Use of Diffusion Tensor Images in Glioma Growth Modeling for Radiotherapy Target Delineation

  • Florian Dittmann
  • Björn Menze
  • Ender Konukoglu
  • Jan Unkelbach
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8159)


In radiotherapy of gliomas, a precise definition of the treatment volume is problematic, because current imaging modalities reveal only the central part of the tumor with a high cellular density, but fail to detect all regions of microscopic tumor cell spread in the adjacent brain parenchyma. Mathematical models can be used to integrate known growth characteristics of gliomas into the target delineation process. In this paper, we demonstrate the use of diffusion tensor imaging (DTI) for simulating anisotropic cell migration in a glioma growth model that is based on the Fisher-Kolmogorov equation. For a clinical application of the model, it is crucial to develop a detailed understanding of its behavior, capabilities, and limitations. For that purpose, we perform a retrospective analysis of glioblastoma patients treated at our institution. We analyze the impact of diffusion anisotropy on model-derived target volumes, and interpret the results in the context of the underlying images. It was found that, depending on the location of the tumor relative to major fiber tracts, DTI can have significant influence on the shape of the radiotherapy target volume.


glioma tumor growth model target delineation diffusion tensor imaging radiotherapy 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Becker, K.P., Yu, J.: Status quo–standard-of-care medical and radiation therapy for glioblastoma. Cancer J. 18(1), 12–19 (2012)CrossRefGoogle Scholar
  2. 2.
    Coons, S.: Anatomy and growth patterns of diffuse gliomas. In: Berger, M., Wilson, C. (eds.) The Gliomas, pp. 210–225. W.B. Saunders Company, Philadelphia (1999)Google Scholar
  3. 3.
    Matsukado, Y., MacCarty, C., Kernohan, J., et al.: The growth of glioblastoma multiforme (astrocytomas, grades 3 and 4) in neurosurgical practice. Journal of Neurosurgery 18, 636 (1961)CrossRefGoogle Scholar
  4. 4.
    Harpold, H.L.P., Alvord Jr, E.C., Swanson, K.R.: The evolution of mathematical modeling of glioma proliferation and invasion. J. Neuropathol. Exp. Neurol. 66(1), 1–9 (2007)CrossRefGoogle Scholar
  5. 5.
    Konukoglu, E., Clatz, O., Bondiau, P.Y., Delingette, H., Ayache, N.: Extrapolating glioma invasion margin in brain magnetic resonance images: suggesting new irradiation margins. Med. Image Anal. 14(2), 111–125 (2010)CrossRefGoogle Scholar
  6. 6.
    Menze, B.H., Van Leemput, K., Lashkari, D., Weber, M.-A., Ayache, N., Golland, P.: A generative model for brain tumor segmentation in multi-modal images. In: Jiang, T., Navab, N., Pluim, J.P.W., Viergever, M.A. (eds.) MICCAI 2010, Part II. LNCS, vol. 6362, pp. 151–159. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  7. 7.
    Jbabdi, S., Mandonnet, E., Duffau, H., Capelle, L., Swanson, K.R., Pélégrini-Issac, M., Guillevin, R., Benali, H.: Simulation of anisotropic growth of low-grade gliomas using diffusion tensor imaging. Magn. Reson. Med. 54(3), 616–624 (2005)CrossRefGoogle Scholar
  8. 8.
    Konukoglu, E., Sermesant, M., Clatz, O., Peyrat, J.-M., Delingette, H., Ayache, N.: A recursive anisotropic fast marching approach to reaction diffusion equation: application to tumor growth modeling. In: Karssemeijer, N., Lelieveldt, B. (eds.) IPMI 2007. LNCS, vol. 4584, pp. 687–699. Springer, Heidelberg (2007)CrossRefGoogle Scholar
  9. 9.
    Cobzas, D., Mosayebi, P., Murtha, A., Jagersand, M.: Tumor invasion margin on the Riemannian space of brain fibers. In: Yang, G.-Z., Hawkes, D., Rueckert, D., Noble, A., Taylor, C. (eds.) MICCAI 2009, Part II. LNCS, vol. 5762, pp. 531–539. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  10. 10.
    Unkelbach, J., Menze, B., Motamedi, A., Dittmann, F., Konukoglu, E., Ayache, N., Shih, H.: Glioblastoma growth modeling for radiotherapy target delineation. In: Proc. MICCAI Workshop on IGRT (2012)Google Scholar
  11. 11.
    Grier, J.T., Batchelor, T.: Low-grade gliomas in adults. The Oncologist 11(6), 681–693 (2006)CrossRefGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2013

Authors and Affiliations

  • Florian Dittmann
    • 1
  • Björn Menze
    • 2
  • Ender Konukoglu
    • 1
  • Jan Unkelbach
    • 1
  1. 1.Massachusetts General HospitalBostonUSA
  2. 2.Computer Vision LaboratoryETH ZurichSwitzerland

Personalised recommendations