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510(k) Data Aggregation

    K Number
    K192405
    Date Cleared
    2020-05-01

    (241 days)

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

    K102533, K072916, K051932

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

    The Image Guidance System for Radiotherapy is intended to be used in combination with the radiotherapy device, for image-guided positioning verification and real-time tracking of target motion for patient radiation therapy. The Image Guidance System for Radiotherapy sends the positioning data or real-time tracking data to the radiotherapy device but does not control any part of the radiotherapy device.

    Device Description

    The product is a medical electrical device which is composed of hardware and software, and is jointly used with the radiation therapy device. Image Guidance System for Radiotherapy is intended to be used in combination with the radiotherapy device, for image-guided positioning verification and real-time tracking of target motion for patient radiation therapy.

    AI/ML Overview

    The provided text describes several bench tests conducted to demonstrate the substantial equivalence of the "Image Guidance System for Radiotherapy" to a predicate device. This submission does not include clinical studies.

    Here's an analysis of the acceptance criteria and performance based on the non-clinical tests:

    1. Table of Acceptance Criteria and Reported Device Performance

    Device Name: Image Guidance System for Radiotherapy (Models: IGTS, IGPS)

    Test CategoryAcceptance CriteriaReported Device Performance
    Compatibility Testing with Radiotherapy Systems
    Targeting Accuracy (integrated with MASEP Gamma Ray SRT)No larger than 1.0 mmWell meets the requirements for SRS (implies ≤ 1.0 mm)
    Targeting Accuracy (integrated with Varian Linear Accelerator)No larger than 1.0 mmWell meets the requirements for SRS (implies ≤ 1.0 mm)
    Targeting Accuracy (integrated with Elekta Linear Accelerator)No larger than 1.0 mmWell meets the requirements for SRS (implies ≤ 1.0 mm)
    Optical Guided Tracking Accuracy Testing
    3D RMS Volumetric Accuracy0.15 mm for extended pyramid volume0.11 mm
    System Positioning Accuracy Testing
    Overall Positioning AccuracyNo larger than 1.0 mmNo larger than 1.0 mm
    Individual Rotational Angle AccuracyNo larger than 1.0°No larger than 1.0°
    System Tracking Accuracy Testing
    Target Tracking AccuracyBetter than 1.5 mmNo larger than 1.5 mm
    System Performance Testing
    Mechanical Accuracy of Imaging CenterNot exceed 0.5 mmMeets the requirement (implies ≤ 0.5 mm)
    Positioning AccuracyNot exceed 1.0 mmMeets the requirement (implies ≤ 1.0 mm)
    Positioning StabilityNot exceed 0.3 mmMeets the requirement (implies ≤ 0.3 mm)
    Detection Accuracy of Target Movement (regular respiratory)Not exceed 1.5 mmMeets the requirement (implies ≤ 1.5 mm)

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

    The document does not explicitly state the specific sample sizes (number of cases/patients/phantoms) used for each individual bench test. It mentions using an "anthropomorphic target phantom" and "anthropomorphic head phantom and a thoracic spine phantom" for system accuracy tests, and a "phantom used for this test provides respiratory waveforms collected from clinical patient data" for tracking accuracy.

    The data provenance is from bench testing conducted by the manufacturer, Jiangsu Rayer Medical Technology Co., Ltd., in Wuxi, Jiangsu, CHINA. The data is non-clinical.

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

    Not applicable. These were non-clinical bench tests using phantoms and controlled setups, not human-annotated data with expert ground truth in the traditional sense. The "ground truth" for the tests was established by physical movements and measurements from the treatment couch or optical tracking systems during the experiments against known values.

    4. Adjudication Method for the Test Set

    Not applicable. As these were bench tests with physical measurements against known references (e.g., treatment couch movements, optical tracking systems), there was no need for expert adjudication of results.

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

    No, an MRMC comparative effectiveness study was not done. The document explicitly states: "No clinical study is included in this submission." The studies were bench tests demonstrating the device's performance alone and its compatibility with existing radiotherapy systems, not a comparison of human reader performance with and without AI assistance.

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

    Yes, standalone performance was assessed through various bench tests. The tests evaluate the intrinsic accuracy and performance characteristics of the "Image Guidance System for Radiotherapy" itself, in terms of positioning and tracking accuracy, mechanical accuracy, and compatibility with other radiotherapy devices. These tests do not involve human-in-the-loop performance evaluation in the context of diagnostic interpretation or decision-making.

    7. The Type of Ground Truth Used

    The ground truth used for these bench tests was based on:

    • Physical measurements and known displacements: For positioning and tracking accuracy, the ground truth was provided by precise movements of a treatment couch acting as a reference, or known positions/displacements of inserts within phantoms.
    • Optical tracking systems: For optical guided tracking accuracy, the ground truth was likely established by a highly accurate optical tracking system (e.g., NDI unit itself or a reference system) against which the device's tracking capabilities were validated.
    • Design specifications and established standards: The acceptance criteria themselves are the ground truth, derived from engineering specifications and industry standards for medical devices, particularly in radiation therapy.

    8. The Sample Size for the Training Set

    The document does not mention a training set. This suggests that the device, or at least the specific aspects being tested for this submission, may not rely on a machine learning model that requires a distinct training dataset, or if it does, the details of the training set are not included in this summary. The tests focus on the physical and algorithmic performance of the system rather than the learning capabilities of a model.

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

    Not applicable, as no training set information is provided or implied by the tests described.

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