Towards a comprehensive delineation of white matter tract-related deformation

Abstract

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) has recently 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 tracts. Three new tract-related strains were proposed, measuring the normal deformation vertical to the fiber tracts (i.e., tract-vertical strain), and shear deformation along and vertical 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 no-concussion). The results showed that four tract-related strain peaks exhibit superior performance compared to 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.

The relationship between brain injury criteria and brain strain across different types of head impacts can be different

“…Additionally, we used the KTH model [32] as the finiteelement head model (FEHM), which is relatively simplified compared to the current state-of-the-art FEHM [58][59][60]. The KTH model has tangential sliding without separation in the normal direction between subdural cerebral spinal fluid and the brain.…”

Fiber orientation downsampling compromises the computation of white matter tract-related deformation

“…To circumvent the orientation downsampling, Garimella et al (2019) explicitly incorporated the whole WM fiber tractography reconstructed from DTI into a head model in which multiple fibers were embedded within one WM element, while Ji et al (2015) transformed the fiber orientation of WM voxels from the DTI space into the coordinate system of the FE head model then computed the tract-oriented strain at the voxel level by resolving the strain tensor of the WM element from pre-computed simulation to the fiber orientation of these transformed voxels. Regardless of these above-described disparities as well as other model-specific choices, maximum tract-oriented strain has been congruently reported as an appropriate measure of injury by several independent groups (Giordano and Kleiven, 2014; Wu et al, 2021a; Zhao et al, 2017; Zhou et al, 2021b). More recently, Zhou et al (2021b) proposed three new tract-related strain metrics, 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), all of which exhibited superior injury predictability over maximum principal strain.…”

“…Regardless of these above-described disparities as well as other model-specific choices, maximum tract-oriented strain has been congruently reported as an appropriate measure of injury by several independent groups (Giordano and Kleiven, 2014; Wu et al, 2021a; Zhao et al, 2017; Zhou et al, 2021b). More recently, Zhou et al (2021b) proposed three new tract-related strain metrics, 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), all of which exhibited superior injury predictability over maximum principal strain. Note that the tract-oriented strain, tract-perpendicular strain, axial-shear strain, and lateral-shear strain are collectively referred to as tract-related strains, each of which characterizes one aspect of the loading regime endured by the fiber tracts.…”

“…The process of spatially resampling orientation information in DTI voxels to match the FE resolution is referred to as orientation downsampling. This or similar element-wise orientation implementation technique has been used in other studies (Chatelin et al, 2011; Colgan et al, 2010; Giordano and Kleiven, 2014; Giordano et al, 2017; Hernandez et al, 2019; Kraft and Dagro, 2011; Kraft et al, 2012; Laksari et al, 2020; Sahoo et al, 2016; Sullivan et al, 2015; Zhao and Ji, 2019b; Zhou et al, 2021b). To circumvent the orientation downsampling, Garimella et al (2019) explicitly incorporated the whole WM fiber tractography reconstructed from DTI into a head model in which multiple fibers were embedded within one WM element, while Ji et al (2015) transformed the fiber orientation of WM voxels from the DTI space into the coordinate system of the FE head model then computed the tract-oriented strain at the voxel level by resolving the strain tensor of the WM element from pre-computed simulation to the fiber orientation of these transformed voxels.…”

Brain strain rate response: addressing computational ambiguity and experimental data for model validation

“…Compared with the many strain-based studies, there are fewer investigations on brain strain rate. This is evidenced by the large body of literature that merely examined the strain-based outputs (e.g., the studies by Zhou, et al [20] and Bian and Mao [9]). For those investigations with a focus on strain rate, it is ubiquitous that the strain rate values are directly reported without any clarification on how they are calculated (e.g., the studies by Beckwith, et al [21] and Post, et al [22]).…”