Research

High-performance computing

Coupling numerical methods and simulation of flow with hgh Schmidt number.

Parallel computation: particular methods.

Tumor growth model

Modeling growth of brain tumor (glioma)

Glioma the most common primary brain tumor Glioma is a type of brain tumor. It is called like that because it arises from glial cells. They are the most common primary brain tumor. This class of tumor has its own particularity. I and my PHD advisor have introduced a class of models dedicated to glioma, adapted both to low grade and multiform glioblastoma. In order to take into account these specificities, we include mainly two effects in the model: on the one hand, the infiltrate behaviors of gliomas, and on the other hand, the impact of brain heterogeneity, of brain anisotropy and of brain geometry on the tumor growth. Our models allow us to evaluate the efficiency of anti-angiogenic drugs and to compare it with the effect of drugs inhibiting the invasion ability of glioma. The models have been implemented in 2D and 3D in actual geometry provided by an atlas.

Parameter estimation (on tumor growth models)

Cancer models has a lot of potential application: better understanding how drugs work, predict tumor growth, optimize therapy design, etc. These model usually involve a lot of parameters. Most of these parameters can only be estimated and a huge variability is observed from one patient to another one. In order to clinical use, an important challenge is to recover these parameters. During my PHD, I have developped some paremeter estimation method. More precisely, it consists in recovering the position of the tumor blood vessel, starting from imaging. The first step is to design a particular vascularization, then we compute the tumor growth with this blood-vessel network by using a model based on partial differential equations and hence we try to recover the initial vascularization solving the inverse problem. We show that the estimated vasculature could be used to efficiently predict the future tumor growth.

CEMRACS 2009 : project STROKE

The purpose is to model and simulate inflammatory process which occurs during ischemic stroke. The dead cells are toxics for their neighborhood. Inflammation helps to eleminate them but can also lead to the death of some other cells. Some numerical simulation are presented to study and discuss the influence of the inflammation during stroke and to propose some possible therapeutic approaches.