Combining retinal nerve fiber layer thickness with individual retinal blood vessel locations allows modeling of central vision loss in glaucoma

Hui Wang; Mengyu Wang; Neda Baniasadi; Qingying Jin; Tobias Elze

doi:10.1117/12.2251132

8 February 2017 Combining retinal nerve fiber layer thickness with individual retinal blood vessel locations allows modeling of central vision loss in glaucoma

Hui Wang, Mengyu Wang, Neda Baniasadi, Qingying Jin, Tobias Elze

Author Affiliations +

Proceedings Volume 10045, Ophthalmic Technologies XXVII; 100451M (2017) https://doi.org/10.1117/12.2251132
Event: SPIE BiOS, 2017, San Francisco, California, United States

Abstract

Purpose: To assess whether modeling of central vision loss (CVL) due to glaucoma by optical coherence tomography (OCT) retinal nerve fiber (RNF) layer thickness (RNFLT) can be improved by including the location of the major inferior temporal retinal artery (ITA), a known correlate of individual RNF geometry. Methods: Pat- tern deviations of the two locations of the Humphrey 24-2 visual field (VF) known to be specifically vulnerable to glaucomatous CVL and OCT RNFLT on the corresponding circumpapillary sector around the optic nerve head within the radius of 1.73mm were retrospectively selected from 428 eyes of 428 patients of a large clinical glaucoma service. ITA was marked on the 1.73mm circle by a trained observer. Linear regression models were fitted with CVL as dependent variable and VF mean deviation (MD) plus either of (1) RNFLT, (2) ITA, and (3) their combination, respectively, as regressors. To assess CVL over all levels of glaucoma severity, the three models were compared to a null model containing only MD. A Baysian model comparison was performed with the Bayes Factor (BF) as measure of strength of evidence (BF<3: no evidence, 3-20: positive evidence, >20: strong evidence over null model). Results: Neither RNFLT (BF=0.9) nor ITA (BF=1.4) alone provided positive evidence over the null model, but their combination resulted in a model with strong evidence (BF=21.4). Conclusion: While the established circumpapillary RNFLT sector, based on population statistics, could not satisfactorily model CVL, the inclusion of a retinal parameter related to individual eye anatomy yielded a strong structure-function model.

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Hui Wang, Mengyu Wang, Neda Baniasadi, Qingying Jin, and Tobias Elze "Combining retinal nerve fiber layer thickness with individual retinal blood vessel locations allows modeling of central vision loss in glaucoma", Proc. SPIE 10045, Ophthalmic Technologies XXVII, 100451M (8 February 2017); https://doi.org/10.1117/12.2251132

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KEYWORDS

Visualization

Eye models

Optical coherence tomography

Visual process modeling

Arteries

Eye

Nerve

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