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In this study, we present an automatic and user-friendly pipeline for generating high-quality hexahedral FEM models directly from voxel-based biomedical images. Our pipeline incorporates advanced boundary smoothing techniques to eliminate staircase artifacts and improve mesh quality, making it particularly well-suited for applications involving 3D images in biomedical research. By addressing common challenges in mesh generation, this pipeline advances the potential for accurate and efficient mesh generation from biomedical images and FEM analysis in biomedical research. 

While studies indicate that females experience a higher concussion risk and more severe outcomes in soccer heading compared to males, comprehensive data on the underlying factors contributing to these sex-based differences are lacking. This study investigates the sex differences in the head-to-ball impact kinematics among college-aged soccer headers in a laboratory-controlled setting. Forty subjects (20 females, 20 males) performed ten headers, and impact kinematics, including peak angular acceleration and velocity (PAA, PAV) and peak linear acceleration (PLA), were measured using mouthguards. Video recordings verified impacts and impact locations. Participants’ head mass was estimated from their weights. The relationship between head mass and kinematic parameters was analyzed using Pearson correlation. The effects of head mass, sex, and impact location on kinematic parameters were assessed using MANOVA with and without head mass as a covariate. Results showed that head mass, larger in males than females, significantly affects PAA and PLA, the greater the head mass, the lower PAA and PLA. However, head mass has no effect on PAV. Females showed significantly higher PAA and PLA components but no significant differences in PAV. Impact location significantly influenced PAV, showing higher magnitudes for frontal impacts compared to top-front impacts, with no significant effects on PAA and PLA. Our results agree with epidemiological evidence that female soccer players face greater concussion risks than males, which can be attributed to their higher header-induced PAA. Future research could consider interventions like changing ball pressure, using protective headgear, and improving heading techniques to reduce high-magnitude accelerations in females. 

Sex differences in brain structure significantly influence traumatic brain injury (TBI) onset and progression, yet this area is understudied. Herein, we developed sex-specific brain anatomical (macroscale) and axonal tract (mesoscale) templates and explored the sex variations at subject level using a set of T1-MRI (609 males, 721 females) and DTI images (506 males, 594 females). The FreeSurfer, ANTs, and DSI-Studio packages were used. We investigated overall/regional volumes, DTI metrics (including fractional anisotropy (FA), mean diffusivity, and radial diffusivity), and connectivity matrix across 23 brain regions. The brain connectome was derived by multiplying the fiber tract counts and the FA values within the connecting tracts, quantifying the connection strength within each pair of regions. Our subject-wise analysis revealed significant sex based differences (Mann-Whitney p-values < 0.05) across most studied regions for all parameters. The largest sex differences in brain connections were observed in five regions: corpus callosum and right/left cortex and cerebral white matter, all stronger in females. Brain regions were typically larger in males, yet females had higher fractional volumes in the majority of regions except for CSF and ventricles, known for their cushioning effect during head impacts. Additionally, the sex-specific templates better represented their targeted sex compared to opposite or mixed-sex populations as evaluated by root-mean-square-errors when comparing the DTI metrics and connectivity from the DTI templates against the median of subjects and deformation field in registering the subjects to the T1-MRI templates. Our findings highlight the necessity of sex-specific templates in accurate brain modeling and TBI research. 

In this study, we aim to investigate the anatomical features and volumetric measurements of brain (macroscale), along with diffusion tensor imaging (DTI) metrics and the connections between brain regions (mesoscale), to explore sex-specific variations in the brain structure from biomechanics perspective. Such information is crucial for future studies involving FEMs in the field of brain biomechanics particularly when examining the impact of sex-specific differences on the onset and outcomes of TBI. 

This study aims to explore these differences and examine the role of head mass and impact location in these distinctions using a controlled laboratory experimental setup. The outcome of this study may inform sex-specific SRC prevention and protective strategies in soccer. 

The human brain is sexually dimorphic and these sex differences have shown to affect brain response to trauma. We investigated the sex differences in the tract structures by studying diffusion weighted (DW) images of 594 females and 506 males from the Human-Connectome-Project dataset. All the female and male DW images were reconstructed in the ICBM152 space using Q-Space diffeomorphic reconstruction technique and their mapped orientation distribution function images were averaged to generate the female- and male-DW-templates. The tract streamlines were generated through tractography for female and male templates and normalized to the total brain volume . The distributions of normalized tract lengths were significantly different between female- and male-templates and the female-template showed to have more longer normalized tracts compared to the male template. For the regional analysis, the templates were parcellated into sixteen regions of interests (ROI) including brain-stem, five subregions of corpus-callosum, and right and left hippocampus, thalamus, cerebellum white-matter (WM), cerebral WM, and cerebellum cortex using a FreeSurfer-based segmentation atlas. For all the ROIs, the average fractional anisotropy (0.5-5.7%) and normalized tract lengths (1.1-2.7%) were larger in female template while the average mean diffusion was larger (1.3-5.6%) in male-template. Quantifying brain connectivity by counting number of tracts passing through pairs of ROIs, showed more pairs with a higher connectivity in female-template, and one of the highest percentages of sex differences in right/left cerebellum WM/cortex connections. Our results reinforce the need to continue investigating the sex variations in axonal structure and their effects to brain trauma. 

he sex-based human brain structural variations alongside the necessity and development process for sex-specific brain templates were investigated in this study. Comparing magnetic resonance images of 500 female and 500 male subjects, no significant sex-based difference was observed for average cortical thickness, however, all the volumetric values, including the total brain volume (TBV) and major 19 brain regions, were found to be significantly different between females and males. Moreover, analyzing the fractional volume of the regions showed that these sex variations were not proportional to TBV for all regions. These findings underscore the importance of distinguishing the sex-based differences in human brain studies. While brain templates have been developed for general population and cohorts with the same characteristics such as race or age, there is a lack of sex-specific brain templates. To fill this gap and find a representative reference brain image for each sex, nonlinear templates were developed for female, male, and mixed population subjects. Next, a separate set of 109 female and 109 male brain images were used to evaluate the sex-specificity of the brain templates. It was observed that the female and male test subjects were registered to their sex-specific templates with the lowest amount of deformation/warping confirming better representativeness of the sex-specific templates for their target population. The findings of this study including the templates and the reported variations can be used in research involving sex dimorphic brain disorders, diseases, and/or injuries such as traumatic brain injury that is affected by the sex-based brain anatomical differences. Statement of significance: Human brain exhibits sex-based variation both in size and volumetric composition of different regions. Despite these differences, there is a paucity of sex-specific brain templates. Addressing this gap marks the significance of our study as briefly explained here. We have shown that differences in male and female brain go beyond simple scaling and the observation of regional differences that are not proportional to the sex-based total brain volume variations has motivated us to develop sex-specific templates. The representativeness and difference of these sex-specific templates were assessed by measuring the amount of required warping in nonlinear registration of test subjects to them. It was shown that registration of female and male subjects to their corresponding sex-specific template involved lower level of warping compared to their registration to their opposite sex or mixed population brain template. 

Abstract Head acceleration measurement sensors are now widely deployed in the field to monitor head kinematic exposure in contact sports. The wealth of impact kinematics data provides valuable, yet challenging, opportunities to study the biomechanical basis of mild traumatic brain injury (mTBI) and subconcussive kinematic exposure. Head impact kinematics are translated into brain mechanical responses through physics-based computational simulations using validated brain models to study the mechanisms of injury. First, this article reviews representative legacy and contemporary brain biomechanical models primarily used for blunt impact simulation. Then, it summarizes perspectives regarding the development and validation of these models, and discusses how simulation results can be interpreted to facilitate injury risk assessment and head acceleration exposure monitoring in the context of contact sports. Recommendations and consensus statements are presented on the use of validated brain models in conjunction with kinematic sensor data to understand the biomechanics of mTBI and subconcussion. Mainly, there is general consensus that validated brain models have strong potential to improve injury prediction and interpretation of subconcussive kinematic exposure over global head kinematics alone. Nevertheless, a major roadblock to this capability is the lack of sufficient data encompassing different sports, sex, age and other factors. The authors recommend further integration of sensor data and simulations with modern data science techniques to generate large datasets of exposures and predicted brain responses along with associated clinical findings. These efforts are anticipated to help better understand the biomechanical basis of mTBI and improve the effectiveness in monitoring kinematic exposure in contact sports for risk and injury mitigation purposes.