Kleerekooper, I; (2021) Investigating neuroinflammatory disease through retinal imaging and biomarkers. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

Neuroinflammatory diseases, in particular multiple sclerosis (MS) and neuromyelitis optica spectrum disorder, often affect the anterior visual pathways. This can occur through direct inflammatory insult in the form of optic neuritis or through retrograde degeneration, but progressive neurodegenerative processes related to axonal loss and atrophy also play a role. Energy failure has been postulated as an important factor mediating factor in these neurodegenerative processes, but its exact role is poorly understood. The advent of optical coherence tomography (OCT) enables high resolution imaging of the retina with relative ease. In neurology research, OCT has mostly been used to quantify retinal layer thicknesses. This thesis focuses on the largely unexplored potential of OCT as a functional biomarker. The primary aim is to develop indirect non-invasive in-vivo biomarkers informing on metabolic function, taking into account the high energy demand of the retina, particularly during dark-adaptation. First, two novel functional OCT measures are presented; the dynamic dark-adaptation related thickening of the outer retinal layers and the relative reflectivity of the ellipsoid zone (EZ), which comprises the majority of retinal mitochondria. Both measures appeared to be reduced in acute optic neuritis, and also in chronic neuroinflammatory disease in the case of EZ reflectivity. Furthermore, pilot OCT-angiography (OCTA) data indicated that vascular density was reduced in acute optic neuritis. As reduced EZ reflectivity and lower vascular density were present to a similar degree in both eyes of acute optic neuritis patients suggest that a background level of mitochondrial dysfunction and hypoperfusion may occur in neuroinflammatory disease, independent from acute inflammatory activity. The work presented in this thesis illustrates that OCT has the potential to provide valuable information on retinal function in neuroinflammatory disease. In the future, artificial intelligence and big data analysis may enable the development of a holistic analysis method for raw OCT data, providing a summary report on both qualitative, such as presence of microcystic macular oedema (MMO), and quantitative scan features, such as layer thickness, vascular density and reflectivity. Comprehensive analysis of both functional and structural OCT data may facilitate diagnosis, inform on prognosis and provide important insight into the role of metabolic failure in the pathophysiology of neuroinflammatory disease.

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