Search Filters

Search Results

Found 1 results

510(k) Data Aggregation

    K Number
    K192400
    Manufacturer
    Date Cleared
    2019-10-03

    (30 days)

    Product Code
    Regulation Number
    892.1680
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    EVS 4343A, EVS 4343AG, EVS 3643A, EVS 3643AG

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

    The EVS 4343A / EVS 4343AG / EVS 3643AG Digital X-ray detector is indicated for digital imaging solution designed for providing general radiographic diagnosis of human anatomy. This device is intended to replace film or screen based radiographic systems in all general purpose diagnostic procedures. This device is not intended for mammography applications.

    Device Description

    The EVS 4343A / EVS 4343AG / EVS 3643A / EVS 3643AG is a flat-panel type digital X-ray detector that captures projection radiographic images in digital format within seconds, eliminating the need for an entire x-rav film or an image plate as an image capture medium. EVS 4343A / EVS 4343AG / EVS 3643A / EVS 3643AG differs from traditional X-ray systems in that, instead of exposing a film and chemically processing it to create a hard copy image, a device called a Detector is used to capture the image in electronic form.

    The EVS 4343A / EVS 4343AG / EVS 3643A / EVS 3643AG Detector is an indirect conversion device in the form of a square plate in which converts the incoming X-rays into visible light. This visible light is then collected by an optical sensor, which generates an electric charges representation of the spatial distribution of the incoming X-ray quanta.

    The charges are converted to a modulated electrical signal through thin film transistors. The amplified signal is converted to a voltage signal and is then converted from an analog to digital signal which can be transmitted to a viewed image print out, transmitted to remote viewing or stored as an electronic data file for later viewing.

    AI/ML Overview

    The provided FDA 510(k) summary (K192400) for the DRTECH EVS 4343A, EVS 4343AG, EVS 3643A, and EVS 3643AG digital X-ray detectors focuses on demonstrating substantial equivalence to a predicate device (K162555). Therefore, the "acceptance criteria" discussed are primarily related to showing that the new devices perform as well as or better than the predicate, particularly in key physical performance metrics.

    Here's an analysis of the acceptance criteria and the study details based on the provided text:

    1. Table of Acceptance Criteria and Reported Device Performance

    The acceptance criteria are implicitly defined by the predicate device's performance and the expectation that the new devices should meet or exceed these values for key metrics like DQE and MTF.

    Performance ParameterPredicate Device (EVS 4343 / EVS 4343G) Acceptance CriteriaSubject Device (EVS 4343A, EVS 3643A, EVS 4343AG, EVS 3643AG) Reported Performance
    DQEEVS 4343: 43.9 % at 1.0 lp/mm
    EVS 4343G: 23.6 % at 1.0 lp/mmEVS 4343A: 52.9 % at 1.0 lp/mm
    EVS 3643A: 50.5 % at 1.0 lp/mm
    EVS 4343AG: 27.2 % at 1.0 lp/mm
    EVS 3643AG: 26.3 % at 1.0 lp/mm
    MTFEVS 4343: 37.7 % at 2.0 lp/mm
    EVS 4343G: 34.0 % at 2.0 lp/mmEVS 4343A: 44.1 % at 2.0 lp/mm
    EVS 3643A: 44.5 % at 2.0 lp/mm
    EVS 4343AG: 49.2 % at 2.0 lp/mm
    EVS 3643AG: 46.3 % at 2.0 lp/mm
    Resolution3.5 lp/mm3.5 lp/mm

    The document states: "it is proved that the DQE and MTF of predicated device and subject device are basically equal or worth than the predicate device." and "As a result, subject devices performance is equal or worth than the predicate device." However, the presented data shows that the subject devices exceed the DQE and MTF values of the predicate device, indicating superior performance in these measured aspects.

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

    The provided summary does not specify a sample size for a clinical test set involving patients or images. The "non-clinical data" discussed pertains to bench testing of the detector's physical performance (DQE, MTF, Resolution). Therefore, the concepts of "test set" in the context of clinical images, "country of origin," and "retrospective/prospective" are not applicable to the non-clinical performance evaluation described.

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

    This information is not applicable as the evaluation was a non-clinical, bench-top performance assessment of the device's physical imaging characteristics (DQE, MTF, resolution), not a clinical study requiring expert interpretation of medical images.

    4. Adjudication Method for the Test Set

    This information is not applicable for the same reasons as point 3.

    5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study was done

    A Multi-Reader Multi-Case (MRMC) comparative effectiveness study was not conducted or described in this 510(k) summary. The submission focuses on demonstrating substantial equivalence based on technical specifications and non-clinical performance, not on a comparison of human reader performance with or without AI assistance.

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

    This is not applicable. The device is an X-ray detector, a hardware component that captures images. It does not contain an AI algorithm for image analysis in isolation (standalone) or for human-in-the-loop performance. Its "performance" refers to how well it acquires images, not how well it interprets them.

    7. The Type of Ground Truth Used

    The ground truth for the non-clinical performance evaluation (DQE, MTF, Resolution) would be based on physical phantom measurements and established international standards (e.g., IEC 62220-1) for characterizing X-ray detector performance. It is not expert consensus, pathology, or outcomes data, as those relate to clinical diagnostic accuracy.

    8. The Sample Size for the Training Set

    This 510(k) summary does not describe a training set. The device is a digital X-ray detector, which is a hardware component. There is no mention of machine learning or AI algorithms requiring a training set for this particular submission. The "study" here is a technical performance assessment of the detector itself.

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

    This information is not applicable as no training set for an AI algorithm is described.

    Ask a Question

    Ask a specific question about this device

    Page 1 of 1