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510(k) Data Aggregation

    K Number
    K153263
    Date Cleared
    2016-04-01

    (143 days)

    Product Code
    Regulation Number
    892.1750
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    Aquilion Lightning, TSX-035A/4 and /5, V7.0

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

    This device is indicated to acquire and display cross-sectional volumes of the whole body, to include the head.

    The Aquilion Lightning has the capability to provide volume sets. These volume sets can be used to perform specialized studies, using indicated software/hardware, by a trained and qualified physician.

    Device Description

    The Aquilion Lightning, TSX-035A/4 and /5, v7.0 is a 16-row CT System that is intended to acquire and display cross-sectional volumes of the whole body, including the head. This system is based upon the technology and materials of previously marketed Toshiba CT systems.

    AI/ML Overview

    I am sorry, but the provided text is a 510(k) premarket notification for a Computed Tomography (CT) X-ray system (Aquilion Lightning, TSX-035A/4 and /5, V7.0). This type of document is a submission to the FDA to demonstrate that a device is substantially equivalent to a predicate device already on the market.

    This specific document does not contain information about the acceptance criteria or a study proving the device meets acceptance criteria in the manner requested (e.g., using metrics like sensitivity, specificity, or performance against a ground truth dataset).

    The document primarily focuses on:

    • Indications for Use: What the device is intended for.
    • Technological Characteristics Comparison: How the new device differentiates from its predicate (e.g., gantry rotation speed, X-ray rated output, patient couch specifications).
    • Safety and Performance Standards Conformance: Listing of relevant IEC standards and CFR parts that the device adheres to.
    • Testing: Mentions "summary tables detailing the risk analysis and verification/validation testing conducted through bench testing" and "successful completion of software validation." It does not provide details of such studies or specific performance metrics that would be considered acceptance criteria for AI/algorithm performance.

    Therefore, I cannot provide the requested information about acceptance criteria, device performance, sample sizes, expert ground truth, adjudication methods, MRMC studies, standalone performance, or training set details because these are not present in the provided text. This document is for a general CT system, not an AI-powered diagnostic algorithm with performance metrics relative to a ground truth dataset.

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