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Multiparametric methods for early detection of prostate cancer

Junior Clinical Cooperation Unit Multiparametric methods for early detection of prostate cancer

PD Dr. Magdalena Görtz

Targeted prostate cancer detection by magnetic resonance imaging/ultrasound fusion biopsy.

Our clinical cooperation unit at the DKFZ and University Hospital Heidelberg aims at developing more individualized approaches for prostate cancer diagnostics and therapy planning. Prostate cancer is characterized by a considerable heterogeneity of aggressiveness and disease progression. In case of suspicious examination findings, MRI imaging and histological securing of the prostate are indicated. However, with the current means for early detection of prostate cancer, not only aggressive but also indolent prostate cancer are diagnosed, which would not result in increased morbidity or mortality.
In our group, we prospectively and systematically compile clinical, laboratory-chemical, radiological, molecular biological and histopathological data for the development of new diagnostic strategies for prostate cancer. Integrated patient data allows to investigate new analytical methods and their prognostic significance, among others parameter extraction, deep neural networks and machine learning. There is an urgent need for new molecular markers to improve diagnostics and risk stratification of prostate cancer. Among others, we investigate predictive biomarkers in form of epigenetic modifications in the circulating cell-free DNA of liquid biopsy samples from prostate cancer patients.

An integrative early detection and risk stratification strategy that combines molecular markers with imaging has the potential to optimize non-invasive diagnostics, to develop more precise prediction models and to allow correlations with tumour aggressiveness. The aim of our clinical cooperation unit is to identify new biomarkers and diagnostic models with predictive and prognostic relevance for the presence and aggressiveness of prostate cancer. In the future, more individualized approaches for the diagnostics and therapy planning of patients with prostate cancer are to be developed.


PD Dr. Magdalena Görtz
Multiparametric methods for early detection of prostate cancer (E250)
Deutsches Krebsforschungszentrum
Im Neuenheimer Feld 223
69120 Heidelberg
Tel: +49 6221/42-2603

Selected Publications

  • Gortz, M., Baumgartner, K., Schmid, T., Muschko, M., Woessner, P., Gerlach, A., Byczkowski, M., Sultmann, H., Duensing, S., and Hohenfellner, M. (2023). An artificial intelligence-based chatbot for prostate cancer education: Design and patient evaluation study. Digit Health 9, 20552076231173304.
  • Eickelschulte, S., Riediger, A.L., Angeles, A.K., Janke, F., Duensing, S., Sultmann, H., and Gortz, M. (2022). Biomarkers for the Detection and Risk Stratification of Aggressive Prostate Cancer. Cancers (Basel) 14.
  • Tavakoli, A.A., Hielscher, T., Badura, P., Gortz, M., Kuder, T.A., Gnirs, R., Schwab, C., Hohenfellner, M., Schlemmer, H.P., and Bonekamp, D. (2023). Contribution of Dynamic Contrast-enhanced and Diffusion MRI to PI-RADS for Detecting Clinically Significant Prostate Cancer. Radiology 306, 186-199.
  • Gortz, M., Radtke, J.P., Hatiboglu, G., Schutz, V., Tosev, G., Guttlein, M., Leichsenring, J., Stenzinger, A., Bonekamp, D., Schlemmer, H.P., et al. (2021). The Value of Prostate-specific Antigen Density for Prostate Imaging-Reporting and Data System 3 Lesions on Multiparametric Magnetic Resonance Imaging: A Strategy to Avoid Unnecessary Prostate Biopsies. Eur Urol Focus 7, 325-331.
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