Search Results

The FUJIFILM Endoscope Models EC-600HL and EC-600LS are intended for the visualization of the lower digestive tract, specifically for the observation, diagnosis, and endoscopic treatment of the rectum and large intestine.

The FUJIFILM Endoscope Models EC-600HL and EC-600LS are comprised of three main sections: an operation section, an insertion portion, and an umbilicus. The operation controls the angulation (up/down/left/right) of the distal end of the endoscope. The insertion contains glass fiber bundles, several channels and a complementary metal-oxide-semiconductor (CMOS) image sensor. The qlass fiber bundles allow light to travel through the endoscope and emit light from the tip of the insertion portion to illuminate the body cavity. This provides enough light to the CMOS image sensor to capture an image and display it on the monitor. The endoscope also contains several channels to deliver air/water and provide suction, as well as a forceps channel. The forceps channel is used to introduce endoscope accessories such as biopsy forceps during the procedure. The umbilicus section consists of electronic components needed to operate the endoscope when plugged in to the video processor and the light source.

The subject device is used in combination with FUJIFILM's video processor, light source and peripheral devices such as water tank, endoscope accessories, monitor, printer, electrosurgical instruments, foot switch, and cart. All of these were previously cleared in K132210.

This document is a 510(k) summary for the Fujifilm Endoscope Models EC-600HL and EC-600LS. It primarily focuses on demonstrating substantial equivalence to a predicate device (FUJIFILM 600 Series Endoscope EC-600WL) rather than establishing novel acceptance criteria or a comprehensive study proving a device meets specific performance metrics for image interpretation by an AI.

Therefore, many of the requested categories for AI-related performance studies cannot be filled as this document concerns a physical endoscope device and its safety/effectiveness, not an AI algorithm for image analysis.

Here's an attempt to address the requested information based only on the provided text, recognizing that much of it is not applicable:

1. Table of Acceptance Criteria and Reported Device Performance

The submission does not specify discrete acceptance criteria in terms of numerical performance metrics for clinical outcomes (e.g., diagnostic accuracy, sensitivity, specificity) for the endoscope's visualization capabilities. Instead, the "acceptance criteria" are implied by adherence to recognized consensus standards for safety and performance of medical devices. The reported device performance is that it meets these standards and is substantially equivalent to the predicate.

Regarding AI-specific questions:

Since this document describes a physical endoscope, not an AI-powered diagnostic device or software, the following information is not present in the provided text:

2. Sample size used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective): Not applicable. The "performance data" refers to technical bench testing against consensus standards, not a clinical study with patient data used for AI evaluation.
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. Ground truth for clinical diagnostic performance is not established as this is a hardware submission, not an AI diagnostic tool.
4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
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: Not applicable.
6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not applicable.
7. The type of ground truth used (expert concensus, pathology, outcomes data, etc): Not applicable in the context of AI diagnostic performance. The "ground truth" for the endoscope itself is its demonstrable adherence to safety and performance standards through engineering and biocompatibility testing.
8. The sample size for the training set: Not applicable. There is no AI training set mentioned.
9. How the ground truth for the training set was established: Not applicable. There is no AI training set mentioned.

Ask a specific question about this device