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1 Acta of Bioengineering and Biomechanics

1 2024

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Investigation of the mechanical characteristics of porcine brain tissue in complex environments

Li Weiqi, Zhang Peiming

Acta of Bioengineering and Biomechanics

2024

Vol. 26, no. 2

136--142

Brain tissue immersed in cerebrospinal fluid often exhibits complex mechanical behaviour, especially the nonlinear stress– strain and rate-dependent responses. Despite extensive research into its material properties, the impact of solution environments on the mechanical behaviour of brain tissue remains limited. This knowledge gap affects the biofidelity of head modelling. This study aimed to investigate the effect of solution environments on brain tissue under quasi-static and dynamic loading conditions. Methods: Porcine brain tissue was characterized in compression through quasi-static nonlinear testing and Dynamic Mechanical Analysis under various environments: air, physiological saline and artificial cerebrospinal fluid. Frequencies from 0.1 to 40 Hz were applied to determine dynamic behaviour, while brain samples were compressed up to a 0.3 strain level to obtain nonlinear response. The effects of strain, frequency and solution environment on the mechanical response of brain tissue were statistically evaluated. Results: As environmental conditions transitioned from air to artificial cerebrospinal fluid, the average stress of brain tissue increased by approximately 1.3, 1.3 and 1.4 times at strain levels of 0.1, 0.2 and 0.3, respectively. A statistically significant increase in dynamic storage and loss moduli was observed between air and artificial cerebrospinal fluid environments. At frequencies above 18 Hz, the tan delta in air was significantly lower. Conclusions: The mechanical characterization of brain tissue exhibited a dependency on solution environment under both quasi-static and dynamic loading conditions. Brain tissue showed higher stress levels and dynamic modulus in solution environments compared to an air environment. The results of this study are valuable for improving head simulations and brain material models.