Shonraj Ballae Ganeshrao1, Andrew Turpin2, Jonathan Denniss3, Allison M McKendrick4. 1. Department of Computing and Information Systems, University of Melbourne, Melbourne, Australia; Department of Optometry and Vision Sciences, University of Melbourne, Melbourne, Australia. 2. Department of Computing and Information Systems, University of Melbourne, Melbourne, Australia. 3. Department of Computing and Information Systems, University of Melbourne, Melbourne, Australia; Department of Optometry and Vision Sciences, University of Melbourne, Melbourne, Australia; Visual Neuroscience Group, School of Psychology, University of Nottingham, Nottingham, United Kingdom. 4. Department of Optometry and Vision Sciences, University of Melbourne, Melbourne, Australia. Electronic address: allisonm@unimelb.edu.au.
Abstract
PURPOSE: To determine whether the structure-function relationship in glaucoma can be strengthened by using more precise structural and functional measurements combined with individualized structure-function maps and custom sector selection on the optic nerve head (ONH). DESIGN: Cross-sectional study. PARTICIPANTS: One eye of each of 23 participants with glaucoma. METHODS: Participants were tested twice. Visual fields were collected on a high-resolution 3° × 3° grid (164 locations) using a Zippy Estimation by Sequential Testing test procedure with uniform prior probability to improve the accuracy and precision of scotoma characterization relative to standard methods. Retinal nerve fiber layer (RNFL) thickness was measured using spectral-domain optical coherence tomography (OCT; 4 scans, 2 per visit) with manual removal of blood vessels. Individualized maps, based on biometric data, were used. To customize the areas of the ONH and visual field to correlate, we chose a 30° sector centered on the largest defect shown by OCT and chose visual field locations using the individualized maps. Baseline structure-function correlations were calculated between 24-2 locations (n = 52) of the first tested visual field and RNFL thickness from 1 OCT scan, using the sectors of the Garway-Heath map. We added additional data (averaged visual field and OCT, additional 106 visual field locations and OCT without blood vessels, individualized map, and customized sector) and recomputed the correlations. MAIN OUTCOME MEASURES: Spearman correlation between structure and function. RESULTS: The highest baseline correlation was 0.52 (95% confidence interval [CI], 0.13-0.78) in the superior temporal ONH sector. Improved measurements increased the correlation marginally to 0.58 (95% CI, 0.21-0.81). Applying the individualized map to the large, predefined ONH sectors did not improve the correlation; however, using the individualized map with the single 30° ONH sector resulted in a large increase in correlation to 0.77 (95% CI, 0.47-0.92). CONCLUSIONS: Using more precise visual field and OCT measurements did not improve structure-function correlation in our cohort, but customizing the ONH sector and its associated visual field points substantially improved correlation. We suggest using customized ONH sectors mapped to individually relevant visual field locations to unmask localized structural and functional loss.
PURPOSE: To determine whether the structure-function relationship in glaucoma can be strengthened by using more precise structural and functional measurements combined with individualized structure-function maps and custom sector selection on the optic nerve head (ONH). DESIGN: Cross-sectional study. PARTICIPANTS: One eye of each of 23 participants with glaucoma. METHODS:Participants were tested twice. Visual fields were collected on a high-resolution 3° × 3° grid (164 locations) using a Zippy Estimation by Sequential Testing test procedure with uniform prior probability to improve the accuracy and precision of scotoma characterization relative to standard methods. Retinal nerve fiber layer (RNFL) thickness was measured using spectral-domain optical coherence tomography (OCT; 4 scans, 2 per visit) with manual removal of blood vessels. Individualized maps, based on biometric data, were used. To customize the areas of the ONH and visual field to correlate, we chose a 30° sector centered on the largest defect shown by OCT and chose visual field locations using the individualized maps. Baseline structure-function correlations were calculated between 24-2 locations (n = 52) of the first tested visual field and RNFL thickness from 1 OCT scan, using the sectors of the Garway-Heath map. We added additional data (averaged visual field and OCT, additional 106 visual field locations and OCT without blood vessels, individualized map, and customized sector) and recomputed the correlations. MAIN OUTCOME MEASURES: Spearman correlation between structure and function. RESULTS: The highest baseline correlation was 0.52 (95% confidence interval [CI], 0.13-0.78) in the superior temporal ONH sector. Improved measurements increased the correlation marginally to 0.58 (95% CI, 0.21-0.81). Applying the individualized map to the large, predefined ONH sectors did not improve the correlation; however, using the individualized map with the single 30° ONH sector resulted in a large increase in correlation to 0.77 (95% CI, 0.47-0.92). CONCLUSIONS: Using more precise visual field and OCT measurements did not improve structure-function correlation in our cohort, but customizing the ONH sector and its associated visual field points substantially improved correlation. We suggest using customized ONH sectors mapped to individually relevant visual field locations to unmask localized structural and functional loss.
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