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510(k) Data Aggregation

    K Number
    K082385
    Manufacturer
    Date Cleared
    2008-12-11

    (114 days)

    Product Code
    Regulation Number
    870.1250
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    CHAPERON GUIDING CATHETER

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

    Chaperon Guiding Catheter is intended for general intravascular use, including the neuro and peripheral vasculature. Chaperon Guiding Catheter can be used to facilitate introduction of diagnostic or therapeutic devices. Chaperon Guiding Catheter is not intended for use in coronary arteries.

    Device Description

    The Chaperon Guiding Catheter system is designed to advance interventional and diagnostic devices through the vasculature. The device is intended for general intravascular use, including the neuro and peripheral vasculature. The Chaperon Guiding Catheter is a two-catheter system comprised of the outer catheter and the inner catheter. The Chaperon Guiding Catheter system can be used individually with 0.035 in or a 0.038 in guidewire or together with the Inner Catheter to access the desired anatomy.

    AI/ML Overview

    This document describes the regulatory submission for the Chaperon Guiding Catheter System. Based on the provided text, the device is a medical catheter and the "study" referred to is a series of bench tests conducted to demonstrate both the safety and performance characteristics of the device, as well as its substantial equivalence to a predicate device.

    Here's the breakdown of the requested information:

    1. Table of Acceptance Criteria and Reported Device Performance

    The provided document lists various "Bench Testing" categories and their "Result," which consistently states "Met established criteria." This implies that specific acceptance criteria were defined for each test and the device successfully fulfilled them. However, the specific quantitative or qualitative acceptance criteria for each test are not detailed in this document.

    Bench Testing CategoryReported Device Performance
    Surface Contamination & Tip ConfigurationMet established criteria
    Dimensional Inspection & Physical AttributesMet established criteria
    Tensile StrengthMet established criteria
    Hub Attachment StrengthMet established criteria
    Tip Attachment StrengthMet established criteria
    Freedom from Leakage - Fluid & AirMet established criteria
    Leak Test (High Static Pressure)Met established criteria
    Hub GaugingMet established criteria
    Separation ForceMet established criteria
    Stress CrackingMet established criteria
    Screwing TorqueMet established criteria
    Ease of AssemblyMet established criteria
    Resistance to OverridingMet established criteria
    Flow RateMet established criteria
    Radio-DetectabilityMet established criteria
    Catheter Burst & LeakageMet established criteria
    Stiffness & Kink ResistanceMet established criteria
    Durability & Lubricity & FatigueMet established criteria

    2. Sample size used for the test set and the data provenance

    The document does not specify the sample sizes used for each of the bench tests. It also does not provide information on data provenance in terms of country of origin or whether it was retrospective/prospective, as these types of clinical study details are not relevant for bench testing of a medical device of this nature in a 510(k) submission. Bench tests are typically conducted in a laboratory setting by the manufacturer.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

    This question is not applicable to the type of "study" described, which is a series of engineering/bench tests. "Ground truth" established by experts is typically relevant for studies involving qualitative assessments or diagnostic interpretation (e.g., image analysis, clinical diagnosis), not for objective physical and mechanical performance testing of a catheter.

    4. Adjudication method (e.g., 2+1, 3+1, none) for the test set

    This question is not applicable. Adjudication methods are typically used in clinical studies where there's a need to resolve discrepancies in expert interpretations or outcomes. For bench testing, the results are typically quantitative measurements or objective assessments against predefined pass/fail criteria, not subject to adjudication in the same sense.

    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

    This question is not applicable. MRMC studies and concepts of AI assistance for human readers are relevant for diagnostic devices, particularly those involving image interpretation. The Chaperon Guiding Catheter System is an interventional device, and the submission details only bench testing.

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

    This question is not applicable. This device is not an algorithm or AI system, but a physical medical device (catheter). Standalone performance refers to the performance of an algorithm without human intervention, which is not relevant here.

    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

    For these bench tests, the "ground truth" would be the engineering specifications and predefined performance thresholds for each test, based on industry standards, regulatory requirements, and the predicate device's characteristics. For example, for "Tensile Strength," the ground truth would be a specific minimum force the catheter must withstand without breaking. For "Flow Rate," it would be a minimum flow volume under specific pressure conditions.

    8. The sample size for the training set

    This question is not applicable. "Training set" refers to data used to train machine learning models. This submission is for a physical medical device and involves bench testing, not machine learning.

    9. How the ground truth for the training set was established

    This question is not applicable, as there is no training set for a machine learning model in this submission.

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