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Priority Programme Radiomics: Next Generation of Biomedical Imaging (SPP 2177)
Termin:
01.07.2022
Fördergeber:
Deutsche Forschungsgemeinschaft (DFG)
In March 2018, the Senate of the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) established the Priority Programme Radiomics: Next Generation of Biomedical Imaging (SPP 2177). The programme is designed to run for six years. The present call now invites proposals for the second three-year funding period.
Biomedical imaging has substantially developed over the last decades and 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 Priority Programme 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 Priority Programme requires complementary, multidisciplinary teams with expertise in different fields, including clinical imaging, computational science, epidemiology and/or health technology assessment. The interaction among interdisciplinary teams will establish a synergistic platform for successful translational research and effective clinical implementation of imaging techniques.
As the Priority Programme should have a lasting impact on the national and international scientific landscape, a mandatory prerequisite for participation is an intention to add value by collaborating with the other projects within the programme. Inclusion of female applicants, clinician-scientists, and early-career researchers is strongly encouraged.
Proposals submitted to this call should address at least one of the following fundamental aims:
- to determine the diagnostic clinical value of advanced post-processing methods of human imaging data in different clinically relevant and/or in basic research settings;
- to determine the prognostic value of advanced post-processing methods of human imaging data in clinically relevant settings and/or in basic research settings.
We highly encourage applications of projects within the field of cross-organ and/or cross-system research. Compared to the first funding period of the Priority Programme, particular emphasis will be given to projects that 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.
Proposals eligible under the present call are proposals that:
- stem from high-quality prospective studies with a statistically reasonable sample size and clearly defined endpoints;
- comprise computed tomography, magnetic resonance imaging data or their combination with other advanced imaging modalities.
Similar to the first call, not eligible are proposals that:
- purely focus on the development of image analysis algorithms;
- include image acquisition or outcome data collection.
Weitere Informationen:
https://www.dfg.de/foerderung/info_wissenschaft/info_wissenschaft_22_20/index.html
Biomedical imaging has substantially developed over the last decades and 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 Priority Programme 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 Priority Programme requires complementary, multidisciplinary teams with expertise in different fields, including clinical imaging, computational science, epidemiology and/or health technology assessment. The interaction among interdisciplinary teams will establish a synergistic platform for successful translational research and effective clinical implementation of imaging techniques.
As the Priority Programme should have a lasting impact on the national and international scientific landscape, a mandatory prerequisite for participation is an intention to add value by collaborating with the other projects within the programme. Inclusion of female applicants, clinician-scientists, and early-career researchers is strongly encouraged.
Proposals submitted to this call should address at least one of the following fundamental aims:
- to determine the diagnostic clinical value of advanced post-processing methods of human imaging data in different clinically relevant and/or in basic research settings;
- to determine the prognostic value of advanced post-processing methods of human imaging data in clinically relevant settings and/or in basic research settings.
We highly encourage applications of projects within the field of cross-organ and/or cross-system research. Compared to the first funding period of the Priority Programme, particular emphasis will be given to projects that 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.
Proposals eligible under the present call are proposals that:
- stem from high-quality prospective studies with a statistically reasonable sample size and clearly defined endpoints;
- comprise computed tomography, magnetic resonance imaging data or their combination with other advanced imaging modalities.
Similar to the first call, not eligible are proposals that:
- purely focus on the development of image analysis algorithms;
- include image acquisition or outcome data collection.
Weitere Informationen:
https://www.dfg.de/foerderung/info_wissenschaft/info_wissenschaft_22_20/index.html