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Longitudinal CBCT-Based Synthetic CT Assessment: Towards Robust, Quality-Assured and Biomarker-Driven Adaptation

University of Bern, Department of Radiation Oncology, Department of Digital Medicine, sitem-insel center, Bern, Switzerland
  • Planned secondments: Boston Massachusetts General Hospital (US), Medical University of Vienna (Austria) and Ion Beam Applications (Belgium)
  • PhD program: University of Bern

Project description

This PhD project aims to advance adaptive proton therapy by establishing a clinically viable workflow for CBCT-based treatment adaptation. The research will contribute to designing an efficient and robust CBCT-based adaptation pipeline that enables daily treatment adjustments in proton therapy. A central component will be the development of reliable quality control tools for CBCT-to-synthetic CT conversion with particular emphasis on longitudinal quality assessment. The expected outcomes include clinically suitable CBCT-based synthetic CT generation, validated quality assurance tools, and the clinical implementation of CBCT-driven adaptation. An additional aspect of this project is the exploration of longitudinal CBCT and synthetic CT trends to identify potential biomarkers. These biomarkers, extending beyond geometrical changes, may pave the way for biological and functional adaptation in proton therapy. Explorative work will investigate the potential of other imaging modalities such as PET and MRI to extract biomarkers, based on limited cases, thereby broadening the scope towards multimodal and functional adaptation. Ultimately, the project seeks to enhance precision and personalization in cancer treatment by integrating longitudinal imaging insights into adaptive workflows.

The successful candidate will be enrolled in the Graduate School for Cellular and Biomedical Sciences (GCB) of the University of Bern, under the supervision of Prof. Antje Knopf. The University of Bern is one of Switzerland’s leading comprehensive universities, combining a strong medical faculty with internationally recognized research in oncology, digital medicine, and translational science. The project will be executed in close partnership with the clinical medical physics team of the Center for Proton Therapy (CPT) at the Paul Scherrer Institut (PSI).

The DC will be part of Prof. Knopf’s research group, which is dedicated to advancing the integration of computational methods and clinical innovation in cancer care and beyond. Closely affiliated with the University Clinic for Radiation Oncology (UKRO) and embedded within the Center for Artificial Intelligence in Oncology (CAIRO), the group builds strong bridges between clinical practice, digital transformation, and cutting-edge research. Within the Department of Digital Medicine, it contributes actively to the digitization strategy of the Medical Faculty of the University of Bern, shaping the future of medical education and clinical decision-making through data-driven approaches.

For more information concerning the research project please contact: 
Antje Knopf

Candidate profile

Doctoral Candidate at University of Bern

The ideal PhD candidate will have a strong academic background in medical physics, biomedical engineering, computer science, or a related discipline, with a demonstrated interest in radiation oncology and digital medicine. A solid foundation in imaging sciences, and quantitative analysis is essential, complemented by skills in programming, data science, and computational modeling. Experience with medical imaging modalities such as CT, CBCT, MRI, or PET, and familiarity with dose calculation or treatment planning in radiotherapy, will be considered a strong asset.
Beyond technical expertise, the candidate should bring curiosity and motivation to explore translational research questions at the interface of clinical practice and computational innovation. Strong analytical skills, the ability to work independently, and a collaborative mindset are crucial, as the project is embedded in a highly interdisciplinary and international research environment. The candidate should be eager to contribute to methodological development while maintaining a clear focus on clinical applicability and patient benefit.
Excellent communication skills, both written and oral, are required to engage with diverse stakeholders, ranging from clinicians and researchers to industry partners. The candidate should be comfortable presenting complex concepts clearly and independently work towards scientific publications and conference abstracts.
Universität_Bern

University of Bern

EMPLOYING ASSOCIATED PARTNER

The University of Bern is one of Switzerland’s leading comprehensive universities, comprising one of the largest medical faculties in Switzerland with a strong emphasis on practical relevance in their degree programs, an exceptional diversity of research topics, and a high level of innovation. Close links between basic research, the clinics, and engineering sciences create the optimal conditions for cutting-edge medical research and translation. The Faculty of Medicine is closely integrated with Inselspital, Bern University Hospital, which provides direct access to a large and diverse patient population. It is home to specialized centers such as the Department of Digital Medicine, which drives innovation in data-driven healthcare and equips future medical professionals with skills in artificial intelligence, digital diagnostics, and virtual care.

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