Translational Imaging in Tumor and Inflammation

• Prof. Dr. med. Tobias Bäuerle
• PD Dr. med. Stephan Ellmann
• Dr. med. vet. Lisa Freier
• Dr. med. Konstantin Hellwig
• Lisa Seyler
• Dr. rer. nat. Vanessa Popp
• Dr. med. Christoph Treutlein

Carcinogenesis and inflammation induce processes of tumor and immune cells that interact with the local microenvironment and may have systemic impact resulting in distant metastasis or a systemic response on inflammation, respectively. Primary area of research is to assess these processes by multimodal imaging on the translational and clinical level including MRI, CT, PET, ultrasound and optical imaging. Aim of our group is to develop novel imaging techniques for assessment of tumor growth, metastasis and inflammatory processes for translational purposes in preclinical models and patients. For this purpose we assess quantitative parameters in local and systemic disease and implement machine learning algorithms to integrate large amounts of imaging data to detect, diagnose or predict oncologic or inflammatory disease. This program is currently funded by national and international consortia, in particular by the Deutsche Forschungsgesellschaft within the Collaborative Research Centers 1181 (Checkpoints for Resolution of Inflammation) and TR 305 (Striking a moving target: From mechanisms of metastatic organ colonization to novel systemic therapies) as well as the Priority Programme SPP 2084 µBone (Colonisation and Interactions of Tumor Cells within the Bone Microenvironment).

Recent Publications (selection):

1. Czegley C, Gillmann C, Seyler L, Schauer C, Naschberger E, Uder M, Schett G, Bäuerle T*, Hoffmann M* (*contributed equally, shared last authorship) (2018). A model of chronic enthesitis and new bone formation characterized by multimodal imaging. Dis Model Mech 11(9): dmm034041
2. Ellmann S, Schlicht M, Dietzel M, Janka R, Hammon M, Saake M, Ganslandt T, Hartmann A, Kunath F, Wullich B, Uder M, Bäuerle T (2020) Computer-aided diagnosis in multiparametric MRI of the prostate: An open-access online tool for lesion classification with high accuracy. Cancers 12(9):E2366
3. Ellmann S, Seyler L, Evers J, Heinen H, Bozec A, Prante O, Kuwert T, Uder M, Bäuerle T (2019) Prediction of early metastatic disease in experimental breast cancer bone metastasis by combining PET/CT and MRI parameters to a Model-Averaged Network. Bone 120:254-261
4. Heinen H, Seyler L, Popp V, Hellwig K, Bozec A, Uder M, Ellmann S, Bäuerle T (2020) Morphological, functional, and molecular assessment of breast cancer bone metastases by experimental ultrasound techniques compared with magnetic resonance imaging and histological analysis. Bone, 144:115821
5. Saake M, Schmidle A, Kopp M, Hanspach J, Hepp T, Laun FB, Nagel AM, Dörfler A, Uder M, Bäuerle T (2019) MRI brain signal intensity and relaxation times in individuals with prior exposure to gadobutrol. Radiology 290(3): 659-668