Coordination Funds

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Compared to the first funding period of the Priority Programme we want to focus on the clinical implementation and value of advanced image analysis as well as the application of these techniques to gain deeper understanding of the role of imaging phenotypes in large-scale population cohorts. There is still not doubt that biomedical imaging plays an increasingly central role in the management of various disease settings in modern medicine. In addition, imaging is progressively more incorporated in research settings, including the formation of large-scale, population-based cohorts, such as the German National Cohort (NAKO Gesundheitsstudie). In parallel, with the advent of powerful, large scale computational power facilities and growing on-site expertise, advanced post-processing methods, including Artificial Intelligence, Deep-Learning, or Radiomics, are used to abstract descriptive, diagnostic, or prognostic information from high-resolution imaging data. As such, these derived parameters (“imaging phenotypes”) complement traditionally available and used image information, such as manual measurements of diameters or the mere presence of disease states and allow for high-volume, reproducible, and high-quality interpretation skills. However, despite these successful endeavours, there is still only early evidence that such advanced computer-based imaging post-processing provides incremental diagnostic and prognostic information in the field of personalised medicine, and algorithms have not fully entered the clinical arena yet. Given the great promise, the PP is designed to further develop and establish the role of advanced image interpretation approaches in different clinical scenarios in personalised medicine, including prevention of disease development. The aims of SPP2177 Phase 2 comprise: Aim 1 Determination of the diagnostic clinical value of advanced post-processing methods of human imaging data in different clinically relevant and/or in basic research settings; Aim 2 Determination of the prognostic value of advanced post-processing methods of human imaging data in clinically relevant settings and/or in basic research settings. The overall goal of the project is to further guarantee an efficient coordination and administration of the in order to further enhance the collaboration between the specific research projects within the programme, and with external stakeholders on national and international level in academia and industry. The activities of the coordinator and his team comprise the organization of retreats, conferences and workshops, support of visiting scientists, the coordination of outreach and public relation activities, the monitoring of gender measures, the control of programme finances and the establishment of communication and reporting structures. Coordination will also ensure scientific coherence of the projects. This project will support administration of central funds needed to organize and coordinate PP-internal activities.