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510(k) Data Aggregation

    K Number
    K012093
    Manufacturer
    Date Cleared
    2001-09-21

    (78 days)

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

    The AETmed Medical image processing Software is a software device intended to be used by qualified medical professionals, after proper installation on an appropriate hardware platform, for capturing, retrieving, viewing, processing, printing, archiving, and communicating medical images, such as cardiac catheterization, echo-cardiography, and general radiological studies.

    Device Description

    The AETmed Medical image processing Software is a software device intended to be used by qualified medical professionals, after proper installation on an appropriate hardware platform, for capturing, retrieving, viewing, processing, printing, archiving, and communicating medical images, such as cardiac catheterization, echo-cardiography, and general radiological studies.

    The Version 3.0 DICOMed Family Software System consists of the following components:

    • DICOMed DIG.IT image acquisition and CD recording station
    • DICOMed P@CS image archiving manager
    • DICOMed Review Cardio review workstation for cardiology
    • DICOMed Review diagnostic review workstation for radiology
    AI/ML Overview

    The provided text is a 510(k) summary for the AETmed Image Processing Software. It focuses on demonstrating substantial equivalence to predicate devices rather than providing detailed acceptance criteria and a study proving the device meets those criteria.

    Therefore, many of the requested items cannot be extracted directly from this document. The document primarily uses a Substantial Equivalence Comparison Chart (Table 1) to compare the features of the AETmed Image Processing Software with predicate devices. This comparison implicitly serves as the "study" for acceptance, indicating that if the new device has comparable or superior features to legally marketed predicate devices, it is considered substantially equivalent.

    Here's a breakdown of what can and cannot be answered based on the provided text:


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

    The document does not explicitly state "acceptance criteria" in the traditional sense of measurable performance metrics with thresholds. Instead, it demonstrates "substantial equivalence" by comparing device features with legally marketed predicate devices. The "reported device performance" is implicitly shown through this feature comparison.

    FeatureAcceptance Criteria (Implied: Substantially Equivalent to Predicates)Reported Device Performance (AETmed Image Processing Software)
    ManufacturerAETmedAETmed
    Classification892.2050; Class II892.2050; Class II
    Intended UseComparable to predicates for medical image capture, viewing, processing, archiving, and communication for cardiac catheterization, echocardiography, and general radiological studies.Capturing, retrieving, viewing, processing, printing, archiving, and communicating medical images (cardiac catheterization, echo-cardiography, general radiological studies). Similar to predicates.
    Graphical User InterfaceYesYes (Matches predicates)
    PlatformPCPC (Matches predicates)
    Operating SystemWindows NT, Windows 2000 (at least Windows NT as per predicates)Windows NT, Windows 2000 (Broader than one predicate, similar to another)
    Display ResolutionUp to 2048x2560 (Comparable to leading predicates)Up to 2048x2560 (Matches leading predicates)
    Gray scale resolutionFrom 8 bits, 256 levels to 24 bits true color (Comparable to leading predicates)From 8 bits, 256 levels to 24 bits true color (Matches leading predicates)
    Multi-monitor supportYesYes (Matches predicates)
    Patient DemographicsYesYes (Matches predicates)
    NetworkingTCP/IPTCP/IP (Matches predicates)
    Image CommunicationDICOM CompliantDICOM Compliant (Matches predicates)
    DICOM CompliantYesYes (Matches predicates)
    Image CompressionJPEG loss-less (at least)JPEG loss-less (Comparable/matches some predicates)
    Video signals grabbingYesYes (Matches predicates)
    Analogic Video Input format525, 625, 1023, 1049, 1249; interlaced or progressive (Comparable to predicates)525, 625, 1023, 1049, 1249; interlaced or progressive (Matches one predicate, exceeds another)
    Analogic Video Input rate<= 30 fps<= 30 fps (Matches predicates)
    Image Archiving (Hard Disk)YesYes (Matches predicates)
    Image Archiving (Removable media)CD-R, MOD, DVD, DLT, other DICOM Entities (Comparable to predicates)CD-R, MOD, DVD, DLT, other DICOM Entities (Broader than one predicate, similar to others)
    Image ReviewStill images, cine-loops, Window, level, zoom, magnifying lens, Configurable layout (Comparable to predicates)Still images, cine-loops, Window, level, zoom, magnifying lens, Configurable layout (Similar to predicates)
    Image ProcessingAnnotations, Distances, Angles, Pixel Values, Pixel Distribution, Grey level statistics, Quantitative Coronary Analysis, Left Ventricle Analysis (Comparable to leading predicates)Annotations, Distances, Angles, Pixel Values, Pixel Distribution, Grey level statistics, Quantitative Coronary Analysis, Left Ventricle Analysis (Matches a leading predicate, exceeds others)
    3D Image ProcessingMPR, MIP, mip, Volume rendering (Comparable to leading predicates)MPR, MIP, mip, Volume rendering (Matches a leading predicate, exceeds others)
    Quality ControlYesYes (Matches known predicates)
    Workflow ManagementYesYes (Matches known predicates)
    Image DatabaseYesYes (Matches predicates)

    2. Sample size used for the test set and the data provenance (e.g., country of origin of the data, retrospective or prospective)

    The document does not describe a "test set" in the context of a performance study with patient data. It is a comparison of product features. Therefore, this information is not applicable and not provided.


    3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts (e.g., radiologist with 10 years of experience)

    This information is not applicable as no "test set" with ground truth established by experts is described for a performance study. The ground truth for feature comparison is the specifications of the predicate devices.


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

    Not applicable, as no test set or adjudication process for clinical performance is described.


    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

    No MRMC comparative effectiveness study is mentioned or implied. The device is image processing software, not an AI diagnostic tool designed to assist human readers in a diagnostic task that can be quantified with an effect size.


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

    The device is image processing software intended for use by "qualified medical professionals." It is not described as a standalone diagnostic algorithm. The demonstration of substantial equivalence focuses on functional features, not independent diagnostic performance.


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

    The document does not report a ground truth based on clinical data or expert consensus in relation to diagnostic accuracy. The "ground truth" for the substantial equivalence claim is the features and specifications of the predicate devices.


    8. The sample size for the training set

    Not applicable. The document describes image processing software, not a machine learning model that requires a training set.


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

    Not applicable, as there is no training set for a machine learning model described.

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