https://sam.ensam.eu:443 The DSpace digital repository system captures, stores, indexes, preserves, and distributes digital research material. Wed, 11 Mar 2026 22:50:28 GMT 2026-03-11T22:50:28Z http://hdl.handle.net/10985/17457 Cell nutriments and motility for mechanobiological bone remodeling in the context of orthodontic periodontal ligament deformation GEORGE, Daniel; ALLENA, Rachele; REMOND, Yves Bone remodeling is a complex phenomenon during which old and new bone is continuously removed and replaced. This phenomenon involves several processes at different length scales such as mechanical, biological, molecular, and chemicals. In the current work, we study the influence of the biological (cells) and molecular (oxygen and glucose) factors coupled with mechanical loads in order to predict bone remodeling for orthodontic treatments. A coupled theoretical mechanobiological model is proposed to extract the oxygen variation due to the deformation of the periodontal ligament leading to cell differentiation and activation. The mechanobiological stimulus is then calculated. The model is applied on a simplified two dimensional geometry to highlight the density variations and migrations of cells and molecular factors influencing the bone remodeling process. Mon, 01 Jan 2018 00:00:00 GMT http://hdl.handle.net/10985/17457 2018-01-01T00:00:00Z GEORGE, Daniel ALLENA, Rachele REMOND, Yves Bone remodeling is a complex phenomenon during which old and new bone is continuously removed and replaced. This phenomenon involves several processes at different length scales such as mechanical, biological, molecular, and chemicals. In the current work, we study the influence of the biological (cells) and molecular (oxygen and glucose) factors coupled with mechanical loads in order to predict bone remodeling for orthodontic treatments. A coupled theoretical mechanobiological model is proposed to extract the oxygen variation due to the deformation of the periodontal ligament leading to cell differentiation and activation. The mechanobiological stimulus is then calculated. The model is applied on a simplified two dimensional geometry to highlight the density variations and migrations of cells and molecular factors influencing the bone remodeling process. http://hdl.handle.net/10985/17460 Integrating molecular and cellular kinetics into a coupled continuum mechanobiological stimulus for bone reconstruction GEORGE, Daniel; ALLENA, Rachele; REMOND, Yves The development of multiphysics numerical models to predict bone reconstruction is a very challenging task as it is a complex phenomenon where many biological, chemical and mechanical processes occur at different lengths and timescales.We present here amechanobiological theoretical numerical model accounting for both the mechanical and biological environments to predict the bone reconstruction process through the use of a global stimulus integrating the contributions of applied external mechanical loads, cellular activities and cellular nutriments such as oxygen and glucose supply. The bone density evolution will hence depend on the overall stimulus and evolve accordingly to the intensities of each of its individual constituents. We show their specific influences and couplings on a simple two-dimensional geometry and confirm that, although the mechanics plays a crucial role in the bone reconstruction process, it is still highly dependent on the occurring biological events and will evolve accordingly. Mon, 01 Jan 2018 00:00:00 GMT http://hdl.handle.net/10985/17460 2018-01-01T00:00:00Z GEORGE, Daniel ALLENA, Rachele REMOND, Yves The development of multiphysics numerical models to predict bone reconstruction is a very challenging task as it is a complex phenomenon where many biological, chemical and mechanical processes occur at different lengths and timescales.We present here amechanobiological theoretical numerical model accounting for both the mechanical and biological environments to predict the bone reconstruction process through the use of a global stimulus integrating the contributions of applied external mechanical loads, cellular activities and cellular nutriments such as oxygen and glucose supply. The bone density evolution will hence depend on the overall stimulus and evolve accordingly to the intensities of each of its individual constituents. We show their specific influences and couplings on a simple two-dimensional geometry and confirm that, although the mechanics plays a crucial role in the bone reconstruction process, it is still highly dependent on the occurring biological events and will evolve accordingly. http://hdl.handle.net/10985/17459 A multiphysics stimulus for continuum mechanics bone remodeling GEORGE, Daniel; ALLENA, Rachele; REMOND, Yves Bone remodelling is a complex phenomenon during which old and damage bone is removed and replaced with new one to ensure the physiological functions of the skeletal system. It involves many biological, mechanical, chemical processes at different scales. The objective of the present work is to predict the kinetics of bone density evolution by taking into account both the mechanical and the biological frameworks. In order to do so, we propose a new computational model in which the global stimulus triggering bone remodelling is the result of the contribution of a mechanical (i.e. external loads and consequent strain energy), a cellular (i.e. osteoblasts and osteoclasts activities) and a molecular (i.e. oxygen and glucose supply) stimulus. The evolution of the bone density depends on the overall behaviour of the global stimulus. More specifically, when the global stimulus is positive, bone synthesis occurs, whereas when the global stimulus is negative, resorption takes place. Although the theoretical model has been applied on a very simple two-dimensional geometry, the final results provide new insights on the influence of each stimulus on the bone remodelling process. In particular, we confirm that mechanics plays a critical role and affects the kinetics of bone reconstruction, but it highly depends on the biological events and the distribution of bone density. Mon, 01 Jan 2018 00:00:00 GMT http://hdl.handle.net/10985/17459 2018-01-01T00:00:00Z GEORGE, Daniel ALLENA, Rachele REMOND, Yves Bone remodelling is a complex phenomenon during which old and damage bone is removed and replaced with new one to ensure the physiological functions of the skeletal system. It involves many biological, mechanical, chemical processes at different scales. The objective of the present work is to predict the kinetics of bone density evolution by taking into account both the mechanical and the biological frameworks. In order to do so, we propose a new computational model in which the global stimulus triggering bone remodelling is the result of the contribution of a mechanical (i.e. external loads and consequent strain energy), a cellular (i.e. osteoblasts and osteoclasts activities) and a molecular (i.e. oxygen and glucose supply) stimulus. The evolution of the bone density depends on the overall behaviour of the global stimulus. More specifically, when the global stimulus is positive, bone synthesis occurs, whereas when the global stimulus is negative, resorption takes place. Although the theoretical model has been applied on a very simple two-dimensional geometry, the final results provide new insights on the influence of each stimulus on the bone remodelling process. In particular, we confirm that mechanics plays a critical role and affects the kinetics of bone reconstruction, but it highly depends on the biological events and the distribution of bone density. http://hdl.handle.net/10985/17455 Mechanobiological stimuli for bone remodeling: mechanical energy, cell nutriments and mobility GEORGE, Daniel; ALLENA, Rachele; REMOND, Yves Mechanobiological stimuli for bone remodeling: mechanical energy, cell nutriments and mobility Sun, 01 Jan 2017 00:00:00 GMT http://hdl.handle.net/10985/17455 2017-01-01T00:00:00Z GEORGE, Daniel ALLENA, Rachele REMOND, Yves Mechanobiological stimuli for bone remodeling: mechanical energy, cell nutriments and mobility http://hdl.handle.net/10985/19815 A new comprehensive approach for bone remodeling under medium and high mechanical load based on cellular activity ALLENA, Rachele; GEORGE, Daniel; BOURZAC, Céline; PALLU, Stéphane; RÉMOND, Yves; BENSIDHOUM, Morad; PORTIER, Hugues Most of the last century, bone remodeling models have been proposed based on the observation that bone density is dependent on the intensity of the applied mechanical loads. Most of these cortical or trabecular bone remodeling models are related to the osteocyte mechanosensitivity, and they all have a direct correlation between the bone mineral density and the mechanical strain energy. However, experiments on human athletes show that high-intensity sport activity tends not to increase bone mineral density but rather has a negative impact. Therefore, it appears that the optimum bone mineral density would develop for “medium”-intensity activity (or medium mechanical loads) and not for the highest-intensity one. The authors would like to thank the CNRS for its financial support through the Défi Mécanobiologie to carry out the work. Wed, 01 Jan 2020 00:00:00 GMT http://hdl.handle.net/10985/19815 2020-01-01T00:00:00Z ALLENA, Rachele GEORGE, Daniel BOURZAC, Céline PALLU, Stéphane RÉMOND, Yves BENSIDHOUM, Morad PORTIER, Hugues Most of the last century, bone remodeling models have been proposed based on the observation that bone density is dependent on the intensity of the applied mechanical loads. Most of these cortical or trabecular bone remodeling models are related to the osteocyte mechanosensitivity, and they all have a direct correlation between the bone mineral density and the mechanical strain energy. However, experiments on human athletes show that high-intensity sport activity tends not to increase bone mineral density but rather has a negative impact. Therefore, it appears that the optimum bone mineral density would develop for “medium”-intensity activity (or medium mechanical loads) and not for the highest-intensity one. http://hdl.handle.net/10985/20266 A preliminary approach in the prediction of orthodontic bone remodeling by coupling experiments, theory and numerical models GEORGE, Daniel; WAGNER, Delphine; BOLENDER, Yves; LAHEURTE, Pascal; PIOTROWSKI, Boris; DIDIER, Paul; BENSIDHOUM, Morad; HERBERT, Valentin; SPINGARN, Camille; RÉMOND, Yves Orthodontic treatments are based on a prolonged application of mechanical forces on the teeth through orthodontic appliances, leading to tooth movement due to the remodeling of the surrounding bone. Bone response is dependent on the biological reactions occurring in the periodontal ligament (PDL) and more specifically on those related to vascular changes (Pavlin and Gluhak-Heinrich 2001). Hence, optimal forces and moments are required to obtain the desired tooth displacements without generating deleterious effects. Although the biological events occurring during orthodontic tooth movement are nowadays better understood, the correlation between orthodontic force systems, desmodontal reactions and bone remodeling is not well established (Meikle 2005). Little is known about the forces and moments developed on more than two adjacent teeth (Badawi et al. 2009). In this work, we focus our analysis on a buccal upper right canine in infraclusion and extract the experimental measurements of the mechanical forces developed onto the complete dental arch. These are then transferred into a numerical finite element (FE) model to determine the PDL deformation and hence, through a theoretical numerical model, quantify the cellular mechanobiological reactions at the root of orthodontic bone remodeling. Wed, 01 Jan 2020 00:00:00 GMT http://hdl.handle.net/10985/20266 2020-01-01T00:00:00Z GEORGE, Daniel WAGNER, Delphine BOLENDER, Yves LAHEURTE, Pascal PIOTROWSKI, Boris DIDIER, Paul BENSIDHOUM, Morad HERBERT, Valentin SPINGARN, Camille RÉMOND, Yves Orthodontic treatments are based on a prolonged application of mechanical forces on the teeth through orthodontic appliances, leading to tooth movement due to the remodeling of the surrounding bone. Bone response is dependent on the biological reactions occurring in the periodontal ligament (PDL) and more specifically on those related to vascular changes (Pavlin and Gluhak-Heinrich 2001). Hence, optimal forces and moments are required to obtain the desired tooth displacements without generating deleterious effects. Although the biological events occurring during orthodontic tooth movement are nowadays better understood, the correlation between orthodontic force systems, desmodontal reactions and bone remodeling is not well established (Meikle 2005). Little is known about the forces and moments developed on more than two adjacent teeth (Badawi et al. 2009). In this work, we focus our analysis on a buccal upper right canine in infraclusion and extract the experimental measurements of the mechanical forces developed onto the complete dental arch. These are then transferred into a numerical finite element (FE) model to determine the PDL deformation and hence, through a theoretical numerical model, quantify the cellular mechanobiological reactions at the root of orthodontic bone remodeling. http://hdl.handle.net/10985/18605 Shape parametrization of bio-mechanical finite element models based on medical images LAUZERAL, Nathan; BORZACCHIELLO, Domenico; KUGLER, Michaël; GEORGE, Daniel; RÉMOND, Yves; HOSTETTLER, Alexandre; CHINESTA SORIA, Francisco The main objective of this study is to combine the statistical shape analysis with a morphing procedure in order to generate shape-parametric finite element models of tissues and organs and to explore the reliability and the limitations of this approach when applied to databases of real medical images. As classical statistical shape models are not always adapted to the morphing procedure, a new registration method was developed in order to maximize the morphing efficiency. The method was compared to the traditional iterative thin plate spline (iTPS). Two data sets of 33 proximal femora shapes and 385 liver shapes were used for the comparison. The principal component analysis was used to get the principal morphing modes. In terms of anatomical shape reconstruction (evaluated through the criteria of generalization, compactness and specificity), our approach compared fairly well to the iTPS method, while performing remarkably better in terms of mesh quality, since it was less prone to generate invalid meshes in the interior. This was particularly true in the liver case. Such methodology offers a potential application for the generation of automated finite element (FE) models from medical images. Parametrized anatomical models can also be used to assess the influence of inter-patient variability on the biomechanical response of the tissues. Indeed, thanks to the shape parametrization the user would easily have access to a valid FE model for any shape belonging to the parameters subspace. Tue, 01 Jan 2019 00:00:00 GMT http://hdl.handle.net/10985/18605 2019-01-01T00:00:00Z LAUZERAL, Nathan BORZACCHIELLO, Domenico KUGLER, Michaël GEORGE, Daniel RÉMOND, Yves HOSTETTLER, Alexandre CHINESTA SORIA, Francisco The main objective of this study is to combine the statistical shape analysis with a morphing procedure in order to generate shape-parametric finite element models of tissues and organs and to explore the reliability and the limitations of this approach when applied to databases of real medical images. As classical statistical shape models are not always adapted to the morphing procedure, a new registration method was developed in order to maximize the morphing efficiency. The method was compared to the traditional iterative thin plate spline (iTPS). Two data sets of 33 proximal femora shapes and 385 liver shapes were used for the comparison. The principal component analysis was used to get the principal morphing modes. In terms of anatomical shape reconstruction (evaluated through the criteria of generalization, compactness and specificity), our approach compared fairly well to the iTPS method, while performing remarkably better in terms of mesh quality, since it was less prone to generate invalid meshes in the interior. This was particularly true in the liver case. Such methodology offers a potential application for the generation of automated finite element (FE) models from medical images. Parametrized anatomical models can also be used to assess the influence of inter-patient variability on the biomechanical response of the tissues. Indeed, thanks to the shape parametrization the user would easily have access to a valid FE model for any shape belonging to the parameters subspace. http://hdl.handle.net/10985/14639 A model order reduction approach to create patient-specific mechanical models of human liver in computational medicine applications. LAUZERAL, Nathan; BORZACCHIELLO, Domenico; KUGLER, Michael; RÉMOND, Yves; GEORGE, Daniel; HOSTETTLER, Alexandre; CHINESTA SORIA, Francisco Background and objective: This paper focuses on computer simulation aspects of Digital Twin models in the medical framework. In particular, it addresses the need of fast and accurate simulators for the mechanical response at tissue and organ scale and the capability of integrating patient-specific anatomy from medical images to pinpoint the individual variations from standard anatomical models. Methods: We propose an automated procedure to create mechanical models of the human liver with patient-specific geometry and real time capabilities. The method hinges on the use of Statistical Shape Analysis to extract the relevant anatomical features from a database of medical images and Model Order Reduction to compute an explicit parametric solution for the mechanical response as a function of such features. The Sparse Subspace Learning, coupled with a Finite Element solver, was chosen to create low-rank solutions using a non-intrusive sparse sampling of the feature space. Results: In the application presented in the paper, the statistical shape model was trained on a database of 385 three dimensional liver shapes, extracted from medical images, in order to create a parametrized representation of the liver anatomy. This parametrization and an additional parameter describing the breathing motion in linear elasticity were then used as input in the reduced order model. Results show a consistent agreement with the high fidelity Finite Element models built from liver images that were excluded from the training dataset. However, we evidence in the discussion the difficulty of having compact shape parametrizations arising from the extreme variability of the shapes found in the dataset and we propose potential strategies to tackle this issue. Conclusions: A method to represent patient-specific real-time liver deformations during breathing is proposed in linear elasticity. Since the proposed method does not require any adaptation to the direct Finite Element solver used in the training phase, the procedure can be easily extended to more complex non-linear constitutive behaviors - such as hyperelasticity - and more general load cases. Therefore it can be integrated with little intrusiveness to generic simulation software including more sophisticated and realistic models. Tue, 01 Jan 2019 00:00:00 GMT http://hdl.handle.net/10985/14639 2019-01-01T00:00:00Z LAUZERAL, Nathan BORZACCHIELLO, Domenico KUGLER, Michael RÉMOND, Yves GEORGE, Daniel HOSTETTLER, Alexandre CHINESTA SORIA, Francisco Background and objective: This paper focuses on computer simulation aspects of Digital Twin models in the medical framework. In particular, it addresses the need of fast and accurate simulators for the mechanical response at tissue and organ scale and the capability of integrating patient-specific anatomy from medical images to pinpoint the individual variations from standard anatomical models. Methods: We propose an automated procedure to create mechanical models of the human liver with patient-specific geometry and real time capabilities. The method hinges on the use of Statistical Shape Analysis to extract the relevant anatomical features from a database of medical images and Model Order Reduction to compute an explicit parametric solution for the mechanical response as a function of such features. The Sparse Subspace Learning, coupled with a Finite Element solver, was chosen to create low-rank solutions using a non-intrusive sparse sampling of the feature space. Results: In the application presented in the paper, the statistical shape model was trained on a database of 385 three dimensional liver shapes, extracted from medical images, in order to create a parametrized representation of the liver anatomy. This parametrization and an additional parameter describing the breathing motion in linear elasticity were then used as input in the reduced order model. Results show a consistent agreement with the high fidelity Finite Element models built from liver images that were excluded from the training dataset. However, we evidence in the discussion the difficulty of having compact shape parametrizations arising from the extreme variability of the shapes found in the dataset and we propose potential strategies to tackle this issue. Conclusions: A method to represent patient-specific real-time liver deformations during breathing is proposed in linear elasticity. Since the proposed method does not require any adaptation to the direct Finite Element solver used in the training phase, the procedure can be easily extended to more complex non-linear constitutive behaviors - such as hyperelasticity - and more general load cases. Therefore it can be integrated with little intrusiveness to generic simulation software including more sophisticated and realistic models.