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510(k) Data Aggregation

    K Number
    K073176
    Manufacturer
    Date Cleared
    2008-03-19

    (127 days)

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

    Kanteron DICOM Station (KDS) is a software device intended for viewing of images acquired from computer tomography (CT), magnetic resonance (MR), computed radiography (CR), digital radiography (DR), ultrasound (US), and other DICOM compliant medical imaging systems when installed on suitable commercial standard hardware.

    Images and data can be captured, stored, communicated, processed and displayed within the system and or across computer networks at distributed locations.

    Lossy compressed mammographic images and digitized film screen images must not be reviewed for primary diagnosis or image interpretation.

    For primary diagnosis, post process DICOM "for presentation" images must be used. Mammographic images must only be viewed with a monitor approved by the FDA for viewing mammographic images.

    It is the User's responsibility to ensure monitor quality, ambient light conditions, and image compression ratios are consistent with clinical application.

    The KDS is not intended for use as a preoperative surgical planning system and must not be used for this purpose.

    Device Description

    The KDS provides services for review and post processing of diagnostic medical images and information. It conforms to the DICOM 3.0 standard to allow the sharing of medical information with other digital imaging systems. Kanteron DICOM Station (KDS) runs on Apple Mac OSX systems and provides high performance review, navigation and post processing functionality for multidimensional and multimodality images. Language files are separate from image software, allowing software to be provided in various languages.

    AI/ML Overview

    The provided text is a 510(k) summary for the KANTERON DICOM Station (KDS) (Software) Version 3.0, a Picture Archiving Communications System. Based on the document, here's a breakdown of the acceptance criteria and the study information:

    1. Table of Acceptance Criteria and Reported Device Performance

    The document states: "As required by the hazard (risk) analysis, designated individuals performed all verification and validation activities and results demonstrated that the predetermined acceptance criteria were met. The System passed all testing criteria."

    However, the specific acceptance criteria (e.g., performance metrics, thresholds) and the detailed reported device performance are not explicitly provided in the given text. The document broadly indicates that the system "passed all testing criteria" and met "predetermined acceptance criteria."

    2. Sample Sizes and Data Provenance

    The document provides no specific details about the sample size used for any test set or the data provenance (e.g., country of origin, retrospective or prospective) for any performance evaluation.

    3. Number and Qualifications of Experts for Ground Truth

    The document provides no information regarding the number of experts used to establish ground truth or their qualifications.

    4. Adjudication Method

    The document provides no information regarding the adjudication method used for any test set.

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

    The document states that the KANTERON DICOM Station (KDS) is a "Picture Archiving Communications System" and a "software device intended for viewing of images acquired from computer tomography (CT), magnetic resonance (MR), computed radiography (CR), digital radiography (DR), ultrasound (US), and other DICOM compliant medical imaging systems." Its primary function appears to be for image handling, manipulation, and viewing, not for AI-assisted diagnostic interpretation.

    Therefore, an MRMC comparative effectiveness study that assesses how much human readers improve with AI vs. without AI assistance is not described or implied in this document as the device's function does not involve AI assistance for diagnostic tasks.

    6. Standalone (i.e., algorithm only without human-in-the-loop performance) Study

    The document provides no information about a standalone algorithm-only performance study. Given the device's function as a DICOM viewing station, standalone performance metrics (like sensitivity/specificity for a diagnostic task) would not be applicable, as it is fundamentally a tool for human review. The text emphasizes that "Prior to any medical decisions, a licensed medical practitioner reviews the output displays of the KDS system, providing ample opportunity for competent human intervention for the interpretation of images and information being displayed and printed."

    7. Type of Ground Truth Used

    The document provides no information about the type of ground truth used (e.g., expert consensus, pathology, outcomes data).

    8. Sample Size for the Training Set

    The document provides no information about the sample size for any training set. This is consistent with a device that is a PACS viewer rather than an AI-driven diagnostic algorithm.

    9. How Ground Truth for the Training Set Was Established

    The document provides no information on how ground truth for any training set was established. Again, this aligns with the device's function.

    Summary of Information Provided:

    The provided 510(k) summary focuses on the KANTERON DICOM Station (KDS) as a Picture Archiving Communications System (PACS) for viewing and manipulating medical images, establishing its substantial equivalence to a predicate device (Aycan Workstation OsiriX). It emphasizes compliance with DICOM and JPEG standards and general safety/effectiveness principles for a medical image viewing platform. The document confirms that "predetermined acceptance criteria were met" and "The System passed all testing criteria" as part of verification and validation activities, but it does not detail these criteria or the specific performance results. The information typically associated with AI/ML device studies (such as specific performance metrics, sample sizes for test/training sets, expert qualifications, and adjudication methods for diagnostic tasks) is not present in this submission, as the KDS is described as a viewing and processing tool, not an AI-based diagnostic aid.

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