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510(k) Data Aggregation

    K Number
    K093160
    Manufacturer
    Date Cleared
    2009-11-05

    (30 days)

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

    HEADWAY 21 MICROCATHETER, MODEL: MC212150S

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

    The Headway 21 Microcatheter is intended for general intravascular use, including the peripheral, coronary and neuro vasculature for the infusion of diagnostic agents, such as contrast media, and therapeutic agents, such as occlusion coils.

    Device Description

    The Headway 21 Microcatheter is a single lumen catheter designed to be introduced over a steerable guidewire to access small, tortuous vasculature. The semi-rigid proximal section transitions to a flexible distal tip to facilitate advancement through vessels. Dual radiopaque markers at the distal end facilitate fluoroscopic visualization. The outer surface of the Microcatheter is coated with a hydrophilic polymer to increase lubricity. A luer fitting on the Microcatheter hub is used for the attachment of accessories.

    AI/ML Overview

    The provided text describes the 510(k) summary for the Headway 21 Microcatheter. This is a medical device, and the acceptance criteria and study information provided are related to its physical and functional performance, not to an AI or software-based medical device that would have clinical performance metrics like sensitivity, specificity, or reader improvement.

    Therefore, many of the requested fields (2-9, and the effect size in 5) are not applicable to this type of device and submission.

    Here's the relevant information based on the provided text:

    Acceptance Criteria and Device Performance

    The Headway 21 Microcatheter performed a series of bench tests to demonstrate its design and functional equivalence to a predicate device. The acceptance criteria for these tests were met if the device "Pass"ed each specified test.

    Bench TestingAcceptance CriteriaReported Device Performance
    Surface and physical attributesPassPass
    Distal tensile strengthPassPass
    Hub tensile strengthPassPass
    Leakage (liquid and air)PassPass
    Static and dynamic burst pressurePassPass
    Simulated usePassPass
    Compatibility with devicesPassPass
    Flow ratePassPass
    Kink resistancePassPass
    Catheter flexural fatiguePassPass

    Study Details Based on the Provided Document:

    1. A table of acceptance criteria and the reported device performance: See table above.

    2. Sample size used for the test set and the data provenance: Not explicitly stated for each bench test. These are engineering/device performance tests, not clinical studies with patient data.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. Ground truth for these physical tests would be defined by engineering standards and test methodology, not clinical expert consensus.

    4. Adjudication method for the test set: Not applicable for these engineering tests. Results are typically determined by predefined pass/fail limits based on engineering specifications.

    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 a physical medical device, not an AI or imaging diagnostic tool.

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

    7. The type of ground truth used: For bench testing, the "ground truth" is typically established by engineering specifications, validated test methods, and industry standards for medical devices of this type (e.g., tensile strength required for a given material, burst pressure, flow rate thresholds).

    8. The sample size for the training set: Not applicable. This is a physical medical device, not a machine learning model.

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

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