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510(k) Data Aggregation

    K Number
    K161341
    Device Name
    LIFESYS PACS
    Date Cleared
    2017-04-05

    (327 days)

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

    LifeSys™ PACS is a Picture Archive and Communications software product used to receive pertinent radiology patient information and DICOM images and allow easy generation of a Radiology Report for distribution over a network.

    LifeSys™ PACS software is intended for use as a primary diagnostic and analysis tool for diagnostic images. LifeSys™ PACS is for hospitals, imaging centers, radiologists, radiology professional services providers and any user who requires and is granted access to patient image, demographic and report information.

    The LifeSys™ PACS viewer displays images from CT, computed radiography, MRI, nuclear medicine. PET. ultrasound. x-rav angiography. and x-ray fluoroscopy.

    Device Description

    LifeSys™ PACS is a PACS software product that provides medical imaging departments of all types (Hospitals, Imaging Centers, and Clinics) with the capability to archive patient imaging studies and generate reports on said studies. LifeSys™ PACS is a single piece of software which includes the following functional modules: LifePACS™, which includes a Worklist, Tech Page, Image acquisition, receipt and archive, Report Editor, and tools for integration; and LifeView™, which includes a DICOM image viewer, rapid loading for fast and efficient reading and reporting and multiple monitor support.

    AI/ML Overview

    The provided document describes the FDA 510(k) premarket notification for the LifeSys™ PACS device. However, it does not contain the detailed information necessary to answer all parts of your request regarding acceptance criteria and studies proving the device meets those criteria.

    Specifically, the document focuses on establishing substantial equivalence to a predicate device (eRAD PACS and eRAD RIS/PACS) based on technical characteristics, general function, application, and intended use. It mentions "Thorough non-clinical system verification and validation testing" and that the "LifeSys™ PACS software passed all in-house testing criteria," but it does not provide any specific acceptance criteria, reported device performance metrics, study details (like sample sizes, ground truth establishment, expert qualifications, or multi-reader studies), or effect sizes for human reader improvement.

    The document states:

    • "The two devices are substantially equivalent in the areas of design, architecture, general function, application, and intended use."
    • "The new device does not raise any new potential safety risks and is equivalent in performance to the predicate device."
    • "Thorough non-clinical system verification and validation testing was conducted in accordance with applicable international standards and internal design requirement to verify that LifeSys™ PACS software product meets user needs and indications for use."

    These statements suggest that performance was evaluated, but the specifics of how that performance was measured against what criteria are not detailed in this 510(k) summary. Given that the device is a Picture Archiving and Communications System (PACS) intended as a "primary diagnostic and analysis tool," its performance in displaying images would be crucial, but the document does not elaborate on this.

    Therefore, many of your questions cannot be answered from the provided text.

    Here's a breakdown of what can and cannot be inferred/extracted from the document:

    1. A table of acceptance criteria and the reported device performance

    • Cannot be provided. The document states that the software "passed all in-house testing criteria" and confirms "equivalence in performance to the predicate device," but it does not specify what those criteria were or detail any quantitative performance metrics.

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

    • Cannot be provided. No information on sample sizes (e.g., number of images, cases, or studies) or data provenance (country of origin, retrospective/prospective) is given for any testing.

    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts

    • Cannot be provided. The document does not describe any test set for which ground truth would be established by experts. The focus is on the software's functional equivalence and technical characteristics rather than diagnostic accuracy studies involving human readers.

    4. Adjudication method (e.g. 2+1, 3+1, none) for the test set

    • Cannot be provided. As no details on a test set or expert evaluation are given, no adjudication method is mentioned.

    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

    • Cannot be provided. The document makes no mention of AI assistance, nor does it describe any MRMC studies or human reader performance comparisons. The device is a PACS, which is a viewing and archiving system, not an AI-powered diagnostic aid.

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

    • Cannot be provided. While "non-clinical system verification and validation testing" was done, the document doesn't provide details on what constitutes "standalone performance" for a PACS (as it's primarily a display and management system for human interpretation). It explicitly states, "A physician, providing ample opportunity for competent human intervention interprets images and information being displayed." indicative of human-in-the-loop operation.

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

    • Cannot be provided. No specific ground truth methodology is mentioned as no independent diagnostic performance study is detailed.

    8. The sample size for the training set

    • Cannot be provided. The document refers to "in-house testing criteria" and verification/validation, but it does not describe a "training set" in the context of an algorithm that learns from data. This device is a PACS software, not an AI/ML algorithm that would typically have a "training set."

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

    • Cannot be provided. (See point 8).

    In conclusion, the provided FDA 510(k) summary for LifeSys™ PACS focuses on demonstrating substantial equivalence primarily through comparing technical specifications and intended use with a predicate device, rather than providing detailed clinical performance studies or specific acceptance metrics for image viewing and diagnostic interpretation capabilities.

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