Research Program "Radiation Oncology and Imaging (ROI)"

Imaging and Radiation Oncology are indispensible components of multidisciplinary management of cancer. Both have substantial cross-linkage with each other.

Innovative data mining approaches as well as the handling, sharing and archiving of big data are prerequistes for research as well as clinical applications. The overall aim of the Radiation Oncology part of the Program is to improve treatment by biological individualization and by technical optimization, including the use of particle radiotherapy. Program activities cover translational clinical trials on particle therapy and biological individualization, the development and preclinical testing of novel technologies (e.g., particle beam imaging; laser acceleration), biomarkers and bioimaging for radiation therapy patient stratification, as well as novel combinations and preclinical trials. In Imaging science the aim is to develop novel PET, MR and CT biomarkers and theranostics as well as to implement standardized, quality-controlled, multiparametric imaging protocols and workflows to enable multicenter preclinical/clinical studies. In view of the growing field of multiparametric imaging an additional aim is to further develop and improve image/texture analysis and radiomics for biological tumor characterization, therapy planning, as well as monitoring and prediction of response to therapy.

Highlight Achievements

  • Image-based and molecular biomarkers for the individualization of radiotherapy (Lohaus et al., Radiother Oncol 2014; Balermpas et al., Int J Cancer 2015; two publications Menegakis et al., Radiother Oncol 2015; Tinhofer et al., Ann Oncol 2014; Geisenberger et al., Acta Neuropathol 2015; Zschaeck et al., Acta Oncol 2015; Bütof et al., J Nucl Med 2015; Chirindel et al., Radiother Oncol 2015; Mönnich et al., Acta Oncol 2015; Linge et al. [DKTK-ROG], Clin Cancer Res. 2016 Epub; Tinhofer et al., Eur J Cancer, 2016 Epub; Baumann et al., Nature Rev Cancer, in press).
  • Creating data exchange strategies for radiation research and an open source system integration approach (Skripcak et al., Radiother Oncol 2014; Skripcak et al., IEEE Journal of Biomedical and Health Informatics, Epub 2015).
  • Treatment planning, verification of novel advanced methods and patient stratification for particle therapy (Jakobi et al., Int J Radiat Oncol Biol Phys 2015; Niklas et al., Int J Radiat Oncol Biol 2013; Dai et al., Radiother Oncol 2014; Baumann, Nature Rev Cancer, in press).
  • PET of CD133(+) tumor stem cells, with a focus on immune therapies and immune PET (Gaedicke etal., Proc Natl Acad Sci U S A 2014) as well as PET tracer studies with CXCR4 in patients with multiple myeloma leading to DKTK multicenter studies (Philipp- Abbrederis et al., EMBO Mol Med 2015).
  • Imaging of in vivo Th1 cell tracking for immunotherapies (Griessinger et al., Proc Natl Acad Sci U S A 2015) and hyperpolarized imaging add new in vivo biomarkers to study tumor metabolism (Hovener et al., Nat Commun 2013).