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Using eye movements to detect visual field loss: a pragmatic assessment using simulated scotoma

Glaucoma is a leading cause of irreversible sight-loss and has been shown to affect natural eye-movements. These changes may provide a cheap and easy-to-obtain biomarker for improving disease detection. Here, we investigated whether these changes are large enough to be clinically useful. We used a g...

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Autores principales: Asfaw, Daniel S., Jones, Pete R., Edwards, Laura A., Smith, Nicholas D., Crabb, David P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7299979/
https://www.ncbi.nlm.nih.gov/pubmed/32555198
http://dx.doi.org/10.1038/s41598-020-66196-2
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author Asfaw, Daniel S.
Jones, Pete R.
Edwards, Laura A.
Smith, Nicholas D.
Crabb, David P.
author_facet Asfaw, Daniel S.
Jones, Pete R.
Edwards, Laura A.
Smith, Nicholas D.
Crabb, David P.
author_sort Asfaw, Daniel S.
collection PubMed
description Glaucoma is a leading cause of irreversible sight-loss and has been shown to affect natural eye-movements. These changes may provide a cheap and easy-to-obtain biomarker for improving disease detection. Here, we investigated whether these changes are large enough to be clinically useful. We used a gaze-contingent simulated visual field (VF) loss paradigm, in which participants experienced a variable magnitude of simulated VF loss based on longitudinal data from a real glaucoma patient (thereby controlling for other variables, such as age and general health). Fifty-five young participants with healthy vision were asked to view two short videos and three pictures, either with: (1) no VF loss, (2) moderate VF loss, or (3) advanced VF loss. Eye-movements were recorded using a remote eye tracker. Key eye-movement parameters were computed, including saccade amplitude, the spread of saccade endpoints (bivariate contour ellipse area), location of saccade landing positions, and similarity of fixations locations among participants (quantified using kernel density estimation). The simulated VF loss caused some statistically significant effects in the eye movement parameters. Yet, these effects were not capable of consistently identifying simulated VF loss, despite it being of a magnitude likely easily detectable by standard automated perimetry.
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spelling pubmed-72999792020-06-18 Using eye movements to detect visual field loss: a pragmatic assessment using simulated scotoma Asfaw, Daniel S. Jones, Pete R. Edwards, Laura A. Smith, Nicholas D. Crabb, David P. Sci Rep Article Glaucoma is a leading cause of irreversible sight-loss and has been shown to affect natural eye-movements. These changes may provide a cheap and easy-to-obtain biomarker for improving disease detection. Here, we investigated whether these changes are large enough to be clinically useful. We used a gaze-contingent simulated visual field (VF) loss paradigm, in which participants experienced a variable magnitude of simulated VF loss based on longitudinal data from a real glaucoma patient (thereby controlling for other variables, such as age and general health). Fifty-five young participants with healthy vision were asked to view two short videos and three pictures, either with: (1) no VF loss, (2) moderate VF loss, or (3) advanced VF loss. Eye-movements were recorded using a remote eye tracker. Key eye-movement parameters were computed, including saccade amplitude, the spread of saccade endpoints (bivariate contour ellipse area), location of saccade landing positions, and similarity of fixations locations among participants (quantified using kernel density estimation). The simulated VF loss caused some statistically significant effects in the eye movement parameters. Yet, these effects were not capable of consistently identifying simulated VF loss, despite it being of a magnitude likely easily detectable by standard automated perimetry. Nature Publishing Group UK 2020-06-17 /pmc/articles/PMC7299979/ /pubmed/32555198 http://dx.doi.org/10.1038/s41598-020-66196-2 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Asfaw, Daniel S.
Jones, Pete R.
Edwards, Laura A.
Smith, Nicholas D.
Crabb, David P.
Using eye movements to detect visual field loss: a pragmatic assessment using simulated scotoma
title Using eye movements to detect visual field loss: a pragmatic assessment using simulated scotoma
title_full Using eye movements to detect visual field loss: a pragmatic assessment using simulated scotoma
title_fullStr Using eye movements to detect visual field loss: a pragmatic assessment using simulated scotoma
title_full_unstemmed Using eye movements to detect visual field loss: a pragmatic assessment using simulated scotoma
title_short Using eye movements to detect visual field loss: a pragmatic assessment using simulated scotoma
title_sort using eye movements to detect visual field loss: a pragmatic assessment using simulated scotoma
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7299979/
https://www.ncbi.nlm.nih.gov/pubmed/32555198
http://dx.doi.org/10.1038/s41598-020-66196-2
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