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510(k) Data Aggregation

    K Number
    K170949
    Device Name
    RadiForce MX315W
    Manufacturer
    Date Cleared
    2017-04-27

    (27 days)

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

    RadiForce MX315W

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

    This product is intended to be used in displaying digital images for review, analysis and diagnosis by trained medical practitioners. It does not support the display of mammography images for diagnosis.

    Device Description

    RadiForce MX315W is a color LCD monitor for viewing medical images other than those of mammography. The color panel employs in-plane switching (IPS) technology allowing wide viewing angles and the matrix size (or resolution) is 4,096 x 2,160 pixels (8MP) with a pixel pitch of 0.1704 mm.

    Since factory calibrated display modes, each of which is characterized by a specific tone curve (including DICOM GSDF), a specific luminance range and a specific color temperature, are stored in lookup tables within the monitor, the tone curve is e.g. DICOM compliant regardless of the display controller used.

    RadiCS is application software to be installed in each workstation offering worry-free quality control of the diagnostic monitors including the RadiForce MX315W based on the QC standards and guidelines and is capable of quantitative tests and visual tests defined by them. The RadiCS and its subset, RadiCS LE, are included in this 510(k) submission as an accessory to the RadiForce MX315W.

    AI/ML Overview

    The provided text describes a 510(k) premarket notification for a medical display device, the EIZO RadiForce MX315W. It outlines the device's technical specifications and compares them to a predicate device, the RadiForce RX840. The document focuses on demonstrating substantial equivalence rather than presenting an AI-powered device.

    Therefore, the document does not contain information about an AI/ML-powered medical device and its performance studies regarding acceptance criteria.

    The questions posed are relevant to AI/ML device submissions, which typically involve performance studies demonstrating accuracy, sensitivity, specificity, or reader improvement. This document is for a display monitor and focuses on physical display characteristics rather than diagnostic performance metrics of an AI algorithm.

    Here's why the requested information cannot be extracted from the provided text:

    • No AI/ML Component: The device, RadiForce MX315W, is a color LCD monitor used for displaying medical images. It does not incorporate artificial intelligence or machine learning for image analysis, diagnosis, or any form of algorithmic assistance.
    • Acceptance Criteria & Performance: The "performance testing" described (Section 9) pertains to the display's physical and optical characteristics (e.g., DICOM GSDF conformance, luminance non-uniformity, chromaticity, MTF, pixel defects). It is about the monitor's fidelity in displaying images, not the diagnostic performance of an AI algorithm. No quantitative metrics like sensitivity, specificity, accuracy, or AUC are mentioned.
    • No Test Set/Ground Truth: Since there's no AI algorithm being evaluated for diagnostic performance, there's no concept of a "test set" of medical images for algorithm validation, "ground truth" derived from expert consensus or pathology, or "training set" for an AI model.
    • No Expert Readers/Adjudication/MRMC Study: The device is a display. While medical practitioners use it, the document does not describe studies where human readers interpret images with or without AI assistance, or where experts establish ground truth for an AI's performance. Therefore, MRMC studies, expert qualifications, and adjudication methods are not applicable and not present.
    • No Standalone Performance: The device is hardware; it doesn't have a "standalone performance" in the context of an algorithm.

    In summary, the provided text is about a medical display monitor and does not offer the necessary information to answer the questions about acceptance criteria and study data for an AI/ML-powered medical device.

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