Research
Tumor growth modelling
| The subject of my PhD thesis is the following: the modelling and analysis of the heterogeneous behavior of some tumors during treatment resistances. My work focused on liver metastases from gastrointestinal cancer, a cancer in which multiple resistance is frequently observed. In collaboration with the CHU (University Hospital Center) of Bordeaux, the first step was to understand the mechanisms governing cancer development and those linked to the acquisition of medical images. Then, a macroscopic PDE model was built. This describes phenomena involved in the growth of a liver metastasis, its interaction with the vascularization as well as the effect of two kinds of treatment. |
Figure 1: Evolution of a liver metastasis on a series of CT-scans.
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Figure 2: Area evolution of the metastasis presented in the Figure 1.
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The model is able to reproduce, for several years for each patient, the metastasis evolution in terms of area (see Figure 2) as well as structure (see Figure 3). Thus, the importance of the inclusion of tumor heterogeneity in the evaluation of treatment efficiency is emphasised. To extract more information on tumor heterogeneity, I have developed criteria to quantify it. This quantifier applies to all kind of grey scale images. It has shown good results on the clinical data that we have, as well as on synthetis images arising from our numerical simulations. |
Figure 3: Spatial evolution of the metastasis given by the numerical simulation.
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