Search Filters

Search Results

Found 1 results

510(k) Data Aggregation

    K Number
    K082135
    Device Name
    SHOWCASE
    Date Cleared
    2008-10-21

    (84 days)

    Product Code
    Regulation Number
    892.2050
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    ShowCase is diagnostic quality radiological viewing software. ShowCase can be used to receive, store, display and manipulate medical images and associated clinical data. This device is not intended for diagnosis of lossy compressed images.

    Device Description

    ShowCase is diagnostic quality radiological viewing software. ShowCase can be used to receive, store, display and manipulate medical images and associated clinical data. This device is not intended for diagnosis of lossy compressed images.

    AI/ML Overview

    The provided text is a 510(k) summary for the Trillium Technology, Inc. ShowCase soft-copy reading system. This document focuses on demonstrating substantial equivalence to predicate devices, rather than presenting a performance study against specific acceptance criteria for a novel algorithm.

    Therefore, many of the requested sections (acceptance criteria, reported performance, sample sizes, ground truth establishment, expert qualifications, adjudication, MRMC studies, standalone performance, training set details) are not applicable or not explicitly detailed in this type of submission.

    The 510(k) summary for the ShowCase device emphasizes its functional equivalence to existing PACS and ultrasound workstations. The validation described is primarily related to software development and general safety, rather than a clinical performance study with statistical endpoints.

    Here's a breakdown based on the available information:

    1. Table of Acceptance Criteria and Reported Device Performance

    Not explicitly defined in terms of quantitative performance metrics for a specific algorithm. The substantial equivalence claim is based on the device's ability to perform functions similar to predicate devices (eFilm Workstation, syngo Ultrasound Workplace, and Volcano s5i for a specific feature) and its adherence to software development and safety protocols.

    Acceptance Criteria (Implied)Reported Device Performance
    Functional Equivalence:
    - Receive, store, display, and manipulate medical images and associated clinical data.ShowCase performs these functions, similar to predicate devices.
    - DICOM compliance.ShowCase is DICOM compliant.
    - Image and structured report viewing.ShowCase includes these functions.
    - Imaging measurements and manipulation tools.ShowCase includes these tools.
    - Stress echo displays (for ultrasound).ShowCase includes stress echo displays.
    - Doppler measurement tools (for ultrasound).ShowCase includes Doppler measurement tools.
    - In-line Digital Display (ILD) for intravascular ultrasound pullback.ShowCase provides ILD image playback.
    Safety and Effectiveness:
    - Labeling with instructions, cautions, and warnings.ShowCase labeling contains these.
    - Use of "off the shelf" computer components.Hardware components are "off the shelf".
    - No direct patient contact or control of life-sustaining devices.Confirmed, leading to a "minor" Level of Concern.
    - Software designed, developed, tested, and validated according to written procedures.Certification provided.
    - Diagnostic quality images and associated information.Claimed by the manufacturer.

    2. Sample size used for the test set and the data provenance

    Not applicable in the context of a clinical performance study for an AI algorithm.
    The "testing" mentioned refers to software verification and validation, not a clinical test set with specific image data.

    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 by experts for a test set is described.

    4. Adjudication method for the test set

    Not applicable. No clinical test set requiring adjudication is described.

    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. ShowCase is a viewing system, not an AI-assisted diagnostic tool as understood in the context of MRMC studies for AI.

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

    Not applicable. ShowCase is a software system for human interpretation, not a standalone diagnostic algorithm.

    7. The type of ground truth used (expert consensus, pathology, outcomes data, etc.)

    Not applicable. The validation described is for software functionality and safety, not for diagnostic accuracy against a clinical ground truth.

    8. The sample size for the training set

    Not applicable. There is no mention of a machine learning or AI algorithm being "trained" in this submission. The "training set" concept is irrelevant to a soft-copy reading system.

    9. How the ground truth for the training set was established

    Not applicable. As above, no training set or associated ground truth establishment is mentioned.

    Summary of Device and Evidence:

    The Trillium Technology ShowCase is a diagnostic quality radiological viewing software (PACS). Its 510(k) submission demonstrates substantial equivalence to predicate devices (eFilm Workstation, syngo Ultrasound Workplace, and the Volcano s5i for its ILD feature) primarily through functional comparison and adherence to software development and quality control processes. The "validation and effectiveness" section describes internal testing by programmers, non-programmers, and potential customers to ensure the software functions as intended and provides diagnostic quality images. This is a typical approach for software-only medical devices that are tools for clinicians, rather than algorithms performing independent diagnoses. The submission does not include a clinical performance study against specific diagnostic acceptance criteria, as it is not presenting a new diagnostic algorithm but rather a viewing system.

    Ask a Question

    Ask a specific question about this device

    Page 1 of 1