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This device is intended for the visualization of the duodenum and upper digestive tract, specifically for the observation, diagnosis, and endoscopic treatment of the esophagus, stomach, and duodenum.

FUJIFILM Duodenoscope Model ED-580XT is comprised of three general sections: a control portion, an insertion portion and an umbilicus. The control portion controls the angulation of the endoscope. This portion also controls the flexibility of the distal end in the endoscope. The insertion portion contains glass fiber bundles, several channels and a complementary Charge-Coupled Device (CCD) image sensor in its distal end. The insertion portion assist in delivering air/suction as well as endoscope accessories, such as forceps. The glass fiber bundles allow light to travel through the endoscope and emit light from the tip of the insertion to illuminate the body cavity. This provides enough light to the CCD image sensor to capture an image and display it on the monitor. The umbilicus consists of electronic components needed to operate the endoscope when plugged in to the video processor and the light source. The endoscope is used in combination with FUJIFILM's video processors, light sources and peripheral devices such as monitor, printer, foot switch, and cart. All of these combinations were previously cleared in K152257 and K172916.

The provided text describes the regulatory clearance of the FUJIFILM Duodenoscope Model ED-580XT and its substantial equivalence to a predicate device. However, it does not contain information about acceptance criteria and a study proving device performance in the context of an AI/algorithm-based medical device.

The document primarily focuses on technical aspects, such as electrical safety, biocompatibility, endoscope-specific testing, cleaning/disinfection validation, and usability. It confirms that the device met performance specifications in various categories (field of view, bending capability, air/water/suction rates, working length, etc.), but these are standard engineering and safety performance metrics for a physical medical device, not AI performance metrics.

Therefore, I cannot provide the requested information for acceptance criteria and a study proving "device performance" in the AI context based on the given text. The questions regarding sample size, data provenance, expert qualifications, adjudication methods, MRMC studies, standalone performance, and ground truth are not applicable to the type of device and information presented.

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