In vivo mapping of foveal photoreceptors in retinal health and disease

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Despite a total of about 100 million light sensitive photoreceptor cells in the human retina, only a small bouquet of cones at the foveal center is used for most visual tasks. Losing function in these cells has dramatic consequences for vision and in many retinal diseases, foveal photoreceptor structure and function is disturbed permanently. Although there are reports from the leading centers worldwide indicating therapy success in genetic therapies of photoreceptors the mechanism of the functional rescue of rods and cones and its correlation with morphological readouts in retinal imaging is not well understood. Adaptive optics imaging now makes it possible to observe microscopic, cellular structural and functional changes in the retina, opening the door for direct microscopic evaluation of the affected tissue and its impact for vision in the living eye. Partially because of insufficient visual resolution and missing analytical tools, the role of the functionally most relevant area, the foveal center, has not been studied yet. To close the gap, this project will first develop AI-assisted analytical tools for an automated pipeline for foveal photoreceptor detection and quantification in AOSLO imagery. We will then assess foveolar cellular topography in a large cohort of different age groups to build a topographical model of the normal fovea, which will also be used to build an atlas of normative foveolar cone topography data. Finally, to foster widespread clinical application, we will correlate our high-resolution topography data with clinical grade lower-resolution image data, studying whether readily available image data can be used as proxy for cell-resolved analysis.