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Division of Radiology

Prof. Dr. med. Dipl.-Phys. Heinz-Peter Schlemmer

Multiparametric morphologic-functional imaging of lung cancer by CT, MR and PET/MR

The Division of Radiology at the DKFZ develops imaging methods for early detection and functional and biologic characterization of cancer using the most recent cross-sectional imaging techniques including ultrasound, dual-energy CT, MR (1.5 T, 3.0 T, 7.0 T), simultaneous PET/MR and PET/CT. Our goal is to further advance individualized diagnosis, image-guided biopsy and therapy of cancer. Methodological developments are performed in close cooperation with the other divisions of the research program and within clinical studies in collaboration with clinical partners of the Heidelberg University Hospital. For this purpose the division operates an MRI suite with two state of the art (1.5 T and 3.0 T) MR scanners the National Center for Tumor Diseases (NCT). Furthermore, the Division of Radiology is a partner of the German Consortium for Translational Oncology (DKTK) and the German Center for Lung Research. Scientific fields of application in oncology include, amongst others, prostate cancer, breast cancer, lung cancer, multiple myeloma and brain tumors. In close collaboration with the divisions of medical physics, medical informatics and radiation oncology tools for tumor diagnosis and quantification of individual therapy responses are developed and applied, to better assess changes in tissue composition during and after treatment and to perform improved quantification of therapy response. Within these collaborations further activities include computer-aided image analysis and computer assisted imaging applications for biopsy and treatment planning, e.g. for improving radiotherapy, or the detection and targeting of prostate cancer.


Prof. Dr. med. Dipl.-Phys. Heinz-Peter Schlemmer
Radiology (E010)
Deutsches Krebsforschungszentrum
Im Neuenheimer Feld 280
69120 Heidelberg
Tel: +49 6221 42 2563

Selected Publications

  • Wehrse E, Sawall S, Klein L, Glemser P, Delorme S, Schlemmer HP, Kachelrieß M, Uhrig M, Ziener CH, Rotkopf LT. Potential of ultra-high-resolution photon-counting CT of bone metastases: initial experiences in breast cancer patients. NPJ Breast Cancer. 2021 Jan 4;7(1):3. doi: 10.1038/s41523-020-00207-3. PMID: 33398008; PMCID: PMC7782694.
  • Zhang KS, Schelb P, Netzer N, Tavakoli AA, Keymling M, Wehrse E, Hog R, Rotkopf LT, Wennmann M, Glemser PA, Thierjung H, von Knebel Doeberitz N, Kleesiek J, Görtz M, Schütz V, Hielscher T, Stenzinger A, Hohenfellner M, Schlemmer HP, Maier-Hein K, Bonekamp D. Pseudoprospective Paraclinical Interaction of Radiology Residents With a Deep Learning System for Prostate Cancer Detection: Experience, Performance, and Identification of the Need for Intermittent Recalibration. Invest Radiol. 2022 Apr 22. doi: 10.1097/RLI.0000000000000878. Epub ahead of print. PMID: 35467572.
  • Paech D, Regnery S, Platt T, Behl NGR, Weckesser N, Windisch P, Deike-Hofmann K, Wick W, Bendszus M, Rieken S, König L, Ladd ME, Schlemmer HP, Debus J, Adeberg S. Assessment of Sodium MRI at 7 Tesla as Predictor of Therapy Response and Survival in Glioblastoma Patients. Front Neurosci. 2021 Dec 1;15:782516. doi: 10.3389/fnins.2021.782516. PMID: 34924945; PMCID: PMC8671745.
  • Wennmann, M., Klein, A., Bauer, F., Chmelik, J., Grözinger, M., Uhlenbrock, C., Lochner, J., Nonnenmacher, T., Rotkopf, L.T., Sauer, S., Hielscher, T., Götz, M., Floca, R., Neher, P., Bonekamp, D., Hillengass, J., Kleesiek, J., Weinhold, N., Weber, T.F., Goldschmidt, H., Delorme, S., Maier-Hein, K., Schlemmer, H.-P. Combining deep learning and radiomics for automated, objective, comprehensive bone marrow characterization from whole-body MRI: a multicentric feasibility study. Invest. Radiol. 2022; 57. In press.
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