The retina, at the back of the eye, is the only part of the brain that can be viewed directly and non-invasively. The retina is actually an outgrowth of brain tissue, and thus changes in the brain due to age and disease are often reflected in the eyes.
Optical Coherence Tomography (OCT) is a relatively new technique which can image the 3D structure of living retinal tissue in near microscopic detail. OCT is already widely used to diagnose, assess and monitor eye conditions such as glaucoma, as well as monitor how systemic conditions such as diabetes are affecting the eyes. However, we believe that
OCT imaging of the eyes has much greater potential to monitor brain health as well. We already know retinal structure reflects demographic factors such as age, sex and ethnicity, and that particular neurodegenerative conditions, such as Alzheimer’s and Parkinson’s disease, are associated with changes in the thickness of the different tissue layers within the
retina. We are excited by the possibility of using OCT scans to also monitor brain health as people age.
Achieving this will require detecting and interpreting very subtle changes in retinal structure, far harder to detect than the gross changes caused by eye diseases like glaucoma or age-related macular degeneration. Changes of concern will have to be discriminated from normal variability within diverse populations. And there is already a shortage of ophthalmologists trained to make even relatively straightforward diagnoses from OCT images. We propose to address this by using artificial intelligence (AI) techniques to recognise and characterise the changes that occur in the retina and their link to a variety of health and well-being questions related to healthy/unhealty ageing but also, for relevant diseases and with access to appropriate data, questions related to diagnosis, prognosis or treatment options.