Histology-informed multiscale modeling of human brain white matter.

In this study, we propose a novel micromechanical model for the brain white matter, which is described as a heterogeneous material with a complex network of axon fibers embedded in a soft ground matrix. We developed this model in the framework of RVE-based multiscale theories in combination with the finite element method and the embedded element technique for embedding the fibers. Microstructural features such as axon diameter, orientation and tortuosity are incorporated into the model through distributions derived from histological data. The constitutive law of both the fibers and the matrix is described by isotropic one-term Ogden functions. The hyperelastic response of the tissue is derived by homogenizing the microscopic stress fields with multiscale boundary conditions to ensure kinematic compatibility. The macroscale homogenized stress is employed in an inverse parameter identification procedure to determine the hyperelastic constants of axons and ground matrix, based on experiments on human corpus callosum. Our results demonstrate the fundamental effect of axon tortuosity on the mechanical behavior of the brain's white matter. By combining histological information with the multiscale theory, the proposed framework can substantially contribute to the understanding of mechanotransduction phenomena, shed light on the biomechanics of a healthy brain, and potentially provide insights into neurodegenerative processes.

Modelling the anisotropic inelastic response of polymeric scaffolds for in situ tissue engineering applications.

In situ tissue engineering offers an innovative solution for replacement valves and grafts in cardiovascular medicine. In this approach, a scaffold, which can be obtained by polymer electrospinning, is implanted into the human body and then infiltrated by cells, eventually replacing the scaffold with native tissue. In silico simulations of the whole process in patient-specific models, including implantation, growth and degradation, are very attractive to study the factors that might influence the end result. In our research, we focused on the mechanical behaviour of the polymeric scaffold and its short-term response. Following a recently proposed constitutive model for the anisotropic inelastic behaviour of fibrous polymeric materials, we present here its numerical implementation in a finite element framework. The numerical model is developed as user material for commercial finite element software. The verification of the implementation is performed for elementary deformations. Furthermore, a parallel-plate test is proposed as a large-scale representative example, and the model is validated by comparison with experiments.

Poro-viscoelastic material parameter identification of brain tissue-mimicking hydrogels.

Understanding and characterizing the mechanical and structural properties of brain tissue is essential for developing and calibrating reliable material models. Based on the Theory of Porous Media, a novel nonlinear poro-viscoelastic computational model was recently proposed to describe the mechanical response of the tissue under different loading conditions. The model contains parameters related to the time-dependent behavior arising from both the viscoelastic relaxation of the solid matrix and its interaction with the fluid phase. This study focuses on the characterization of these parameters through indentation experiments on a tailor-made polyvinyl alcohol-based hydrogel mimicking brain tissue. The material behavior is adjusted to ex vivo porcine brain tissue. An inverse parameter identification scheme using a trust region reflective algorithm is introduced and applied to match experimental data obtained from the indentation with the proposed computational model. By minimizing the error between experimental values and finite element simulation results, the optimal constitutive model parameters of the brain tissue-mimicking hydrogel are extracted. Finally, the model is validated using the derived material parameters in a finite element simulation.