Abstract
Glioma is a broad class of brain and spinal cord tumors arising from glia cells, which are the main brain cells that can develop into neoplasms. They are highly invasive and lead to irregular tumor margins which are not precisely identifiable by medical imaging, thus rendering a precise enough resection very difficult. The understanding of glioma spread patterns is hence essential for both radiological therapy as well as surgical treatment. In this paper we propose a multiscale model for glioma growth including interactions of the cells with the underlying tissue network, along with proliferative effects. Our current accounting for two subpopulations of cells to accomodate proliferation according to the go-or-grow dichtomoty is an extension of the setting in [16]. As in that paper, we assume that cancer cells use neuronal fiber tracts as invasive pathways. Hence, the individual structure of brain tissue seems to be decisive for the tumor spread. Diffusion tensor imaging (DTI) is able to provide such information, thus opening the way for patient specific modeling of glioma invasion. Starting from a multiscale model involving subcellular (microscopic) and individual (mesoscale) cell dynamics, we perform a parabolic scaling to obtain an approximating reaction-diffusion-transport equation on the macroscale of the tumor cell population. Numerical simulations based on DTI data are carried out in order to assess the performance of our modeling approach.
Highlights
Gliomas are malignant primary tumors in the human brain with a poor prognosis [37]
In this work we focus on the interaction of tumor cells with the underlying tissue and on proliferative effects
For modeling tumor growth we rely on the go-or-grow hypothesis, which states that cancer cells can either move or proliferate [15, 21]
Summary
Gliomas are malignant primary tumors in the human brain with a poor prognosis [37]. The common treatment approach involves surgical resection, usually followed by radiotherapy. Diffusion tensor imaging (DTI) is one of the most common radiological methods in the detection of brain tumors [32]. Modern imaging methods rely on evaluating the diffusion behaviour of water molecules within structured tissue. This reveals the orientation and anisotropy (meaning the extent to which fibers align together) of neuronal fibers making up white matter tracts. This information is interesting for surgical and radiation therapy. We assume that cancer cells use neuronal fibre tracts as invasive pathways, which makes the individual brain structure interesting for patient specific modelling of glioma.
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