Sunday, January 5, 2025
1/5/2025
Project Summary Glaucoma is a leading cause of vision morbidity and blindness worldwide. Early disease detection and sensitive monitoring of progression are crucial to allow timely treatment for preservation of vision. The introduction of ocular imaging technologies significantly improves these capabilities, but in clinical practice there are still substantial challenges at certain stages of the disease severity spectrum, specifically in the early stage and in advanced disease. These difficulties are due to a variety of causes that change over the course of the disease, including large between-subject variability, inherent measurement variability, image quality, varying dynamic ranges of measurements, minimal measurable level of tissues, etc. In this proposal, we build on our long-standing contribution to ocular imaging and propose novel and sensitive means to detect glaucoma and its progression that are optimized to the various stages of disease severity. We will use information gathered from visual fields (functional information) and a leading ocular imaging technology – optical coherence tomography (OCT; structural information) to map the capability of detecting changes across the entire disease severity spectrum to identify optimal parameters for each stage of the disease. Both commonly used parameters provided by the technologies and newly developed parameters with good diagnostic potential will be analyzed. We will use state-of-the-art automated computerized machine learning methods, namely the deep learning approach, to identify structural features embedded within OCT images that are associated with glaucoma and its progression without any a priori assumptions. This will provide novel insight into structural information, and has shown very encouraging preliminary results. We will also utilize a new imaging technology, the visible light OCT, to generate retinal images with outstanding resolution to extract information about the oxygen saturation of the tissue. This will provide in-vivo, real time, and noninvasive insight into tissue functionality. Taken together, this program will advance the use of structural and functional information with a substantial impact on the clinical management of subjects with glaucoma
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