Dataset Information


Improving Visual Field Examination of the Macula Using Structural Information.

ABSTRACT: 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.

SUBMITTER: Montesano G 

PROVIDER: S-EPMC6314223 | BioStudies | 2018-01-01T00:00:00Z

REPOSITORIES: biostudies

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