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510(k) Data Aggregation

    K Number
    K131369
    Device Name
    FLEXIBLE VIDEO-URETERO-RENOSCOPE SYSTEM
    Manufacturer
    KARL STORZ ENDOSCOPY-AMERICA, INC.
    Date Cleared
    2013-11-26

    (197 days)

    Product Code
    FGB
    Regulation Number
    876.1500
    Type
    Traditional
    Panel
    Gastroenterology/Urology
    Reference & Predicate Devices
    K060269,K003325
    Predicate For
    K141250,K171076,K172098,K180367,K183188
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Karl Storz Flexible Video-Uretero-Renoscope System is indicated for endoscopic examination in the urinary tract and can be used to examine the interior of the kidney, and using additional accessories, to perform various diagnostic and therapeutic procedures.

    Device Description

    The Flexible Video-Uretero-Renoscope System is used for visualization purposes during diagnostic and therapeutic procedures. The crucial components of the system are the Flexible Video-Uretero-Renoscope and the Image 1 HD Camera Control Unit. The Flexible Video-Uretero-Renoscope uses an LED light integrated in the handle and fiber light guides to illuminate the cavity under examination. The video image is produced by a complementary metal-oxide-semiconductor (CMOS) imaging sensor is located at the tip of the insertion shaft. The imaging sensor transfers the video signal to the Image1 HD CCU via electronics in the handle. The Image1 HD CCU processes the sensor images and displays them on a standard SD or HD monitor. The Karl Storz Flexible Video-Uretero-Renoscope System is a Class II device under 21 CFR 876.1500.

    AI/ML Overview

    The provided text describes a 510(k) summary for the Karl Storz Flexible Video-Uretero-Renoscope System. This device is not an AI/ML medical device, therefore, the information requested in the prompt related to acceptance criteria for AI performance, sample sizes for test/training sets, ground truth establishment, expert adjudication, or MRMC studies for AI devices is not applicable.

    The document focuses on demonstrating substantial equivalence to predicate devices through technical characteristics comparison and non-clinical performance and safety testing.

    Here's the relevant information that can be extracted from the provided text:

    1. Table of Acceptance Criteria and Reported Device Performance
    The document does not explicitly state quantitative acceptance criteria in a table; rather, it refers to successful testing against established standards. The performance is summarized qualitatively.

    Test CategoryAcceptance Criteria (Implicit)Reported Device Performance
    Non-Clinical Performance DataMeets relevant standards for optical and mechanical characteristics"Successfully tested for its functions and performance, including verification of optical characteristics per ISO 8600 (image quality, illumination) and mechanical characteristics (bend, deflection, articulation), leak testing, and insertion testing)."
    Safety TestingMeets relevant standards for electrical safety, EMC, and biocompatibility"Safety testing was performed including electrical safety IEC 60601-1 and IEC 60601-2-18, electromagnetic compatibility per IEC 60601-1-2 and biocompatibility of the patient contacting materials per ISO 10993."
    Additional ValidationsDemonstrated effectiveness for software, cleaning, and sterilization"Additional validations were conducted for the system software, the manual cleaning method, sterilization process, and sterilant rinsing efficacy."

    2. Sample sized used for the test set and the data provenance (e.g. country of origin of the data, retrospective or prospective)
    Not applicable. This is a medical device for visualization, not an AI/ML device that uses data for a test set. The validation methods involved physical device testing, not data analysis sets.

    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. There is no mention of expert-established ground truth related to diagnostic performance or image interpretation, as the device is for direct visualization.

    4. Adjudication method (e.g. 2+1, 3+1, none) for the test set
    Not applicable, as this is not an AI/ML diagnostic device with a test set requiring adjudication.

    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 is not an AI-assisted device, and no MRMC study is mentioned.

    6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
    Not applicable. This device is an endoscope system that is used with a human in the loop for live visualization and procedures.

    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc)
    Not applicable. The "ground truth" for this device would be its physical and optical performance characteristics as measured against engineering specifications and international standards (e.g., ISO 8600, IEC 60601 series).

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

    9. How the ground truth for the training set was established
    Not applicable.

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