Working Group Artificial Intelligence in Radiation Oncology

Research Focus:

  • Agentic AI for interactive medical treatment planning (AI-PIONEER ERC-funded project)
  • Application of large language models as an information source and decision-support system (AIDvice project)
  • Multimodal foundation models for gastrointestinal cancers (BZKF Lighthouse)
  • AI-based analysis for patients with brain metastases (AURORA Multicenter Study of the AG Stereotaxy of DEGRO)
  • AI-based analysis of patients with anal carcinoma (DKTK Multicenter Study)
  • AI-based analysis of patients with soft tissue sarcomas
  • AI-based analysis of patients with prostate carcinoma (Co-IMPACT consortium)
  • Development and improvement of neural networks for tumor and risk organ segmentation
  • Prediction of side effects of radiation therapy (DFG SPP 2177)

 

Current team members:

  • Josef Buchner (Physician Scientist)
  • Dr. med. Julia Fabian (Physician Scientist)
  • Dr. med. Dr. rer. Nat. Kim Kraus (Physician Scientist)
  • Linus Marx (Physician Scientist)
  • Dr. med. Mai Nguyen (Physician Scientist)
  • Dr. med. Samuel Vorbach (Physician Scientist)
  • Dr. med. Lucas Zander (Physician Scientist)
  • Can Erdur (MSc; PhD-student)
  • Stefan Fischer (MSc; PhD-student)
  • Ahmed El Gohary Yasser Mohamed (MSc; PhD-student)
  • Johannes Kiechle (MSc; PhD-student)
  • Lukas Atzelsberger (Medical Doctoral Thesis)
  • Lena-Maria Paula Irmgard Baumann (Medical Doctoral Thesis)
  • Annika Domres (Medical Doctoral Thesis)
  • Franziska Duschinger (Medical Doctoral Thesis)
  • Stella Matthiessen Krausenecker (Medical Doctoral Thesis)
  • Melissa Olufs (Medical Doctoral Thesis)
  • Danai Pletzer (Medical Doctoral Thesis)
  • Katharina Riegger (Medical Doctoral Thesis)
  • Nora Windeler (Medical Doctoral Thesis)
  • Lukas Reuter (Medical Doctoral Thesis)

 

Former Team Members:

  • Joachim Akhgar (Physician)
  • Mohamed Shouman (Physician)
  • Maksym Oreshko (Physician)
  • Nora Windeler (Physician)
  • Fernando Navarro (PhD)

 

Funding:

Image featuring six logos of funding and partner organizations: Bavarian Center for Cancer Research, Wilhelm Sander Foundation, German Research Foundation, Else Kröner-Fresenius Foundation, Google.org, and the European Research Council.

 

Selected publications:

  • Reuter LM, Kraus KM, Fischer SM, …, Peeken, JC (2026). Prediction of Symptomatic Radiation Pneumonitis in Lung Cancer Patients: A Radiomics and Dosiomics Machine Learning Approach Using the Prospective Multicenter RTOG 0617 and REQUITE Trials. International journal of radiation oncology, biology, physics, S0360-3016(26)00365-2. https://doi.org/10.1016/j.ijrobp.2026.01.031.
  • Peeken JC*, Etzel L*, Tomov T et al. Development and benchmarking of a Deep Learning-based MRI-guided gross tumor segmentation algorithm for Radiomics analyses in extremity soft tissue sarcomas. Radiother Oncol. 2024 Aug;197:110338. doi: https://doi.org/10.1016/j.radonc.2024.110338. *shared authorship.
  • Buchner JA, Kofler F, Mayinger M, ... , Peeken JC. Radiomics-based prediction of local control in patients with brain metastases following postoperative stereotactic radiotherapy. Neuro Oncol. 2024 Sep 5;26(9):1638-1650. https://doi.org/10.1093/neuonc/noae098.
  • Kraus KM, Oreshko M, Schnabel JA, ..., Peeken JC. Dosiomics and radiomics-based prediction of pneumonitis after radiotherapy and immune checkpoint inhibition: The relevance of fractionation. Lung Cancer. 2024 Mar;189:107507. doi: https://doi.org/10.1016/j.lungcan.2024.107507.
  • Zamboglou C*, Peeken JC*, Janbain A, et al. Development and Validation of a Multi-institutional Nomogram of Outcomes for PSMA-PET-Based Salvage Radiotherapy for Recurrent Prostate Cancer. JAMA Netw Open [Internet]. 2023; 6: e2314748. https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2805173, * shared authorship.
  • Spohn SKB, Schmidt-Hegemann N-S, Ruf J, ..., Peeken JC. Development of PSMA-PET-guided CT-based radiomic signature to predict biochemical recurrence after salvage radiotherapy. Eur J Nucl Med Mol Imaging. 2023; Available at: https://doi.org/10.1007/s00259-023-06195-3.
  • Buchner JA, Kofler F, Etzel L, ..., Peeken JC. Development and external validation of an MRI-based neural network for brain metastasis segmentation in the AURORA multicenter study. Radiother Oncol. 2023; 178: 109425. available at: https://doi.org/10.1016/j.radonc.2022.11.014
  • Spohn SKB, Farolfi A, Schandeler S, ..., Peeken JC. The maximum standardized uptake value in patients with recurrent or persistent prostate cancer after radical prostatectomy and PSMA-PET-guided salvage radiotherapy-a multicenter retrospective analysis. Eur J Nucl Med Mol Imaging. 2022 Dec;50(1):218-227. doi: https://doi.org/10.1007/s00259-022-05931-5.
  • Peeken JC, Asadpour R, Specht K, et al. MRI-based Delta-Radiomics predicts pathologic complete response in high-grade soft-tissue sarcoma patients treated with neoadjuvant therapy. Radiother Oncol. 2021 Nov;164:73-82. https://doi.org/10.1016/j.radonc.2021.08.023.
  • Peeken JC, Shouman MA, Kroenke M et al. A CT-based radiomics model to detect prostate cancer lymph node metastases in PSMA radioguided surgery patients. Eur J Nucl Med Mol Imaging. 2020;47(13):2968-2977. https://doi.org/10.1007/s00259-020-04864-1.
Prof. Dr. med. Jan Peeken
Managing Senior Physician
Head of Research Group: