Early diagnosis of diabetic retinopathy hopes raised

Research is under way to develop new techniques for detecting diabetic retinopathy at early onset with the hope of improving prevention and treatment of this major cause of blindness.

Diabetic retinopathy is the most common cause of sight loss in people of working age. It is estimated that in England every year 4,200 people are at risk of blindness caused by diabetic retinopathy, with 1,280 new cases identified annually.

As part of the Retinal Vascular Modelling, Measurement and Diagnosis (REVAMMAD) project led by the University of Lincoln, UK, Marie Curie Researcher Georgios Leontidis is investigating new methods for the early screening and diagnosis of the disease by developing computer models which can detect small changes in the blood vessels of the eye.

Funded by the European Union’s 7th Framework (FP7) Marie Curie Initial Training Network programme, the University of Lincoln has been awarded 900,000 euros from the 3.8 million euro budget to lead the project and to develop retinal imaging and measurement training and research. It aims to improve diagnosis, prognosis and prevention of diseases such as diabetes, hypertension, stroke and coronary heart disease and retinal diseases.

Georgios, an Electronics and Computer Engineer within the University of Lincoln’s School of Computer Science, is investigating the effects of diabetes on the retina’s vessel walls and how this ultimately affects the flow of blood in the whole vasculature of the retina. He said: “Here at the University of Lincoln, our efforts focus on analysing images of diabetic patients before the first stage of diabetic retinopathy. In that way we want to see what changes diabetes causes to the retina vessels and how these changes progress to retinopathy. We will then try to correlate the standard features we extract from these images with functional changes that occur, such as abnormality in blood pressure, blood flow volume and blood flow velocity, as well as to associate them with some risk factors like age, type of diabetes, duration of diabetes, gender and smoking.”