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510(k) Data Aggregation

    K Number
    K200232
    Date Cleared
    2020-06-23

    (145 days)

    Product Code
    Regulation Number
    892.2050
    Reference & Predicate Devices
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    L Vivo platform is intended for non-invasive processing of ultrasound images to detect, measure, and calculate relevant medical parameters of structures and function of patients with suspected disease.

    Device Description

    The LVivo System analyzes echocardiographic patient examination DICOM movies for Global ejection fraction (EF) evaluation. EF is evaluated using two orthogonal planes, four-chamber (4CH) and two-chamber (2CH) views, to provide fully automated analyses of LV function from the echo examination movies. It also has the ability to measure strain and to evaluate the Right Ventricle and well as to measure the bladder.

    AI/ML Overview

    This document describes the acceptance criteria and study results for DiA Imaging Analysis Ltd's LVivo Software Application, specifically focusing on its LVivoRV (Right Ventricular) and LVivo Bladder modules.

    1. Table of Acceptance Criteria and Reported Device Performance

    ModuleMetricAcceptance CriteriaReported Device Performance
    LVivoRVFAC Correlation75% correlation (r ≥ 0.75) between LVivoRV's FAC measurement and manual FAC measurements by sonographers. This value is based on statistical data reported by FDA cleared systems for semi-automated RV function evaluation (e.g., EchoInsight by Epsilon).Primary Endpoint Met: Excellent correlation (r=0.79, p<0.0001) between LVivoRV FAC and manual measurements.
    EDA Correlation(Secondary Endpoint) Implied expectation of good correlation with manual measurements.Excellent correlation (r=0.92) between LVivoRV EDA and the average of two sonographers' manual measurements (p<0.0001).
    ESA Correlation(Secondary Endpoint) Implied expectation of good correlation with manual measurements.Excellent correlation (r=0.93) between LVivoRV ESA and the average of two sonographers' manual measurements (p<0.0001).
    TAPSE Correlation(Secondary Endpoint) Implied expectation of correlation similar to "real life" performance of VVI compared to M-mode.Correlation of 0.62 with manual M-Mode measurements (similar to VVI vs. M-Mode correlation of r=0.66). When 5 outlier cases were omitted, r=0.72.
    Free Wall Strain Correlation(Secondary Endpoint) Implied expectation of good correlation with manual measurements.Positive correlation of R=0.6 with 2D VVI. When 6 outlier cases were omitted, r=0.78.
    LVivo BladderBladder Volume Agreement (200mL threshold)Kappa of at least 0.61 (substantial agreement) between the automated and manual method when differentiating between post-voiding volumes above or below 200mL. This threshold is considered clinically important for catheter placement decisions.Primary Endpoint Met: Excellent Kappa of 0.84, indicating excellent agreement between methods for the 200mL threshold. High overall agreement (0.93) and high sensitivity (100%) and specificity (80%).
    Bladder Volume Correlation(Secondary / Implied) Implied expectation of good correlation between automated bladder volume calculation and manual tracing.Very high correlation (r=0.94) between automated bladder volume calculation by LVivo Bladder and volume calculated by manual tracing (routinely used method).

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

    • LVivoRV: The exact sample size for the test set is not explicitly stated. The study mentions that examinations were collected over a period of 22 months retrospectively. It includes RV clips from 4CH and 4CH modified views that had 2-3 stable recorded beats.

      • Data Provenance: Retrospective, single-center study. The data was retrieved from PACS systems available on-site at the study center.
    • LVivo Bladder: 226 bladder images (113 pairs of transverse and longitudinal views) were included.

      • Data Provenance: Retrospective, single-center study. Examinations were retrieved from PACS systems available in Terem's clinic. The data was collected as part of routine abdominal examinations.

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

    • LVivoRV:

      • FAC, EDA, ESA: Ground truth was established by two sonographers who manually traced the ED and ES frames. Their qualifications are not explicitly detailed beyond being "sonographers."
      • TAPSE: Ground truth was established by a sonographer (using M-Mode) and an echo cardiologist (using VVI).
      • S': Ground truth was established by a sonographer (using M-Mode) and an echo cardiologist (using VVI).
      • RV Strain: Ground truth was established by an echo cardiologist (using VVI).
      • Overall Qualification Level: Sonographers and echo cardiologists are qualified medical professionals routinely performing these measurements.
    • LVivo Bladder:

      • Ground truth was established by one expert sonographer who performed manual measurements of bladder volume (D1, D2, D3) from the trans and long views. The manual measurements were considered the reference/ground truth.

    4. Adjudication Method for the Test Set

    • LVivoRV:

      • For EDA, ESA, and FAC, the LVivoRV's automated values were compared to the average of the values obtained manually by the two sonographers. This implies a form of consensus or averaging method.
      • For TAPSE and S', measurements from a sonographer (M-Mode) and an echo cardiologist (VVI) were used for comparison, but it's not explicitly stated if there was an adjudication for a single ground truth value when both measurements were available. However, the report compares LVivoRV to "manual measurement using M-Mode" and also notes correlation between VVI and M-Mode, suggesting separate comparisons rather than a combined adjudication.
    • LVivo Bladder:

      • The manual measurements performed by the single expert sonographer served as the ground truth. There was no explicit adjudication among multiple experts since only one expert provided the manual measurements for the validation.

    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, evaluating human readers with and without AI assistance, was reported in this document. The studies were focused on the standalone performance of the LVivoRV and LVivo Bladder modules against manual measurements or established methods.

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

    • Yes, standalone performance studies were done for both LVivoRV and LVivo Bladder.
      • LVivoRV: The algorithm's output was generated "by an automated batch processing after all data was ready and considered locked." This indicates the algorithm processed the data without human intervention to influence its initial measurements. Manual adjustments are available in the device, but the reported study focuses on the automated output.
      • LVivo Bladder: The algorithm was applied "by an automated batch processing on all pairs of trans and long views," also indicating standalone performance for the reported results. The device allows for manual caliper adjustments, but the validation appears to have used the automated result.

    7. The Type of Ground Truth Used

    • LVivoRV: Expert consensus/manual measurements from qualified medical professionals (sonographers and echo cardiologists) based on conventional echocardiography methods (2D manual measurements, M-Mode, VVI).
    • LVivo Bladder: Expert manual measurements by an expert sonographer, considered the routinely used method for bladder volume measurement.

    8. The Sample Size for the Training Set

    • The document does not explicitly state the sample size used for the training set for either LVivoRV or LVivo Bladder. It only describes the algorithms and their application to the test sets.

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

    • The document does not provide details on how the ground truth for the training set was established. It describes the technology for LVivoRV as combining "image processing and Deep Learning Neural Network (NN)" and for LVivo Bladder as using "a combination of machine learning and active contour," implying the use of training data, but no specifics are given regarding its ground truth establishment.
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