Revisiting the structure/function relationship in glaucoma for improved patient care

Glaucoma is a leading cause of irreversible blindness, characterized by a progressive loss of retinal ganglion cells (RGCs) and their axons and associated loss of visual field (VF). Lowering intraocular pressure (IOP) is an effective treatment for the disease, but early detection of glaucoma and detection of progression is a major clinical challenge. The diagnosis and follow-up of the disease includes functional testing using automated perimetry and structural imaging using optical coherence tomography (OCT). Relating structural to functional damage in glaucoma is referred to as the structure/function relationship. This may help to integrate information from both structural and functional tests into progression analysis. Current models do, however, only provide relatively weak corrections between structure and function, because of inter-individual variability, measurements errors, dynamic measurement ranges of the techniques and challenges in defining abnormality. Here we propose to improve our understanding of the structure/function relationship in glaucoma with a number of novel approaches: 1. Use of widefield OCTs that cover areas of 12x12 mm or 15x9 mm and therefore contain information from both the macular and the optic nerve head area; 2. Correction of anatomical confounders such as retinal angioarchitecture, fovea-disc angle and optic disc size; 3. Inclusion of vascular density information from OCT angiography (OCTA) measurements; 4. Development of machine learning and deep learning models for advanced structure/function relationship. Our central hypothesis is that the structure/function relationship can be improved using this framework and that this will result in improved prediction of future glaucoma progression in individual patients. This is done in an effort to integrate both structural and functional test results into diagnosis and follow up glaucoma for improved clinical care. A combined OCT/VF outcome may also be considered as an outcome measure for neuroprotection clinical trials.