Mathematical modeling of human glioma growth based on brain topological structures: study of two clinical cases

C. SUAREZ; F. MAGLIETTI; M. COLONNA; K. BREITBURD; G. MARSHALL

PLOS ONE

PUBLIC LIBRARY SCIENCE

Lugar: San Francisco; Año: 2012 vol. 7 p. 1 - 12

1932-6203

Gliomas are the most common primary brain tumors and yet almost incurable due mainly to theirgreat invasion capability, many times underestimated by present imaging techniques. This represents a challenge to present clinical oncology. Here, we introduce a three-dimensional (3D) space and time, reaction-diusion mathematical model whose space domain distinguish dierent brain topological struc-tures, that aims to improve tumor spreading capability denition. The model is solved numerically usingpatient-specic parametrization, nite dierences and standard relaxation techniques. The spatial do-main consists in a series of digitized images from brain slices covering the whole human brain. TheTalairach atlas, incorporated in our model, describes brain structures at dierent levels. Simulationsconsider an initial state only with cellular proliferation (benign tumor) and an advanced state wherecellular inltration begins (malignization). The inclusion of the Brodmann areas allows prediction ofthe brain functions that are being aected during tumor evolution and the estimation of their correlated symptoms. The survival time is estimated on the basis of tumor size and location. The model was associated to two clinical cases predicting, in the rst one, that real inltrative areas are underestimated by current diagnostic imaging. In the second clinical case, tumor spreading predictions were shown to be more accurate than those from previous models from literature. Our model suggests that the inclusion of dierential migration based on topological brain structures in glioma growth is another step towards a better prediction of the extension and shape of tumor inltration at the moment of surgical or radiosur-gical target denition. Also, the addition of physiological/psychological considerations to the previous anatomical glioma growth model will surely provide a better and integral understanding of the patient disease at the moment of deciding therapeutic options, taking into account not only survival but also life quality.