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510(k) Data Aggregation

    K Number
    K981291
    Manufacturer
    Date Cleared
    1998-06-29

    (81 days)

    Product Code
    Regulation Number
    892.1200
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Vantage 3.0 InSynch ™ option to the ADAC Gamma Camera Systems is intended to produce images of two emission isotopes simultaneously while also acquiring a transmission image.

    Device Description

    Vantage 3.0 InSynch™ is a software program, which will be marketed as an optional addition to ADAC Laboratories Gamma Camera products. This is a modification of the Vantage 2.0 ExSPECT software package, cleared in 510(k) K971878.

    Vantage 3.0 InSynch™ is a computer program that produces nuclear medicine images of two isotopes acquired simultaneously, corresponding to specific energy levels and a transmission image from external radioactive scanning line sources. Vantage 3.0 InSynch™ is an extension of Vantage 2.0 ExSPECT which acquires a single isotope image with the transmission image produced by the external radioactive scanning line sources.

    AI/ML Overview

    Here's an analysis of the provided text regarding the acceptance criteria and study for the Vantage 3.0 InSynch™ device:

    Acceptance Criteria and Reported Device Performance

    The provided 510(k) summary does not explicitly state quantitative acceptance criteria in a dedicated section. However, the "Testing" section implies that the primary acceptance criterion was demonstrating comparable image quality between simultaneous dual-isotope scanning (new device, Vantage 3.0 InSynch™) and sequential dual-isotope scanning (predicate device, Vantage 2.0 ExSPECT).

    Acceptance Criteria (Implied)Reported Device Performance
    Comparable image quality between simultaneous dual-isotope scanning (Vantage 3.0 InSynch™) and sequential dual-isotope scanning (Vantage 2.0 ExSPECT)."The quality of the images produced was similar to the quality of images produced by the predicate device." "A study was conducted to demonstrate that Vantage 3.0 InSynch™ provides comparable images..."

    Detailed Study Information:

    1. Sample size used for the test set and the data provenance:

      • The document does not specify the sample size (number of images or patients) used for the test set.
      • The data provenance (e.g., country of origin, retrospective or prospective) is not mentioned.
    2. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

      • The document does not mention the use of experts to establish ground truth or their qualifications. The evaluation of image quality appears to be a direct comparison within the study, rather than against an independently established ground truth.
    3. Adjudication method (e.g., 2+1, 3+1, none) for the test set:

      • The document does not describe any adjudication method.
    4. 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:

      • The document describes a comparison between two imaging methods (simultaneous vs. sequential dual-isotope scanning) produced by different software versions. It does not describe an MRMC study or evaluate the improvement of human readers with or without AI assistance. The device itself is software for image acquisition and reconstruction, not an AI-assisted diagnostic tool for human readers in the modern sense.
    5. If a standalone (i.e., algorithm only without human-in-the-loop performance) was done:

      • Yes, the study described is a standalone evaluation of the algorithm's output (image quality). The comparison is between the images produced by the new software (Vantage 3.0 InSynch™) and the images produced by the predicate software (Vantage 2.0 ExSPECT). There's no human reader "in-the-loop" as part of the primary performance evaluation described.
    6. The type of ground truth used (expert consensus, pathology, outcomes data, etc.):

      • The concept of a "ground truth" as a separate, definitive diagnostic standard does not appear to be directly applicable or explicitly used in the described study. Instead, the study's goal was to demonstrate equivalence in image quality between the new and predicate device's output. The "ground truth" for the comparison was effectively the image quality produced by the predicate device as a benchmark for what is acceptable.
    7. The sample size for the training set:

      • The document does not mention a "training set" in the context of machine learning, as this device appears to be a software modification for image acquisition and reconstruction in a gamma camera, not an AI/ML algorithm that requires a traditional training set.
    8. How the ground truth for the training set was established:

      • Not applicable, as a training set and its associated ground truth are not mentioned for this device.
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