European Training Network for Excellence in Molecu.. (BETATRAIN)
European Training Network for Excellence in Molecular Imaging in Diabetes
Date du début: 1 janv. 2012,
Date de fin: 31 déc. 2015
Currently, 180 million people suffer from diabetes worldwide and this number is expected to double until 2030. Diabetes-related healthcare costs may rise to 40% of the total healthcare budget in high incidence countries. Despite these daunting numbers, our knowledge about the pathophysiology of T1D and T2D remains limited and many questions about the relation of the of the beta cell mass, the beta cell function and the metabolism of different tissues remain unanswered. In order to address these urgent questions, great hope has been put on the development of novel tracers, and functional and molecular imaging methods, which only recently have become available for in vivo diabetes imaging. However, it remains difficult to build up top level expertise as few, if any, European institutions are able to offer a profound combined molecular imaging/diabetes training, a shortcoming that continues to hamper the progress of the field. As a consequence, most available molecular imaging techniques are insufficiently characterised for clinical use in diabetes.To address this challenge, we propose a training network (“BetaTrain”) to connect academic/private sector partners from 5 leading European FP7 consortia with top level expertise in beta cell/diabetes imaging. Like this, BetaTrain will not only provide a unique multidisciplinary intersectoral training opportunity to young scientists in the field, but will also address the urgent challenges in our combat against diabetes.In order to non-invasively characterize beta cells and other relevant tissues in animal models and humans suffering from diabetes, it will be necessary to combine different molecular imaging techniques to provide information complementary to that obtained by other imaging, laboratory, and functional tests. The scientific training program of BetaTrain will therefore characterise, cross-calibrate and map these technologies/tracers in order to create the basis for personalised diagnosis and therapy in diabetes.
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