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The SPY Cystoscopes/Hysteroscopes are intended to provide visualization in general urological and gynecological surgery through the minimally invasive approach, by utilizing natural orifices to access the surgical site.

The SPY Cystoscope/Hysteroscope is part of Stryker's rigid endoscope product portfolio. The SPY Cystoscope/Hysteroscope is an optical instrument used to visualize or image a patient's anatomy during minimally invasive, endoscopic procedures for examination, diagnosis or therapy. The SPY Cystoscope/Hysteroscope transmits light in the visible spectrum to illuminate the anatomy, then forms and relays the image of the surgical site to a camera system for image processing and display.

The provided text describes a 510(k) premarket notification for the Stryker Endoscopy SPY Cystoscope/Hysteroscope. It focuses on demonstrating substantial equivalence to a predicate device, rather than a standalone study proving specific clinical performance metrics with a test set, ground truth, or human reader involvement for an AI/ML device.

Therefore, the requested information regarding "acceptance criteria and the study that proves the device meets the acceptance criteria" in the context of an AI/ML device with details like sample sizes, expert ground truth, adjudication methods, MRMC studies, or standalone algorithm performance, is not applicable to this document.

This document details:

• Device Type: A traditional medical device (optical instrument for visualization in surgery), not explicitly an AI/ML powered device.
• Regulatory Pathway: 510(k) Pre-market Notification, which focuses on demonstrating substantial equivalence to an existing legally marketed predicate device.
• Performance Testing: Primarily non-clinical bench testing and compliance with recognized voluntary consensus standards.

Here's a breakdown of what is provided, framed as closely as possible to your request, but highlighting the absence of AI/ML specific criteria:

1. Table of Acceptance Criteria and Reported Device Performance

The document lists various performance tests and their "Pass" results, indicating that the device met the criteria set by the respective standards or comparative testing. The acceptance criteria themselves are implicitly defined by compliance with these standards (e.g., "In accordance with FDA-recognized voluntary consensus standard IEC 60601-1:2020").

2. Sample size used for the test set and the data provenance: Not applicable. This document describes non-clinical testing of a physical medical device, not a performance study on a test set of data (e.g., images for an AI algorithm).

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for an AI/ML algorithm is not relevant to the described testing.

4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not applicable.

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. The device is a direct visualization tool, not an AI-assisted diagnostic or interpretative system for human readers.

6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not applicable.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.): Not applicable. The "ground truth" here is compliance with established engineering and safety standards, and equivalence to a predicate device's performance.

8. The sample size for the training set: Not applicable. The device does not involve a training set as it's not an AI/ML product.

9. How the ground truth for the training set was established: Not applicable.

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