Investigative ophthalmology & visual science · 2023
Spatial Summation in the Glaucomatous Macula: A Link With Retinal Ganglion Cell Damage.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Montesano Giovanni, Redmond Tony, Mulholland Pádraig J, Garway-Heath David F, Ometto Giovanni, Romano Dario, Antonacci Federica, Tanga Lucia, Carnevale Carmela, Rossetti Luca M, Crabb David P, Oddone Francesco
Аннотация
PURPOSE: The purpose of this study was to test whether functional loss in the glaucomatous macula is characterized 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 patients with glaucoma, and 20 age-similar controls was tested with a 10-2 grid with stimuli of 5 different area sizes. Structural estimates of point-wise RGC density were obtained from optical coherence tomography (OCT) 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 patients with glaucoma 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 a change in RA). Root mean squared error (RMSE) of the model fits to perimetric sensitivity were compared. Ninety-five percent confidence intervals were bootstrapped. The dynamic range of the functional and structural RGC density estimates was denoted by their 1st and 99th percentiles.
RESULTS: The RMSE was 2.09 (95% CI = 1.92-2.26) under H1 and 2.49 (95% CI = 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 patients with glaucoma, and 20 age-similar controls was tested with a 10-2 grid with stimuli of 5 different area sizes. Structural estimates of point-wise RGC density were obtained from optical coherence tomography (OCT) 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 patients with glaucoma 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 a change in RA). Root mean squared error (RMSE) of the model fits to perimetric sensitivity were compared. Ninety-five percent confidence intervals were bootstrapped. The dynamic range of the functional and structural RGC density estimates was denoted by their 1st and 99th percentiles.
RESULTS: The RMSE was 2.09 (95% CI = 1.92-2.26) under H1 and 2.49 (95% CI = 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.