Centre for Cancer Biomarkers


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New imaging center on campus

A new imaging center on campus with state-of-the-art imaging equipment will strengthen research activities. Three research projects have received funding to be integrated with the novel Medical Imaging and Visualisation Centre.

Illustration of two medical workers discussing over MRI pictures.


New cross-disciplinary imaging facility

The University of Bergen in collaboration with Haukeland University Hospital has recently through financial support from the Bergen Research Foundation (BFS), established the Medical Imaging and Visualization Centre. This is localized at Haukeland University Hospital, the Radiology Department.

​The purpose of the center is to strengthen cross-disciplinary research activities related to the state-of-the-art imaging equipment, i.e. high field MRI, CT and pre-/clinical PETCT. With emphasis on the natural sciences, the long-term goal of the center is to achieve excellence in imaging (physics, chemistry, radiography, radiology), visualization (computer science and mathematics) and in vivo clinical and research applications (including applications in basic research and preclinical validation). 

The aim of the center is to research new methods in quantitative imaging and interactive visualization to predict changes in health and disease across spatial and temporal scales.

Congratulations to CCBIO collaborators

Earlier this year, BFS announced funding for a total of three research projects that would be linked to the center. The funding has now been announced. 25 researchers submitted project proposals, and two of the accepted investigators were CCBIO collaborators Ingfrid Haldorsen at the Department of Clinical Medicine and Arvid Lundervold at the Department of Biomedicine.

In addition to BFS, which contributes 40.6 million NOK, Helse Bergen (the regional health authority) contributes with 13.6 million NOK to the center. The University of Bergen and Helse Bergen also contribute financially to the three accepted projects.

Finding biomarkers through imaging

Professor Haldorsen is a radiology specialist and has collaborated closely with researchers at the Women's Clinic at Haukeland University Hospital and CCBIO's Gynaecologic Cancer Research Group on advanced image investigation of patients with gynecological cancer. The collaboration has made it possible to compare the characteristics of the tumor based on advanced imaging methods such as MRI and PET (positron emission tomography) and findings in tumor tissues. The imaging findings prove to be important for the patient's life expectancy and risk of relapse.

"We have among other found that tumors with high glucose metabolism and with reduced blood circulation are more aggressive and are associated with increased mortality for the patient. In this and similar ways, we can detect image biomarkers that may help to map the extent and aggressiveness of the tumor, enabling physicians to choose the best option of surgical treatment and provide the right patients with radiotherapy and chemotherapy, based on the patient's risk profile", Professor Haldorsen explains.

Developing technology to support doctors

Professor Lundervold received support for his project "Computational Medical Imaging and Machine Learning Methodology and e-Infrastructure». Lundervold’s project will develope and deploy machine learning technologies that allow automated analysis of medical images. Machine learning, or more precisely “Deep Neural Networks” are computational techniques that allow computers to help analyze medical images in a similar way as a trained doctor would – partly faster, more reliably, and with much higher capacity. By employing this technique on the images acquired on high-tech medical imaging equipment, and integrating other data such as omics data, clinical findings and epidemiology, one claim is that the trained machines will be able to improve “precision medicine” for doctors and patients. The development of new methods in machine learning will play an important role in the project. The project is highly translational in nature: many of the preclinical and clinical research groups in Bergen collaborate with Lundervold and his team, among other CCBIO, particularly the Prostate Cancer Therapy Research Group

We look very much forward to further collaboration with the Medical Imaging and Visualization Centre and Professors Haldorsen and Lundervold!