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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)

Abstract

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.

Keywords

glioma tumor growth model target delineation diffusion tensor imaging radiotherapy 

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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

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