Due to copyright reasons, an electronic copy of the thesis must be ordered from the faculty. In order for the faculty to have time to process the order, it must be received by the faculty no later than 2 days prior to the public defence. Orders received later than 2 days before the defence will not be processed. Inquiries regarding the thesis after the public defence must be addressed to the candidate.
Trial Lecture – time and place
See Trial Lecture.
Adjudication committee
- First opponent: Professor Marion Smits, Erasmus MC - University Medical Centre Rotterdam
- Second opponent: Associate Professor Henrietta Nittby Redebrandt, Lund University
- Third member and chair of the evaluation committee: Professor Trygve Brauns Leergaard, University of Oslo
Chair of the Defence
Professor II Bjørnar Hassel, University of Oslo
Principal Supervisor
Professor II Atle Bjørnerud, University of Oslo
Summary
Brain lesions, given their location, may have a profound and often life-threatening impact on the patients’ life. An accurate and timely diagnosis of disease is critical for optimal treatment decisions. Magnetic resonance imaging (MRI) is the best imaging method to visualize brain lesions. New imaging options have evolved in MRI, with the goal to reach diagnoses that are more precise. Any new method has also its costs, in both time and other resources.
The overall aim of this thesis was to evaluate whether new techniques make a clinical impact on diagnostic imaging and outcome prediction in patients with brain lesions.
In patients with brain lesions, the central sulcus, an important region for determining risk of motor deficit after surgery, was easier identified using anatomical and volumetric MRI methods compared to that of a functional MRI (BOLD) technique.
An automated machine learning based method, called support-vector machine (SVM) provides reliable data for assessing survival in patients with glioma, with better reproducibility and less user dependency, than traditional MRI methods.
In a multicenter study we assessed the potential consequences for the treatment of glioma patients, taking into account the observers’ (radiologists’) confidence, using structural MRI features without and with dynamic susceptibility contrast-enhanced (DSC) perfusion. We found that the choice of surgical intervention was associated with the complexity of tumor infiltration and low observer confidence was associated with more extensive adjuvant treatment.
Additional information
Contact the research support staff.