Department of Biomedical Engineering, Lawrence Technological University, Southfield, MI, 48075, USA.
The Joint Department of Biomedical Engineering, Marquette University and Medical College of Wisconsin, Milwaukee, WI, 53226, USA.
Comput Biol Med. 2024 Oct;181:109063. doi: 10.1016/j.compbiomed.2024.109063. Epub 2024 Aug 23.
Investigating and understanding the biomechanical kinematics and kinetics of human brain axonal fibers during head impact process is crucial to study the mechanisms of Traumatic Axonal Injury (TAI). Such a study may require the explicit incorporation of brain fiber tracts into the host brain in order to distinguish the mechanical states of axonal fibers and brain tissue. Herein we extend our previously developed human head model by using an embedded element method to include fiber tracts reconstructed from diffusion tensor images in a host brain with the purpose of numerically tracking the deformation state of axonal fiber tracts during a head impact simulation. The updated model is validated by comparing its prediction of intracranial pressures with experimental data, followed by a thorough study of the effects of element types used for fiber tracts and the stiffness ratios of fiber to host brain. The validated model is also used to predict and visualize the damaged region of fiber tracts during the head impact process based on different injury criteria. The model is promising in tracking the state of fiber tracts and can add more objective functions such as axonal fiber deformation if used in the future design optimization of head protective equipment such as a football helmet.
研究和理解头部撞击过程中人类脑轴突纤维的生物力学运动学和动力学对于研究创伤性轴索损伤(TAI)的机制至关重要。这样的研究可能需要将脑纤维束明确纳入宿主脑内,以区分轴突纤维和脑组织的力学状态。在此,我们通过使用嵌入式元素方法扩展了我们之前开发的人类头部模型,将从扩散张量图像重建的纤维束纳入具有宿主脑的模型中,以便在头部撞击模拟过程中数值跟踪轴突纤维束的变形状态。通过将颅内压力的预测与实验数据进行比较来验证更新后的模型,然后深入研究用于纤维束的单元类型和纤维与宿主脑之间的刚度比的影响。还根据不同的损伤标准,使用验证后的模型来预测和可视化头部撞击过程中纤维束的损伤区域。该模型在跟踪纤维束状态方面具有很大的应用潜力,如果在未来的头部防护设备(如橄榄球头盔)的设计优化中使用,它还可以添加更多的目标函数,如轴突纤维的变形。