Search Filters

Search Results

Found 1 results

510(k) Data Aggregation

    K Number
    K150949
    Device Name
    FibroScan
    Manufacturer
    Date Cleared
    2015-06-03

    (56 days)

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

    The FibroScan® system is intended to provide 50Hz shear wave speed measurements and estimates of tissue stiffhess as well as 3.5 MHz ultrasound coefficient of attenuation (CAP: Controlled Attenuation Parameter) in internal structures of the body.

    FibroScan® is indicated for noninvasive measurement in the liver of 50 Hz shear wave speed and estimates of stiffness as well as 3.5 MHz ultrasound coefficient of attenuation (CAP: Controlled Attenuation Parameter). The shear wave speed and stiffness, and CAP may be used as an aid to clinical management of adult patients with liver disease.

    Shear wave speed and stiffness may be used as an aid to clinical management of pediatric patients with liver disease.

    Device Description

    FibroScan®, based on Vibration-Controlled Transient Elastography (VCTE™) technology, is designed to perform non-invasive measurements of liver shear wave speed and estimates of tissue stiffness. A mechanical vibrator produces low-amplitude elastic waves that travel through the skin and intercostal space into the liver. The speed of propagation of the shear (elastic) wave is measured using ultrasounds. A new FibroScan® parameter labeled CAP (Controlled Attenuation Parameter), ranging between 100 and 400 decibels per meter (dB/m), provides an estimation of the total aforementioned ultrasonic wave attenuation (forward and return paths) at 3.5 MHz, measured concomitantly with tissue stiffness.

    AI/ML Overview

    The provided text describes the FibroScan® system, which performs non-invasive measurements of liver shear wave speed and tissue stiffness, as well as an ultrasound coefficient of attenuation (CAP). The new submission (K150949) focuses on the addition of CAP measurements.

    Here's an analysis of the acceptance criteria and the study that proves the device meets them:

    1. Table of Acceptance Criteria and Reported Device Performance

    The acceptance criteria are not explicitly stated in numerical thresholds, but rather as comparative performance to the predicate devices. The performance is assessed in terms of bias and precision for both shear wave measurements (from the predicate FibroScan®) and the new CAP measurements (from the candidate FibroScan®).

    MetricAcceptance Criteria (inferred: similar or better than predicate)FibroScan® Predicate Device Performance (Shear Wave)Candidate Device Performance (CAP)
    Bias (M+ probe)< 13%[-11.5%; 0.7%] (Overall range <13%)[-4.9%; -0.4%] (Overall range <5%)
    Bias (XL+ probe)< 16%[-13.9%; 1.3%] (Overall range <16%)[-3.5%; 6.5%] (Overall range <10%)
    Precision (M+ probe)< 2%[0.6%; 1.9%] (Overall range <2%)[0%; 0.1%] (Overall range <1%)
    Precision (XL+ probe)< 4%[0%; 3.1%] (Overall range <4%)[0.4%; 1%] (Overall range <1%)

    Conclusion from table: The candidate FibroScan® device successfully meets the acceptance criteria (inferred as being similar or better than the predicate) as its bias and precision values for CAP measurements are indeed better than those reported for the shear wave measurements of the predicate FibroScan® device.

    2. Sample Size Used for the Test Set and Data Provenance

    The provided text only mentions "tests performed on phantoms with known attenuations" for the performance data.

    • Sample Size for Test Set: Not explicitly stated. The description mentions "tests performed on phantoms," implying multiple tests but no specific number of phantoms or measurements.
    • Data Provenance: The tests were performed on "phantoms," indicating a controlled laboratory setting (bench testing). There is no information provided regarding the country of origin or whether it was retrospective or prospective data from human subjects.

    3. Number of Experts Used to Establish the Ground Truth for the Test Set and Qualifications of Those Experts

    • Since the test was performed on "phantoms with known attenuations," the ground truth was established by the physical properties of the phantoms themselves. Therefore, no human experts were used to establish ground truth for this specific performance evaluation.

    4. Adjudication Method for the Test Set

    • No adjudication method is relevant as the ground truth was based on the known, objective properties of the phantoms.

    5. Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study

    • No MRMC comparative effectiveness study was mentioned. The study focused on the technical performance of the device on phantoms, not on human reader performance with or without AI assistance.

    6. Standalone Performance (Algorithm Only without Human-in-the-Loop Performance)

    • Yes, the performance data presented is a standalone evaluation of the device as an algorithm/system measuring physical properties (shear wave speed, tissue stiffness, CAP) on phantoms. There is no mention of human interaction or interpretation being part of this specific performance evaluation.

    7. Type of Ground Truth Used

    • Known Attenuations of Phantoms: The ground truth for the test set was the "known attenuations" of the phantoms. This is a form of objective, engineered ground truth.

    8. Sample Size for the Training Set

    • The document primarily describes a 510(k) submission for a device, particularly focusing on the performance validation of its new feature (CAP) using bench testing. It does not mention a "training set" in the context of machine learning or AI models. This device, based on VCTE™ technology, seems to be a measurement instrument, not a learning algorithm that requires a training set in the typical machine learning sense.

    9. How the Ground Truth for the Training Set Was Established

    • As no training set is discussed or implied for a machine learning model, this question is not applicable to the information provided. The "training" for such a physical measurement device would involve its design, calibration, and manufacturing processes to ensure it accurately measures the intended physical properties.
    Ask a Question

    Ask a specific question about this device

    Page 1 of 1