Abstract
Purpose: to test whether functional loss in the glaucomatous macula is characterised by an enlargement of Ricco’s area (RA) through the application of a computational model linking retinal ganglion cell (RGC) damage to perimetric sensitivity.
Methods: one eye from each of 29 visually-healthy subjects <40 years old, 30 glaucoma patients and 20 age-similar controls was tested with a 10-2 grid with stimuli of five different area sizes. Structural estimates of point-wise RGC density were obtained from Optical Coherence Tomography scans. Structural and functional data from the young healthy cohort were used to estimate the parameters of a computational spatial summation model to generate a template. The template was fitted with a Bayesian hierarchical model to estimate the latent RGC density in glaucoma patients and age matched controls. We tested two alternative hypotheses: fitting the data by translating the template horizontally (H1: change in RA) or vertically (H2: loss of sensitivity without change in RA). Root Mean Squared Error (RMSE) of the model fits to perimetric sensitivity were compared. 95%-Confidence Intervals were bootstrapped. The dynamic range of the functional and structural RGC density estimates was denoted by their 1st and the 99th percentile.
Results: the RMSE was 2.09 [1.92-2.26] under H1 and 2.49 [2.24-2.72] under H2 (p < 0.001). The average dynamic range for the structural RGC density estimates was only 11% that of the functional estimates.
Conclusions: macular sensitivity loss in glaucoma is better described by a model in which RA changes with RGC loss. Structural measurements have limited dynamic range.
Methods: one eye from each of 29 visually-healthy subjects <40 years old, 30 glaucoma patients and 20 age-similar controls was tested with a 10-2 grid with stimuli of five different area sizes. Structural estimates of point-wise RGC density were obtained from Optical Coherence Tomography scans. Structural and functional data from the young healthy cohort were used to estimate the parameters of a computational spatial summation model to generate a template. The template was fitted with a Bayesian hierarchical model to estimate the latent RGC density in glaucoma patients and age matched controls. We tested two alternative hypotheses: fitting the data by translating the template horizontally (H1: change in RA) or vertically (H2: loss of sensitivity without change in RA). Root Mean Squared Error (RMSE) of the model fits to perimetric sensitivity were compared. 95%-Confidence Intervals were bootstrapped. The dynamic range of the functional and structural RGC density estimates was denoted by their 1st and the 99th percentile.
Results: the RMSE was 2.09 [1.92-2.26] under H1 and 2.49 [2.24-2.72] under H2 (p < 0.001). The average dynamic range for the structural RGC density estimates was only 11% that of the functional estimates.
Conclusions: macular sensitivity loss in glaucoma is better described by a model in which RA changes with RGC loss. Structural measurements have limited dynamic range.
| Original language | English |
|---|---|
| Journal | Investigative Ophthalmology and Visual Science |
| Publication status | Accepted/In press - 3 Oct 2023 |
