acceptance criteria and reported performance cannot be generated.

The "Discussion of tests and test results" section states:

• Acceptance Criteria (Implicit/General): To "assess the biocompatibility and the performance of the material."
• Reported Device Performance: "It passed the requirements of all tests and was shown to be safe and effective as a surgical mesh for soft tissue reinforcement."

This statement is a high-level summary without any detailed, quantifiable results.

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

The document does not provide details on the sample size used for any specific tests or the provenance of the data (e.g., country of origin, retrospective/prospective). It only mentions "a number of tests" were performed.

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

This information is not provided. The document doesn't describe the use of experts to establish a "ground truth" for test sets. The tests mentioned appear to be material and biological assessments, not expert-adjudicated clinical outcomes.

4. Adjudication Method for the Test Set

No adjudication method is described, as the tests mentioned are not clinical trials requiring human expert review with adjudication.

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

No, an MRMC comparative effectiveness study is not mentioned or implied in this 510(k) summary. This type of study is more common for diagnostic imaging devices involving interpretation by multiple readers.

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

This question is not applicable. The ACell UBM Surgical Mesh is a physical medical device (surgical mesh), not an algorithm or AI system. Therefore, the concept of "standalone performance" in the context of AI does not apply.

7. The Type of Ground Truth Used

The concept of "ground truth" as typically used in AI/diagnostic studies (e.g., pathology, clinical outcomes) is not explicitly detailed for this submission. The "tests" mentioned are likely in-vitro, in-vivo (animal), and potentially some form of biocompatibility assessments, where "ground truth" would be the results of standard laboratory analyses rather than clinical outcomes or expert consensus on patient data.

8. The Sample Size for the Training Set

This question is not applicable. The ACell UBM Surgical Mesh is a physical medical device, not an AI model requiring a training set.

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

This question is not applicable for the same reason as above.

Summary of Device-Specific Information from the Text:

• Device Trade Name: ACell UBM Surgical Mesh
• Device Common Name: Surgical mesh
• Classification Name: Mesh, Surgical (FTM, 21 CFR 878.3300)
• Predicate Devices: K021637 (ACell, Inc., ACell UBM Lyophilized Wound Dressing), K980431 (Cook Biotech, Inc., SurgiSIS®)
• Device Description: Composed of porcine collagen, supplied sterile in single sheet sizes ranging from 16 cm² to 360 cm².
• Intended Use/Indications for Use: Implantation to reinforce soft tissue, intended for one-time use.
• Conclusion: Substantially equivalent to predicate devices with respect to material composition, device characteristics, and intended use.
• Tests Performed: "A number of tests to assess the biocompatibility and the performance of the material." Details of these tests and their specific results are not included in this summary.

Key takeaway: This document is a 510(k) Premarket Notification summary, which aims to demonstrate substantial equivalence to legally marketed predicate devices. It typically provides an overview of testing rather than the granular detail of a full clinical study report, especially concerning specific acceptance criteria and detailed quantitative results. The criteria outlined in the input prompt are more relevant to AI/diagnostic device submissions than for a physical surgical mesh device like this one.

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