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510(k) Data Aggregation

    K Number
    K180522
    Device Name
    IGTFusion
    Manufacturer
    Date Cleared
    2018-08-16

    (170 days)

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

    IGTFusion

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

    IGTFusion is a stand-alone software product that provides the physician 3 means for comparison of medical imaging data from multiple DICOM conformant imaging modality sources. It allows the display, registration and fusing of medical images as an aid during use by diagnostic radiology, oncology, radiation therapy planning, interventional radiology and other medical Specialties. IGTFusion is not intended for mammography diagnosis.

    Device Description

    The purpose of IGTFusion is to assist the user with the visual evaluation, comparison, and merging of information between anatomical and functional images from a single patient. The user needs to take into consideration the product's limitations and accuracy when integration from the registration results for final interpretation. IGTFusion does not replace the usual procedures for visual comparison of datasets by a user. Fusion images are intended to provide additional information to a user's existing workflow for patient evaluation.

    AI/ML Overview

    The provided text is a 510(k) summary for the device IGTFusion. It explicitly states that "No clinical studies were conducted." Therefore, there is no information available within this document to address the criteria listed in your request regarding acceptance criteria, device performance, sample size, expert ground truth, adjudication methods, MRMC studies, standalone performance, or ground truth for training/test sets.

    The product relies on demonstrating substantial equivalence to predicate devices (VelocityAIS and RTx) based on technological similarities (visualization capabilities, registration, DICOM Compliance, GUI, reporting capabilities) and arguing that any differences (simplified interface, focused on essential representations, no volume rendering/annotations) do not raise new issues of safety and effectiveness.

    The document states that the image registration engine has been "extensively tested to show that is as accurate existing solutions without the need of extra tools," but does not provide any data, methodology, or results of this testing.

    Therefore, I cannot populate the requested table or answer the specific questions about the study design and results, as this information is not present in the provided document.

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