Studying the eye to improve detection of small vessel disease in the brain

The BHF-Turing Cardiovascular Data Science Awards (Second Call): Uncovering retinal microvascular predictors of compromised brain haemodynamics in small vessel disease (joint funding with The Alan Turing Institute)

Cerebral small vessel disease (SVD) is a common disease affecting the small blood vessels of the brain. SVD is responsible for nearly half of all dementia cases and a fifth of all strokes worldwide. The cause of the disease is poorly understood and there is no proven treatment. SVD is difficult to detect and study because the vessels where the disease starts are too small to be visible with current brain imaging technology. However, the small blood vessels at the back of the eye – the retinal microvasculature – are closely related to the small blood vessels in the brain, and can be seen in detail with high definition retinal imaging cameras. A team of scientists at the University of Edinburgh, led by computational biologist Dr Miguel Bernabeu and neuroimaging expert Professor Joanna Wardlaw, will apply data science methods to high resolution retinal images to discover what they can tell us about the onset and progression of SVD. The team will develop mathematical and computational techniques to characterise the retinal microvasculature of people with SVD and determine which vessels do not have adequate blood flow or have other abnormal characteristics. The researchers will then investigate how this data relates to blood flow in vessels of the brain and whether it can be used to predict the onset and progression of SVD. This research could aid the development of a non-invasive technology that is much cheaper and can diagnose SVD much earlier than current methods.