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510(k) Data Aggregation

    K Number
    K031311
    Date Cleared
    2003-06-20

    (57 days)

    Product Code
    Regulation Number
    892.2050
    Reference & Predicate Devices
    Why did this record match?
    Device Name :

    INTEGRADWEB BY DYNAMIC IMAGING, INC.

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

    INTEGRADWeb™ by Dynamic Imaging, Inc. is a device that receives medical images and data from various imaging sources. Images and data can be stored, communicated, processed and displayed within the system or across computer networks at distributed locations. Typical users of this system are trained professionals, as in physicians, nurses, and technicians.

    Device Description

    INTEGRADWeb™ is an Internet based software picture archiving and communications system that provides users with capabilities relating to the acceptance, transfer, display, storage, and digital processing of medical images. INTEGRADWeb™ includes features to access and manage medical imaging studies from cat-scan (CT), magnetic radiography (MR), ultrasound (US), nuclear medicine (NM), computerized radiography (CR), digital radiography (DR), digital x-ray (DX), x-ray angiography (XA), PET scan (PT), and other imaging modalities. INTEGRADWeb™ is designed to be deployed over conventional TCP/IP networking infrastructure available in most healthcare organizations, and utilizes commercially available computer platforms (Intel Pentium-based) and operating systems (Microsoft Windows 2000, Windows NT, and Windows 98). The system does not produce any original medical images. All images located on INTEGRADWeb™ have been received from DICOM compliant modalities and/or systems.

    AI/ML Overview

    The provided text is a 510(k) summary for INTEGRADWeb™ by Dynamic Imaging, Inc., a Picture Archiving Communications System. Based on the document, this device is a software system for managing and displaying medical images. It does not produce original medical images, nor does it make any diagnostic interpretations or claims about medical performance. As such, the document does not contain information about acceptance criteria or a study proving device performance in the way typically associated with AI/CADe devices that perform image analysis or diagnostic aid.

    Here's why the direct questions cannot be answered from the provided text:

    • The device is a PACS system, primarily for image management, storage, communication, and display. It explicitly states, "The system does not produce any original medical images." and "A physician, providing ample opportunity for competent human intervention interprets images and information being displayed and printed." This indicates that the device supports human interpretation rather than performing automated diagnostic tasks.
    • The 510(k) application focuses on demonstrating "substantial equivalence" to a predicate PACS device (ISITE RADIOLOGY) by highlighting technological characteristics, indications for use, and a hazard analysis. It does not involve a performance study against a ground truth for diagnostic accuracy, sensitivity, or specificity.

    Therefore, the following points are not applicable or cannot be extracted from the document:

    1. A table of acceptance criteria and the reported device performance: Not applicable, as there are no diagnostic performance metrics for this type of device.
    2. Sample sized used for the test set and the data provenance: Not applicable. No diagnostic test set is mentioned.
    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts: Not applicable. No ground truth establishment for diagnostic performance is mentioned.
    4. Adjudication method (e.g. 2+1, 3+1, none) for the test set: Not applicable.
    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 applicable. This is not an AI diagnostic aid device.
    6. If a standalone (i.e. algorithm only without human-in-the loop performance) was done: Not applicable. This is a system for image management, not autonomous algorithmic performance.
    7. The type of ground truth used: Not applicable.
    8. The sample size for the training set: Not applicable. There is no mention of an AI algorithm requiring a training set.
    9. How the ground truth for the training set was established: Not applicable.

    In summary, the provided 510(k) document pertains to a Picture Archiving Communications System (PACS) that facilitates the handling and viewing of medical images, rather than performing automated analysis or diagnosis. Consequently, the performance criteria and study details requested are not relevant or present within this type of regulatory submission for this specific device. The 'study' mentioned is a hazard analysis and a comparison to a predicate device for substantial equivalence, not a clinical performance study.

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