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510(k) Data Aggregation

    K Number
    K142647
    Device Name
    mint Lesion
    Manufacturer
    Date Cleared
    2015-04-13

    (208 days)

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

    mint Lesion

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

    Mint Lesion is a software solution intended to be used for viewing, manipulation, storage, 3Dvisualization and comparison of medical images from multiple imaging multiple time-points. Mint Lesion is a software only medical device which will be delivered on CDROM / DVD to be installed by trained service personnel.

    Mint Lesion is a medical diagnostic application for viewing, manipulation and comparison of medical images from multiple imaging modalities and/or multiple time-points. The application supports functional data, such as PET or SPECT as well as anatomical datasets, such as CT or MR. The images can be viewed in a number of output formats including MPR, MIP and volume rendering.

    Mint Lesion enables visualization of information that would otherwise have to be visually compared disjointedly. Mint Lesion provides analytical tools to help the user assess, and document the stage of a disease and/or the response to therapy in accordance with user selected standards. Mint Lesion supports the interpretation and evaluation of examinations and follow up documentation of findings within healthcare institutions, for example, in Radiology, Oncology, and Nuclear Medicine environments.

    Note: The clinician retains the ultimate responsibility for making the pertinent diagnosis based on their standard practices and visual comparison of the separate unregistered images. Mint Lesion is a complement to these standard procedures. Mint Lesion is not to be used in mammography.

    Device Description

    mint Lesion™ is a software based Picture Archiving and Communication System (PACS) used with general purpose computing hardware for the display and visualization of medical image data. It runs on either a native or a virtualized Microsoft Windows platform.

    mint Lesion™ functionality provides for communication, storage, processing, rendering, and display of DICOM compliant image data derived from various sources including anatomical datasets (e.g. CT, MRI) and functional datasets (e.g. PET), lesion measurement, tabulation and summation of measurements, lesion categorization and standard evaluation in accordance with radiological staging and response criteria, and generation of a structured report. The user controls these functions with a system of interactive menus and tools.

    AI/ML Overview

    I am sorry, but the provided text does not contain the specific details about acceptance criteria, the study proving the device meets those criteria, or the detailed information regarding sample sizes, ground truth establishment, or multi-reader multi-case studies.

    The document is a 510(k) premarket notification acceptance letter and a summary of the device mint Lesion. It focuses on:

    • Substantial Equivalence: Comparing mint Lesion to predicate devices (OncoTrac and Syngo.via MI Workflows) to demonstrate that it is as safe and effective.
    • Intended Use: Describing the device's purpose for viewing, manipulating, storing, 3D-visualizing, and comparing medical images for assessment, staging, and documenting disease and therapy response.
    • General Information: Manufacturer details, classifications, and regulatory compliance.

    While it mentions that "The mint Lesion™ software has been extensively tested on Windows 64 bit systems by members of the development and quality control teams" and that "Verification and Validation activities have been successfully performed," it does not provide any quantitative data, specific acceptance criteria, or details of any clinical or performance studies.

    Therefore, I cannot populate the table or provide answers to the specific questions you've asked based on the provided text.

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