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The Cellvizio® 100 Series System with Confocal Miniprobes™ is a confocal laser system with fiber optic probes that are intended to allow imaging of the internal microstructure of tissues.

The CystoFlex™ UHD R Confocal Miniprobe can be used within anatomical tracts, i.e., urinary, including, but not limited to, urethra, bladder, and ureter, accessed through an endoscope or endoscopic accessories.

The CystoFlex UHD R Confocal Miniprobe, when used as part of the Cellvizio 100 Series system and the Cellvizio system, is intended to allow confocal laser imaging of the internal microstructure of tissues in anatomical tracts, i.e., urinary, including, but not limited to, urethra and bladder, accessed through an endoscope or endoscopic accessories.

The CystoFlex UHD R Confocal Miniprobe is similar in design to the UroFlex B Confocal Miniprobe, except for its distal optical head, which is a UHD-type distal head. The CystoFlex UHD R Confocal Miniprobe can be inserted into endoscope lumens with inner diameter equal to or higher than 2.8mm, allowing them to work in currently used rigid cystoscopes.

The provided text describes a 510(k) premarket notification for the Cellvizio 100 Series System with Confocal Miniprobes, specifically focusing on the CystoFlex UHD R Confocal Miniprobe. The submission aims to demonstrate substantial equivalence to a previously cleared predicate device, the UroFlex B Confocal Miniprobe.

Here's an analysis of the acceptance criteria and study information based on the provided text:

1. Table of Acceptance Criteria and Reported Device Performance:

The document primarily focuses on demonstrating substantial equivalence to a predicate device rather than defining new, specific performance acceptance criteria for a novel AI device. The "performance" assessment is based on the device's technical specifications and physical design modifications.

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

The document does not explicitly mention "test sets," "sample sizes," or "data provenance" in the context of clinical studies for performance metrics. The testing described is primarily engineering and design verification/validation directly related to the physical changes and compatibility of the device.

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

This information is not provided in the document. As the submission is for a physical medical device (confocal miniprobe) and focuses on substantial equivalence based on design and technical specifications, rather than AI algorithm performance requiring expert-adjudicated ground truth, this type of information is not relevant to the content provided.

4. Adjudication Method for the Test Set:

This information is not provided and is not relevant given the nature of the submission (hardware modification seeking substantial equivalence).

5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size of How Much Human Readers Improve with AI vs Without AI Assistance:

This information is not applicable/not provided. The device is a confocal miniprobe for imaging, not an AI-assisted diagnostic or decision-support system for human readers. Therefore, an MRMC study related to AI assistance is not relevant to this submission.

6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done:

This information is not applicable/not provided. The device is a physical diagnostic tool for imaging, not a standalone algorithm.

7. The Type of Ground Truth Used:

The "ground truth" in this context is primarily related to the engineering specifications and functional performance of the physical device and its compatibility. For example, fitting into a cystoscope with a certain internal diameter, or ensuring biocompatibility. It's not about clinical diagnostic accuracy against a definitive pathological diagnosis for patient cases as would be seen with an AI diagnostic tool.

8. The Sample Size for the Training Set:

This information is not applicable/not provided. The device is not an AI algorithm that requires a training set.

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

This information is not applicable/not provided. The device is not an AI algorithm that requires a training set.

Summary of what the document focuses on:

The provided document is a 510(k) summary for a physical medical device (confocal miniprobe). The core argument for FDA clearance is substantial equivalence to a previously cleared predicate device. This equivalence is established by:

• Demonstrating that the fundamental technology and operating principles are unchanged.
• Confirming that the indications for use are identical.
• Detailing minor design modifications (distal optical head) and providing verification and validation testing to show these modifications meet design specifications and user needs.
• Ensuring biocompatibility remains unchanged.
• Verifying compatibility with existing medical equipment (cystoscopes) for the stated use.

Therefore, the study information requested (e.g., sample sizes for test/training sets, expert ground truth, adjudication methods, MRMC studies, standalone AI performance) is typically relevant for AI/software as a medical device (SaMD) submissions, not for this type of hardware-focused 510(k) submission based on substantial equivalence to an existing device with minor design changes.

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