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The VS3 is intended for viewing internal surgical sites during general endoscopic and laparoscopic surgical procedures.

The VS3 consists of the following components: Endoscope, Light source, Camera Control Unit (CCU), Camera, Display monitors, 2D Endoscope coupler. The VS3 Stereoscopic High Definition ("3DHD") system is based on the proximal HD camera concept with a stereoscopic camera block located on the proximal side of the endoscope (the handle). This allows high resolution capture of the 3D video stream. The stereoscopic images are transmitted from the visual field at the distal tip of the endoscope to the proximal camera block containing the HD sensor module. The VS3 system allows for separation of the camera module with image sensor module and electronics from the endoscope shaft housinq optical relay components and light fibers. The VS3 system also includes 2D coupler capability that allows the VS3 system to be used with FDA-cleared, third party 2D scopes at user sites to display monocular video.

The provided text describes a 510(k) submission for the Visionsense VS3 Stereoscopic Vision System, a Class II medical device. However, it does not contain the detailed information required to fill out the table regarding acceptance criteria, study details, and performance metrics as it is primarily focused on establishing substantial equivalence to a predicate device.

Specifically, the document states:

• "No performance standards or special controls have been developed under Section 514 of the Federal Food, Drug, and Cosmetic Act ("FD&C Act") for endoscopes."
• "However, the VS3 system and its components follow FDA recognized consensus standards for electrical safety, electromagnetic compatibility, and biocompatibility. In addition, cleaning validation, sterilization, and software validation were performed for the subject device. The completed testing listed above demonstrates that the subject device is as safe and effective as the predicate device."

This indicates that the "study" proving the device meets acceptance criteria is primarily a series of verification and validation tests against recognized consensus standards and internal quality controls, rather than a clinical performance study with specific acceptance criteria in terms of diagnostic accuracy or other performance metrics typically associated with AI/software devices. Therefore, many of the requested fields cannot be answered from the provided text.

However, based on the information provided, here's what can be extracted and what cannot be:

1. Table of acceptance criteria and the reported device performance:

Note: The text explicitly states "No performance standards or special controls have been developed under Section 514 of the Federal Food, Drug, and Cosmetic Act ("FD&C Act") for endoscopes." This implies there are no specific quantitative or clinical performance acceptance criteria (e.g., sensitivity, specificity, accuracy) provided in this document as would be expected for a diagnostic AI device. The "performance" described focuses on meeting safety, electromagnetic, and material standards, and demonstrating functional equivalence to the predicate device with the added feature of HD.

Additional Information (where available or noted as unavailable):

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

• Not provided. The document describes engineering and quality assurance validation (e.g., electrical safety, sterilization validation) against consensus standards but does not detail sample sizes or data provenance for a "test set" in the context of clinical performance data or AI model evaluation.

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

• Not applicable/Not provided. This information is relevant for studies validating interpretations or diagnostic outputs, typically in AI/software clinical performance studies. The provided text does not describe such a study.

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

• Not applicable/Not provided. As above, this pertains to expert-led ground truth establishment for performance studies.

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, an MRMC comparative effectiveness study was not done (or at least not described in this submission summary). The device is a stereoscopic vision system (hardware-based 3D visualization), not an AI-assisted diagnostic tool for human readers.

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

• Not applicable/Not provided. The device is an endoscopic system providing visualization, not a standalone algorithm.

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

• Not applicable/Not provided. The device's validation focuses on engineering and safety standards, and functional equivalence to a predicate, rather than validating against a clinical "ground truth" for diagnostic accuracy.

8. The sample size for the training set:

• Not applicable/Not provided. This is not an AI/machine learning device in the context of this submission. "Training set" would not apply in the conventional sense.

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

• Not applicable/Not provided. As above, this is not an AI/machine learning device.

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