Quantification of retinal vascular reactivity during acute hyperglycaemia

Diabetes affects nearly half a billion people worldwide, with 1 in 5 developing sight-threatening retinal problems. Imaging blood vessels within the eye is a key tool in assessing retinal health and disease progression. Current imaging can detect advanced disease through blood vessel loss, but we lack the ability to detect early warning signs to identify those most at risk of vision loss.

Our recent research shows that retinal blood vessels become thinner and less reactive to light stimulation early in diabetes, well before visible vessel loss occurs. This project will translate these laboratory findings into a clinical test that can detect early retinal changes and help prevent diabetes-related blindness.

The retina is highly energy-demanding, and its blood vessels must respond quickly to increased neural activity by dilating to deliver more oxygen and glucose. However, we do not understand how raising blood glucose levels affect this vessel response, or how to accurately measure these complex changes across the three-dimensional retinal vessel network.

This project will investigate how glucose impacts the control of retinal blood vessel diameter during times of increased metabolic need. In collaboration with MDAP, the team will create a bespoke analysis package using comprehensive retinal vascular maps to visualise and quantify how vessels change in response to light stimulation and glucose fluctuations.

MDAP's expertise in image analysis, network mapping, software design and machine learning is essential to this project. The team will design analytical approaches to quantify vessel responses, determine whether all vessels respond similarly, identify differences between retinal layers, and reveal which parameters are most sensitive to glucose changes.

The research will produce two key outputs: fundamental data on how glucose affects human retinal vessel function, and a novel analysis platform for quantifying vessel reactivity.

These findings will inform the development of a biomarker for early diabetic retinopathy and enable clinical studies, that aim to improve diabetes management and possibly identify those most at risk of vision loss. The analysis platform could also be applied to research other vascular conditions, including glaucoma and mild cognitive decline.