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510(k) Data Aggregation

    K Number
    K161727
    Manufacturer
    Date Cleared
    2016-10-04

    (104 days)

    Product Code
    Regulation Number
    886.1120
    Reference & Predicate Devices
    Predicate For
    N/A
    AI/MLSaMDIVD (In Vitro Diagnostic)TherapeuticDiagnosticis PCCP AuthorizedThirdpartyExpeditedreview
    Intended Use

    The Eyenez V200 fundus camera is intended to be used to capture images of the retina of the eye.

    Device Description

    The Eyenez Ophthalmic Camera is a handheld ophthalmic camera that combines a condensing lens with a built-in digital camera to capture a digital photograph of the retina and allow for the examination of the picture by an ophthalmic specialist. The Eyenez Ophthalmic Camera will allow users to capture images of the retina. Images may be saved to a flash memory card and also have connectivity towards PC using a USB interface. Device has a rechargeable battery.

    AI/ML Overview

    The Eyenez LLC Ophthalmic Camera Model V200 was evaluated through a clinical study to demonstrate substantial equivalence to its predicate device, the Optomed Smartscope M5 EY3 and ES1 (Volk Pictor Ret1).

    Here's a breakdown of the acceptance criteria and study details:

    1. Table of Acceptance Criteria and Reported Device Performance

    Acceptance Criteria (Study Endpoint)Reported Device Performance
    At least 90% equivalent in ability to capture presence/absence of retinal pathology compared to predicate deviceEyenez OC Retina Camera images were comparable to the Volk Pictor OP on 33 out of 34 patients (97%).

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

    • Sample Size: 34 subjects.
      • 19 subjects with various retinal pathologies.
      • 15 healthy subjects.
    • Data Provenance: The document does not explicitly state the country of origin or whether the study was retrospective or prospective. However, given it's a clinical study conducted for 510(k) submission, it's highly likely to be a prospective study within the US or a region with comparable clinical practices.

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

    • Number of Experts: One.
    • Qualifications of Experts: The ground truth was established by an "independent Ophthalmologist." No further details on years of experience or subspecialty are provided.

    4. Adjudication Method for the Test Set

    • The document implies that the single independent Ophthalmologist served as the adjudicator, comparing images from both devices. There is no mention of a consensus-based or multi-reader adjudication method (e.g., 2+1, 3+1).

    5. If a Multi-Reader Multi-Case (MRMC) Comparative Effectiveness Study Was Done, and the Effect Size

    • No, an MRMC comparative effectiveness study was not explicitly done. The study design described involved a comparison of images from the investigational device and the predicate device by a single independent ophthalmologist. The goal was to establish comparability, not to measure the improvement of human readers with AI assistance.

    6. If a Standalone (Algorithm Only Without Human-in-the-Loop Performance) Was Done

    • Not applicable. The Eyenez Ophthalmic Camera is a hardware device for capturing images, not an AI algorithm for image analysis. Therefore, a standalone algorithm performance study is not relevant to this submission. The study focused on the image capture capability of the device itself.

    7. The Type of Ground Truth Used

    • Expert Consensus (single expert): The ground truth was established by a single independent Ophthalmologist who reviewed the retinal images and concluded on their comparability regarding the presence or absence of retinal pathology.

    8. The Sample Size for the Training Set

    • Not applicable. As the Eyenez Ophthalmic Camera is a hardware device for image acquisition rather than an AI-powered diagnostic algorithm, there is no mention of a training set in the context of machine learning.

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

    • Not applicable. As there is no training set for an AI algorithm mentioned, this question is not relevant to the provided document.
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