粘弹性
有限元法
白质
脑组织
材料科学
各向同性
矢状面
生物医学工程
人脑
各向异性
创伤性脑损伤
结构工程
解剖
神经科学
物理
磁共振成像
复合材料
医学
生物
光学
放射科
工程类
精神科
作者
Sowmya N. Sundaresh,John D. Finan,Benjamin S. Elkin,Changhee Lee,Jingwei Xiao,Barclay Morrison
标识
DOI:10.1016/j.brain.2021.100041
摘要
The goal of this study was to measure the mechanical properties of porcine brain tissue and determine if they were dependent on anatomical region or direction. Multistep stress relaxation indentations with a cylindrical probe were performed at 10, 20, and 30% nominal strain on multiple regions in the sagittal, horizontal, and coronal planes. Linear and nonlinear (using the quasilinear theory of viscoelasticity [QLV]) constitutive formulations were applied to extract parameters to capture the mechanical behavior of brain tissue. The linear viscoelastic analytic approach provided the best fit to the experimental data of the models tested. Within each directional plane there were region-dependent differences. The cerebellum was the softest region within each loading direction. Although the majority of the regions were isotropic, the cerebellum white matter and thalamus were anisotropic. The characterization of these mechanical properties can be used to inform finite element models of the pig brain to help predict a more biofidelic response in animal models of traumatic brain injury. Statement of Significance: Finite element models been developed to predict brain tissue response to traumatic brain injury (TBI) to advance protective and preventative strategies. In order to improve the accuracy of these computational models, appropriate mechanical experimentation is required to identify brain viscoelasticity, heterogeneity, and anisotropy. Our custom indentation design allows for high spatial resolution to characterize mechanical properties based on anatomical region and loading direction. Due to the challenges in procuring human brain tissue, porcine brain models are a suitable substitute to study TBI based on its structural similarities to that of human brains. This study will further illuminate the complexity of brain tissue mechanics in response to injury loading.
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