An image-informed Cahn–Hilliard Keller–Segel multiphase field model for tumor growth with angiogenesis

نویسندگان

چکیده

In this paper we develop a new four-phase tumor growth model with angiogenesis, derived from diffuse-interface mixture composed by viable component, necrotic liquid component and an angiogenetic coupled two massless chemicals representing perfectly diluted nutrient factor. This is variational principles complying the second law of thermodynamics in isothermal situations, starting biological constitutive assumptions on cells adhesion properties infiltrative mechanics tumor-induced vasculature tissues, takes form degenerate Cahn–Hilliard Keller–Segel system for components reaction diffusion equations chemicals. The informed neuroimaging data, which give informations about patient-specific brain geometry tissues microstructure, distribution different components, white matter fiber orientations density. We describe specific robust preprocessing steps to extract quantitative data construct computational platform solve basis. further introduce finite element approximation preserve qualitative continuous solutions. Finally, show simulation results evolution patient affected GlioBlastoma Multiforme, considering test cases before surgery, corresponding situations high or low supply inside tumor, case after surgery. perform sensitivity based parameters estimation longitudinal acquired at time points that our correctly predicts overall extension intensity process, paving way assisting clinicians properly assessing therapy outcomes designing optimal therapeutic schedules.

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ژورنال

عنوان ژورنال: Applied Mathematics and Computation

سال: 2023

ISSN: ['1873-5649', '0096-3003']

DOI: https://doi.org/10.1016/j.amc.2023.127834