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510(k) Data Aggregation

    K Number
    K972366
    Device Name
    IMNET DICOM NETWORK AGENT
    Manufacturer
    IMNET SYSTEMS, INC.
    Date Cleared
    1997-09-23

    (90 days)

    Product Code
    LMD
    Regulation Number
    892.2020
    Type
    Traditional
    Panel
    Radiology
    Reference & Predicate Devices
    N/A
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The IMNET DICOM Network Agent is a software device intended for use within the medical imaging environment. The product is a communication tool which facilitates the transfer of medical images from one system to another. Receiving medical images from a DICOM source and transmitting them to another DICOM compatible target, the product is a communication gateway for the DICOM environment.

    Device Description

    The IMNET DICOM Network Agent is a software device intended for use within the medical imaging environment. The product is a communication tool which facilitates the transfer of medical images from one system to another. Receiving medical images from a DICOM source and transmitting them to another DICOM compatible target, the product is a communication gateway for the DICOM environment.

    AI/ML Overview

    I am sorry, but based on the provided text, there is no information available regarding acceptance criteria or a study proving the device meets said criteria.

    The document is a 510(k) clearance letter from the FDA for the "Imnet Dicom Network Agent." It confirms that the device is substantially equivalent to legally marketed predicate devices. The second document, "EXHIBIT G: USE FORM," describes the "Indications for Use" for the device, stating it's a software device intended for transferring medical images between DICOM-compatible systems.

    This type of regulatory document typically focuses on substantial equivalence to a predicate device rather than detailed performance studies and acceptance criteria as would be found in a clinical trial report or a comprehensive technical specification.

    Therefore, I cannot provide the requested information, including:

    1. A table of acceptance criteria and the reported device performance: This information is not present.
    2. Sample size used for the test set and the data provenance: Not mentioned.
    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not mentioned.
    4. Adjudication method (e.g., 2+1, 3+1, none) for the test set: Not mentioned.
    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 mentioned. The device is described as a "communication tool" and "communication gateway," not an AI-powered diagnostic or assistive tool for human readers.
    6. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done: Not mentioned.
    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc): Not mentioned.
    8. The sample size for the training set: Not mentioned.
    9. How the ground truth for the training set was established: Not mentioned.
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