Date of Publication :31st December 2017

Abstract: In this paper, we propose a proof of concept for the automatic planning of personalized radiotherapy for brain tumours. A computational model of brain tumor growth is combined with an exponential cell survival model to describe the effect of radiotherapy. The model is personalized to the magnetic resonance images (MRIs) of a given patient. It takes into account the uncertainty in the model parameters, together with the uncertainty in the MRI segmentation. The computed probability distribution over tumor cell densities, together with the cell survival model, is used to define the prescription dose distribution, which is the basis for subsequent Intensity Modulated Radiation Therapy (IMRT) planning. Depending on the clinical data available first, we include the uncertainty in the segmentation process. We show how our method allows the user to compute a patient specific radiotherapy planning conformal to the tumor growth. The presented approach and its proof of concept may help in the future to better target the tumor and spare organs at risk

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