The eye as a window to the central nervous system – an artificial intelligence approach to biomarker discovery for MS

The eye, with common embryonic origins to the brain and other shared anatomical features such as a blood–tissue barrier and nerves, is an area of the central nervous system amenable to non-invasive study. Optical Coherence Tomography (OCT) measures thickness of nerve fibres in the retina, with MS patients showing axonal loss through a marked thinning of this layer. OCT has also revealed a lower density of blood vessels around the optic nerve in MS while our own pilot data from fundus imaging suggests further differences in venules in the peripheral retina associate with disease progression. Retinal metrics may therefore reflect neurodegeneration and
neurovascular change with possible utility in early detection of MS and prediction of disease progression.

With access to different machines in Edinburgh, the student will combine images through development of novel post-processing to build an unparalleled view or description of the retinal vasculature not previously attempted, including the smallest discernible vessels around the macula to the main arcades near the optic nerve and their branches extending out to the periphery.

The student will probe for a vascular mechanism in the pathogenesis of MS using novel metrics and combine with established measures of neuroretinal anatomy to investigate association with disease via cutting-edge artificial intelligence, machine learning and statistics (e.g. neural network-based deep learning).