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Breast diagnostics / Gynecological radiology

Breast imaging

Research group

  • PD Dr. med. Sebastian Bickelhaupt
  • Prof. Dr. med. Matthias Dietzel
  • Prof. Dr. med. Rolf Janka
  • Dr. med. Lorenz Kapsner
  • Prof. Dr. rer. nat. Frederik Laun
  • Dr. med. Sabine Ohlmeyer
  • Prof. Dr. med. Evelyn Wenkel
  • Dr. med. Matthias Wetzl

Summary

Breast cancer is the most common cancer in women. Imaging plays a pivotal role in early detection and staging, as well as for the assessment of therapeutic response and therapy monitoring. Novel imaging methods allow for a comprehensive assessment of the entire organ providing insight in the complexity of tissue microstructure and metabolism. The areas of research thus aim at expanding the dimensions of breast imaging beyond single modalities or techniques. The unique pool of research imaging technologies being evaluated in clinical studies consists of 0.55T to 7T MRI devices, breast CT and a combined US/DBT-device, next to all routine imaging modalities. Aim of the research group is to decipher imaging bio-signatures for risk stratification in early detection of breast cancer in average and high-risk groups and to utilize them in prognostic and therapy-response assessments in order to improve the breast health care for women. This includes redesigning of imaging sequences and hardware components. In order to achieve this aim novel technological imaging approaches are combined with innovative data evaluation techniques using artificial intelligence and big-data analyses in a unique collaborative and interdisciplinary environment.

Recent Publications (selection):

  1. Ohlmeyer S, Laun FB, Palm T, Janka R, Weiland E, Uder M, Wenkel E.
    Simultaneous Multislice Echo Planar Imaging for Accelerated Diffusion-Weighted. Imaging of Malignant and Benign Breast Lesions. Invest Radiol. 2019. Aug;54(8):524-530. doi: 10.1097/RLI.0000000000000560. PMID: 30946181.
  2. Dietzel M, Schulz-Wendtland R, Ellmann S, Zoubi R, Wenkel E, Hammon M, Clauser P, Uder M, Runnebaum IB, Baltzer PAT. Automated volumetric radiomic analysis of breast cancer vascularization improves survival prediction in primary breast cancer. Sci Rep. 2020
  3. Palm T, Wenkel E, Ohlmeyer S, Janka R, Uder M, Weiland E, Bickelhaupt S, Ladd ME, Zaitsev M, Hensel B, Laun FB. Diffusion kurtosis imaging does not improve differentiation performance of breast lesions in a short clinical protocol. Magn Reson Imaging. 2019 Nov;63:205-216. doi: 10.1016/j.mri.2019.08.007. PMID: 31425816.
  4. Bickelhaupt S, Jaeger PF, Laun FB, Lederer W, Daniel H, Kuder TA, Wuesthof L, Paech D, Bonekamp D, Radbruch A, Delorme S, Schlemmer HP, Steudle FH, Maier-Hein KH. Radiomics Based on Adapted Diffusion Kurtosis Imaging Helps to Clarify Most Mammographic Findings Suspicious for Cancer. Radiology. 2018 Jun;287(3):761-770. doi: 10.1148/radiol.2017170273.
  5. Kalender WA, Kolditz D, Steiding C, Ruth V, Lück F, Rößler AC, Wenkel E. Technical feasibility proof for high-resolution low-dose photon-counting CT of the breast. Eur Radiol. 2017 Mar;27(3):1081-1086. doi: 10.1007/s00330-016-4459-3