Home > Research and Education > Project stories > Baltic and Norwegian scientists collaborate to improve …

Baltic and Norwegian scientists collaborate to improve eye health of diabetic patients

Experience story of the project “Integrated model for personalized diabetic retinopathy screening and monitoring using risk-stratification and automated AI-based fundus image analysis (PerDiRe)”

Modern medicine is unthinkable without science and technology. However, sometimes the interaction of science, technology and medicine leads to challenging problems. The international project PerDiRe, in which Latvia was a leading partner, was dedicated to the early recognition of diabetic retinopathy and the development of new approaches to patient monitoring. This project, in which 500 patients from Latvia, Lithuania, Estonia and Norway participated, was dedicated not only to improving eye health, but also to the application of new technologies and data analysis in medicine.

Diabetic retinopathy (or diabetic eye disease) is one of the leading causes of vision loss in developed countries. The aim of the project was to improve the diagnosis and prognosis of diabetic retinopathy by applying a new artificial intelligence-based screening and monitoring program for diabetic retinopathy, which introduced machine learning and image analysis.

Activities and achievements of the project

The project’s activities included monitoring patients for one year, where clinical factors were monitored and analysed with the help of artificial intelligence, as well as an innovative approach in the analysis of eye images. The cost-effectiveness of this solution was evaluated. When observing patients, in addition to the standard ophthalmologist examination, as part of diabetic retinopathy screening, we also collected data on diabetes history, comorbidities, and some clinical factors (e.g., blood pressure). As one of the new and promising biomarkers for determining the risk of progression of diabetic retinopathy, we measured sugar metabolism products in the skin of the patients. In addition, genetic risk factors for diabetic retinopathy were also searched within the project. Currently, the analysis of project data is still ongoing. However, we can already report the first results.  First, experience at Oslo University Hospital shows that AI-based fundus image analysis for monitoring diabetic retinopathy is cost-effective. Second, we managed to develop a new approach for early automated diagnosis of diabetic retinopathy using image segmentation method. Second, we managed to develop a new approach for early automated diagnosis of diabetic retinopathy using image segmentation method. Thirdly, the results of the project clearly indicate that screening for diabetic retinopathy should not be limited to an eye doctor’s examination. To effectively observe the patient and reduce the risk of vision loss, the cooperation of several specialists (ophthalmologist, endocrinologist, general practitioner) and the observation and correction of clinical factors in close connection with the treatment of eye changes are required. For example, the project data demonstrate that many diabetic patients have a blood pressure that is outside the recommended norms, and they are not prescribed appropriate treatment or are not explained the importance of taking medication regularly to prevent the development of diabetes complications. Fourth, the new biomarkers studied in the project (detection of end products of sugar metabolism in the skin and genetic factors) may improve the determination of the severity and risk of progression of diabetic retinopathy.

Project challenges and further development

However, the implementation of the project was not without challenges. During the pandemic, patient recruitment was delayed and there were difficulties with the supply of equipment and materials. We could not organize the project opening event in person, which affected the start of the project. Optimal project management was also a challenge at times.

Despite these difficulties, the project was a positive test of cooperation and innovation. Cooperation was strengthened, knowledge exchange took place intensively, and all project partners gained new skills and experience. Quality clinical care was provided to diabetic patients and the results of the project will later contribute to further research in the field of diabetic retinopathy. We are glad that during the project rallies, we got to know the screening approaches of diabetic retinopathy in the institutions of the project participants and there was an exchange of experiences.

In the future, the scientific direction of the project will be further developed. It is planned to apply to Eurostars and ICPerMed project calls to continue the work on the analysis of eye images with artificial intelligence and the study of new biomarkers of diabetic retinopathy. As part of these new project applications, it is planned to expand the PerDiRe consortium and continue the research and analysis of the obtained data. This experience is not only medically significant, but also provided an opportunity to develop new collaboration and research opportunities.

The Baltic Research Programme is implemented with the support of EEA grants within the framework of programme “Research and Education”, which is implemented by the Ministry of Education and Science and the Latvian Council of Science. The total funding of the programme is 8,676,084 euros, of which the state budget co-financing is 15% or 1,301,413 euros and the EEA co-financing is 85% or 7,374,671 euros. In the Baltic research programme, 9 research projects and 5 small cooperation projects are implemented in Latvia.

The Baltic Research Programme’s project “Integrated model for personalized diabetic retinopathy screening and monitoring using risk-stratification and automated AI-based fundus image analysis (PerDiRe)” is implemented by the University of Latvia (Latvia), University of Oslo (Norway), Lithuanian University of Health Sciences (Lithuania), University of Tartu (Estonia).