Porous and viscous behaviour of human brain tissue

Computational modelling in biomechanics can provide important insights into the underlying mechanisms of cerebral pathologies that go far beyond the possibilities of traditional methods. The improvement of current prevention and treatment strategies via numerical simulation can only be achieved with a realistic biomechanical model for brain tissue. Understanding and characterizing its short- and long-term biomechanical response, and linking it to its underlying microstructure is essential to develop reliable models. We aim to characterize the mechanical response of brain tissue via the development of a biphasic constitutive model based on a comprehensive set of experimental data. To achieve this goal, the work program is divided into four specific aims: (1) We will devise new experimental set- ups to adequately characterize the visco-porous nature of brain tissue under arbitrary loading conditions. There are very few published studies characterizing the porous effects in brain tissue, all restricted to a single loading mode. Yet, we need to fit multiple loading conditions simultaneously for the identified model parameters to produce accurate computational results. (2) We will elucidate the relation between the macroscopic mechanical response and the tissue microstructure through microstructural investigations of the tested samples, and, potentially, identify structural model parameters. These investigations are key to confirming our assumptions that porous and viscous phenomena observed in experiments are intrinsically linked to the tissue components, and the interconnectivity of cells. (3) We will develop a poro-viscoelastic model to capture, at the continuum level, the individual effects of the fluid and solid components, and their interaction. The experimental findings in (1) and the structural parameters identified in (2) will enable us to replace phenomenological constitutive equations, previously used to describe brain tissue behaviour, with comprehensive microstructurally motivated material laws. A robust finite element framework will allow for the successful implementation of the proposed model. (4) We will accurately calibrate the model parameters through an inverse material parameter identification scheme and evaluate their physical meaning considering the observed porous and viscous phenomena. The outcome of the project will be a better understanding of the role porous and viscous e ffects have in the response of brain tissue to mechanical loading. We will have linked the microstructure of the tissue to its macroscopic behaviour via experimental and computational investigations. With the resulting calibrated model, we will further explore how structure and mechanical response are linked, as well as demonstrate the potential for application of the proposed model in clinically-relevant problems.

This project aimed to advance our understanding of the mechanical behavior of the human brain by combining experimental testing, biomaterials, and computational modeling. Recognizing the brain as a soft, porous, and fluid-saturated organ, the project used brain tissue-mimicking hydrogels as ethical and tunable surrogates for human and animal tissue. A poro-viscoelastic material model was developed and validated across these materials, enabling the separation of porous and viscous contributions to brain mechanics. This modeling approach supports the development of patient-specific digital twins and improves our understanding of how external devices interact with brain tissue. In addition to advancing computational simulations, the project contributed fundamental knowledge on the mechanics of hydrated soft materials and demonstrated how synthetic hydrogels can support the 3Rs principle by replacing animal tissue in many tests. The findings also laid the groundwork for future research on complex tissue deformation, fluid flow, and the integration of medical tools and devices.