Mechanical behaviour of brain-skull interface (meninges) under shear loading through experiment and finite element modelling: Preliminary results

TL;DR

This study combines experimental shear testing and finite element modelling to characterize the mechanical properties of the brain-skull interface, aiming to improve the realism of computational head injury models.

Contribution

It introduces an integrated experimental and computational framework to determine subject-specific properties of the brain-skull interface under shear loading.

Findings

Cohesive layer models the force-displacement behavior of the interface.

Maximum normal tractions ranged from 2.8-3.4 kPa.

Maximum tangential tractions ranged from 1.8-2.1 kPa.

Abstract

The brain-skull interface (meninges) plays a critical role in governing brain motion during head impacts, yet computational models often simplify this interface using idealized contact conditions due to limited experimental data. This study presents an improved protocol combining experimental testing and computational modelling to determine the mechanical properties of the brain-skull interface under shear loading. Brain tissue and brain-skull complex samples were extracted from sheep cadaver heads and subjected to shear loading. Magnetic resonance imaging (MRI) was used to obtain accurate 3D geometries of the samples, which were then used to create computational grids (meshes) for simulation of the experiments using finite element (FE) models to determine subject-specific properties of the brain tissue and brain-skull interface. A second-order Ogden hyperelastic model was used for the brain tissue, and a cohesive layer was employed to model the brain-skull interface. Our results indicate that a cohesive layer captures the force-displacement and damage initiation of the brain-skull interface. The calibrated cohesive properties showed consistent patterns across samples, with maximum normal tractions ranging from 2.8-3.4 kPa and maximum tangential tractions from 1.8-2.1 kPa. This framework provides a foundation for improving the biofidelity of computational head models used in injury prediction and neurosurgical planning by replacing arbitrary boundary conditions with formulations derived from experimental data on brain-skull interface (meninges) biomechanical behaviour.