Capturing variability of tumor-induced mass-effect in glioma growth models

Abler, Daniel; Büchler, Philippe; Rockne, Russell C. (22 July 2019). Capturing variability of tumor-induced mass-effect in glioma growth models (Unpublished). In: Annual Meeting of the Society for Mathematical Biology. Montreal, Canada. July 21-26 2019.

Glioblastoma (GBM) is the most frequent malignant brain tumor in adults. Its in-vasive growth is frequently modeled as reaction diffusion process that results in growth phenotypes classified on a spectrum between nodal and diffuse growth. GBM patients also present with varying amounts of mass-effect, tumor-induced tissue deformation and associated mechanical stresses in the tissue. Elevated solid stress in brain tumors is linked to neuronal loss and neurological dysfunction, affects the tumor environment and may contribute to tumor progression.

This suggests that the propensity of an individual tumor to displace healthy tissue can provide information about the tumor micro-environment and might be of predictive value for treatment and outcome. However, tumors of similar imaging volumes have been observed to give rise to different amounts of tumor mass-effect, possibly resulting in distinct mechanical stress distributions and magnitudes.
An open question is whether this variability in tumor mass-effect can be explained by common growth characteristics, such as the tumor’s proliferative and invasive potential.

We investigate this question using a spatial model of mechanically-coupled tumor growth that includes the tumor’s displacive potential as distinct growth characteristic.Invasive glioma growth is represented as a reaction-diffusion process. To simulate the tissue-displacing mass-effect, we model the growth domain as an elastic continuum in which the actual deformation of a tissue element is given by the combination of growth-induced strains and strains associated with the elastic response of the tissue. The model assumes a linear constitutive relation between mechanical stress and strain, and postulates a linear isotropic coupling between tumor cell concentration and growth-induced strain to represent the displacive potential of the tumor.

We present evidence from quantitative analysis of tumor mass-effect on clinical imaging data, and discuss findings from parametric studies of our mechanically-coupled tumor growth model.

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