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The Flexible HD Cysto-Urethroscope System is used to provide visualization and operative access during diagnostic and therapeutic endoscopic procedures of urinary tract including the urethra, bladder, ureters, and kidneys.

The components subject of this submission are: the Flexible HD Cysto-Urethroscope (Part Number: 11272VH(U)), the LUER ports (Part Number: 11014L(U)), the Suction Valve (Part Number: 091011-20), and the IMAGE1 S CCU. The CCU consists of the IMAGE1 S Connect Module (Model Number: TC200US) and IMAGE1 S X-Link (Model Number: TC301US). The Flexible HD Cysto-Urethroscope (Part Number: 11272VH(U)) is a reusable, flexible video scope with an insertion shaft OD of 5.5 mm and length of 37 cm, a working channel OD of 2.3 mm, and a suction channel. Users can choose to attach either a LUER port with stopcocks (Part Number: 11014L) or a double LUER port (Part Number: 11014LU) to the working channel port. In terms of optics, it has direction of view of 0 degrees and field of view of 100 degrees.

The provided document does not describe the acceptance criteria or a study that proves the device meets those criteria in the context of diagnostic performance (e.g., sensitivity, specificity, accuracy). Instead, it focuses on the substantial equivalence of the Flexible HD Cysto-Urethroscope System to predicate devices based on non-clinical performance data, primarily concerning electrical safety, EMC, biocompatibility, and reprocessing validation.

Here's an analysis of the available information:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not provide a table with specific performance metrics like sensitivity, specificity, or image quality scores that would typically be associated with acceptance criteria for diagnostic devices. Instead, the "performance" is demonstrated through compliance with various safety and technical standards for medical devices.

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

No sample size for a "test set" in the context of diagnostic performance (e.g., patient data, image dataset) is mentioned. The studies performed were non-clinical bench testing to evaluate electrical safety, EMC, biocompatibility, and reprocessing. These tests involve laboratory procedures on device components or the entire device, not on human subjects or patient data. Therefore, data provenance (country of origin, retrospective/prospective) is not applicable in this context.

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

Not applicable. Since the studies were non-clinical bench tests (e.g., electrical measurements, material testing, sterilization efficacy), there was no "ground truth" to be established by experts in the diagnostic sense. The results of these tests are typically evaluated against established engineering specifications and regulatory standards.

4. Adjudication Method for the Test Set:

Not applicable for the same reasons as above. There was no need for expert adjudication for non-clinical bench testing.

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

No, an MRMC comparative effectiveness study was not done. The document explicitly states: "Clinical testing was not required to demonstrate the substantial equivalence to the predicate devices. Non-clinical bench testing was sufficient to establish the substantial equivalence of the modifications." This indicates that there was no human reader study, and therefore, no effect size of AI assistance could be determined.

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

No, a standalone algorithm performance study was not done. This device is a physical endoscope system, not an AI algorithm.

7. The Type of Ground Truth Used:

As noted, there was no "ground truth" in the diagnostic context. For the non-clinical tests, the "ground truth" implicitly refers to the established scientific and regulatory standards (e.g., specific voltage limits for electrical safety, acceptable cytotoxicity levels for biocompatibility, sterility assurance levels for reprocessing).

8. The Sample Size for the Training Set:

Not applicable. This device is not an AI/ML algorithm that requires a training set.

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

Not applicable for the same reason as above.

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