Biomechanical characterization of the human pia–arachnoid complex using bulge inflation testing and the virtual fields method

The cranial meninges are crucial structures in protecting the brain against injury. Hence, a biofidelic mechanical representation of these tissues is essential for accurate computational predictions of stress and strain in the brain during a traumatic brain injury. This study presents a biomechanical analysis of human pia-arachnoid complex tissue, which is formed by the two innermost meningeal layers. Bulge inflation experiments were performed on 29 pia-arachnoid complex samples to investigate their in-plane mechanical properties and parameters of the modified one-term Ogden model were derived with the virtual fields method. Due to its anatomical structure, pia-arachnoid complex tissue has an inhomogeneous thickness with a median value of 0.400mm. A bivariate normal probability density function was identified for the log-transformed parameters obtained from different specimens and samples with mean values μ=0.30MPa and α=36.97. Results show that the mechanical behavior of pia-arachnoid complex tissue is highly nonlinear in contrast to the linear elastic models often implemented in state-of-the-art finite element head models. Since the pia-arachnoid complex tissue is closely wrapped around the brain, it is important to include a more realistic mechanical behavior into these models. Statement of significance This study presents a biomechanical characterization of the human pia-arachnoid complex tissue by employing advanced techniques such as bulge inflation testing and the virtual fields method. To the best of the author's knowledge, this research is the first to characterize the in-plane properties of the human pia-arachnoid complex tissue. Additionally, this is also the first time that properties of the pia-arachnoid complex tissue are derived based on multiaxial testing. These findings are crucial for understanding the protective function of the pia-arachnoid complex in the brain. Furthermore, this research is also a critical step towards developing more accurate computational models of the human head, which are essential for studying traumatic brain injuries.