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510(k) Data Aggregation

    K Number
    K192102
    Date Cleared
    2019-09-25

    (51 days)

    Product Code
    Regulation Number
    892.5050
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    Aktina Thermoplastic Masks are medical devices used for patient positioning and immobilization during external beam radiation therapy procedures. Thermoplastic masks are intended for the duration of the treatment.

    Device Description

    This is a Traditional 510(k) for the Aktina Medical Thermoplastic Mask. The low-temperature thermoplastic mask is made of Aquaplast polycaprolactone sheets. When immersed in water heated to 70-75°C [160 to 170°F], the material softens, allowing the user to shape or stretch the mask over the contours of the patient's anatomy while cooling. When the material reaches room temperature, the mask hardens into the anatomical shape. The mask can then be placed over the patient treatment area to consistently immobilize the area from treatment to treatment. Predicate device manufacturers have used polycaprolactone materials for this intended use for over 25 years. The mask also has a polycarbonate frame with holes for mounting to the user's existing patient support hardware.

    AI/ML Overview

    The provided document is a 510(k) summary for the Aktina Medical Thermoplastic Mask, not a study describing the acceptance criteria and performance of an AI/ML-based device. This document is for a medical device (thermoplastic mask) used for patient immobilization during radiation therapy and does not involve AI/ML.

    Therefore, I cannot extract the requested information (acceptance criteria, study details, sample sizes, expert qualifications, adjudication, MRMC, standalone performance, ground truth, training set information) as it is not present in the provided text.

    The document primarily focuses on demonstrating substantial equivalence to a predicate device based on material properties, design, and intended use, rather than performance evaluation against specific acceptance criteria for an AI/ML algorithm.

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