Zhou Zhou, Li Xiaogai, Liu Yuzhe, Fahlstedt Madelen, Georgiadis Marios, Zhan Xianghao, Raymond Samuel J, Grant Gerald, Kleiven Svein, Camarillo David, Zeineh Michael
Department of Bioengineering, Stanford University, Stanford, California, USA.
Neuronic Engineering, KTH Royal Institute of Technology, Stockholm, Sweden.
J Neurotrauma. 2021 Dec;38(23):3260-3278. doi: 10.1089/neu.2021.0195. Epub 2021 Nov 11.
Finite element (FE) models of the human head are valuable instruments to explore the mechanobiological pathway from external loading, localized brain response, and resultant injury risks. The injury predictability of these models depends on the use of effective criteria as injury predictors. The FE-derived normal deformation along white matter (WM) fiber tracts (i.e., tract-oriented strain) recently has been suggested as an appropriate predictor for axonal injury. However, the tract-oriented strain only represents a partial depiction of the WM fiber tract deformation. A comprehensive delineation of tract-related deformation may improve the injury predictability of the FE head model by delivering new tract-related criteria as injury predictors. Thus, the present study performed a theoretical strain analysis to comprehensively characterize the WM fiber tract deformation by relating the strain tensor of the WM element to its embedded fiber tract. Three new tract-related strains with exact analytical solutions were proposed, measuring the normal deformation perpendicular to the fiber tracts (i.e., tract-perpendicular strain), and shear deformation along and perpendicular to the fiber tracts (i.e., axial-shear strain and lateral-shear strain, respectively). The injury predictability of these three newly proposed strain peaks along with the previously used tract-oriented strain peak and maximum principal strain (MPS) were evaluated by simulating 151 impacts with known outcome (concussion or non-concussion). The results preliminarily showed that four tract-related strain peaks exhibited superior performance than MPS in discriminating concussion and non-concussion cases. This study presents a comprehensive quantification of WM tract-related deformation and advocates the use of orientation-dependent strains as criteria for injury prediction, which may ultimately contribute to an advanced mechanobiological understanding and enhanced computational predictability of brain injury.
人体头部的有限元（FE）模型是探索从外部载荷、局部脑反应到由此产生的损伤风险的力学生物学途径的重要工具。这些模型的损伤预测能力取决于使用有效的标准作为损伤预测指标。最近有人提出，沿白质（WM）纤维束的有限元衍生正常变形（即束向应变）是轴突损伤的合适预测指标。然而，束向应变仅代表了WM纤维束变形的部分描述。对与束相关的变形进行全面描述，通过提供新的与束相关的标准作为损伤预测指标，可能会提高有限元头部模型的损伤预测能力。因此，本研究进行了理论应变分析，通过将WM单元的应变张量与其嵌入的纤维束相关联，全面表征WM纤维束的变形。提出了三种具有精确解析解的与束相关的新应变，分别测量垂直于纤维束的正常变形（即束垂直应变）以及沿纤维束和垂直于纤维束的剪切变形（即轴向剪切应变和横向剪切应变）。通过模拟151次已知结果（脑震荡或非脑震荡）的撞击，评估了这三种新提出的应变峰值以及先前使用的束向应变峰值和最大主应变（MPS）的损伤预测能力。结果初步表明，在区分脑震荡和非脑震荡病例方面，四个与束相关的应变峰值表现优于MPS。本研究全面量化了与WM束相关的变形，并提倡使用与方向相关的应变作为损伤预测标准，这最终可能有助于对脑损伤有更深入的力学生物学理解，并提高计算预测能力。
