Mathematical modelling of glioma growth: the use of Diffusion Tensor Imaging (DTI) data to predict the anisotropic pathways of cancer invasion.
J Theor Biol
; 323: 25-39, 2013 Apr 21.
Article
en En
| MEDLINE
| ID: mdl-23376578
ABSTRACT
The nonuniform growth of certain forms of cancer can present significant complications for their treatment, a particularly acute problem in gliomas. A number of experimental results have suggested that invasion is facilitated by the directed movement of cells along the aligned neural fibre tracts that form a large component of the white matter. Diffusion tensor imaging (DTI) provides a window for visualising this anisotropy and gaining insight on the potential invasive pathways. In this paper we develop a mesoscopic model for glioma invasion based on the individual migration pathways of invading cells along the fibre tracts. Via scaling we obtain a macroscopic model that allows us to explore the overall growth of a tumour. To connect DTI data to parameters in the macroscopic model we assume that directional guidance along fibre tracts is described by a bimodal von Mises-Fisher distribution (a normal distribution on a unit sphere) and parametrised according to the directionality and degree of anisotropy in the diffusion tensors. We demonstrate the results in a simple model for glioma growth, exploiting both synthetic and genuine DTI datasets to reveal the potentially crucial role of anisotropic structure on invasion.
Texto completo:
1
Base de datos:
MEDLINE
Asunto principal:
Neoplasias Encefálicas
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Imagen de Difusión Tensora
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Glioma
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Modelos Biológicos
Tipo de estudio:
Guideline
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Prognostic_studies
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Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
J Theor Biol
Año:
2013
Tipo del documento:
Article
País de afiliación:
Reino Unido