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510(k) Data Aggregation

    K Number
    K071000
    Device Name
    MYRIAN
    Manufacturer
    Date Cleared
    2007-05-14

    (35 days)

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

    Myrian is a multi modality medical diagnostic device. It is aimed at reviewing and analysing anatomy and pathology. It also includes DICOM communication capabilities and media interchange features (printing, CD burning, storing). It runs on any standard PC including laptops that might be purchased independently by the end user. It provides user a set of tools meant to create and modify volumes of interest. This device is not indicated for mammography use. Lossy compressed mammography images and digitized film screen images must not be used for primary image interpretations. Mammographic images may only be interpreted using an FDA approved monitor that offers at least 5 mega pixel resolution and meets other technical specifications approved by the FDA.

    Device Description

    Myrian® system is a software suite providing the following services : Import of DICOM images from any DICOM modality, workstation or PACS Visualization of DICOM images in thin MPR, thick MPR and full 3D volume rendering Creation of VOI (Volume Of Interest) with dedicated tools Calculation of volumes, surface and of average, minimum and maximum densities of VOI Follow-up of patient examination Generation of medical reports Export of DICOM images to any format, DICOM entity or media

    AI/ML Overview

    Here's an analysis of the provided text regarding the Intrasense MYRIAN device:

    Analysis of Intrasense MYRIAN Device Performance and Study

    1. Table of Acceptance Criteria and Reported Device Performance

    Based on the provided text, specific numerical acceptance criteria and corresponding reported device performance metrics are not explicitly stated. The submission focuses on demonstrating substantial equivalence to predicate devices and adherence to general software safety guidelines.

    Acceptance Criteria CategoryAcceptance Criteria (As stated or inferred)Reported Device Performance (As stated or inferred)
    General ComplianceRequirements of FDA "Guidance of the Content of Pre Market Submissions for Software Contained in Medical Devices"MYRIAN meets the required specifications.
    Adverse EffectsNo adverse effects detected.No adverse effects have been detected.
    Feature FunctionalityAll described functionalities (Image import, Visualization, VOI creation, Calculation, Follow-up, Reporting, Export) operate as intended.User Site Testing and Benchmarking demonstrate MYRIAN meets required specifications. Implied successful operation of features.
    Safety and EffectivenessSubstantially equivalent to predicate devices in terms of safety and effectiveness.The technological characteristics, features, specifications, materials, mode of operation, and intended use of MYRIAN device are equivalent to those of the predicate devices. Differences do not raise new issues of safety or effectiveness.

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

    The document mentions "User Site Testing, Benchmarking and clinical data analysis" for performance verification. However, no specific sample sizes for the test set or details about data provenance (e.g., country of origin, retrospective/prospective nature) are provided.

    3. Number of Experts Used to Establish Ground Truth and Qualifications

    The document does not specify the number of experts used to establish ground truth or their qualifications. It states that "Typical users of Myrian® with its Modules are trained medical professionals, including but not limited to radiologists, technologists and clinicians," and that images, "When interpreted by a trained physician, filmed or displayed images on the Myrian® and its Modules may be used as a basis for diagnosis." This implies that medical professionals would be involved in evaluating the device, but no details on ground truth establishment are given.

    4. Adjudication Method

    The document does not mention any specific adjudication method (e.g., 2+1, 3+1) for the test set.

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

    The document does not indicate that a Multi-Reader Multi-Case (MRMC) comparative effectiveness study was performed. There is no mention of comparing human readers with and without AI assistance or any effect size of improvement. The device description and performance data focus on its standalone functionality and equivalence to predicate devices.

    6. Standalone (Algorithm Only) Performance Study

    The document implies that the device's performance was evaluated in various settings, stating "User Site Testing, Benchmarking and clinical data analysis demonstrate that MYRIAN meet the required specifications." This suggests that the algorithm and its features were tested for their intended functionality, which aligns with standalone performance evaluation. However, specific metrics of "algorithm-only" performance (like sensitivity, specificity, accuracy for a particular task) are not provided. The focus is on the software suite's general functionality for image processing, visualization, and measurement.

    7. Type of Ground Truth Used

    The document does not explicitly state the type of ground truth used (e.g., expert consensus, pathology, outcomes data). While it mentions that images interpreted by a trained physician may be used for diagnosis, it doesn't describe how ground truth was established for the purpose of validating the device's performance.

    8. Sample Size for the Training Set

    The document does not specify the sample size used for any training set. Given the submission date (2007) and the description of the device (a software suite for general image processing and visualization), it's highly likely that this device does not utilize deep learning or other machine learning algorithms that require explicit "training sets" in the modern sense. It appears to be a rule-based or conventional image processing software.

    9. How Ground Truth for the Training Set Was Established

    As there's no mention of a training set, the document does not describe how ground truth for a training set was established.

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