Tone Frost Bathen
Background and activities
As head of the The MR Cancer Group, my main research interests are focused towards personalised medicine and studies of functional and metabolic properties of cancer using magnetic resonance imaging (MRI) and spectroscopy (MRS). By developing, optimising and applying advanced MR (in combination with other molecular methods) to characterize cancer, our goal is to establish better diagnostic tools for stratification of patients to treatment and treatment monitoring. Current research activities mainly focus on breast and prostate cancer, enabled by a close collaboration with clinicians at the St. Olavs University Hospital in Trondheim. Although clinical research has high priority, a broad spectrum of systems for cancer studies provides translational research, covering ex vivo as well as in vivo MR imaging and spectroscopy of cancer cells and laboratory animals. We also maintain several large biobanks of human tissue and biofluid samples. The research group is also involved in biomedical research related to cardiac heart disease, preeclampsia and testing of new contrast agents.
Publications registered in Pubmed:
https://www.ncbi.nlm.nih.gov/pubmed/?term=Bathen+TF
Courses
- RAT3001 - Introduction to Medical Imaging Technology
- RAT6000 - Introduction to Medical Imaging Technology
- MEDT8010 - Metabolomics- Methods and Applications
- KLMED8014 - Research methods in radiology and nuclear medicine
- RAT3002 - Image Processing and Automated Classification
- RAT3104 - Advanced MR Physics: General Methods
Scientific, academic and artistic work
A selection of recent journal publications, artistic productions, books, including book and report excerpts. See all publications in the database
2021
- (2021) Spatial differentiation of metabolism in prostate cancer tissue by MALDI-TOF MSI. Cancer & Metabolism.
- (2021) Effects of echo time on IVIM quantifications of locally advanced breast cancer in clinical diffusion-weighted MRI at 3 T. NMR in Biomedicine.
- (2021) Classification and biomarker identification of prostate tissue from TRAMP mice with hyperpolarized 13C-SIRA. Talanta: The International Journal of Pure and Applied Analytical Chemistry. vol. 235.
- (2021) Understanding diffusion-weighted MRI analysis: Repeatability and performance of diffusion models in a benign breast lesion cohort. NMR in Biomedicine. vol. 34 (7).
- (2021) Cross-sectional and prospective associations between aerobic fitness and lipoprotein particle profile in a cohort of Norwegian schoolchildren. Atherosclerosis. vol. 321.
- (2021) Multiparametric Prostate MRI in Biopsy-Naïve Men: A Prospective Evaluation of Performance and Biopsy Strategies. Frontiers in Oncology. vol. 11.
- (2021) Utility of T2-weighted MRI texture analysis in assessment of peripheral zone prostate cancer aggressiveness: a single-arm, multicenter study. Scientific Reports. vol. 11:2085.
- (2021) Characterization of the diffusion signal of breast tissues using multi-exponential models. Magnetic Resonance in Medicine.
- (2021) The reproducibility of deep learning-based segmentation of the prostate gland and zones on t2-weighted mr images. Diagnostics (Basel). vol. 11 (9).
- (2021) Exploring the diagnostic potential of adding T2 dependence in diffusion-weighted MR imaging of the prostate. PLOS ONE. vol. 16 (5).
2020
- (2020) Simultaneous detection of zinc and its pathway metabolites using MALDI MS imaging of prostate tissue. Analytical Chemistry. vol. 92 (4).
- (2020) Discrimination of Breast Cancer from Healthy Breast Tissue Using a Three-component Diffusion-weighted MRI Model. Clinical Cancer Research. vol. 27.
- (2020) Germline HOXB13 mutations p.G84E and p.R217C do not confer an increased breast cancer risk. Scientific Reports. vol. 10:9688 (1).
- (2020) Concentration and Distribution of Naphthenic Acids in the Produced Water from Offshore Norwegian North Sea Oilfields. Environmental Science and Technology. vol. 54 (5).
- (2020) Detection of recurrent prostate cancer with 18F-Fluciclovine PET/MRI. Frontiers in Oncology. vol. 10:582092.
- (2020) Automated reference tissue normalization of T2-weighted MR images of the prostate using object recognition. Magnetic Resonance Materials in Physics, Biology and Medicine. vol. 34 (2).
- (2020) A quality control system for automated prostate segmentation on T2-weighted MRI. Diagnostics (Basel). vol. 10 (9).
- (2020) Modeling the diffusion-weighted imaging signal for breast lesions in the b = 200 to 3000 s/mm 2 range: quality of fit and classification accuracy for different representations. Magnetic Resonance in Medicine. vol. 84 (2).
2019
- (2019) Simultaneous detection of the cancer biomarkers zinc and citrate in prostate cancer tissue using mass spectrometry imaging. European Urology. Supplement. vol. 18 (8).
- (2019) Semi-automatic segmentation from intrinsically-registered 18F-FDG-PET/MRI for treatment response assessment in a breast cancer cohort: comparison to manual DCE-MRI. Magnetic Resonance Materials in Physics, Biology and Medicine. vol. 33.