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510(k) Data Aggregation

    K Number
    K960294
    Date Cleared
    1996-04-19

    (88 days)

    Product Code
    Regulation Number
    892.1000
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Phase Conjugate Symmetry (PCS) Option reduces the acquistion time by approximately 40% without impacting the resolution. The indications for use are the same as for standard MR Imaging.

    Device Description

    The Phase Conjugate Symmetry (PCS) Option is a software feature which reduces the acquistion time by reducing the number of phase encodings needed to create an image.

    AI/ML Overview

    This document describes a medical device, the "Phase Conjugate Symmetry Option for Outlook," which is a software feature for MRI systems. The primary claim of this device is to reduce MRI acquisition time by approximately 40% without impacting resolution.

    Here's an analysis of the provided information concerning acceptance criteria and the study proving the device meets them:

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

    The document doesn't explicitly state "acceptance criteria" in a quantitative performance metric sense (e.g., target SNR reduction, specific resolution values). Instead, it relies on a comparison to a predicate device (DVP Software K895151) and asserts equivalence in performance.

    ParameterAcceptance Criteria (Implied by Predicate Equivalence)Reported Device Performance (Phase Conjugate Symmetry Option for Outlook)
    General UseOperator selectable, usable with all sequences (with stated exceptions for predicate)Operator selectable, can be used with all sequences (with stated exception)
    Reconstruction AlgoSame as predicate (Symmetry properties of the Fourier transform used to synthesizeSame as predicate
    Acquisition TimeReduced as compared to a "normal" acquisitionReduces acquisition time by approximately 40%
    SNRReduced in a mathematically predictable manner (same as predicate)Same as predicate
    ResolutionNo Impact (same as predicate)Same as predicate (no impact)
    Intended UseSame as MRSame as MR

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

    The provided document does not mention a specific test set, patient data, or human expert evaluations. The demonstration of safety and effectiveness relies on a comparison to a predicate device's technology and performance characteristics. No clinical study involving patient data or image analysis by experts is described.

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

    Not applicable. No test set involving human experts is described.

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

    Not applicable. No test set requiring expert adjudication 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:

    Not applicable. This device is a software feature for an MRI system, not an AI-assisted diagnostic tool. No MRMC study is mentioned.

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

    The "study" described is essentially a technical comparison of the software's characteristics and expected physical effects (e.g., SNR reduction, resolution impact) to a previously cleared predicate device. It confirms that the underlying mathematical principles and expected outcomes regarding image properties are the same as the predicate. This is a form of standalone evaluation of the algorithm's effect on image characteristics, but it's not described as a formal quantitative study with specific metrics.

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

    The "ground truth" used for this submission is the established performance and characteristics of the predicate device (DVP Software K895151). The claim is that the new device's software feature operates on the same principles and yields equivalent results. This is a reliance on a "truth by analogy" rather than a direct independent ground truth acquisition for the new device.

    8. The sample size for the training set:

    Not applicable. This is a software feature, not a machine learning model requiring a training set in the conventional sense. Its functionality is based on established mathematical principles of Fourier transforms.

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

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

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