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510(k) Data Aggregation

    K Number
    K123806
    Device Name
    FIBROSCAN
    Manufacturer
    Date Cleared
    2013-04-05

    (116 days)

    Product Code
    Regulation Number
    892.1560
    Reference & Predicate Devices
    Predicate For
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    FibroScan® is intended to provide 50Hz shear wave velocity measurements through internal structures of the body.

    FibroScan® is indicated for noninvasive measurement of shear wave speed at 50 Hz in the liver. The shear wave speed may be used as an aid to clinical management of patients with liver disease.

    Diagnostic ultrasound imaging or fluid flow analysis of the human body as follows: Abdominal (Mode of Operation: N, Other*: N 1, 2)

    Device Description

    FibroScan® uses transient elastography for the non-invasive measurement of liver shear wave speed. A mechanical vibrator produces low-amplitude elastic waves that travel through the skin and intercostal space into the liver. Ultrasound is used to track the shear wave and to measure its speed, which is correlated with the elasticity of the liver.

    AI/ML Overview

    The document describes the FibroScan® System, an ultrasound device for non-invasive measurement of shear wave speed in the liver. The provided text primarily focuses on non-clinical performance data and does not contain information about clinical studies with human participants that establish acceptance criteria and device performance based on those criteria.

    Here's the relevant information based on the provided text regarding the non-clinical performance:

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

    The acceptance criteria are implied by comparison to a predicate device.

    Performance MetricAcceptance Criteria (Implied from Predicate Device)Reported Device Performance (FibroScan®)
    Bias (Difference in mean shear wave speed, normalized, in percent)Overall range of bias values ~50% (Range: -9.4% to 43.4%)Overall range of bias values < 20% (Range: -13.9% to 1.3%)
    Precision (Standard deviation of individual measurements, normalized)Range of values ~4% (Range: 0% to 3.9%)Range of values ~3% (Range: 0% to 3.1%)

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

    • Sample size for test set: Not applicable. The performance data for this device was based on tests performed on phantoms (not human subjects). The number of phantoms or measurements performed on them is not specified.
    • Data provenance: Not applicable, as the tests were on phantoms.

    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)

    • Not applicable. The ground truth for the phantom tests was based on the known elasticity of the phantoms, not expert consensus.

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

    • Not applicable. Ground truth was based on known phantom properties.

    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 was done. The device performance (accuracy and precision) was evaluated against a predicate device using phantom data.
    • The document mentions a published report by Fraquelli et al. (Gut, 2007) that documented high measurement reproducibility (intraclass correlation coefficient of 0.98 both within and between operators) in a cohort of 200 patients. This study, however, is cited as supporting the general reproducibility of the technology, not as a comparative effectiveness study involving AI or human reader improvement with AI.

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

    • The performance analysis described (bias and precision) is inherent to the device's measurement capabilities on phantoms and therefore represents a standalone evaluation of the device's technical performance. No human-in-the-loop performance is discussed for these specific non-clinical tests.

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

    • For the non-clinical performance described, the ground truth was the known elasticity of phantoms.

    8. The sample size for the training set

    • Not applicable. The document describes a medical device (ultrasound system) that measures shear wave speed based on physical principles, not an AI/machine learning algorithm requiring a "training set" in the conventional sense.

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

    • Not applicable, as there is no mention of a training set for an AI/ML algorithm.
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