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510(k) Data Aggregation

    K Number
    K973953
    Date Cleared
    1998-01-14

    (90 days)

    Product Code
    Regulation Number
    892.5710
    Reference & Predicate Devices
    N/A
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    In Radiation Therapy, it is often necessary to create irregularly shaped fields to contour to the desired treatment shape. Irregular shaped fields for electron beam cases can be achieved by supplementing the shaping ability of the treatment machine's electron collimation system with tertiary beam blocks. These Beam Blocks are inserted into the ends of the electron cones. The electron beam blocks are created from low melting point lead alloy that is poured in a molten state into a pre-cut Styrofoam form. When the molten lead alloy cools it creates a hard, lead shield custom shaped for the desired form.

    Device Description

    This device is intended to be used in Radiation Therapy for creating irregularly shaped treatment fields in electron beam therapy. The electron beam block is mounted in the end of an electron cone and is not in contact with the patient at any time when in use. The electron beam blocks are created from low melting point lead alloy that is poured in a molten state into a pre-cut Styrofoam form. When the molten lead alloy cools it creates a hard, lead shield custom shaped for the desired form.

    AI/ML Overview
    1. Acceptance Criteria and Reported Device Performance:

      The provided document is a 510(k) premarket notification for an "Electron Beam Field Shaping System" (K973953). This type of submission relies on demonstrating substantial equivalence to a legally marketed predicate device, rather than establishing specific performance acceptance criteria and then proving the device meets them through studies with defined metrics.

      Therefore, there is no table of acceptance criteria and reported device performance in the document as it would be found in a De Novo or PMA application. Instead, the "performance" described is in terms of similarity to the predicate device.

      The key statement regarding performance is:
      "This device is similar in design, construction, materials, intended use and performance characteristics to the predicate devices. No new issues of safety or effectiveness are introduced by using this device."

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

      No formal "test set" with a defined sample size for performance evaluation is mentioned. The submission focuses on demonstrating substantial equivalence through design and material similarity, and intended use, rather than presenting a study with a test set of data.

    3. Number of Experts and Qualifications for Ground Truth:

      Not applicable. Since no formal performance study with a test set and ground truth establishment is described, there's no mention of experts or their qualifications for this purpose.

    4. Adjudication Method:

      Not applicable. As no independent test set or ground truth establishment is described, there is no mention of an adjudication method.

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

      No MRMC comparative effectiveness study was conducted or reported. This submission is for a physical device (beam shaping blocks) used in radiation therapy, not an AI software system that would typically undergo such a study to evaluate human reader improvement with AI assistance.

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

      Not applicable. This device is a passive physical component in a radiation therapy system, not an algorithm or AI system. Its function is to create irregularly shaped treatment fields, and it's used in conjunction with a treatment machine and human operators.

    7. Type of Ground Truth Used:

      Not applicable. The concept of "ground truth" (e.g., expert consensus, pathology, outcomes data) is not relevant to this 510(k) submission, which focuses on device design and functionality rather than diagnostic or prognostic accuracy.

    8. Sample Size for the Training Set:

      Not applicable. This is not an AI or machine learning device, so there is no "training set" in the conventional sense.

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

      Not applicable. As there is no training set mentioned, there is no ground truth established for it.

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