Turid Torheim

Breast cancer tumours show heterogeneity at all levels: as genomic variation, tissue heterogeneity and heterogeneous appearance in radiological images. Data at all these levels are available, but so far there have been no integrative studies where all levels of heterogeneity are combined to gain comprehensive understanding of the disease. My project aims to fill this major gap by describing, comparing and correlating breast cancer heterogeneity at multiple levels.


since 04/2016
Postdoctoral research at Cancer Research UK Cambridge Research Institute

02/2012 - 04/2016
PhD student at the Department of Mathematical Sciences and Technology, Norwegian University of Life Sciences, Norway.
Main advisor: Prof. Cecilia Marie Futsaether


Ph.D in Computational Biology
Norwegian University of Life Sciences

M.Sc. in Mathematical, Physical and Computational Sciences
Norwegian University of Life Sciences

B.Sc. in Natural Sciences (Physics)
Norwegian University of Life Sciences

Turid Torheim

Turid Torheim
University of Cambridge
CRUK Cambridge Institute
Li Ka Shing Centre
Robinson Way
Cambridge, CB2 0RE, UK
e: first.last@cruk.cam.ac.uk
p: +44 (0) 1223 40 4318

CRUK logo Cambridge University


  1. Intratumoral Heterogeneity of Tumor Infiltration of Glioblastoma Revealed by Joint Histogram Analysis of Diffusion Tensor Imaging
    C Li, S Wang, J-L Yan, RJ Piper, H Liu, T Torheim, H Kim, NR Boonzaier, R Sinha, T Matys, F Markowetz, SJ Price
  2. Low Perfusion Compartments in Glioblastoma Quantified by Advanced Magnetic Resonance Imaging: Correlation with Patient Survival
    C Li, J-L Yan, T Torheim, MA McLean, NR Boonzaier, Y Huang, BRJ Van Dijken, T Matys, F Markowetz, SJ Price
  3. In Quest of the Alanine R3 Radical: Multivariate EPR Spectral Analyses of X-Irradiated Alanine in the Solid State
    EO Jaastad, T Torheim, KM Villeneuve, K Kvaal, EO Hole, E Sagstuen, E Malinen, CM Futsaether
    Journal of Physical Chemistry A (2017)
    PMID:28829916 | doi:10.1021/acs.jpca.7b06447
  4. Haralick texture features from apparent diffusion coefficient (ADC) MRI images depend on imaging and pre-processing parameters
    P Brynolfsson, D Nilsson, T Torheim, T Asklund, C Thellenberg, J Trygg, T Nyholm, A Garpebring
    Scientific Reports (2017)
    PMID:28642480 | doi:10.1038/s41598-017-04151-4
  5. Autodelineation of cervical cancers using multiparametric MRI and machine learning
    T Torheim, E Malinen, KH Hole, KV Lund, UG Indahl, H Lyng, K Kvaal, CM Futsaether
    Acta Oncologica (2017)
    PMID:28464746 | doi:10.1080/0284186X.2017.1285499
  6. Dynamic 2-deoxy-2-[18F]fluoro-d-glucose positron emission tomography for chemotherapy response monitoring of breast cancer xenografts
    A Kristian, JE Holtedahl, T Torheim, CM Futsaether, E Hernes, O Engebraaten, G Maelandsmo, E Malinen
    Molecular Imaging and Biology (2017)
    PMID:27541026 | doi:10.1007/s11307-016-0998-x
  7. Cluster analysis of dynamic contrast enhanced MRI reveals tumour subregions related to locoregional relapse for cervical cancer patients
    T Torheim, AR Groendahl, EKF Andersen, K Kvaal, H Lyng, E Malinen, CM Futsaether
    Acta Oncologica (2016)
    PMID:27564398 | doi: 10.1080/0284186X.2016.1189091
  8. Classification of dynamic contrast enhanced MR images of cervical cancer using texture analysis and support vector machines
    T Torheim, E Malinen, K Kvaal, H Lyng, UG Indahl, EKF Andersen, CM Futsaether
    IEEE Transactions on Medical Imaging (2014)
    PMID:24802069 | doi: 10.1109/TMI.2014.2321024
  9. Surface waves from bottom vibrations in uniform open-channel flow
    PA Tyvand T Torheim
    European Journal of Mechanics. B, Fluids (2012)
    doi: 10.1016/j.euromechflu.2012.04.006