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AnQing Medical Single Use Flexible Cystoscope is used to provide visualization and operative access during diagnostic and therapeutic endoscopic procedures of the lower urinary tract, including the bladder and urethra.

The Flexible Cystoscope is intended for use in a hospital environment or medical office environment. The Flexible Cystoscope is designed for use in adults.

The Flexible Cystoscope (Model: CY50H-20EU, CY50H-20US, CY55H-24EU, CY55H-24US) is a sterile single-use endoscope which is used with the video processor (Model: EOS-H-01, FDA cleared #K211169) produced by AnQing for providing endoscopic imaging of the lower urinary tract, including the bladder and urethra for the purpose of diagnosis and treatment.

The CY50H-20 and CY55H-24 difference is the size of Distal End Outer Diameter and Working Channel Inner Diameter. The US and EU model are identical except the deflection versions, which is opposite from each other (EU version or US version).

The Flexible Cystoscope is a single-use endoscope, which consists of Handle, Insertion Section, Distal Tip, and Endoscope Connector.

The handle includes a deflection lever, a lever lock, a push button for picture taking/video recording and a Luer port for insertion of accessory devices and irrigation to the working channel. The insertion contains one working channel and wiring to transmit the image signals to the Video Processor. The distal bending section of the insertion section is controlled by the user via the deflection lever on the handle. The distal end of the insertion section contains a CMOS sensor for capturing image and transmitting it to the Video Processor, LEDs for illumination, and the distal opening of the working channel. The endoscope connector connects the endoscope handle to the video processor, which provides power and processes video signals from the endoscope.

The provided document does not describe the acceptance criteria and study proving device meets acceptance criteria in the format requested. Specifically, it does not include a table of acceptance criteria vs. device performance, or details regarding sample sizes, data provenance, ground truth establishment, expert qualifications, adjudication methods, MRMC studies, or standalone algorithm performance.

The document is a 510(k) premarket notification for a Flexible Cystoscope, primarily focusing on demonstrating substantial equivalence to a predicate device (Ambu aScope 4 Cysto) through non-clinical testing.

Here's a breakdown of the information that is available in relation to your request, and what is missing:

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

• Not explicitly provided in the requested format. Instead, the document provides a "Comparison with Predicate Device" table (pages 5-6) which compares various physical, optical, and technological characteristics of the subject device to the predicate device. However, this table lists characteristics and indicates "Same" or "Similar" for comparison, rather than specific acceptance criteria and quantitative performance results for each criterion.
• "Summary of Testing" (page 8-9) lists the types of non-clinical tests performed (Electrical Safety, EMC, Photobiological safety, Mechanical and Optical Performance, Biocompatibility, Sterilization, Shelf life, Package Validation) and the standards they comply with, but does not provide specific acceptance criteria or performance values for the subject device against these criteria.

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

• Not provided. The document describes non-clinical bench testing, but does not specify sample sizes for these tests or the origin of any data (as it's physical device testing, not data collection from patients).

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)

• Not applicable/Not provided. This type of information is typically relevant for AI/ML-based devices where expert-labeled datasets are used to establish ground truth. The Flexible Cystoscope is a physical medical device, and its performance is evaluated against engineering specifications and standards, not against expert-established ground truth on medical images or diagnoses.

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

• Not applicable/Not provided. As above, this is relevant for AI/ML evaluation, not for the direct performance testing of a physical endoscope.

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, not done. The document explicitly states under "Summary of Clinical Tests" (page 9): "The subject of this premarket submission, did not require clinical studies to support substantial equivalence." This means no human-in-the-loop or MRMC studies were conducted.

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

• Not applicable/Not done. The device is a physical cystoscope, not an algorithm.

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

• Not applicable/Not provided. The "ground truth" for this device's performance relies on established engineering standards (e.g., ISO 8600 for optical measurements, IEC 62471 for photobiological safety, ISO 10993 for biocompatibility) and direct physical measurements and tests of the device's characteristics (e.g., outer diameter, working length, deflection, depth of field).

8. The sample size for the training set

• Not applicable/Not provided. There is no AI/ML component, so no training set.

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

• Not applicable/Not provided. There is no AI/ML component, so no training set or ground truth for it.

In summary, the provided document details the non-clinical testing and comparison of a flexible cystoscope to a predicate device to demonstrate substantial equivalence, rather than providing the specific AI/ML-related performance evaluation details requested.

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