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Vesair Cystoscopes are indicated to provide the user with the means for endoscopic diagnostic and therapeutic surgical procedures. Examples for the devices include the visualization and manipulation of anatomy as the surgeon deems appropriate. Vesair Cystoscopes are intended to be used in general urological surgery through a minimally invasive approach by utilizing natural orifices to access the surgical site.

The Vesair Cystoscopes described in this submission are rigid reusable endoscopes for visualization of the operating site during cystoscopic minimally invasive procedures in conjunction with a commercially available light guide, light source, video camera, monitor, and printer. Light that is created by an external light source is transmitted from the endoscope's light guide connector through the endoscope itself to the tip via a fiber optic system. Images are transferred the other way back through a rigid lens system.

Technical parameters of the Vesair Cystoscopes that characterize the optical view are the Direction of View (0°, 30°, 70°) and the Field of View (105°). The image can be displayed by a camera/monitor system which can be connected to the endoscope eyepiece. The Vesair Cystoscopes have the same diameter (4mm), and are available in different lengths of the insertion tube (0° - 280mm length, 30° - 185mm or 278mm length, 70° - 185mm or 281mm length). None of the cystoscope models have a working channel. Like other currently marketed rigid cystoscopes, all models have patient-contacting outer surfaces mainly made from metal (304 stainless steel) and incorporate fiber optics for light transmission and rigid lenses for image transmission.

Each cystoscope model is provided non-sterile and requires cleaning and steam sterilization prior to use and between subsequent uses.

The provided text describes the Vesair Cystoscopes, which are rigid reusable endoscopes, and details their comparison to predicate and reference devices for a 510(k) submission. However, it does not describe an AI/ML device or a study that establishes ground truth through expert consensus, pathology, or outcomes data, nor does it include information on a multi-reader multi-case (MRMC) comparative effectiveness study, standalone algorithm performance, or training set details.

Therefore, most of the requested information regarding AI device acceptance criteria and study details cannot be extracted from this document.

The document focuses on demonstrating substantial equivalence to legally marketed predicate devices based on technological characteristics and performance testing relevant to an endoscope, not an AI/ML system.

Here's a breakdown of what can be extracted and what cannot:

1. Table of Acceptance Criteria and Reported Device Performance:

The document does not explicitly state "acceptance criteria" in the context of an AI/ML device's performance metrics (e.g., sensitivity, specificity, AUC). Instead, it lists performance tests conducted for a medical device (endoscope) and reports that these tests met the required specifications.

2. Sample size used for the test set and data provenance:

• Test set sample size: Not applicable/Not provided. The performance testing described (reprocessing, biocompatibility, safety, shelf-life, optical quality) relates to the physical and functional characteristics of the endoscope, not an AI model evaluated on a data set.
• Data Provenance: Not applicable/Not provided. The tests described are bench tests or laboratory analyses on the device itself, not data derived from patients or clinical sources.

3. Number of experts used to establish the ground truth for the test set and qualifications of those experts:

• Not applicable/Not provided. Ground truth in the context of expert consensus for AI/ML performance is not relevant to this device's submission which is for an endoscope. The tests performed would have relied on standard testing methodologies and equipment, not clinical experts establishing ground truth for data interpretation.

4. Adjudication method for the test set:

• Not applicable/Not provided. Adjudication methods (e.g., 2+1, 3+1) are used for resolving discrepancies in expert interpretations to establish ground truth for AI/ML models. This is not relevant to the described device testing.

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:

• No, a MRMC comparative effectiveness study was not done. This type of study is specific to evaluating diagnostic AI/ML devices in conjunction with human readers, which is not what the Vesair Cystoscopes are.

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

• No, a standalone algorithm performance study was not done. The Vesair Cystoscopes are physical medical devices (endoscopes) and do not involve an algorithm.

7. The type of ground truth used:

• Not applicable/Not provided. The concept of "ground truth" (expert consensus, pathology, outcomes data) as it applies to AI/ML device validation is not relevant here. The "truth" for the performance tests would be established by reference standards, validated methods, and compliance with specifications.

8. The sample size for the training set:

• Not applicable/Not provided. This device is not an AI/ML system and therefore does not have a training set.

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

• Not applicable/Not provided. As there is no AI component, there is no training set or associated ground truth establishment.

In summary, the provided text describes a traditional medical device (cystoscope) submission and its performance testing, which does not involve AI or the associated methodologies for validating AI/ML performance.

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