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510(k) Data Aggregation

    K Number
    K993791
    Date Cleared
    1999-11-24

    (15 days)

    Product Code
    Regulation Number
    892.1750
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    CT Perfusion is an image analysis software package that allows the user to produce dynamic image data and to generate information with regard to changes in image intensity over time. It supports the analysis of CT Perfusion images obtained by cine imaging after the injection of contrast and to calculate the various perfusion related parameters (ie: regional cerebral blood flow, regional cerebral blood volume, time to peak). The results are displayed in user-friendly graphic format as parametric images. This software runs on the Advantage Workstation (AW) platform and will aid physicians in the assessment of the extent and type of brain perfusion disturbances.

    Device Description

    CT Perfusion is an image analysis software package that allows the user to process dynamic image data and to generate information with regard to changes in image intensity over time. It supports the analysis of CT Perfusion images and displays the analysis data in a user friendly graphic format and as parametric (single image that is calculated from a set of time course images at a single location) images.

    Application examples include:

    • ° characterization of the amount of blood present in a local region.
    • ° provides the volume of blood that flows through a cerebral circulation region.
    • ° returns the average transit time.
    • o characterizes image intensity increase during a dynamic process.
    • o allows selection of any time-series or "dynamic" data set.
    AI/ML Overview

    The provided text is a 510(k) summary for the GE Medical Systems CT Perfusion option. It describes the device, its intended use, and its substantial equivalence to predicate devices. However, it does not include detailed information about specific acceptance criteria, a study proving device performance against those criteria, or most of the other requested details regarding sample sizes, expert qualifications, or ground truth establishment.

    Here's a breakdown of what can be extracted and what cannot:

    1. Table of Acceptance Criteria and Reported Device Performance:

    The document does not state specific acceptance criteria in terms of quantitative metrics (e.g., sensitivity, specificity, accuracy, or correlation coefficients) or any reported device performance against such criteria. The "Conclusions" section broadly states: "This product provides images comparable to the predicate device." This is a qualitative statement of equivalence, not a performance metric.

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

    This information is not provided in the document. There is no mention of a test set, its size, or the provenance (country, retrospective/prospective) of any data used for validation.

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

    This information is not provided in the document. There is no mention of ground truth establishment or expert involvement for a test set.

    4. Adjudication Method:

    This information is not provided.

    5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

    This information is not provided. There is no mention of an MRMC study or any effect size related to human reader improvement with AI assistance.

    6. Standalone Performance:

    The device is described as an "image analysis software package" that "allows the user to process dynamic image data" and "will aid physicians." This implies it's a tool for human review rather than a fully autonomous diagnostic algorithm. While it performs calculations, there's no standalone performance study in the sense of an algorithm making a diagnosis without human intervention mentioned. The document focuses on its functionality as a post-processing tool.

    7. Type of Ground Truth Used:

    This information is not provided.

    8. Sample Size for the Training Set:

    This information is not provided. There is no mention of a training set or its size. The document refers to a "Software Development and Validation Process" and "Software Verification Plan," but no details on data used in these processes are given.

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

    This information is not provided.


    Summary of Available Information from the Provided Text:

    The document primarily focuses on establishing substantial equivalence to predicate devices (GEMS Functool, GEMS CT 9800 Regional Cerebral Blood Flow) for its CT Perfusion Option. It describes the device's function (processing dynamic image data to generate perfusion parameters like regional cerebral blood flow, regional cerebral blood volume, time to peak) and its intended use (aiding physicians in assessing brain perfusion disturbances).

    The basis for equivalence is stated as:

    • The algorithms used to calculate perfusion parameters are "similar" to the GEMS CT 9800 Regional Cerebral Blood Flow device.
    • The product "provides images comparable to the predicate device."

    It is crucial to understand that this 510(k) summary does not contain the detailed clinical study data or performance metrics that would typically be described as "acceptance criteria" and "device performance" in a modern regulatory submission for an AI/ML device. The regulatory landscape and expectations for evidence of effectiveness for such software were significantly different in 1999. The focus then was more on functional equivalence and safety based on hazard analysis and software development processes, rather than extensive clinical performance studies using quantitative metrics as is common today.

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