Department of Radiation Oncology

Inselspital Bern

The Department is one of the leading providers of radiation therapy in Switzerland. It conducts extensive research programs in the fields of clinical research, technology development, medical physics, radiobiology, data science, and artificial intelligence.

To the Inselspital website

Director

Prof. Daniel M. Aebersold

Profile

Teaching

Undergraduate lectures are provided for students in medicine, physics, biomedical engineering, molecular and biomedical sciences as well as in dental medicine at the University of Bern; undergraduate teaching does also include practical training for medical students; lectures are given within the master in “Artificial Intelligence in Medicine” at University of Bern; postgraduate lectures in medical physics are given at the Department of Physics at the Swiss Federal Institute of Technology in Zurich; a CAS program for palliative care is run in cooperation with various faculties of the University of Bern and the Bern University of Applied Sciences; various PhD and MD-PhD positions are provided in radiation biology, medical physics, and palliative care

Clinical Research

(a) Prostate cancer: salvage radiotherapy, metabolomic signatures; (b) head neck cancer: Upfront neck dissection in the context of primary radiotherapy; single vocal cord irradiation; POLARES (Personalized discovery and validation multi-Omics pLAtform for Recurrent hEad and Neck Squamous Cell Carcinoma) (c) brain tumor: automatic segmentation of brain tumors, postoperative radiosurgery; (d) Total Neoadjuvant Treatment with HYPErthermia in high risk extremity and trunk soft tissue sarcoma (TNT-HYPE); (e) Impact of MRI for planning and followup of SBRT in spinal metastases; (f) palliative care: advance care planning, early integration of palliative care; best care for the dying patient; community palliative care, regional networks

Medical physics research

(a) Dynamic Trajectory Radiotherapy (DTRT) and Dynamic Mixed Beam Arc Therapy (DYMBARC); (b) Standard Electron Beam Application using a Photon Multi Leaf Collimator; (c) Very High Electron Energy Radiotherapy; (d) Independent Dose Calculation and Dosimetric Impact of Implants in the Context of Robotic Stereotactic Radiotherapy; (e) Efficient Quality Assurance for External Beam Radiotherapy and Accurate Dose Calculation for Brachytherapy; (f) Medical Imaging Related Research Topics

Radiation biology research

(a) Genomic landscapes of metastatic and recurrent head and neck squamous cell carcinoma (HNSCC) tumors; SPRR2A in invasiveness and therapeutic resistance in HNSCC; (b) Immune signatures predictive of chemoradiation-induced toxicities in HNSCC patients; (c) Functional characterizations of a newly identified MET receptor tyrosine kinase phosphorylation site in physiological conditions and cancer; (d) Investigation of algorithms for data from next-generation sequencing, genomic and transcriptomic data in particular; (e) Work with the International Cancer Genome Consortium on standardized pipelines for omics data

Data science and artificial intelligence

(a) The effect of small cohort sizes and population heterogeneity on differential expression analysis; (b) Automatic segmentation of brain metastasis and primary brain tumors; (c) Exploring of large language models in radiation oncology

External Partners

Multidisciplinary and multi-institutional national and international collaboration within the SAKK & EORTC networks; Institute for Biomedical Engineering, Swiss Federal Institute of Technology (ETH), Zürich, Switzerland; Princess Margaret Cancer Center, Toronto, Canada; ACRF Image X Institute, University of Sidney, Australia; Department of Clinical Medicine, Aarhus University, Denmark; Carleton Laboratory for Radiotherapy Physics, Carleton University, Ottawa, Canada; Oncogenomics Group, Department for BioMedical Research, University of Bern, Switzerland; Scailyte AG, Basel, Switzerland; Merck KGaA, Darmstadt, Germany; Children's Hospital Los Angeles, USA

Grants

SNSF; EU; Innosuisse; Krebsforschung; Krebsliga; SAKK; Werner and Hedy Berger-Janser Foundation; Ruth & Arthur Scherbarth Foundation; Stiftung für klinisch-experimentelle Tumorforschung; Insel DLF; Insel DLF and Faculty of Medicine; Sitem-Insel Support Funds; Merck; VARIAN

Highlights 2025

The A-BEACON Process. By using feedback and corrections from human experts, the AI continuously learns and improves, aiming for "zero-miss" accuracy to ensure no tumors are overlooked.

Prof. Dr. Mauricio Reyes of the ARTORG Medical Image Analysis Laboratory and CAIRO Center have been awarded the prestigious SNSF MAPS fund for their project, "A-BEACON" (AI-based Brain MEtastases TrACking and SegmentatiON). In collaboration with partners from Poland, Romania, and Bulgaria, the team aims to develop an advanced AI system capable of "Zero-Miss Detection" to assist clinicians in the precise and efficient analysis of brain MRIs. This international initiative was one of only 29 projects selected from over 300 proposals.

Combined treatment outcome depends on genetic background

HPV and p53 status determine the response of head and neck cancer to radiotherapy combined with DNA-PKcs targeting

Inhibition of DNA damage response pathways has the potential to increase radiotherapy efficacy. We show that administration of a specific DNA-PKcs inhibitor radiosensitizes various head and neck cancer models but the actual cell fate upon this treatment is determined by their p53 and HPV status. Whereas HPV-positive or p53-mutated cancer cells are eliminated by apoptosis, p53-proficient tumors undergo senescence.

MIRACLE: MIcrobeam RAdiotherapy – paradigm change in CLinical cancEr treatment

MIRACLE seeks to translate the exceptional tumour control and tissue-sparing benefits of microbeam radiation therapy into clinical applicable sub-millimetre spatially fractionated radiotherapy on conventional megavoltage linear accelerators. Through digital twin development, experimental validation, and radiobiological investigation, MIRACLE aims to enable a paradigm shift in radiotherapy and potentially improve the outcomes and quality of life for future cancer patients.

To the SNSF Website

Four key aspects required for the clinical implementation of an auto-segmentation model.

A comprehensive multifaceted technical evaluation framework for implementation of auto-segmentation models in radiotherapy

This study introduces COMMUTE, a comprehensive framework designed to guide the evaluation of such AI tools. The framework was tested on an in-house developed model for outlining organs at risk in the brain. The results showed good accuracy, high expert approval, and significant time savings. COMMUTE supports safer and faster implementation of AI in radiotherapy by promoting higher-quality models.

Poel et al., Commun Med (Lond). 2025