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This instrument has been designed to be used with an Olympus Light Source, documentation equipment, display monitor, suction pump, Endo-Therapy accessories, and other ancillary equipment for endoscopic diagnosis and treatment within the bladder, urethra and kidney.

The subject device, the XCYF-TP3 is basically identical to the predicate device (XCYF-1T3) which is the flexible endoscope for use in the bladder, urethra and kidney. Subject device may be used with three different Light source as follow, · A rechargeable powered Miniature Light source, or, · A battery powered Miniature Light source as predicate device, XENF-DP, or, · Light guide cable as predicate device, XENF-DP. In conclusion, this subject device is technically the same as the predicate device, which we describe in the table above.

The provided text is a 510(k) summary for the Olympus XCYF-TP3 Cystofiberscope/Nephrofiberscope. This type of submission focuses on demonstrating substantial equivalence to a legally marketed predicate device rather than presenting a detailed study proving the device meets specific acceptance criteria as would be found in a clinical trial report for a novel device. As such, the information you've requested regarding acceptance criteria and performance studies is not explicitly detailed in the provided document in the format you expect for a new, AI-enabled medical device.

However, I can extract information related to the demonstration of substantial equivalence, which is the core of this 510(k) submission.

Here's an interpretation based on the provided text, addressing your questions where possible:

1. A table of acceptance criteria and the reported device performance

The document does not provide a table of acceptance criteria and reported device performance in the form of specific quantitative metrics for sensitivity, specificity, accuracy, etc., as would be seen for an AI-enabled diagnostic device. Instead, the "acceptance criteria" for a 510(k) submission are based on demonstrating substantial equivalence to a predicate device. The "performance" is implicitly deemed acceptable if it's shown to be equivalent in terms of intended use, technological characteristics, and safety and effectiveness.

Here's how we can frame it based on the document:

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)

The document states, "Therefore, the clinical data is not necessary for its evaluation of safety and efficacy." This indicates that no dedicated clinical test set or study was required or performed to demonstrate performance for this 510(k) submission, as substantial equivalence was established through technical and design comparisons to the predicate device.

3. 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)

Since no separate clinical data or test set was generated for this 510(k), no experts were used to establish ground truth in the context of a new performance study. The "ground truth" for substantial equivalence rests on the predicate device's established safety and effectiveness.

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

As no specific test set was generated or analyzed for performance, no adjudication method was applied.

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 MRMC study was conducted, nor is this device an AI-assisted diagnostic tool. It is a traditional endoscope.

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

Not applicable, as this is a physical medical device (an endoscope), not a standalone algorithm.

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

The "ground truth" for this 510(k) approval rests on the established safety and effectiveness of the legally marketed predicate device (Olympus XCYF-1T3). This implies that the predicate device's performance was previously demonstrated or accepted, likely through a combination of design validation, materials testing, and potentially prior clinical use or previous 510(k) submissions that established its safety and effectiveness.

8. The sample size for the training set

Not applicable. This device is an endoscope, not an AI model, and therefore does not have a "training set" in the machine learning sense.

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

Not applicable. See point 8.

In summary, the provided document is a 510(k) notification for a physical medical device (an endoscope), not an AI/ML-powered diagnostic tool. Therefore, it focuses on demonstrating substantial equivalence to a predicate device through technical comparisons, rather than presenting a performance study with acceptance criteria, test sets, or ground truth establishment as would be done for a novel, data-driven device.

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