Cargando…

Improving Visual Field Examination of the Macula Using Structural Information

PURPOSE: To investigate a novel approach for structure-function modeling in glaucoma to improve visual field testing in the macula. METHODS: We acquired data from the macular region in 20 healthy eyes and 31 with central glaucomatous damage. Optical coherence tomography (OCT) scans were used to esti...

Descripción completa

Detalles Bibliográficos
Autores principales: Montesano, Giovanni, Rossetti, Luca M., Allegrini, Davide, Romano, Mario R., Crabb, David P.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Association for Research in Vision and Ophthalmology 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6314223/
https://www.ncbi.nlm.nih.gov/pubmed/30619656
http://dx.doi.org/10.1167/tvst.7.6.36
_version_ 1783384081436770304
author Montesano, Giovanni
Rossetti, Luca M.
Allegrini, Davide
Romano, Mario R.
Crabb, David P.
author_facet Montesano, Giovanni
Rossetti, Luca M.
Allegrini, Davide
Romano, Mario R.
Crabb, David P.
author_sort Montesano, Giovanni
collection PubMed
description PURPOSE: To investigate a novel approach for structure-function modeling in glaucoma to improve visual field testing in the macula. METHODS: We acquired data from the macular region in 20 healthy eyes and 31 with central glaucomatous damage. Optical coherence tomography (OCT) scans were used to estimate the local macular ganglion cell density. Perimetry was performed with a fundus-tracking device using a 10-2 grid. OCT scans were matched to the retinal image from the fundus perimeter to accurately map the tested locations onto the structural damage. Binary responses from the subjects to all presented stimuli were used to calculate the structure-function model used to generate prior distributions for a ZEST (Zippy Estimation by Sequential Testing) Bayesian strategy. We used simulations based on structural and functional data acquired from an independent dataset of 20 glaucoma patients to compare the performance of this new strategy, structural macular ZEST (MacS-ZEST), with a standard ZEST. RESULTS: Compared to the standard ZEST, MacS-ZEST reduced the number of presentations by 13% in reliable simulated subjects and 14% with higher rates (≥20%) of false positive or false negative errors. Reduction in mean absolute error was not present for reliable subjects but was gradually more important with unreliable responses (≥10% at 30% error rate). CONCLUSIONS: Binary responses can be modeled to incorporate detailed structural information from macular OCT into visual field testing, improving overall speed and accuracy in poor responders. TRANSLATIONAL RELEVANCE: Structural information can improve speed and reliability for macular testing in glaucoma practice.
format Online
Article
Text
id pubmed-6314223
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher The Association for Research in Vision and Ophthalmology
record_format MEDLINE/PubMed
spelling pubmed-63142232019-01-07 Improving Visual Field Examination of the Macula Using Structural Information Montesano, Giovanni Rossetti, Luca M. Allegrini, Davide Romano, Mario R. Crabb, David P. Transl Vis Sci Technol Articles PURPOSE: To investigate a novel approach for structure-function modeling in glaucoma to improve visual field testing in the macula. METHODS: We acquired data from the macular region in 20 healthy eyes and 31 with central glaucomatous damage. Optical coherence tomography (OCT) scans were used to estimate the local macular ganglion cell density. Perimetry was performed with a fundus-tracking device using a 10-2 grid. OCT scans were matched to the retinal image from the fundus perimeter to accurately map the tested locations onto the structural damage. Binary responses from the subjects to all presented stimuli were used to calculate the structure-function model used to generate prior distributions for a ZEST (Zippy Estimation by Sequential Testing) Bayesian strategy. We used simulations based on structural and functional data acquired from an independent dataset of 20 glaucoma patients to compare the performance of this new strategy, structural macular ZEST (MacS-ZEST), with a standard ZEST. RESULTS: Compared to the standard ZEST, MacS-ZEST reduced the number of presentations by 13% in reliable simulated subjects and 14% with higher rates (≥20%) of false positive or false negative errors. Reduction in mean absolute error was not present for reliable subjects but was gradually more important with unreliable responses (≥10% at 30% error rate). CONCLUSIONS: Binary responses can be modeled to incorporate detailed structural information from macular OCT into visual field testing, improving overall speed and accuracy in poor responders. TRANSLATIONAL RELEVANCE: Structural information can improve speed and reliability for macular testing in glaucoma practice. The Association for Research in Vision and Ophthalmology 2018-12-28 /pmc/articles/PMC6314223/ /pubmed/30619656 http://dx.doi.org/10.1167/tvst.7.6.36 Text en Copyright 2018 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
spellingShingle Articles
Montesano, Giovanni
Rossetti, Luca M.
Allegrini, Davide
Romano, Mario R.
Crabb, David P.
Improving Visual Field Examination of the Macula Using Structural Information
title Improving Visual Field Examination of the Macula Using Structural Information
title_full Improving Visual Field Examination of the Macula Using Structural Information
title_fullStr Improving Visual Field Examination of the Macula Using Structural Information
title_full_unstemmed Improving Visual Field Examination of the Macula Using Structural Information
title_short Improving Visual Field Examination of the Macula Using Structural Information
title_sort improving visual field examination of the macula using structural information
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6314223/
https://www.ncbi.nlm.nih.gov/pubmed/30619656
http://dx.doi.org/10.1167/tvst.7.6.36
work_keys_str_mv AT montesanogiovanni improvingvisualfieldexaminationofthemaculausingstructuralinformation
AT rossettilucam improvingvisualfieldexaminationofthemaculausingstructuralinformation
AT allegrinidavide improvingvisualfieldexaminationofthemaculausingstructuralinformation
AT romanomarior improvingvisualfieldexaminationofthemaculausingstructuralinformation
AT crabbdavidp improvingvisualfieldexaminationofthemaculausingstructuralinformation