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510(k) Data Aggregation

    K Number
    K153103
    Device Name
    CARESTREAM Vue PACS
    Manufacturer
    CARESTREAM HEALTH, INC.
    Date Cleared
    2016-02-12

    (109 days)

    Product Code
    LLZ
    Regulation Number
    892.2050
    Type
    Traditional
    Panel
    Radiology
    Reference & Predicate Devices
    K120196,K132095,K973835
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The CARESTREAM Vue PACS is an image management system whose is to provide completely scalable local and wide area PACS solutions for hospital and related institutions/sites, which will archive, retrieve and display images and data from all hospital modalities and information systems.

    The system contains interactive tools in order to ease the process of analyzing and comparing three dimensional (3D), CT Perfusion (CTP), and Digital Subtraction Angiography (DSA) images. It is a single system that integrates review, dictation and reporting tools to create a productive work environment for the radiologists and physicians.

    The system contains a Perfusion module with interactive tools to ease the process of analyzing and comparing Computed Tomography Perfusion (CTP) images of adult patients. The Arterial Input Function (AIF), Venous Output Function (VOF), and Brain Centerline are automatically detected with the ability for manual correction by the user. Blood perfusion parameters are automatically calculated and displayed as a set of user friendly perfusion maps and perfusion tables summarizing the results. The perfusion maps include relative Cerebral Blood Volume (rCBV), relative Cerebral Blood Flow (rCBF), Mean Transit Time (MTT), Time to Peak (TTP), and Time to maximum impulse response function (TMAX). The perfusion tables include the calculation of parameters related to tissue blood volume.

    The system supports Subtractive tools to aid with the analysis of Digital Subtraction Angiography (DSA) images in both interventional radiology and cardiology. Subtraction automatically subtracts a mask from contrast frames of an X-Ray Angiography study for visualization of vascular anatomy and pathology of adult patients.

    The Vue Motion software program is used for patient management by clinicians in order to access and display patient data, medical reports, medical data, and medical images for different modalities including CR, DR, CT, MR, NM, ECG, and US.

    Vue Motion provides wireless and portable access to medical images for remote reading or referral purposes from web browsers including usage with validated mobile device is not intended to replace full workstations and should be used only when there is no access to a workstation. For primary interpretation and review of mammography images, only use display hardware that is specifically designed for and cleared by FDA for mammography.

    Device Description

    CARESTREAM Vue PACS is an image management system. It provides functionality to allow remote site access to image and patient data enabling diagnostic reading through industry standard interfaces. The modification to the Vue PACS device described in this submission includes the addition of the following modules:

      1. Perfusion Module The calculation of parameters related to tissue flow (perfusion) and tissue blood volume.
      1. Subtraction Feature Subtraction of two images representing the same part of the anatomy (one with contrast media and one without contrast media) resulting in an image that displays the vascular anatomy/pathology only.
    AI/ML Overview

    The provided text describes a 510(k) premarket notification for the CARESTREAM Vue PACS, which includes a Perfusion Module and a Subtraction Feature. The document aims to demonstrate substantial equivalence to predicate devices rather than fulfilling specific acceptance criteria in the form of numerical performance targets. Therefore, a direct "acceptance criteria" table with numerical performance metrics isn't explicitly stated in the document as would be typical for an AI performance study with strict thresholds.

    However, based on the information provided, we can infer the acceptance criteria and study findings in relation to establishing substantial equivalence.

    Here's an attempt to structure the information as requested, acknowledging the nature of a 510(k) submission focused on substantial equivalence:

    Inferred Acceptance Criteria and Reported Device Performance

    Criteria CategoryInferred Acceptance CriteriaReported Device Performance
    Perfusion ModuleEquivalent clinical quality (radiologist evaluation of key metrics) to the Olea Sphere Perfusion Module.A clinical study demonstrated "equivalent clinical quality" between the investigational Carestream Vue PACS Perfusion Module and the predicate Olea Sphere Perfusion Module using radiologist evaluation of key CTP image metrics.
    Subtraction FeatureCorrect application of subtraction to XA test patterns and clinical images for all grey shades and boundary conditions, with functionality as intended. Substantial equivalence to the Philips Easy Vision Family Workstation Option Vascular Analysis.Engineering Tests demonstrated that the “Subtraction Feature was applied correctly to both X-Ray Angiography (XA) test pattern and XA clinical images for all grey shades and boundary conditions using both quantitative and visual tests.” The feature “functioned as intended,” demonstrating “substantial equivalence.”

    Detailed Study Information:

    1. Sample Size Used for the Test Set and Data Provenance:

      • Perfusion Module: The document mentions a "clinical study" but does not specify the sample size (number of cases or patients) used for the test set. It also does not specify the data provenance (e.g., country of origin, retrospective or prospective nature of the data).
      • Subtraction Feature: The document mentions "Engineering Tests" using "XA test pattern and XA clinical images." It does not specify the number of clinical images used or their provenance.

    2. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications:

      • Perfusion Module: The document mentions "radiologist evaluation of key metrics" in the clinical study. It does not specify the number of radiologists involved or their specific qualifications (e.g., years of experience, subspecialty).
      • Subtraction Feature: The document mentions "quantitative and visual tests" in the Engineering Tests. It does not specify if experts with specific qualifications were used to establish ground truth, nor the number of such experts.

    3. Adjudication Method for the Test Set:

      • The document does not explicitly describe any formal adjudication method (e.g., 2+1, 3+1) for either the Perfusion Module or the Subtraction Feature studies. For the Perfusion Module, "radiologist evaluation" is mentioned, but the method of consensus or independent assessment is not detailed.

    4. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study:

      • Perfusion Module: A "clinical study" was performed comparing the investigational device with a predicate device through "radiologist evaluation." This could imply a comparative study involving human readers, but the details (e.g., if readers used both systems, if it was a reader performance study) are not provided.
      • Effect Size: The document does not provide any effect size or quantitative measure of how much human readers improve with AI vs. without AI assistance. The focus is on demonstrating "equivalent clinical quality" between the investigational device and the predicate, not on human reader improvement with AI assistance. The device itself is a PACS module, providing interactive tools for analysis, rather than an AI for a diagnostic task.

    5. Standalone Performance (Algorithm Only without Human-in-the-Loop Performance):

      • Perfusion Module: The Perfusion Module automatically calculates parameters. While the "radiologist evaluation" assesses the output of the module, the study focuses on the clinical quality of the results rather than a standalone algorithmic diagnostic performance. The document describes the module as providing "interactive tools" and automatic detection with "ability for manual correction by the user," suggesting a human-in-the-loop design. No standalone performance metrics for the algorithm are provided.
      • Subtraction Feature: This feature "automatically subtracts" images. The "Engineering Tests" assessed its correct application and function. This suggests an evaluation of the algorithm's output, but it's not presented as a standalone diagnostic performance study.

    6. Type of Ground Truth Used:

      • Perfusion Module: "Radiologist evaluation of key metrics" applicable to CTP images was used for comparison. This implies expert consensus or expert interpretation served as the reference for clinical quality. It does not explicitly state pathology or outcomes data.
      • Subtraction Feature: The ground truth for the Engineering Tests involved "XA test pattern" (likely known, manufactured patterns) and "XA clinical images." The correctness was assessed through "quantitative and visual tests," implying a comparison against expected outcomes or expert visual inspection for clinical images.

    7. Sample Size for the Training Set:

      • The document does not provide any information regarding a training set size. As a 510(k) submission for a PACS module with specific functionalities (perfusion calculations, image subtraction), the development might involve rule-based algorithms or models trained on data, but this information is not disclosed in the summary.

    8. How the Ground Truth for the Training Set Was Established:

      • As no training set information is provided, there is no information on how its ground truth was established.
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