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510(k) Data Aggregation

    K Number
    K000327
    Manufacturer
    Date Cleared
    2000-05-02

    (90 days)

    Product Code
    Regulation Number
    886.1760
    Reference & Predicate Devices
    N/A
    Why did this record match?
    Device Name :

    WAVESCAN WAVEFRONT SYSTEM MODEL HS 1

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

    The VISX WaveScan™ Wavefront System is a diagnostic instrument indicated for the automated measurement and analysis of refractive errors of the eye including hyperopia and myopia from +6.00 to -8.00 diopters spherical, and astigmatism from 0.00 to -6.00 diopters.

    Device Description

    The WaveScan™ Wavefront System Model HS 1 autorefractor device is a diagnostic instrument designed to measure refractive error of the eye automatically by use of wavefront technology. Light travels in a procession of flat sheets known as wavefronts. As these wavefronts pass through an imperfect refractive medium including the cornea and the lens, the aberrations which are created by the irregular surfaces "wrinkle" the light rays and create wavefront errors or distortions. The instrument contains tiny sensors which measure the gradient, or slope, of the wavefront which emanate from the eye. After light travels through the eye's optical system and out again, the sensors accurately detect slight variations of wavefront irregularities as they exit the eye. The sensors then provide additional information within the confines of the instrument through a series of lenses and apertures which are subject to mathematical algorithms and software. Once analyzed by the computer, a refractive error read-out is provided to the user. This analysis is made from multiple points of light which precisely pinpoint variations in refractive status across the entrance pupil of the eye. This allows for the high level of accuracy of the instrument thus providing the user with very precise readings of refractive error.

    AI/ML Overview

    Here's an analysis of the provided text, broken down by your requested categories:

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

    The document doesn't explicitly state "acceptance criteria" with numerical targets for accuracy, reproducibility, or other performance metrics. Instead, it describes a
    comparison study against a predicate device (Canon R-50m) to demonstrate equivalence. The reported performance is relative to this predicate.

    Acceptance Criteria (Implicit)Reported Device Performance (WaveScan™ Wavefront System)
    Equivalence or Superiority to Predicate Device (Canon R-50m) in AccuracyPerformed within statistical 95% level of confidence in all parameters measured
    Equivalence or Superiority to Predicate Device (Canon R-50m) in RepeatabilityEquivalent or superior to the control instrument (Canon R-50m) in accuracy and repeatability. Estimates of refractive error with less variability than the control device (lower standard deviation).

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

    • Test Set Sample Size: The tests were conducted using a "model test eye developed by VISX, Inc. and modeled after the Gullstrand Standard Test Eye Model." Each test condition (combinations of myopic, hyperopic, and astigmatic errors) was repeated five times. The exact number of "test conditions" or specific refractive error combinations is not quantified, so a precise sample size for the test set in terms of individual measurements cannot be determined from the provided text.
    • Data Provenance:
      • Origin: The model test eye was "developed by VISX, Inc."
      • Retrospective/Prospective: Neither. The testing was a bench study using a physical eye model, not human data.

    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 test set was established by the design of the "model test eye" which was constructed to represent specific refractive errors. There were no human experts involved in establishing the ground truth for this bench testing.

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

    Not applicable. There was no human adjudication as the testing was done against a physical model with known characteristics.

    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. This document describes the performance of an automated diagnostic instrument (autorefractor) directly measuring refractive error. It is a standalone device, and no human-in-the-loop or MRMC study comparing human readers with and without AI assistance was performed or described.

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

    Yes, a standalone performance evaluation was conducted. The WaveScan™ Wavefront System Model HS 1 is an "autorefractor device" designed to "automatically measure refractive error of the eye." The testing described is directly evaluating the device's ability to measure refractive errors on its own using a test eye model.

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

    The ground truth used was known, precisely engineered refractive errors as embodied in the "Gullstrand Standard Test Eye Model" on which the VISX model eye was based.

    8. The sample size for the training set

    Not applicable. This device is an autorefractor, which uses optical principles and mathematical algorithms to determine refractive error. It is not described as a machine learning or AI device that requires a "training set" in the conventional sense. Its algorithms are based on established physics and optics.

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

    Not applicable, as there is no mention of a training set for a machine learning algorithm.

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