Research

Department of Translational Imaging in Oncology

The Department of Translational Imaging in Oncology aims to improve clinical research on new therapies through the use and development of imaging. The focus is on questions regarding the role of imaging for clinical decision processes such as combining systemic and local therapeutic approaches and the value of functional imaging in individual therapy management.

High quality anatomical and functional imaging will be used to support clinical trials and registries. Disease spread and biological characteristics will be non-invasively imaged using the most innovative and accurate methods both in primary or recurrent disease and for monitoring response after surgery, radiotherapy, systemic therapy or a combination of these procedures.
 

Thus, PET/MRI imaging will be further developed in the following aspects:

1. Understanding derived parameters of tumor distribution, tumor volume, and tumor configuration

2. Imaging functional processes in the tumor for the choice of the best possible individual tumor therapy

3. Imaging of immunological processes

Contact

Prof. Dr. med. Matthias Miederer
Head of the Department of Translational Imaging in Oncology
email: matthias.miederer(at)nct-dresden.de

2023

Genetic Code Expansion for Site-Specific Labeling of Antibodies with Radioisotopes.
Koehler C, Sauter PF, Klasen B, Waldmann C, Pektor S, Bausbacher N, Lemke EA, Miederer M. ACS Chem Biol. 2023 Mar 8. doi: 10.1021/acschembio.2c00634. Online ahead of print. PMID: 36889678

Up-Regulation of PSMA Expression In Vitro as Potential Application in Prostate Cancer Therapy.
Runge R, Naumann A, Miederer M, Kotzerke J, Brogsitter C. Pharmaceuticals (Basel). 2023 Apr 4;16(4):538. doi: 10.3390/ph16040538

PET/CT reading for relapse in non-small cell lung cancer after chemoradiotherapy in the PET-Plan trial cohort.
Alexander Brose; Kerstin Michalski; Juri Ruf; Marco Tosch; Susanne M Eschmann; Mathias Schreckenberger; Jochem König; Ursula Nestle; Matthias Miederer. Cancer Imaging 23, 45 (2023). https://doi.org/10.1186/s40644-023-00567-6


Link to page "NCT/UCC Imaging Platform" with further information