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510(k) Data Aggregation

    K Number
    K180341
    Date Cleared
    2018-08-03

    (177 days)

    Product Code
    Regulation Number
    876.1500
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    FUJIFILM 600 Series Endoscope EG-600WR v2

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

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

    Device Description

    FUJIFILM 600 Series Endoscope EG-600WR v2 is an upper gastrointestinal endoscope that captures images when used in combination with a video processor and light source. Light travels from the light source, through the glass fiber bundles in the endoscope, and out 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.

    AI/ML Overview

    The provided text describes the Fujifilm 600 Series Endoscope EG-600WR v2, a medical device intended for the visualization and treatment of the upper digestive tract. It details a 510(k) premarket notification for this device, claiming substantial equivalence to a predicate device (Fujifilm 600 Series Endoscopes EC-600WL and EG-600WR, K132210).

    However, the document does not contain information about an AI/ML-driven medical device, nor does it describe a study involving algorithms, human-in-the-loop performance, or reader studies with experts for ground truth establishment.

    The provided text focuses on the endoscope device itself, and the modifications made to it. The performance testing outlined is for the physical device's characteristics (e.g., field of view, bending capability, resolution, safety, and reprocessing).

    Therefore, I cannot provide the requested information regarding acceptance criteria and studies for an AI/ML device because the document describes a physical medical endoscope and not an AI/ML system.

    If the request refers to the acceptance criteria for the physical endoscope, the available information is as follows:

    1. Table of Acceptance Criteria and Reported Device Performance:

    The document states: "In all cases, the device met the pre-defined acceptance criteria for the test." However, the specific numerical acceptance criteria for each performance parameter are not explicitly listed in the provided text. Only the parameters tested are mentioned.

    Acceptance Criteria (Not Explicitly Stated)Reported Device Performance
    Field of viewMet pre-defined criteria
    Bending capabilityMet pre-defined criteria
    Air supply rateMet pre-defined criteria
    Water supply rateMet pre-defined criteria
    Suction rateMet pre-defined criteria
    Working lengthMet pre-defined criteria
    Forceps channel diameterMet pre-defined criteria
    Viewing directionMet pre-defined criteria
    ResolutionMet pre-defined criteria
    LG output (Light Guide Output)Met pre-defined criteria
    Electrical safety (ANSI/AAMI ES60601-1, etc.)Compliant
    Biocompatibility (ISO 10993)Compliant
    Endoscopic performance (ISO 8600-1)Compliant
    Cleaning, high-level disinfection, sterilization validationCompliant
    Storage and transportation validationCompliant

    2. Sample sized used for the test set and the data provenance: Not applicable as this is a physical device and not a data-driven AI/ML system. The testing involved samples of the physical endoscope.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth as typically understood for AI/ML models (e.g., expert consensus on image findings) is not relevant for the performance testing of a physical endoscope.

    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. This document is not about an AI-assisted device.

    6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done: Not applicable. This is not an algorithm.

    7. The type of ground truth used (expert concensus, pathology, outcomes data, etc): For the physical device, performance was evaluated against technical specifications and consensus standards (e.g., ISO 8600-1 for endoscopic performance, IEC and ISO for safety and biocompatibility).

    8. The sample size for the training set: Not applicable. This is a physical device, not an AI/ML model.

    9. How the ground truth for the training set was established: Not applicable. This is a physical device, not an AI/ML model.

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