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The Mirus™ Ligating clip is intended for use in open general surgery procedures on tubular structures or vessels wherever a metal ligating clip is indicated. The tissue being ligated should be consistent with size of the clip.

Mirus™ Ligating Clip applier is intended to apply ligating clips on tubular structures or vessels wherever a metal ligating clip is indicated.

Mirus™ Ligating clip are sterile, single use, implantable device made of implant grade titanium (ISO 5832-2 / ASTM F 67). The clips are available in various sizes with 6 clips packed in a single plastic cartridge.

Mirus™ Ligating clips are supplied with multiuse non sterile stainless steel Mirus™ Ligating Clip applier, allows the end user to ligate a wide range of vessels and tissue structures using the ligating clips

The provided document is a 510(k) premarket notification for a medical device called "Mirus™ Ligating Clip" and "Mirus™ Ligating Clip Applier." The document focuses on establishing substantial equivalence to predicate devices and describes various performance tests conducted. However, it does not contain a specific study that directly proves the device meets detailed acceptance criteria in the manner of a clinical trial or comparative effectiveness study with human readers assisting AI.

Here's the breakdown of the requested information based on the provided text:

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

The document lists performance tests but does not explicitly state numerical acceptance criteria or detailed results for all of them. It broadly states that the device was "subjected to the performance testing" and implies that these tests were passed, leading to the conclusion of 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 does not specify the sample sizes used for each of the performance tests. It also does not provide details on the data provenance in terms of country of origin or whether the studies were retrospective or prospective. These tests appear to be bench or lab-based rather than human clinical studies.

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 information is not applicable to the type of device and tests described. The tests are for the physical and biological characteristics of a ligating clip, not for an AI algorithm requiring expert ground truth in image interpretation or diagnosis.

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

This information is not applicable. The tests described are laboratory-based performance and biocompatibility assessments, not clinical studies requiring adjudication of outcomes by experts.

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 such study was conducted or mentioned in the document. This type of study is relevant for AI-powered diagnostic or assistive devices, not for a medical device like a ligating clip and applier.

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

This information is not applicable. The device is a physical medical device (ligating clip and applier), not an algorithm or AI system.

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

The document does not explicitly use the term "ground truth" in the context of expert consensus or pathology. For the performance tests (e.g., radial pull-off force, leakage), the "ground truth" would be established by physical measurement against predefined engineering or material specifications and standards (e.g., ISO, ASTM standards). For biocompatibility, the ground truth would be the results of standard biological assays according to established protocols.

8. The sample size for the training set

This information is not applicable. The device is a physical medical device, not an AI system that requires a training set.

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

This information is not applicable, as there is no training set for this device.

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