Glaucoma is a disease of the optic nerve which is accompanied by visual ?eld (VF) loss. While accurate VF loss diagnosis and the detection of its progression over time is of high relevance to clinical practitioners as it indicates the initiation of or change in ocular therapy, there is no consensus on objective measures for this purpose, and VF measurements are known to be often unreliable. The main objective of this project is to develop clinically applicable measures to improve the diagnosis of glaucomatous VF loss and of its progression by two approaches: First, the identi?cation of representative loss patterns and their progression, achieved by large-scale, customized bioinformatical procedures applied to data from glaucoma patients from nine clinical centers and second, the inclusion of eye and patient speci?c personalized parameters. In total, 480,486 VFs, are available for this project. One major aim is to develop novel diagnostic indices based on computationally identi?ed evolution patterns of VF loss, particularly (1) an index that denotes the probability of glaucomatous vision loss and (2) an index that assigns probabilities to a VF that follow-up measurements will be in a certain defect class. The indices will be statistically evaluated on separate VF samples and compared to existing approaches. Routinely available patient speci?c parameters which are candidates to impact glaucomatous vision loss are patient ethnicity, type of glaucoma, spherical equivalent (SE) of refractive error and the location of the blind spot relative to ?xation. The effect of these parameters on the vision loss patterns will be systematically studied. The impact of their inclusion in the novel diagnostic indices and their potential improvement on glaucoma diagnosis will be quanti?ed on a separate data set. A further aim is the calculation of a spatial map speci?c to a measured VF that represents the preferred VF locations of future defects as well as their reliability as an aid to event-based progression diagnosis. A second major objective is the investigation of the relationship of VF loss and individual parameters related to retinal structure, based on retinal nerve ?ber layer thickness (RNFLT) measurements around the optic disc. The inter-relationship of representative patterns of RNFLT and its decrease over time with trajectories of major retinal arteries, SE, and blind spot location is systematically studied, and the impact on patterns of VF loss is quantitatively analyzed with the goal to improve the interpretation of existing VF loss and to predict future glaucomatous vision loss. Main contributions of the project with relevance to clinical practice are publicly available open-source software implementations of new diagnostic indices and maps, enhanced by individual functional and structural parameters, and a detailed and personalized model for the relationship between retinal structure and glaucomatous vision loss.

Public Health Relevance

Glaucoma is an ocular disease accompanied by vision loss which may progress over time up to total blindness, but the assessment of glaucomatous vision loss is noisy, and it is often hard for clinical practitioners to decide whether changes over time re?ect true changes of functional vision or are the result of normal measurement variations or artifacts. This project contributes directly and immediately to public health by exploring the impact of individual anatomical parameters on the spatial patterns of glaucomatous vision loss in order to improve the diagnosis of vision loss and of its progression. Main objective of the project is the development of new quantitative diagnostic indices, implemented as publicly available software.

National Institute of Health (NIH)
National Eye Institute (NEI)
Research Project (R01)
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Special Emphasis Panel (ZRG1)
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Liberman, Ellen S
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Schepens Eye Research Institute
United States
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