Experimental study on the mechanical properties of pediatric porcine brain tissue and calibration of the transversely isotropic hyperelastic constitutive model using two methods.

Abstract

Although many studies have investigated the mechanical properties of the adult brain, data specific to pediatric brains-particularly those of infants and toddlers-are scarce due to ethical limitations. In this study, 4-week-old piglet brain tissue was used as a suitable proxy for infant and toddler brains in tension and compression tests to assess the directional and regional effects. The white matter demonstrated anisotropy in tension, with higher stress observed along the axonal fibers compared to perpendicular loading. Regionally, white matter exhibited higher stress than gray matter, while the cerebellum was stiffer than both cerebral cortex and corona radiata in tension and compression tests. A transversely isotropic hyperelastic constitutive model (Mooney-Rivlin-Weiss model) was used to characterize the mechanical properties of brain tissue. Its direct calibration was challenging due to inhomogeneous deformation under large strain and non-uniaxial testing conditions. To address the challenge, a manual calibration method was proposed. To prove its effectiveness, a comparative analysis with the common-used inverse optimization method was conducted. Both methodologies enabled the successful determination of parameters of the hyperelastic constitutive model. The inverse optimization method required less manual interference and was easy to master, but the computational cost was large, and more importantly, the parameter ranges should be well controlled. Conversely, the proposed manual calibration method demonstrated superior computational efficiency but required more manual intervention, which should be further improved on user-friendliness. Overall, the anisotropic mechanical properties of the immature brain tissue were obtained and the proposed manual calibration method should be helpful in determining the material parameter values of constitutive models.