PurposeTo characterize macular ganglion cell layer (GCL) changes with age and provide a framework to assess changes in ocular disease. This study used data clustering to analyze macular GCL patterns from optical coherence tomography (OCT) in a large cohort of subjects without ocular disease.MethodsSingle eyes of 201 patients evaluated at the Centre for Eye Health (Sydney, Australia) were retrospectively enrolled (age range, 20–85); 8 × 8 grid locations obtained from Spectralis OCT macular scans were analyzed with unsupervised classification into statistically separable classes sharing common GCL thickness and change with age. The resulting classes and gridwise data were fitted with linear and segmented linear regression curves. Additionally, normalized data were analyzed to determine regression as a percentage. Accuracy of each model was examined through comparison of predicted 50-year-old equivalent macular GCL thickness for the entire cohort to a true 50-year-old reference cohort.ResultsPattern recognition clustered GCL thickness across the macula into five to eight spatially concentric classes. F-test demonstrated segmented linear regression to be the most appropriate model for macular GCL change. The pattern recognition–derived and normalized model revealed less difference between the predicted macular GCL thickness and the reference cohort (average ± SD 0.19 ± 0.92 and −0.30 ± 0.61 μm) than a gridwise model (average ± SD 0.62 ± 1.43 μm).ConclusionsPattern recognition successfully identified statistically separable macular areas that undergo a segmented linear reduction with age. This regression model better predicted macular GCL thickness. The various unique spatial patterns revealed by pattern recognition combined with core GCL thickness data provide a framework to analyze GCL loss in ocular disease.
PURPOSE. To investigate the effect of stimulus size and disease status on the structure-function relationship within the central retina, we correlated the differential light sensitivity (DLS) with Goldmann stimulus size I to V (GI-V) and optical coherence tomography (OCT) derived in vivo ganglion cell count per stimulus area (GCc) within the macular area in normal subjects and patients with early glaucoma.METHODS. Humphrey Field Analyzer 10-2 visual field data with GI through V and Spectralis OCT macular ganglion cell layer (GCL) thickness measurements were collected from normal and early glaucoma cohorts including 25 subjects each. GCc was calculated from GCL thickness data and correlated with DLSs for different stimulus sizes.RESULTS. Correlation coefficients attained with smaller stimulus size were higher compared to larger stimulus sizes in both normal (GI-GII: R 2 ¼ 0.41-0.43, GIII-GV: R 2 ¼ 0.16-0.41) and diseased cohorts (GI-GII: R 2 ¼ 0.33-0.41, GIII-GV: R 2 ¼ 0.19-0.36). Quadratic regression curves for combined GI to V data demonstrated high correlation (R 2 = 0.82-0.90) and differed less than 1 dB of visual sensitivity within the GCc range between cohorts. The established structure-function relationship was compatible with a histologically derived model correlation spanning the range predicted by stimulus sizes GI to GIII.CONCLUSIONS. Stimulus sizes within critical spatial summation area (GI-II) improved structurefunction correlations in the central visual field. The structure-function relationship was identical in both normal and diseased cohort when GI to GV data were combined. Congruency of GI and GII structure-function correlation with those previously derived with GIII from more peripheral locations further suggests that the structure-function relationship is governed by the number of ganglion cell per stimulus area.
Nivison-Smith L. Macula ganglion cell thickness changes display location-specific variation patterns in intermediate age-related macular degeneration. Invest Ophthalmol Vis Sci. 2020;61(3):2. https://doi.org/10.1167/iovs.61.3.2 PURPOSE.The purpose of this study was to examine changes in the ganglion cell layer (GCL) of individuals with intermediate age-related macular degeneration (AMD) using grid-wise analysis for macular optical coherence tomography (OCT) volume scans. We also aim to validate the use of age-correction functions for GCL thickness in diseased eyes. METHODS.OCT macular cube scans covering 30°× 25°were acquired using Spectralis spectral-domain OCT for 87 eyes with intermediate AMD, 77 age-matched normal eyes, and 254 non-age-matched normal eyes. The thickness of the ganglion cell layer (GCL) was defined after segmentation at 60 locations across an 8 × 8 grid centered on the fovea, where each grid location covered 0.74 mm 2 (approximately 3°× 3°) within the macula. Each GCL location of normal eyes (n = 77) were assigned to a specific iso-ganglion cell density cluster in the macula, based on patterns of age-related GCL thickness loss. Analyses were then performed comparing AMD GCL grid-wise data against corresponding spatial clusters, and significant AMD GCL thickness changes were denoted as values outside the 95% distribution limits. RESULTS.Analysis of GCL thickness changes revealed significant differences between spatial clusters, with thinning toward the fovea, and thickening toward the peripheral macula. The direction of GCL thickness changes in AMD were associated more so with thickening than thinning in all analyses. Results were corroborated by the application of GCL thickness age-correction functions.CONCLUSIONS. GCL thickness changed significantly and nonuniformly within the macula of intermediate AMD eyes. Further characterization of these changes is critical to improve diagnoses and monitoring of GCL-altering pathologies.
The study highlighted the importance of combining both structural and functional assessments in glaucoma. Current imaging technology demonstrated limited usefulness for event diagnosis due to the persistent difficulties of defining structural and functional loss in glaucoma, thus highlighting the need for new glaucoma assessment techniques. Short-term didactic teaching programs may only result in limited improvement of glaucoma diagnostic ability in optometrists, and hence, it may need to be combined with long-term and/or non-didactic training components to obtain a greater effect.
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