Non-operable glioblastoma: proposition of patient-specific forecasting by image-informed poromechanical model

Urcun, S.; Baroli, D.; Rohan, P.-Y.; Skalli, W.; Lubrano, V.; Bordas, S.; Sciume, G.

doi:10.1101/2023.01.10.523475

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bioRxiv · 10.1101/2023.01.10.523475

Non-operable glioblastoma: proposition of patient-specific forecasting by image-informed poromechanical model

Urcun, S.·Baroli, D.·Rohan, P.-Y.·Skalli, W.·Lubrano, V.·Bordas, S.·Sciume, G.

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Abstract

We propose a novel image-informed glioblastoma mathematical model within a reactive multiphase poromechanical framework. Poromechanics offers to model in a coupled manner the interplay between tissue deformation and pressure-driven fluid flows, these phenomena existing simultaneously in cancer disease. The model also relies on two mechano-biological hypotheses responsible for the heterogeneity of the GBM: hypoxia signaling cascade and interaction between extra-cellular matrix and tumor cells. The model belongs to the category of patient-specific image-informed models as it is initialized, calibrated and evaluated by the means of patient imaging data. The model is calibrated with patient data after 6 cycles of concomitant radiotherapy chemotherapy and shows good agreement with treatment response 3 months after chemotherapy maintenance. Sensitivity of the solution to parameters and to boundary conditions is provided. As this work is only a first step of the inclusion of poromechanical framework in image-informed glioblastoma mathematical models, leads of improvement are provided in the conclusion.

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Urcun, S., Baroli, D., Rohan, P.-Y., Skalli, W., Lubrano, V., Bordas, S., Sciume, G.. 2023-01-12. Non-operable glioblastoma: proposition of patient-specific forecasting by image-informed poromechanical model. https://doi.org/10.1101/2023.01.10.523475

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