Due to copyright issues, an electronic copy of the thesis must be ordered from the faculty. For the faculty to have time to process the order, the order must be received by the faculty at the latest 2 days before the public defence. Orders received later than 2 days before the defence will not be processed. After the public defence, please address any inquiries regarding the thesis to the candidate.
Trial Lecture – time and place
See Trial Lecture.
Adjudication committee
- First opponent: Associate Staff Scientist Petra van Houdt, Netherlands Cancer Institute
- Second opponent: Professor Mattijs Elschot, Norwegian University of Science and Technology, Trondheim
- Third member and chair of the evaluation committee: Associate Professor Siri Lagethon Heck, University of Oslo
Chair of the Defence
Professor Mona Kristiansen Beyer, University of Oslo
Principal Supervisor
Head of Research Therese Seierstad, Oslo University Hospital
Summary
Breast cancer treatment outcomes vary widely between patients, partly due to biological differences in tumor structure, oxygenation, and blood supply. These factors influence how tumors respond to therapy, but are not captured by conventional imaging or tissue biopsies.
The aim of this thesis was to investigate how quantitative magnetic resonance imaging (MRI) can be used to measure and model features of the tumor microenvironment that affect treatment response. Diffusion-weighted and dynamic contrast-enhanced MRI were combined with pharmacokinetic and mathematical modeling to map oxygen levels, vascular function, and local variations in tumor tissue.
The studies demonstrated that MRI-based biomarkers can detect hypoxia and early vascular changes in response to treatment, and that these imaging features can be linked to biological mechanisms influencing response. The results also showed that individualized simulation models incorporating imaging data can simulate and predict local tumor evolution under therapy for macroscopic pieces of tumor.
Overall, the work demonstrates that advanced MRI can provide non-invasive, repeatable, and clinically relevant information about tumor physiology. Such imaging biomarkers may support earlier assessment of treatment effect and guide more personalized and adaptive breast cancer therapy in the future.
Additional information
Contact the research support staff.