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510(k) Data Aggregation

    K Number
    K182102
    Date Cleared
    2019-02-06

    (187 days)

    Product Code
    Regulation Number
    874.4760
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    This instrument is intended to be used with an Olympus video system center, light source, documentation equipment, display monitor, and other ancillary equipment for endoscopic diagnosis. This instrument is indicated for use within the nasal lumens and airway anatomy (including nasopharynx and trachea).

    Device Description

    This instrument is intended to be used with an Olympus video system center, light source, documentation equipment, display monitor, and other ancillary equipment for endoscopic diagnosis. This instrument is indicated for use within the nasal lumens and airway anatomy (including nasopharynx and trachea).

    It mainly consists of four functional parts:

    • video connection section including a video connector and video cable that connects the endoscope to the video system center for displaying images on compatible video monitors.
    • light guide connector section that links the endoscope with light source and transmits light to the distal end of the endoscope.
    • control section that operates endoscope such as controlling angulation to guide insertion and observation.
    • insertion section that goes through and contacts with the nasal lumens and airway anatomy (including nasopharynx and trachea) under light guide.
    AI/ML Overview

    The provided text describes the regulatory clearance for the Olympus RHINO-LARYNGO VIDEOSCOPE ENF-VH2 and ENF-V4 devices and details various performance tests conducted. However, it does not contain specific acceptance criteria, reported device performance metrics (such as sensitivity, specificity, or accuracy), or explicit details about a study designed to prove the device meets such criteria in the quantifiable manner typically seen for AI/ML medical devices.

    The document focuses on demonstrating substantial equivalence to a predicate device (VISERA RHINO-LARYNGO VIDEOSCOPE OLYMPUS ENF TYPE V2, K061313) through non-clinical and some clinical testing, primarily for safety, durability, and basic functionality of an endoscope.

    Here's an attempt to answer your questions based only on the provided text, highlighting where information is absent:


    1. Table of Acceptance Criteria and Reported Device Performance

    The document lists various performance tests but does not provide a table with quantifiable acceptance criteria or reported performance metrics (like sensitivity, specificity, or accuracy) for the device's diagnostic capabilities. The tests are generally focused on safety, functionality, and manufacturing compliance.

    Acceptance Criteria CategorySpecific Test/EvaluationAcceptance Criteria (from text)Reported Device Performance (from text)
    ReprocessingReprocessing Validation Testing"conducted and documentation was provided as recommended by Guidance for Industry and Food and Drug Administration Staff, 'Reprocessing Medical Devices in Health Care Setting: Validation Methods and Labeling'"Implied: Complies with relevant guidance for reprocessing.
    BiocompatibilityCytotoxicity Study"conducted in accordance with FDA's Guidance for Industry and Food and Drug Administration Staff, Use of International Standard ISO 10993-1..."Implied: Complies with ISO 10993-1.
    Intracutaneous Study in Rabbits"conducted in accordance with FDA's Guidance for Industry and Food and Drug Administration Staff, Use of International Standard ISO 10993-1..."Implied: Complies with ISO 10993-1.
    Guinea Pig Maximization Sensitization Test"conducted in accordance with FDA's Guidance for Industry and Food and Drug Administration Staff, Use of International Standard ISO 10993-1..."Implied: Complies with ISO 10993-1.
    SoftwareSoftware Verification and Validation"conducted and documentation was provided as recommended by FDA's Guidance for Industry and FDA Staff, 'Guidance for the Content of Premarket Submissions for Software Contained in Medical Devices' and 'Content of Premarket Submissions for Management of Cybersecurity in Medical Devices'."Implied: Complies with relevant FDA software guidance.
    Electrical Safety & EMCElectrical Safety Testing"The system complies with the ANSI/AAMI ES 60601-1:2005/(R)2012 and A1:2012 and IEC 60601-2-18:2009 standards for safety"Complies with listed standards.
    EMC Testing"and the IEC 60601-1-2:2014 standards for EMC."Complies with listed standard.
    Bench PerformanceThermal Safety Test"conducted to ensure that the subject device performs as intended and meet design specifications."Implied: Meets design specifications.
    Mechanical Durability Test"conducted to ensure that the subject device performs as intended and meet design specifications."Implied: Meets design specifications.
    Optical Performance Test"conducted to ensure that the subject device performs as intended and meet design specifications."Implied: Meets design specifications.
    Color Performance Test"conducted to ensure that the subject device performs as intended and meet design specifications."Implied: Meets design specifications.
    Clinical PerformanceEvaluation for supporting evidence of marketing claim"conducted to support the market claims."Implied: Supports market claims. (No specific quantifiable metrics given).
    Meta-analysis"conducted to support the market claims."Implied: Supports market claims. (No specific quantifiable metrics given).
    Risk AnalysisRisk analysis based on ISO 14971:2007"established in-house acceptance criteria based on ISO 14971:2007""The design verification tests and their acceptance criteria were identified and performed as a result of this risk analysis assessment."

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

    The document mentions "Clinical testing for ENF-VH2 and ENF-V4... was conducted to support the market claims" including an "Evaluation for supporting evidence of marketing claim" and "Meta-analysis." However, no specific sample sizes for the test set or information about the country of origin of the data, or whether it was retrospective or prospective, are provided.

    3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications

    This information is not provided in the document. The general nature of the clinical testing ("Evaluation for supporting evidence of marketing claim") doesn't specify how ground truth was established or if experts were involved in a quantifiable assessment.

    4. Adjudication Method for the Test Set

    This information is not provided in the document.

    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

    The document does not indicate that an MRMC comparative effectiveness study was done, nor does it mention AI. The device described is an endoscope, not an AI-powered diagnostic tool in the sense of image interpretation software.

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

    This question is not applicable as the device is a videoscope, which is a physical instrument for visualization, not a standalone algorithm.

    7. The Type of Ground Truth Used (expert consensus, pathology, outcomes data, etc.)

    The document generically states "Clinical testing... was conducted to support the market claims" and a "Meta-analysis" was performed. It does not specify the type of ground truth used for these clinical evaluations. Given the nature of an endoscope, the "ground truth" for its performance would likely relate to visualization quality, ability to identify anatomical structures, or successful completion of procedures, rather than a diagnostic 'truth' established by pathology in the context of an AI device.

    8. The Sample Size for the Training Set

    This question is not applicable as the device is a videoscope and not an AI/ML algorithm that requires a training set.

    9. How the Ground Truth for the Training Set was Established

    This question is not applicable as the device is a videoscope and not an AI/ML algorithm that requires a training set.


    Summary of Missing Information:

    The provided document is a 510(k) summary for a videoscope, demonstrating substantial equivalence to a predicate device. It focuses on the safety and basic functional performance of the hardware. The type of rigorous quantitative performance evaluation (e.g., sensitivity, specificity, ground truth establishment with expert consensus, sample sizes for test/training sets) typically associated with AI/ML-powered diagnostic devices is not present in this document. The "clinical testing" mentioned is generic and lacks the detail required to answer most of your specific questions about acceptance criteria and study design for a diagnostic algorithm.

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