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510(k) Data Aggregation

    K Number
    K063241
    Date Cleared
    2006-11-09

    (14 days)

    Product Code
    Regulation Number
    892.1750
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    CSTC-002A, Extended Field of View Software is a post processing software option for the TSX-201A CT system. This product increases the amount of image information from the Large 70 cm field of view (FOV) to a 85 cm field of view.

    Device Description

    The CSTC-002A will be added to the previously cleared TSX-201A Aquilion LB CT system. This addition requires software modifications to the existing device. Addition of this option will allow for visualization of the body and patient couch beyond the normal field of view.

    AI/ML Overview

    The provided text does not contain detailed acceptance criteria or a study proving the device meets specific performance metrics. It is a 510(k) summary for a software option (CSTC-002A, Extended Field of View Software Option) for a CT system.

    Here's an analysis based on the available information:

    1. Table of Acceptance Criteria and Reported Device Performance:

    The document does not specify quantitative acceptance criteria or provide a table of reported device performance. The entire submission focuses on establishing substantial equivalence to a predicate device (Siemens Extended Field of View; K032536) rather than demonstrating specific performance against predefined metrics.

    The "Summary of Intended Uses" states: "CSTC is intended to display the body and patient table beyond the normal field of view. Images generated by this software are not to be used for diagnostic purposes. Standard distance measurements are allowed." This implies that the primary "performance" is the ability to display a wider field of view, but no quantitative measure of this display capability (e.g., image quality, distortion levels) is presented as an acceptance criterion or reported performance.

    2. Sample Size Used for the Test Set and the Data Provenance:

    No information regarding a "test set" in the context of clinical or performance data is provided. The submission focuses on software modifications and its similarity to a predicate device. Therefore, no sample size for a test set or data provenance (country of origin, retrospective/prospective) is mentioned.

    3. Number of Experts Used to Establish the Ground Truth for the Test Set and the Qualifications of Those Experts:

    Since no test set with clinical data is described, there is no mention of experts, ground truth establishment, or their qualifications.

    4. Adjudication Method:

    No adjudication method is mentioned as there is no clinical or performance data requiring such a process.

    5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

    No MRMC study was conducted or referenced. The submission does not discuss human reader performance with or without AI assistance.

    6. Standalone (Algorithm Only Without Human-in-the-Loop Performance) Study:

    While the device itself is a software option (an algorithm), a standalone performance study in the sense of demonstrating specific quantifiable metrics outside of integration with the CT system is not detailed. The focus is on its functional equivalence and safety within the existing CT system. The statement "Images generated by this software are not to be used for diagnostic purposes" significantly limits the scope of performance validation typically associated with diagnostic AI.

    7. Type of Ground Truth Used:

    No ground truth is mentioned, as no performance study or diagnostic claim is being made that would require it.

    8. Sample Size for the Training Set:

    No information about a training set is provided. The document outlines a modification to existing software and its similarity to a predicate device, not the development of a new algorithm based on machine learning from a training set.

    9. How the Ground Truth for the Training Set Was Established:

    Not applicable, as no training set is discussed.

    Summary of what the document does indicate regarding substantial equivalence:

    The submission focuses on the technological characteristics and intended uses being similar to the predicate device.

    • Technological Characteristics: "This package is similar in uses and applications as those of the predicate devices. The main difference is in the method used to obtain the final results."
    • Safety and Effectiveness Concerns: The device is designed and manufactured under Quality System Regulations (21 CFR § 820) and conforms to applicable parts of IEC 60601-1, IEC 60601-2-32, and IEC 60601-2-44.
    • Substantial Equivalence Argument: "This package provides similar tools to those found in the predicate device. This package does not provide new indications or functions when compared to those that are already available in products already being marketed."

    Essentially, the "proof" the device meets acceptance criteria, in this context, is that it is substantially equivalent to a previously cleared device, performing a similar function (extended field of view display) for non-diagnostic purposes, while adhering to relevant safety and quality standards. Specific quantitative performance data and clinical studies are not presented because the device is a software option for display only, with no diagnostic claims.

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