“Integrated model for personalized diabetic retinopathy screening and monitoring using risk-stratification and automated AI-based fundus image analysis - PerDiRe”

During the intensive meeting program, project teams from all four countries presented their results. Despite the Covid-19 pandemic, which affected all project activities, progress was achieved in all work packages of the first year of the project. Recruitment of participants has started in all Member States.

Consortium leader J. Sokolovska in her presentation reminded about the deliverables and publicity measures to be achieved in the project. During the project meeting, participants from the Baltic States were introduced to the organization and research directions of the Eye Research Institute at the University of Oslo. Then there was a meeting with RetinaRisk and BubliCam to assess the possibilities of cooperation within this and future projects.

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Project EEA-RESEARCH-60 “Integrated model for personalized diabetic retinopathy screening and monitoring using risk-stratification and automated AI-based fundus image analysis - PerDiRe” is one of the Baltic Research Programme’s projects, which is financially supported by the European Economic Area (EEA) Grants. The project is developed by University of Latvia in cooperation with University of Oslo, Lithuanian University of Health Sciences and Tartu University. The implementation of the project started on May 1, 2021 and the project will last until 31.03.2024. Available funding is 1 000 000 Eur.

Information about the project can be found at the webpage https://www.perdire.lu.lv/.

@EEANorwayGrantsLatvia

The main task of the project is development of the personalized approach for the screening and monitoring of the eye complications of diabetes mellitus. This approach would allow to determine the personalized screening interval for each patient. The activities of the project will include ophthalmological examination of patients with diabetes, collection of data on the risk factors of diabetic retinopathy, automated grading of diabetic retinopathy with the use of artificial intelligence, application of machine learning methods for determination of the risk factors for diabetic retinopathy and the optimal screening interval, evaluation of the cost-efficacy of the new diabetic retinopathy monitoring program.

The project will develop and pilot the new personalized screening and monitoring approach in diabetic retinopathy care. We suggest to shift from the rigid “one-size-fits-all” approach for determination of the screening interval for patients with diabetes. Instead, we will determine the risk of progression of diabetic retinopathy using analysis of wide variety of risk factors and fundus images using artificial intelligence. We will assess the cost-effectiveness of this new system and present it to the healthcare authorities. The project will allow for capacity building of young researchers, including elaboration of PhD thesis. In addition, it will provide a platform for further scientific collaborations. The activities of the project will foster the development of the integrated care of patients with diabetes and e-health directly and through knowledge tranfer