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Interpretation of the Visual Field in Neuro-ophthalmic Disorders.

Authors :
Banc, Ana
Kedar, Sachin
Source :
Current Neurology & Neuroscience Reports; Mar2024, Vol. 24 Issue 3, p67-81, 15p
Publication Year :
2024

Abstract

Purpose of Review: In this review, we will describe current methods for visual field testing in neuro-ophthalmic clinical practice and research, develop terminology that accurately describes patterns of field deficits, and discuss recent advances such as augmented or virtual reality-based perimetry and the use of artificial intelligence in visual field interpretation. Recent Findings: New testing strategies that reduce testing times, improve patient comfort, and increase sensitivity for detecting small central or paracentral scotomas have been developed for static automated perimetry. Various forms of machine learning-based tools such as archetypal analysis are being tested to quantitatively depict and monitor visual field abnormalities in optic neuropathies. Studies show that the combined use of optical coherence tomography and standard automated perimetry to determine the structure-function relationship improves clinical care in neuro-ophthalmic disorders. Summary: Visual field assessment must be performed in all patients with neuro-ophthalmic disorders affecting the afferent visual pathway. Quantitative visual field analysis using standard automated perimetry is critical in initial diagnosis, monitoring disease progression, and guidance of therapeutic plans. Visual field defects can adversely impact activities of daily living such as reading, navigation, and driving and thus impact quality of life. Visual field testing can direct appropriate occupational low vision rehabilitation in affected individuals. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15284042
Volume :
24
Issue :
3
Database :
Complementary Index
Journal :
Current Neurology & Neuroscience Reports
Publication Type :
Academic Journal
Accession number :
176497954
Full Text :
https://doi.org/10.1007/s11910-024-01332-3