Prognostic value of body composition out of PSMA-PET/CT in prostate cancer patients undergoing PSMA-therapy
In this proof-of-principle study the implementation of a deep learning-based whole-body analysis provides a robust and detailed CT-based assessment of body composition in mCRPC patients undergoing RLT. Potential prognostic parameters have to be corroborated in larger prospective datasets.
Authors
- Kambiz Rahbar (ORCID: https://orcid.org/0000-0002-4591-4055)
- Julian Varghese (ORCID: https://orcid.org/0000-0002-7206-3719)
- Wolfgang Roll (ORCID: https://orcid.org/0000-0002-3746-9393)
- David Ventura (ORCID: https://orcid.org/0000-0002-4346-2606)
- Max Masthoff (ORCID: https://orcid.org/0000-0001-5338-9193)
- Philipp Schindler (ORCID: https://orcid.org/0000-0002-8098-9853)
- Lucas Plagwitz (ORCID: https://orcid.org/0000-0001-7626-8853)
- Claus Backhaus (ORCID: https://orcid.org/0000-0002-0032-4705)
Institutions
- University of Münster (DE)
- German Cancer Society (DE)
- University Hospital Münster (DE)
Publication Details
- Journal
- European Journal of Nuclear Medicine and Molecular Imaging
- Published
- 2025-06-28
- DOI
- https://doi.org/10.1007/s00259-025-07416-7
- Citations
- 2
- Primary Topic
- Prostate Cancer Treatment and Research
- Type
- article
- Field-Weighted Citation Impact
- 3.04