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The Flexible Video-Choledochoscope is indicated for use in diagnostic and therapeutic applications during endoscopic procedures in the pancreatico-biliary system including the hepatic ducts.

Flexible Video-Choledochoscope is a kind of medical instrument, also known as optical camera, which can enter into the human biliary and pancreatic duct for observation and diagnosis. The operator delivers the optical camera system to the site of diagnosis and treatment by means of a mechanical part with a flexible insertion tube and a system of bends. This device must be used with a duodenoscope. The product is equipped with tiny size digital imaging parts -- photoelective sensors "CMOS", on which the objects in human cavity will be transferred though lens optical system, and converts light signals. The electrical signal will be transferred to Imaging Processor System (Including Light Source) and display images on its monitor output for doctor observation and diagnosis.

I am sorry, but the provided text does not contain information about the acceptance criteria and the study that proves the device meets those criteria. The document is an FDA 510(k) clearance letter for a Flexible Video-Choledochoscope, which asserts substantial equivalence to a predicate device based on technical and performance characteristics.

Specifically, the document mentions:

• No Clinical Study is included in this submission. (Section 5.9 Clinical Test Data)
• Non-clinical Performance Data: "The following performance tests were conducted to substantial equivalence: mechanical performance: duodenosoone compatibility testing and flexible surgical instrument compatibility testing and comparison performance testing." (Section 5.8 Non-clinical Performance Data)

Therefore, I cannot provide the detailed information requested in your prompt regarding acceptance criteria, device performance, sample sizes, ground truth establishment, or any comparative effectiveness studies.

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The Flexible Video-Choledo-Cysto-Ureteroscope System is indicated for endoscopic examination in the urinary tract and can be used percutaneously to examine the interior of the kidney, and using additional accessories, to perform various diagnostic and therapeutic procedures. The Flexible Video-Choledo-Cysto-Ureteroscope System is also indicated for the examination of bile ducts surgically, and using additional accessories, to perform various diagnostic and therapeutic procedures during cholecystectomy.

Imaging Processor System (Including Light Source) is composed of lighting system, image processing board. The lighting system provides the light source for the endoscope probe at the back end. The image processing board receives electronic signals from the front-end camera module and processes them, and finally transmits them to the display through the video interface. Flexible Video-Choledo-Cysto-Ureteroscope is a kind of medical electronic optical instrument, also known as optical camera, which can enter into the human bladder, ureter, biliary and pancreatic duct for observation and diagnosis. The operator delivers the optical camera system to the site of diagnosis and treatment by means of a mechanical part with a flexible insertion tube and a system of bends. The product is equipped with tiny size digital imaging parts -- photoelectric sensors "CMOS", on which the objects in human cavity will be transferred though lens optical system, and converts light signals into electrical signals. The electrical signal will be transferred to Imaging Processor System (Including Light Source) and display images on it's monitor output for doctor observation and diagnosis.

This document is a 510(k) premarket notification for a new medical device, the Flexible Video-Choledo-Cysto-Ureteroscope System (PL-2100). This type of submission relies on demonstrating "substantial equivalence" to a predicate device, meaning it's as safe and effective as a device already legally marketed. Therefore, the "study" referred to is primarily a non-clinical performance evaluation comparing the proposed device to a predicate device, rather than a clinical trial or AI-specific validation study typically associated with AI/ML devices.

Here's an analysis of the provided information concerning acceptance criteria and the "study":

1. Table of Acceptance Criteria and Reported Device Performance:

The document provides a comparative table between the proposed device (PL-2100) and its primary predicate device (Flexible Video-Choledo-Cysto-Ureteroscope System, K211686, Model: PL-1000). The "acceptance criteria" are implied by the predicate device's characteristics, and the "reported device performance" are the proposed device's characteristics. The goal is to show they are "Same" or "Similar" in ways that don't raise new questions of safety or effectiveness.

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

The document explicitly states: "No Clinical Study is included in this submission." This means there isn't a "test set" in the sense of patient data used for algorithm validation. The evaluation is primarily based on non-clinical engineering and performance testing.

3. Number of Experts Used to Establish Ground Truth and Qualifications:

Not applicable, as no clinical study or expert-adjudicated ground truth dataset was used for device efficacy or performance evaluation in this 510(k) submission.

4. Adjudication Method for the Test Set:

Not applicable, as no clinical study or expert adjudication process for a test set was performed.

5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

Not applicable. This device is an endoscope system, not an AI/ML-assisted diagnostic device that would typically undergo an MRMC study to evaluate human reader improvement with AI assistance.

6. Standalone Algorithm Performance:

Not applicable. The device is a hardware system (endoscope and imaging processor), not a standalone algorithm.

7. Type of Ground Truth Used:

For the non-clinical performance and safety evaluations, the "ground truth" is established by international and national standards (e.g., IEC 60601-1, IEC 60601-1-2, ISO 10993) and the specified performance characteristics of the predicate device. The proposed device's performance is measured against these established engineering and safety benchmarks.

8. Sample Size for the Training Set:

Not applicable. This is not an AI/ML device, so there is no "training set."

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

Not applicable, as there is no training set for an AI/ML algorithm.

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The values are used in conventional gastrointestinal endoscope to control the functions of water/gas injection and suction during the endoscopic operation.

Disposable Endoscope Valves Kit consists of Water/gas button, Attraction button, Biopsy cap and Water injection adapter. Disposable Endoscope Valves Kit connect the endoscope operating handle matched with the model, and install the water gas button into the water gas port of the operating handle; Align the positioning boss of the suction button with the card slot of the operating handle and install it into the suction port; Install the biopsy cap into the clamp opening of the operating handle.

The provided text describes the acceptance criteria and a study demonstrating the substantial equivalence of the "Disposable Endoscope Valves Kit" to a predicate device. However, it does not include information typically found in studies proving an AI/ML device meets acceptance criteria, such as specific performance metrics like sensitivity, specificity, or AUC, detailed sample sizes for test sets, expert qualifications, or adjudication methods for ground truth.

This document is a 510(k) summary for a medical device that does not appear to be an AI/ML device. It seems to be a physical medical accessory. Therefore, the questions related to AI/ML specific criteria (such as effect size of human readers with AI vs without AI, standalone algorithm performance, training set details) are not applicable to this submission.

The study described is a non-clinical performance data study, not a clinical study involving AI/ML.

Here's an attempt to answer the relevant questions based on the provided text, while noting the limitations due to the nature of the device:

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

The document frames "acceptance criteria" as meeting regulatory standards and demonstrating substantial equivalence to a predicate device through non-clinical testing. It doesn't list quantitative performance metrics for the proposed device in the way one would for an AI/ML diagnostic tool (e.g., sensitivity, specificity).

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

The document mentions "bench tests" were performed. For these non-clinical performance tests (Appearance, Physical properties), the specific sample size is not explicitly stated, nor is the data provenance. These would typically involve testing a certain number of manufactured units.

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

This question is not applicable as the device is a physical accessory and the evaluation is based on engineering and material standards, not diagnostic interpretation requiring expert ground truth in the AI/ML context.

4. Adjudication method for the test set

This question is not applicable for the same reasons as above. The evaluation of appearance and physical properties would follow established testing protocols and standards, not a clinical adjudication process.

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 such study was conducted or reported. This type of study is relevant for AI/ML diagnostic devices, which this device is not. The document explicitly states: "No Clinical Study is included in this submission."

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

This question is not applicable. The device is a physical endoscope accessory, not an algorithm.

7. The type of ground truth used

For the non-clinical tests (biological evaluation, sterilization, appearance, physical properties), the "ground truth" would be compliance with established international standards (ISO series) and predefined specifications for the physical characteristics of the device. This is not "expert consensus, pathology, or outcomes data" in the typical sense of AI/ML diagnostic validation.

8. The sample size for the training set

This question is not applicable as this is not an AI/ML device and therefore does not have a "training set."

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

This question is not applicable for the same reason as above.

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