https://sam.ensam.eu:443 The DSpace digital repository system captures, stores, indexes, preserves, and distributes digital research material. Fri, 05 Jun 2026 22:43:55 GMT 2026-06-05T22:43:55Z http://hdl.handle.net/10985/25443 Single and bi-compartment poro-elastic model of perfused biological soft tissues: FEniCSx implementation and tutorial LAVIGNE, Thomas; URCUN, Stéphane; ROHAN, Pierre-Yves; SCIUME, Giuseppe; BAROLI, Davide; BORDAS, Stéphane Pierre Alain Soft biological tissues demonstrate strong time-dependent and strain-rate mechanical behavior, arising from their intrinsic visco-elasticity and fluid–solid interactions. The time-dependent mechanical properties of soft tissues influence their physiological functions and are related to several pathological processes. Poro-elastic modeling represents a promising approach because it allows the integration of multiscale/multiphysics data to probe biologically relevant phenomena at a smaller scale and embeds the relevant mechanisms at the larger scale. The implementation of multiphase flow poro-elastic models however is a complex undertaking, requiring extensive knowledge. The open-source software FEniCSx Project provides a novel tool for the automated solution of partial differential equations by the finite element method. This paper aims to provide the required tools to model the mixed formulation of poro-elasticity, from the theory to the implementation, within FEniCSx. Several benchmark cases are studied. A column under confined compression conditions is compared to the Terzaghi analytical solution, using the L2-norm. An implementation of poro-hyper-elasticity is proposed. A bi-compartment column is compared to previously published results (Cast3m implementation). For all cases, accurate results are obtained in terms of a normalized Root Mean Square Error (RMSE). Furthermore, the FEniCSx computation is found three times faster than the legacy FEniCS one. The benefits of parallel computation are also highlighted. This research was funded in whole, or in part, by the Luxembourg National Research Fund (FNR), grant reference No. 17013182. Mon, 01 May 2023 00:00:00 GMT http://hdl.handle.net/10985/25443 2023-05-01T00:00:00Z LAVIGNE, Thomas URCUN, Stéphane ROHAN, Pierre-Yves SCIUME, Giuseppe BAROLI, Davide BORDAS, Stéphane Pierre Alain Soft biological tissues demonstrate strong time-dependent and strain-rate mechanical behavior, arising from their intrinsic visco-elasticity and fluid–solid interactions. The time-dependent mechanical properties of soft tissues influence their physiological functions and are related to several pathological processes. Poro-elastic modeling represents a promising approach because it allows the integration of multiscale/multiphysics data to probe biologically relevant phenomena at a smaller scale and embeds the relevant mechanisms at the larger scale. The implementation of multiphase flow poro-elastic models however is a complex undertaking, requiring extensive knowledge. The open-source software FEniCSx Project provides a novel tool for the automated solution of partial differential equations by the finite element method. This paper aims to provide the required tools to model the mixed formulation of poro-elasticity, from the theory to the implementation, within FEniCSx. Several benchmark cases are studied. A column under confined compression conditions is compared to the Terzaghi analytical solution, using the L2-norm. An implementation of poro-hyper-elasticity is proposed. A bi-compartment column is compared to previously published results (Cast3m implementation). For all cases, accurate results are obtained in terms of a normalized Root Mean Square Error (RMSE). Furthermore, the FEniCSx computation is found three times faster than the legacy FEniCS one. The benefits of parallel computation are also highlighted. http://hdl.handle.net/10985/25444 Non-operable glioblastoma: Proposition of patient-specific forecasting by image-informed poromechanical model URCUN, Stéphane; BAROLI, Davide; ROHAN, Pierre-Yves; SKALLI, Wafa; LUBRANO, Vincent; BORDAS, Stéphane Pierre Alain; SCIUME, Giuseppe 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. Statement of significance: In this study, we employ mechanics of reactive porous media to effectively model the dynamic progression of a glioblastoma. Traditionally, glioblastoma tumors are surgically removed a few weeks post-diagnosis. To address this, we focus on a non-operable clinical scenario which allows us to have sufficient time points for the calibration and subsequent validation of our mathematical model. It is paramount to underscore that the tumor’s evolution is significantly influenced by chemotherapy and radiotherapy. These therapeutic effects find incorporation within our mathematical framework. Notably, the approach we present is distinctive for two key reasons: Firstly, the mathematical model inherently captures the complex multiphase and hierarchical nature of brain tissue. Secondly, our constitutive laws factor in the ever-changing properties of cells and tissues, mirroring the local phenotypic alterations observed within the tumor. This work constitutes an initial stride towards systematically integrating multiphase poromechanics into patient-specific glioblastoma growth modeling. As we look ahead, we acknowledge areas for potential enhancement in pursuit of advancing this promising direction. Work funding with a grant fromLuxembourg National Research Fund (FNR) grant number INTER/ANR/21/16399490 and from Réseau Santé des Arts et Métiers. Wed, 01 Mar 2023 00:00:00 GMT http://hdl.handle.net/10985/25444 2023-03-01T00:00:00Z URCUN, Stéphane BAROLI, Davide ROHAN, Pierre-Yves SKALLI, Wafa LUBRANO, Vincent BORDAS, Stéphane Pierre Alain SCIUME, Giuseppe 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. Statement of significance: In this study, we employ mechanics of reactive porous media to effectively model the dynamic progression of a glioblastoma. Traditionally, glioblastoma tumors are surgically removed a few weeks post-diagnosis. To address this, we focus on a non-operable clinical scenario which allows us to have sufficient time points for the calibration and subsequent validation of our mathematical model. It is paramount to underscore that the tumor’s evolution is significantly influenced by chemotherapy and radiotherapy. These therapeutic effects find incorporation within our mathematical framework. Notably, the approach we present is distinctive for two key reasons: Firstly, the mathematical model inherently captures the complex multiphase and hierarchical nature of brain tissue. Secondly, our constitutive laws factor in the ever-changing properties of cells and tissues, mirroring the local phenotypic alterations observed within the tumor. This work constitutes an initial stride towards systematically integrating multiphase poromechanics into patient-specific glioblastoma growth modeling. As we look ahead, we acknowledge areas for potential enhancement in pursuit of advancing this promising direction. http://hdl.handle.net/10985/21321 Cortex tissue relaxation and slow to medium load rates dependency can be captured by a two-phase flow poroelastic model URCUN, Stéphane; SCIUMÈ, Giuseppe; BORDAS, Stéphane P.A.; ROHAN, Pierre-Yves This paper investigates the complex time-dependent behavior of cortex tissue, under adiabatic condition, using a two-phase flow poroelastic model. Motivated by experiments and Biot’s consolidation theory, we tackle time-dependent uniaxial loading, confined and unconfined, with various geometries and loading rates from 1 µm/s to 100 µm/s. The cortex tissue is modeled as the porous solid saturated by two immiscible fluids, with dynamic viscosities separated by four orders, resulting in two different characteristic times. These are respectively associated to interstitial fluid and glial cells. The partial differential equations system is discretised in space by the finite element method and in time by Euler-implicit scheme. The solution is computed using a monolithic scheme within the open-source computational framework FEniCS. The parameters calibration is based on Sobol sensitivity analysis, which divides them into two groups: the tissue specific group, whose parameters represent general properties, and sample specific group, whose parameters have greater variations. Our results show that the experimental curves can be reproduced without the need to re-sort to viscous solid effects, by adding an additional fluid phase. Through this process, we aim to present multiphase poromechanics as a promising way to a unified brain tissue modeling framework in a variety of settings. Fri, 01 Jan 2021 00:00:00 GMT http://hdl.handle.net/10985/21321 2021-01-01T00:00:00Z URCUN, Stéphane SCIUMÈ, Giuseppe BORDAS, Stéphane P.A. ROHAN, Pierre-Yves This paper investigates the complex time-dependent behavior of cortex tissue, under adiabatic condition, using a two-phase flow poroelastic model. Motivated by experiments and Biot’s consolidation theory, we tackle time-dependent uniaxial loading, confined and unconfined, with various geometries and loading rates from 1 µm/s to 100 µm/s. The cortex tissue is modeled as the porous solid saturated by two immiscible fluids, with dynamic viscosities separated by four orders, resulting in two different characteristic times. These are respectively associated to interstitial fluid and glial cells. The partial differential equations system is discretised in space by the finite element method and in time by Euler-implicit scheme. The solution is computed using a monolithic scheme within the open-source computational framework FEniCS. The parameters calibration is based on Sobol sensitivity analysis, which divides them into two groups: the tissue specific group, whose parameters represent general properties, and sample specific group, whose parameters have greater variations. Our results show that the experimental curves can be reproduced without the need to re-sort to viscous solid effects, by adding an additional fluid phase. Through this process, we aim to present multiphase poromechanics as a promising way to a unified brain tissue modeling framework in a variety of settings. http://hdl.handle.net/10985/25521 Oncology and mechanics: Landmark studies and promising clinical applications URCUN, Stéphane; LORENZO, Guillermo; BAROLI, Davide; ROHAN, Pierre-Yves; SCIUME, Giuseppe; SKALLI, Wafa; LUBRANO, Vincent; BORDAS, Stéphane Pierre Alain Clinical management of cancer has continuously evolved for several decades. Biochemical, molecular, and genomics approaches have brought and still bring numerous insights into cancerous diseases. It is now accepted that some phenomena, allowed by favorable biological conditions, emerge via mechanical signaling at the cellular scale and via mechanical forces at the macroscale. Mechanical phenomena in cancer have been studied in-depth over the last decades, and their clinical applications are starting to be understood. If numerous models and experimental setups have been proposed, only a few have led to clinical applications. The objective of this contribution is to review a large scope of mechanical findings which have consequences on the clinical management of cancer. This review is mainly addressed to doctoral candidates in mechanics and applied mathematics who are faced with the challenge of the mechanics-based modeling of cancer with the aim of clinical applications. We show that the collaboration of the biological and mechanical approaches has led to promising advances in terms of modeling, experimental design, and therapeutic targets. Additionally, a specific focus is placed on imaging-informed mechanics-based models, which we believe can further the development of new therapeutic targets and the advent of personalized medicine. We study in detail several successful workflows on patient-specific targeted therapies based on mechanistic modeling. Wed, 01 Jun 2022 00:00:00 GMT http://hdl.handle.net/10985/25521 2022-06-01T00:00:00Z URCUN, Stéphane LORENZO, Guillermo BAROLI, Davide ROHAN, Pierre-Yves SCIUME, Giuseppe SKALLI, Wafa LUBRANO, Vincent BORDAS, Stéphane Pierre Alain Clinical management of cancer has continuously evolved for several decades. Biochemical, molecular, and genomics approaches have brought and still bring numerous insights into cancerous diseases. It is now accepted that some phenomena, allowed by favorable biological conditions, emerge via mechanical signaling at the cellular scale and via mechanical forces at the macroscale. Mechanical phenomena in cancer have been studied in-depth over the last decades, and their clinical applications are starting to be understood. If numerous models and experimental setups have been proposed, only a few have led to clinical applications. The objective of this contribution is to review a large scope of mechanical findings which have consequences on the clinical management of cancer. This review is mainly addressed to doctoral candidates in mechanics and applied mathematics who are faced with the challenge of the mechanics-based modeling of cancer with the aim of clinical applications. We show that the collaboration of the biological and mechanical approaches has led to promising advances in terms of modeling, experimental design, and therapeutic targets. Additionally, a specific focus is placed on imaging-informed mechanics-based models, which we believe can further the development of new therapeutic targets and the advent of personalized medicine. We study in detail several successful workflows on patient-specific targeted therapies based on mechanistic modeling. http://hdl.handle.net/10985/21521 Numerical investigation of the time-dependent stress–strain mechanical behaviour of skeletal muscle tissue in the context of pressure ulcer prevention LAVIGNE, T.; SCIUMÈ, Giuseppe; LAPORTE, Sébastien; PILLET, Helene; URCUN, Stéphane; WHEATLEY, B.; ROHAN, Pierre-Yves Background Pressure-induced tissue strain is one major pathway for Pressure Ulcer development and, especially, Deep Tissue Injury. Biomechanical investigation of the time-dependent stress–strain mechanical behaviour of skeletal muscle tissue is therefore essential. In the literature, a viscoelastic formulation is generally assumed for the experimental characterization of skeletal muscles, with the limitation that the underlying physical mechanisms that give rise to the time dependent stress–strain behaviour are not known. The objective of this study is to explore the capability of poroelasticity to reproduce the apparent viscoelastic behaviour of passive muscle tissue under confined compression. Methods Experimental stress-relaxation response of 31 cylindrical porcine samples tested under fast and slow confined compression by Vaidya and collaborators were used. An axisymmetric Finite Element model was developed in ABAQUS and, for each sample a one-to-one inverse analysis was performed to calibrate the specimen-specific constitutive parameters, namely, the drained Young's modulus, the void ratio, hydraulic permeability, the Poisson's ratio, the solid grain's and fluid's bulk moduli. Findings The peak stress and consolidation were recovered for most of the samples (N = 25) by the poroelastic model (normalised root-mean-square error ≤0.03 for fast and slow confined compression conditions). Interpretation The strength of the proposed model is its fewer number of variables (N = 6 for the proposed poroelastic model versus N = 18 for the viscohyperelastic model proposed by Vaidya and collaborators). The incorporation of poroelasticity to clinical models of Pessure Ulcer formation could lead to more precise and mechanistic explorations of soft tissue injury risk factors. Soumission associée au prix jeune chercheur 2021 de la Société de Biomécanique Sat, 01 Jan 2022 00:00:00 GMT http://hdl.handle.net/10985/21521 2022-01-01T00:00:00Z LAVIGNE, T. SCIUMÈ, Giuseppe LAPORTE, Sébastien PILLET, Helene URCUN, Stéphane WHEATLEY, B. ROHAN, Pierre-Yves Background Pressure-induced tissue strain is one major pathway for Pressure Ulcer development and, especially, Deep Tissue Injury. Biomechanical investigation of the time-dependent stress–strain mechanical behaviour of skeletal muscle tissue is therefore essential. In the literature, a viscoelastic formulation is generally assumed for the experimental characterization of skeletal muscles, with the limitation that the underlying physical mechanisms that give rise to the time dependent stress–strain behaviour are not known. The objective of this study is to explore the capability of poroelasticity to reproduce the apparent viscoelastic behaviour of passive muscle tissue under confined compression. Methods Experimental stress-relaxation response of 31 cylindrical porcine samples tested under fast and slow confined compression by Vaidya and collaborators were used. An axisymmetric Finite Element model was developed in ABAQUS and, for each sample a one-to-one inverse analysis was performed to calibrate the specimen-specific constitutive parameters, namely, the drained Young's modulus, the void ratio, hydraulic permeability, the Poisson's ratio, the solid grain's and fluid's bulk moduli. Findings The peak stress and consolidation were recovered for most of the samples (N = 25) by the poroelastic model (normalised root-mean-square error ≤0.03 for fast and slow confined compression conditions). Interpretation The strength of the proposed model is its fewer number of variables (N = 6 for the proposed poroelastic model versus N = 18 for the viscohyperelastic model proposed by Vaidya and collaborators). The incorporation of poroelasticity to clinical models of Pessure Ulcer formation could lead to more precise and mechanistic explorations of soft tissue injury risk factors. http://hdl.handle.net/10985/21320 Digital twinning of Cellular Capsule Technology: Emerging outcomes from the perspective of porous media mechanics URCUN, Stéphane; SKALLI, Wafa; NASSOY, Pierre; BORDAS, Stéphane Pierre Alain; SCIUMÈ, Giuseppe; ROHAN, Pierre-Yves Spheroids encapsulated within alginate capsules are emerging as suitable in vitro tools to investigate the impact of mechanical forces on tumor growth since the internal tumor pressure can be retrieved from the deformation of the capsule. Here we focus on the particular case of Cellular Capsule Technology (CCT). We show in this contribution that a modeling approach accounting for the triphasic nature of the spheroid (extracellular matrix, tumor cells and interstitial fluid) offers a new perspective of analysis revealing that the pressure retrieved experimentally cannot be interpreted as a direct picture of the pressure sustained by the tumor cells and, as such, cannot therefore be used to quantify the critical pressure which induces stress-induced phenotype switch in tumor cells. The proposed multiphase reactive poro-mechanical model was cross-validated. Parameter sensitivity analyses on the digital twin revealed that the main parameters determining the encapsulated growth configuration are different from those driving growth in free condition, confirming that radically different phenomena are at play. Results reported in this contribution support the idea that multiphase reactive poro-mechanics is an exceptional theoretical framework to attain an in-depth understanding of CCT experiments, to confirm their hypotheses and to further improve their design. Fri, 01 Jan 2021 00:00:00 GMT http://hdl.handle.net/10985/21320 2021-01-01T00:00:00Z URCUN, Stéphane SKALLI, Wafa NASSOY, Pierre BORDAS, Stéphane Pierre Alain SCIUMÈ, Giuseppe ROHAN, Pierre-Yves Spheroids encapsulated within alginate capsules are emerging as suitable in vitro tools to investigate the impact of mechanical forces on tumor growth since the internal tumor pressure can be retrieved from the deformation of the capsule. Here we focus on the particular case of Cellular Capsule Technology (CCT). We show in this contribution that a modeling approach accounting for the triphasic nature of the spheroid (extracellular matrix, tumor cells and interstitial fluid) offers a new perspective of analysis revealing that the pressure retrieved experimentally cannot be interpreted as a direct picture of the pressure sustained by the tumor cells and, as such, cannot therefore be used to quantify the critical pressure which induces stress-induced phenotype switch in tumor cells. The proposed multiphase reactive poro-mechanical model was cross-validated. Parameter sensitivity analyses on the digital twin revealed that the main parameters determining the encapsulated growth configuration are different from those driving growth in free condition, confirming that radically different phenomena are at play. Results reported in this contribution support the idea that multiphase reactive poro-mechanics is an exceptional theoretical framework to attain an in-depth understanding of CCT experiments, to confirm their hypotheses and to further improve their design.