Nicole Tueni

Reliable characterization of spatial variations in brain tissue stiffness is essential for predictive biomechanical modeling, yet most current methods rely on coarse regional parameter assignments based on invasive mechanical testing. In this study, we propose a new approach to obtain subject-specific mechanical properties at voxel resolution from in vivo diffusion tensor magnetic resonance imaging (DTI) based on a linear regression between the fractional anisotropy (FA) from DTI and experimentally measured stiffness values. To assess how such heterogeneity in mechanical properties influences simulated brain deformation, we construct a finite element model based on two material parameterizations of the same human brain: one employing nine anatomically defined regions, each with uniform material parameters, and another in which the shear modulus is assigned voxel-wise on the corresponding FA value. Applying this FA-stiffness mapping yields a smoothly varying mechanical property distribution that better captures local microstructural differences not represented by region-wise parameterizations. Both parameterizations are subjected to an identical atrophy-driven loading scenario. They exhibit comparable overall volume loss, but diverge in regional behavior. The voxel-resolved parameterization predicts more pronounced ventricular expansion and differs in the displacement and stretch distributions, indicating that variability in stiffness can alter local predicted responses even when global outcomes appear similar. This work presents a pipeline for estimating individualized mechanical properties directly from imaging protocols that are routinely performed on patients, with important implications for brain biomechanics. While the approach depends on a simplified linear FA-stiffness relation and assumes isotropic constitutive behavior, it provides a framework for integrating imaging-based microstructure into subject-specific simulations. Future validation against in vivo or experimental deformation data is needed to determine the fidelity and clinical utility of FA-derived stiffness fields.

Tissus cardiaques : étude du lien entre organisation du tissu et propriétés mécaniques.: Le myocarde est un tissu complexe, principalement constitué de cellules cardiaques et d'une matrice collagénique extracellulaire, disposés selon une microstructure hiérarchique. Cette microstructure évolue au cours du temps, de manière physiologique ou pathologique, altérant les propriétés mécaniques macroscopiques du cœur, donc sa fonction. L'objectif de cette thèse est d'améliorer notre compréhension des relations structure-propriétés dans le tissu cardiaque en s'intéressant au rôle de la mésostructure, appelée feuillet, sur les propriétés mécaniques macroscopiques. Dans une première partie, une revue de la littérature existante sur le rôle du feuillet est réalisée. Dans le deuxième chapitre, nous présentons un montage expérimental que nous avons développé, combinant un imageur polarimétrique Mueller plein champ et un dispositif de traction in-situ avec une mesure locale de la déformation lors de l'étirement de l'échantillon. On observe une cohésion globale des tissus à part sur des lignes de séparation à mésoéchelle, qui ont tendance à s'ouvrir sous traction. Nous émettons l'hypothèse que ces lignes sont les couches collagéniques séparant les feuillets, des faisceaux de cardiomyocytes entourés de couches de collagène périmysial. Dans le troisième chapitre, nous proposons une méthode optique simple combinée à une analyse d'image rapide pour extraire l'orientation locale des feuillets sur des coupes de ventricule gauche, afin de construire une cartographie 3D de l'organisation des feuillets dans le cœur. Dans la deuxième partie de la thèse (chapitre quatre), nous proposons un modèle multi-échelle du myocarde visant à déterminer l'origine structurale de l'anisotropie mécanique macro-échelle observée. En effet, l'orthotropie observée peut être due soit à la rotation de l'orientation des cellules, soit à la présence des couches collagéniques méso-échelle. Nous concevons trois mésostructures constituées de différentes configurations de cardiomyocytes et de collagène. La réponse mécanique de ces mésostructures est homogénéisée avec une homogénéisation périodique numérique, et les paramètres de matériau obtenus sont utilisés dans une simulation macroscopique d'une expérience de cisaillement. La comparaison entre nos résultats et les données expérimentales montre que les couches de collagène sont nécessaires pour reproduire l'orthotropie du matériau. Le dernier chapitre de ce manuscrit présente quelques perspectives de ce travail.

Brain aging and atrophy involve complex multiscale factors of cellular degeneration and morphological changes. Although previous biomechanical models have advanced our understanding of brain shrinkage due to physiological and pathological aging, they often rely on simplified representations of tissue properties with limited regional differentiation. Building on established links between regional mechanics and neurodegeneration, we extend atrophy models by introducing detailed mechanical heterogeneity across 17 anatomically and mechanically distinct brain regions. Using region-specific experimental material properties, the model differentiates local mechanical behavior and reveals effects that homogeneous models overlook, providing new clinical insight into region-specific vulnerabilities. We then compare this heterogeneous model with progressively simplified variants to assess the impact of regional variability on brain deformation. While global and regional volume changes remain largely unaffected by mechanical heterogeneity, volume fractions of the corpus callosum and ventricles are sensitive to regional differences in material parameters. Analysis of the displacement field shows that mechanical heterogeneity significantly influences local displacement patterns within brain regions. Stress and stretch analyses reveal discrepancies between simplified and heterogeneous models, particularly in the corpus callosum, the internal brain structures, and some cortical regions. These results emphasize the importance of incorporating regional mechanical heterogeneity to enhance the accuracy of brain simulations and underscore the need for more comprehensive experimental characterization of brain tissue properties.

Orthopedics is undergoing a transformative shift driven by personalized medical technologies that enhance precision, efficiency, and patient outcomes. Virtual surgical planning, robotic assistance, and real-time 3D navigation have revolutionized procedures like total knee arthroplasty and hip replacement, offering unparalleled accuracy and reducing recovery times. Integrating artificial intelligence, advanced imaging, and 3D-printed patient-specific implants further elevates surgical precision, minimizes intraoperative complications, and supports individualized care. In sports orthopedics, wearable sensors and motion analysis technologies are revolutionizing diagnostics, injury prevention, and rehabilitation, enabling real-time decision-making and improved patient safety. Health-tracking devices are advancing recovery and supporting preventative care, transforming athletic performance management. Concurrently, breakthroughs in biologics, biomaterials, and bioprinting are reshaping treatments for cartilage defects, ligament injuries, osteoporosis, and meniscal damage. These innovations are poised to establish new benchmarks for regenerative medicine in orthopedics. By combining cutting-edge technologies with interdisciplinary collaboration, the field is redefining surgical standards, optimizing patient care, and paving the way for a highly personalized and efficient future.

BMP-1/tolloid-like proteinases (BTPs) are major players in tissue morphogenesis, growth and repair. They act by promoting the deposition of structural extracellular matrix proteins and by controlling the activity of matricellular proteins and TGF-β superfamily growth factors. They have also been implicated in several pathological conditions such as fibrosis, cancer, metabolic disorders and bone diseases. Despite this broad range of pathophysiological functions, the putative existence of a specific endogenous inhibitor capable of controlling their activities could never be confirmed. Here, we show that procollagen C-proteinase enhancer-2 (PCPE-2), a protein previously reported to bind fibrillar collagens and to promote their BTP-dependent maturation, is primarily a potent and specific inhibitor of BTPs which can counteract their proteolytic activities through direct binding. PCPE-2 therefore differs from the cognate PCPE-1 protein and extends the possibilities to fine-tune BTP activities, both in physiological conditions and in therapeutic settings.