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indicated for use in a variety of gynecologic, general, thoracic, and urologic endoscopic procedures to create and maintain a port of entry.

VersaOne™ Bladed Trocar is available in 11mm fixation and smooth standard. 12mm fixation and smooth standard, and 12mm fixation and smooth long. VersaOne™ Bladed Trocar consists of an obturator component with a bladed tip and a cannula assembly. VersaOne™ Bladeless Trocar is available in 5mm fixation short. standard, and long, 11mm fixation standard, 12mm fixation short, standard, and long, and 12mm smooth standard. VersaOne™ Bladeless Trocar consists of an obturator component with a bladeless tip and a cannula assembly. The devices are supplied sterile single-use.

Here's a breakdown of the acceptance criteria and study information for the VersaOne™ Bladed Trocar and VersaOne™ Bladeless Trocar, based on the provided FDA 510(k) summary:

This submission is for a medical device (surgical trocar) and the documentation primarily focuses on demonstrating substantial equivalence to predicate devices through performance testing and material compliance. As such, concepts like "acceptance criteria" for a diagnostic algorithm, "expert ground truth," "MRMC studies," or "training sets" are not applicable in this context. The "performance data" here refers to engineering and biocompatibility testing, not diagnostic accuracy.

Acceptance Criteria and Reported Device Performance

The document does not explicitly present a table of quantitative acceptance criteria in the way one might for an AI/diagnostic device (e.g., sensitivity, specificity thresholds). Instead, the performance is evaluated against the specifications of the proposed devices and comparability to predicate devices for aspects like mechanical function and biocompatibility.

Study Details (as inferable from the document)

Given this is a 510(k) for a physical medical device (trocar), the "study" is a series of engineering tests and biocompatibility assessments, not a clinical trial or AI performance study.

1. 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 exact sample sizes for the performance tests (e.g., how many trocars were tested for insertion force, seal integrity, etc.).
   • The data provenance is not mentioned, but these types of tests are typically conducted in a laboratory setting, often by the manufacturer or a contracted lab. They are prospective in the sense that the tests are designed and executed to evaluate the new device.

2. 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 concept is not applicable here. "Ground truth" in this context would be engineering specifications and standards (e.g., ISO 10993-1). The evaluation is objective, based on measurable physical properties and material responses, rather than expert interpretation.

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

   • This is not applicable. Performance tests for physical devices are generally evaluated against pre-defined engineering criteria, not through expert adjudication.

4. 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 is not applicable. The device is a surgical instrument, not an AI or diagnostic tool.

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

   • This is not applicable. The device is a surgical instrument, not an algorithm.

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

   • For performance testing, the "ground truth" consists of engineering specifications, regulatory standards (e.g., ISO 10993-1 for biocompatibility), and established performance characteristics of the predicate devices. The device's performance is compared against these objective benchmarks rather than expert interpretation of medical images or pathology.

7. The sample size for the training set:

   • This is not applicable. There is no machine learning or AI component to this device, and thus no "training set."

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

   • This is not applicable as there is no training set.

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