Glioblastoma (GBM) is the most frequent malignant brain tumour in adults. Its growth is characterized by infiltration of surrounding healthy tissue, and the formation of a necrotic core. GBM presents with varying degree of mass-effect which results in healthy-tissue deformation, midline shift or herniation. Biomechanical forces, such as those resulting from displacive tumour growth, shape the tumour environment, contribute to tumour progression and may affect treatment response and outcome.To investigate the role of tumour mass-effect for tumour evolution, we have previously developed a mechanically-coupled reaction-diffusion model that captures three dominant aspects of macroscopic GBM growth: (a) tumour cell proliferation, (b) the diffuse invasion of the growing tumour into surrounding healthy tissue, and (c) the resulting mass effect.Here we present an implementation of this model in FENICS and first steps towards an image-based optimization approach, based on dolphin-adjoint, to estimate patient-specific parameters from clinical magnetic-resonance imaging (MRI).
