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Quantifying Gaze Tracking for Visual Field Reliability Estimation. A Systematic Review.

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    |September 15, 2025
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    Summary
    This summary is machine-generated.

    Quantitative metrics from gaze tracking (GT) show promise for improving visual field (VF) test reliability, especially with SITA Standard testing. Further research is needed to explore AI

    Keywords:
    automated perimetrygaze trackingglaucomavisual field

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    Area of Science:

    • Ophthalmology
    • Visual Science
    • Medical Technology

    Background:

    • Visual field (VF) testing is crucial for diagnosing and monitoring eye conditions.
    • Evaluating the reliability of VF test results is essential for accurate clinical interpretation.
    • Automated perimeters generate data, including gaze tracking (GT) outputs, that may offer insights into test reliability.

    Purpose of the Study:

    • To systematically review the literature on the use of quantitative metrics from gaze tracking (GT) during automated visual field (VF) testing.
    • To determine if GT metrics can enhance the evaluation of VF test reliability.

    Main Methods:

    • A systematic search of major biomedical databases (PubMed, Cochrane, LILACS, IBECS) was performed up to August 31, 2024.
    • Included studies analyzed quantitative metrics derived from GT outputs during VF testing.
    • Studies were categorized by the testing strategy employed (SITA Standard, Fast, Faster).

    Main Results:

    • Eight studies (3,687 patients, 8,181 VF tests) were included.
    • In SITA Standard testing, GT parameters correlated with VF reproducibility and glaucoma structure-function relationships, though influenced by ocular surface factors.
    • Results for SITA Fast/Faster were mixed; some studies indicated GT metrics could supplement existing reliability measures, while others found no significant added clinical value.

    Conclusions:

    • Quantitative analysis of GT traces shows potential as an objective reliability parameter for VF testing, particularly with the SITA Standard strategy.
    • Future research should focus on automated quantification of GT parameters using advanced techniques like artificial intelligence.
    • Evaluating the impact of these advanced metrics on VF data reliability and clinical decision-making is warranted.