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510(k) Data Aggregation

    K Number
    K242726
    Device Name
    Synapsys VHIT
    Manufacturer
    Date Cleared
    2025-01-03

    (115 days)

    Product Code
    Regulation Number
    882.1460
    Reference & Predicate Devices
    Why did this record match?
    Applicant Name (Manufacturer) :

    Inventis S.r.l.

    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Synapsys VHIT is a medical device designed to assess the vestibular-ocular-reflex (VOR) by measuring, recording, displaying, and analyzing eye and head movements.

    Device Description

    Synapsys VHT (Video Head Impulse Test) allows to assess the vestibular-ocular-reflex (VOR) by measuring, and analyzing eye and head movements. Synapsys VHT does not require the patient to wear goggles, since it consists of a remote camera placed 90 cm from the subject, framing the subject's eyes and head. The device features real-time eyes detection and tracking, thanks to a built-in infrared illuminator hat lights up the subject. Head displacements are retrieved using algorithms that extract motion data from real time images recorded by the camera.

    AI/ML Overview

    The provided document is an FDA 510(k) summary for the Inventis Synapsys VHIT device. It details a comparative analysis with a predicate device, ICS Impulse, rather than a standalone study of the Synapsys VHIT's performance against defined acceptance criteria for accuracy or clinical effectiveness. The information is limited regarding the specific details requested about statistical methodology and ground truth establishment for a standalone performance study.

    Based on the provided text, here's what can be extracted and inferred regarding the "acceptance criteria" and "study that proves the device meets the acceptance criteria":

    General Approach and "Acceptance Criteria"

    The study described is a comparative analysis rather than a direct performance assessment against a pre-defined absolute accuracy (e.g., Sensitivity/Specificity targets). The core "acceptance criterion" appears to be the agreement between the Synapsys VHIT and the predicate device (ICS Impulse) in VOR Gain measurements.

    • Acceptance Criteria for VOR Gain Measurement: The primary criterion for the comparative analysis was that "the average VOR Gain computed by the two devices fell within a confidence interval of ±0.1."

    Study Details Related to "Acceptance Criteria" and "Device Performance"

    Here's the information organized as requested, with details extracted from the document:


    1. Table of Acceptance Criteria and Reported Device Performance

    Acceptance Criteria (for Comparative Study)Reported Device Performance
    Average VOR Gain (Synapsys VHIT) vs. Average VOR Gain (ICS Impulse) difference within a confidence interval of ±0.1."The results of the comparative analysis demonstrate that the VOR gain differences fall within the predefined confidence interval of ±0.1."

    Note: The document primarily focuses on demonstrating substantial equivalence to a predicate device through VOR gain agreement, not on establishing independent accuracy metrics like sensitivity or specificity against a definitive ground truth of vestibular function.


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

    • Sample Size: Not explicitly stated. The document mentions tests on "pathological and nonpathological patients" but does not provide the number of patients or the number of tests performed.
    • Data Provenance: Not explicitly stated (e.g., country of origin). The study used "pathological and nonpathological patients," implying real patient data. It is a prospective comparison of measurements from two devices on the same subjects.

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

    This information is not provided in the document. The "ground truth" in this comparative study is the measurement obtained from the predicate device (ICS Impulse) and consistency in eye/head movement trajectories between the two devices, rather than an independent expert-derived clinical diagnosis.


    4. Adjudication method for the test set

    This information is not provided. As this was a comparative measurement study rather than a diagnostic performance study where human readers would adjudicate results, an adjudication method in the traditional sense (e.g., for image interpretation) is unlikely to have been applied. The comparison was statistical on the quantitative VOR gain values and qualitative assessment of trajectories.


    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. An MRMC study was not performed as described. The device is a diagnostic tool for measuring VOR; it is not an AI-powered image analysis tool that assists human readers in making diagnoses. The study performed a direct comparison of quantitative measurements from two medical devices.


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

    Yes, in spirit. The comparison was between the measurements generated by the Synapsys VHIT device (which uses "software algorithms for eye tracking and head pose estimation") and the predicate device. While human operators perform the tests, the analysis of VOR gain is an algorithmic output. The study's focus was on the agreement of the device's algorithmic output with that of the predicate. It did not involve assessing the device's diagnostic performance (e.g., sensitivity/specificity for a specific condition) against an independent clinical ground truth in a standalone manner.


    7. The type of ground truth used

    The "ground truth" in this study was the measurements provided by the legally marketed predicate device (ICS Impulse). Additionally, the consistency of "trajectories of head and eye movements" observed by both devices served as a secondary form of 'truth' or agreement. This is a common approach for demonstrating substantial equivalence for quantitative measurement devices.


    8. The sample size for the training set

    Not applicable/Not Provided. The document describes a verification and validation study for a medical device that includes "software algorithms." It does not provide details of an AI/ML model's training set as one might find for a deep learning algorithm. The "software algorithms" mentioned are likely deterministic signal processing or computer vision algorithms for eye and head tracking, rather than a machine learning model that requires a "training set" in the conventional sense of supervised learning. If there was an ML component, the training data details are not disclosed.


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

    Not applicable/Not Provided. As mentioned above, the document does not describe a training set for an AI/ML model. Therefore, how its "ground truth" was established is not relevant or not provided.

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