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510(k) Data Aggregation

    K Number
    K073059
    Date Cleared
    2007-12-10

    (41 days)

    Product Code
    Regulation Number
    892.5050
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    PROBEAT WITH DISCRETE SPOT SCANNING SYSTEM

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

    Hitachi's PROBEAT with DSSS is a medical device designed to produce and deliver a proton beam for the treatment of patients with localized tumors and other conditions susceptible to treatment by radiation.

    Device Description

    The PROBEAT with DSSS is a proton beam irradiation system, which provides a therapeutic proton beam for clinical treatment. It is designed to deliver a proton beam with the prescribed dose, dose distribution and directed to the prescribed patient treatment site. The PBTS is designed to be safe and reliable. The equipment to perform the above work is comprised of two main components. One is a beam delivery system whose primary responsibility is to ensure that the desired prescription parameters are properly delivered. The other is the equipment necessary to generate the proton beam and direct it to the beam delivery system.

    AI/ML Overview

    The provided text describes a Special 510(k) submission for the PROBEAT with DSSS, a modification to an existing proton beam therapy system. This type of submission is used for devices that are substantially equivalent to a predicate device and have only minor modifications that do not raise new questions of safety or effectiveness. As such, the submission primarily focuses on demonstrating substantial equivalence rather than presenting extensive new performance data or clinical studies like those for novel devices.

    Therefore, many of the typical acceptance criteria and study details you requested for AI/software-based medical devices are not explicitly mentioned in this document. The document states that performance testing was conducted, but it does not detail specific acceptance criteria in terms of quantitative metrics, sample sizes, or expert involvement as one would expect for an AI algorithm.

    Here's an attempt to answer your questions based on the provided text, indicating where information is not available:

    1. Table of Acceptance Criteria and Reported Device Performance

    Acceptance CriteriaReported Device Performance
    Not explicitly defined in terms of specific measurable clinical or analytical performance metrics for a novel technology. The focus is on demonstrating that the added DSSS feature performs as intended within the context of the device's overall function and does not negatively impact safety or effectiveness.The submission includes a summary of performance testing that Hitachi conducted to demonstrate that the device meets its performance specifications. (Specific results or metrics are not detailed in this summary.)
    The DSSS feature should not alter the intended use or indications of the PROBEAT system.The PROBEAT with DSSS has the same intended use and indications as the cleared PROBEAT.
    The DSSS feature should maintain the safe and reliable operation of the proton beam therapy system.The PBTS (Proton Beam Therapy System) is designed to be safe and reliable. The DSSS is a component of this system.
    The DSSS feature should properly deliver the desired prescription parameters (dose, dose distribution, and directed to the treatment site).The PROBEAT with DSSS is designed to deliver a proton beam with the prescribed dose, dose distribution, and directed to the prescribed patient treatment site.

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

    Not applicable in the context of this 510(k) summary for a hardware modification to an existing proton therapy system. The "test set" would likely refer to engineering and system validation tests rather than a clinical dataset in the AI sense. The document does not specify details of these tests, their sample sizes, or data provenance.

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

    Not applicable. This information is not provided. Ground truth in this context would likely be based on physical measurements and engineering specifications, not expert interpretation of data.

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

    Not applicable. This information is not provided.

    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 hardware modification for a proton beam therapy system, not an AI-based diagnostic or assistive device that would involve human readers.

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

    Not applicable. This refers to the performance of the overall Proton Beam Therapy System with the added DSSS component, which is a physical beam delivery system, not an algorithm.

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

    Not explicitly stated. For a proton beam therapy system, ground truth for performance testing would typically involve:

    • Physical measurements: Verifying beam parameters (dose, energy, shape, position) using phantoms, dosimeters, and other radiation detectors.
    • Engineering specifications: Comparing actual performance against designed specifications.
    • Pre-clinical verification: Potentially using biological samples or animal models to assess beam effects (though not explicitly mentioned here for this modification).

    8. The sample size for the training set

    Not applicable. This is a hardware modification to an existing proton therapy system. The concept of a "training set" is relevant for machine learning algorithms, which is not the primary subject of this 510(k) summary.

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

    Not applicable for the same reasons as above.

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