An image of the human retina captured using fundus photography

We are funding a PhD studentship investigating how to detect early blood vessel functional changes in diabetic retinopathy using non-invasive imaging techniques. This research, from PhD student, Ines Zamoun and Dr Adam Dubis and his team, could help identify treatment entry points and develop a better understanding of diabetic eye disease associated changes.

What is non-invasive imaging?

Learn more

Non-invasive imaging refers to methods of seeing structures inside the body. It can help to determine the cause if someone is ill without the need to undergo exploratory surgery. Examples of non-invasive imaging techniques include X-rays, CAT scans, MRIs, and Ultrasound. Non-invasive imaging to investigate conditions that affect the eye and vision include fundus imaging, OCT (optical coherence tomography) and AOSLO (adaptive optics scanner light ophthalmoscope imaging).

The challenge

A good and functional blood supply to the back of the eye is essential for maintaining a healthy retina – the light sensitive layer at the back of the eye. In diabetic retinopathy these blood vessels can be disrupted, resulting in vision loss. 

Currently, diabetic retinopathy can be detected by taking photographs of the eye during a diabetic eye screening. However, significant blood vessel wall weakening occurs before the damage can be visualised, yet these early changes are not included in assessing the severity of diabetic retinopathy. 

There is sufficient evidence to suggest sight loss occurs before the onset of visible diabetic retinopathy, which is why it is so important to detect these early changes.

Finding a solution

This project will develop a number of tools for understanding vascular blood flow using retinal imaging techniques. For example, a custom camera will be used for cellular imaging. 

Several methods to examine how retinal blood flows through vessels will be created, validated and used in a small clinical trial. 

Measurements of how the vessels expand and contract in response to pulse rate will be taken and the researchers will look at how fast the blood moves through the vessels in relation to cardiac cycle (one heartbeat to the next). 

Additional modern data science tools will be utilised to analyse the blood flow and reduce the very complex data into easily understandable terms.

The potential

Currently, there is an unmet need to detect very early changes in diabetic retinopathy and this research could help with developing non-invasive methods to do this. 

Advancing our understanding of these early changes also paves the way for future work towards the development of new treatments, with the ultimate goal of preventing sight loss.

Project Details

Funding scheme

PhD Studentship


Adam Dubis

Area(s) of work

Diabetic retinopathy

Award level


Start date

October 2020

Grant reference