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510(k) Data Aggregation

    K Number
    K200907
    Date Cleared
    2020-06-03

    (58 days)

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

    The THALES 3D MR SCANNER system is designed to measure the characteristic radiation beam for an irradiation unit. The beam data is stored in the software program and can be exported from there for use during commissioning in a treatment planning system (TPS) or for quality assurance. The THALES 3D MR SCANNER system can be used with irradiation units with integrated magnetic resonance imaging and a magnetic field of less than or equal to 0.35 tesla.

    Device Description

    The THALES 3D MR SCANNER system consists of a water phantom with a carriage system, a manual control unit and a software program. A water basin with the corresponding pump, a control unit with an electrometer, and a motor controller are integrated in the carriage system. The software program is used to control the three axes of the water basin, perform measurements and analyse measured data.

    The software program has the following properties: Acquisition of measured data, analysis, and recording of photon beams with the water phantom. Generation and export of beam data libraries for a treatment planning system (TPS) for commissioning of irradiation units. The software program is equipped with a central database and/or a file system for central storage of all recorded data for different irradiation units within a large hospital network with different sites. The software program offers the option of defining different user levels to support the typical clinical workflows.

    AI/ML Overview

    Here's an analysis of the provided text regarding the acceptance criteria and study for the THALES 3D MR Scanner:

    Important Note: The provided FDA 510(k) summary focuses on demonstrating substantial equivalence to a predicate device, not necessarily on a comprehensive efficacy study with predefined acceptance criteria for its performance metrics as one might see in a clinical trial. The "acceptance criteria" here are more about meeting safety, electromagnetic compatibility, and dosimeter standards, and showing that its operational parameters are comparable or superior without introducing new risks. There is no information about a comparative effectiveness study (MRMC) with human readers, nor a standalone algorithm performance study as would be applicable for AI/CADe devices.


    1. Table of Acceptance Criteria and Reported Device Performance

    Acceptance Criteria CategorySpecific Criteria (from predicate comparison/standards)Reported Device Performance (THALES 3D MR Scanner)
    Intended UseQA for radiation therapy systems, commissioning, and other occasions; use with integrated MRI (up to 1.5T for predicate)QA for radiation therapy systems, commissioning, and other occasions; use with integrated MRI with magnetic field ≤ 0.35 Tesla
    Scanning Range408mm * 355mm * 248mm (predicate)380mm * 380mm * 242mm
    Tank ShapeSquareSquare
    Wall MaterialPMMAPMMA
    Chamber Holder OrientationHorizontal and verticalHorizontal and vertical
    Motor Scanning ModeStep by stepStep by step
    Step Size0.1mm0.1mm
    Maximum Speed30mm/s (predicate)40mm/s
    Position Accuracy+/-0.1mm (predicate)+/- 0.25mm (at 0.35Tesla)
    Reproducibility+/-0.1mm (predicate)+/- 0.25mm (at 0.35Tesla)
    MRI CompatibilityUp to 1.5 Tesla (predicate)Up to 0.35 Tesla
    Electrometer Channels2 entries2 entries
    Electrometer Resolution10 fA (predicate)1 fA
    Electrical SafetyIEC 61010IEC 61010
    Dosimeter TestingIEC 60731IEC 60731
    EMCIEC 60601-1-2:2007 (predicate)IEC 60601-1-2:2015
    MRI SafetyN/A (implied by predicate's MRI compatibility)Tested in accordance with applicable ASTM standards

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

    The document does not describe a "test set" in the context of an AI/ML algorithm or a specific patient-data based study. Instead, it details performance characteristics of a physical measurement device (water phantom) for radiation therapy. The performance testing refers to evaluating the device's physical and electrical characteristics against standards (IEC, ASTM). Therefore, there is no information about a sample size or data provenance related to patient data. The "test set" implies physical testing of the device itself.

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

    Not applicable. The ground truth for this device's performance is established by engineering and physics standards (IEC, ASTM) for safety, compatibility, and measurement accuracy, not by human expert consensus on clinical data.

    4. Adjudication Method for the Test Set

    Not applicable. There's no clinical data or expert review process described that would require an adjudication method.

    5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done

    No. The document makes no mention of an MRMC study or any study involving human readers or comparative effectiveness in a clinical workflow with or without AI assistance. This device is a measurement tool, not an AI diagnostic or assistive tool in the traditional sense.

    6. If a Standalone (i.e., algorithm only without human-in-the-loop performance) Was Done

    No. This is not an AI algorithm but a physical device with integrated software to control movement, acquire, analyze, and export measurement data. Its "performance" refers to how accurately it physically measures radiation beams, not its ability to interpret images or suggest diagnoses.

    7. The Type of Ground Truth Used

    The ground truth used for validating the device's performance comes from established engineering and medical device standards:

    • Electrical and mechanical safety: IEC 61010
    • EMC: IEC 60601-1-2
    • Dosimeter requirements: IEC 60731
    • MRI safety: Applicable ASTM standards
    • Performance metrics (e.g., position accuracy, electrometer resolution) are likely validated against manufacturer-defined specifications derived from engineering principles and comparison to the predicate device.

    8. The Sample Size for the Training Set

    Not applicable. This device is not an AI/ML model that requires a "training set" of data in the conventional sense. Its software controls hardware and processes raw measurement data based on established physics, not learned patterns from a "training set."

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

    Not applicable, as there is no training set for an AI/ML algorithm.

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