Consequences of head size following trauma to the human head

American Football On-Field Head Impact Kinematics: Influence of Acceleration Signal Characteristics on Peak Maximal Principal Strain

Recorded head kinematics from head-impact measurement devices (HIMd) are pivotal for evaluating brain stress and strain through head finite element models (hFEM). The variability in kinematic recording windows across HIMd presents challenges as they yield inconsistent hFEM responses. Despite establishing an ideal recording window for maximum principal strain (MPS) in brain tissue, uncertainties persist about the impact characteristics influencing vulnerability when this window is shortened. This study aimed to scrutinize factors within impact kinematics affecting the reliability of different recording windows on whole-brain peak MPS using a validated hFEM. Utilizing 53 on-field head impacts recorded via an instrumented mouthguard during a Canadian varsity football game, 10 recording windows were investigated with varying pre- and post-impact-trigger durations. Tukey pair-wise comparisons revealed no statistically significant differences in MPS responses for the different recording windows. However, specific impacts showed marked variability up to 40%. It was found, through correlation analyses, that impacts with lower peak linear acceleration exhibited greater response variability across different pre-trigger durations. Signal shape, analyzed through spectral analysis, influenced the time required for MPS development, resulting in specific impacts requiring a prolonged post-trigger duration. This study adds to the existing consensus on standardizing HIMd acquisition time windows and sheds light on impact characteristics leading to peak MPS variation across different head impact kinematic recording windows. Considering impact characteristics in research assessments is crucial, as certain impacts, affected by recording duration, may lead to significant errors in peak MPS responses during cumulative longitudinal exposure assessments.

Anatomical Features and Material Properties of Human Surrogate Head Models Affect Spatial and Temporal Brain Motion under Blunt Impact

Traumatic brain injury (TBI) is a biomechanical problem where the initiating event is dynamic loading (blunt, inertial, blast) to the head. To understand the relationship between the mechanical parameters of the injury and the deformation patterns in the brain, we have previously developed a surrogate head (SH) model capable of measuring spatial and temporal deformation in a surrogate brain under blunt impact. The objective of this work was to examine how material properties and anatomical features affect the motion of the brain and the development of injurious deformations. The SH head model was modified to study six variables independently under blunt impact: surrogate brain stiffness, surrogate skull stiffness, inclusion of cerebrospinal fluid (CSF), head/skull size, inclusion of vasculature, and neck stiffness. Each experimental SH was either crown or frontally impacted at 1.3 m/s (3 mph) using a drop tower system. Surrogate brain material, the Hybrid III neck stiffness, and skull stiffness were measured and compared to published properties. Results show that the most significant variables affecting changes in brain deformation are skull stiffness, inclusion of CSF and surrogate brain stiffness. Interestingly, neck stiffness and SH size significantly affected the strain rate only suggesting these parameters are less important in blunt trauma. While the inclusion of vasculature locally created strain concentrations at the interface of the artery and brain, overall deformation was reduced.

An inverse analysis procedure for characterizing the homogeneous skull model used for predicting blast-induced brain response

Based upon the homogeneous skull model, the skull/brain assembly can be simplified as a homogeneous-shell (HMS)/core structure, in which the exterior shell and interior core represent the skull and brain, respectively. From the blast responses of the spherical shell/core structures calculated via finite element modeling, it is found that the existing homogeneous skull model developed by the well-accepted approach based upon three-point bending tests cannot properly describe the blast response of the skull, modeled as a three-layered sandwich (TLS) shell in the present work, e.g. the average error in the calculated core (brain) pressure is up to ∼30%. Moreover, an innovative approach based upon inverse analysis procedure is then proposed to develop a modified homogeneous skull model, which can give a proper description of the blast response of the skull (a TLS shell), e.g. the average error in the calculated core (brain) pressure is reduced to ∼7%. It is concluded that the well-accepted three-point bending approach cannot develop an effective HMS skull model for studying the blast response of the skull/brain assembly, upon which the model parameter will be overestimated by ∼60%; instead, the innovative approach based upon inverse analysis procedure should be adopted.

Evaluating child helmet protection and testing standards: A study using PIPER child head models aged 1.5, 3, 6, and 18 years

The anatomy of children's heads is unique and distinct from adults, with smaller and softer skulls and unfused fontanels and sutures. Despite this, most current helmet testing standards for children use the same peak linear acceleration threshold as for adults. It is unclear whether this is reasonable and otherwise what thresholds should be. To answer these questions, helmet-protected head responses for different ages are needed which is however lacking today. In this study, we apply continuously scalable PIPER child head models of 1.5, 3, and 6 years old (YO), and an upgraded 18YO to study child helmet protection under extensive linear and oblique impacts. The results of this study reveal an age-dependence trend in both global kinematics and tissue response, with younger children experiencing higher levels of acceleration and velocity, as well as increased skull stress and brain strain. These findings indicate the need for better protection for younger children, suggesting that youth helmets should have a lower linear kinematic threshold, with a preliminary value of 150g for 1.5-year-old helmets. However, the results also show a different trend in rotational kinematics, indicating that the threshold of rotational velocity for a 1.5YO is similar to that for adults. The results also support the current use of small-sized adult headforms for testing child helmets before new child headforms are available.

A Morphologically Individualized Deep Learning Brain Injury Model

The brain injury modeling community has recommended improving model subject specificity and simulation efficiency. Here, we extend an instantaneous (< 1 sec) convolutional neural network (CNN) brain model based on the anisotropic Worcester Head Injury Model (WHIM) V1.0 to account for strain differences due to individual morphological variations. Linear scaling factors relative to the generic WHIM along the three anatomical axes are used as additional CNN inputs. To generate training samples, the WHIM is randomly scaled to pair with augmented head impacts randomly generated from real-world data for simulation. An estimation of voxelized peak maximum principal strain of the whole-brain is said to be successful when the linear regression slope and Pearson's correlation coefficient relative to directly simulated do not deviate from 1.0 (when identical) by more than 0.1. Despite a modest training dataset (N = 1363 vs. ∼5.7 k previously), the individualized CNN achieves a success rate of 86.2% in cross-validation for scaled model responses, and 92.1% for independent generic model testing for impacts considered as complete capture of kinematic events. Using 11 scaled subject-specific models (with scaling factors determined from pre-established regression models based on head dimensions and sex and age information, and notably, without neuroimages), the morphologically individualized CNN remains accurate for impacts that also yield successful estimations for the generic WHIM. The individualized CNN instantly estimates subject-specific and spatially detailed peak strains of the entire brain and thus, supersedes others that report a scalar peak strain value incapable of informing the location of occurrence. This tool could be especially useful for youths and females due to their anticipated greater morphological differences relative to the generic model, even without the need for individual neuroimages. It has potential for a wide range of applications for injury mitigation purposes and the design of head protective gears. The voxelized strains also allow for convenient data sharing and promote collaboration among research groups.

Thoughts and perspectives on biomechanical numerical models under impacts: Are women forgotten from research?

The present paper explores a series of articles in the literature which deal with impact biomechanics of the head and thorax/abdomen segments, investigating the "sex specific properties/data" used in the studies. Statements in these studies are analyzed and point out, the use of male or female subjects for the developments of finite element models and their validation against experimental data. The present analysis raises the question about "androcentrism," and how biomechanical engineering findings and the design of the derived protecting devices are focused on male subjects.

Approximating subject-specific brain injury models via scaling based on head-brain morphological relationships

Most human head/brain models represent a generic adult male head/brain. They may suffer in accuracy when investigating traumatic brain injury (TBI) on a subject-specific basis. Subject-specific models can be developed from neuroimages; however, neuroimages are not typically available in practice. In this study, we establish simple and elegant regression models between brain outer surface morphology and head dimensions measured from neuroimages along with age and sex information (N = 191; 141 males and 50 females with age ranging 14-25 years). The regression models are then used to approximate subject-specific brain models by scaling a generic counterpart, without using neuroimages. Model geometrical accuracy is assessed using adjusted [Formula: see text] and absolute percentage error (e.g., 0.720 and 3.09 ± 2.38%, respectively, for brain volume when incorporating tragion-to-top). For a subset of 11 subjects (from smallest to largest in brain volume), impact-induced brain strains are compared with those from "morphed models" derived from neuroimage-based mesh warping. We find that regional peak strains from the scaled subject-specific models are comparable to those of the morphed counterparts but could be considerably different from those of the generic model (e.g., linear regression slope of 1.01-1.03 for gray and white matter regions versus 1.16-1.19, or up to ~ 20% overestimation for the smallest brain studied). These results highlight the importance of incorporating brain morphological variations in impact simulation and demonstrate the feasibility of approximating subject-specific brain models without neuroimages using age, sex, and easily measurable head dimensions. The scaled models may improve subject specificity for future TBI investigations.

Use of Brain Biomechanical Models for Monitoring Impact Exposure in Contact Sports

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.

Concussion Prone Scenarios: A Multi-Dimensional Exploration in Impact Directions, Brain Morphology, and Network Architectures Using Computational Models

While individual susceptibility to traumatic brain injury (TBI) has been speculated, past work does not provide an analysis considering how physical features of an individual's brain (e.g., brain size, shape), impact direction, and brain network features can holistically contribute to the risk of suffering a TBI from an impact. This work investigated each of these features simultaneously using computational modeling and analyses of simulated functional connectivity. Unlike the past studies that assess the severity of TBI based on the quantification of brain tissue damage (e.g., principal strain), we approached the brain as a complex network in which neuronal oscillations orchestrate to produce normal brain function (estimated by functional connectivity) and, to this end, both the anatomical damage location and its topological characteristics within the brain network contribute to the severity of brain function disruption and injury. To represent the variations in the population, we analyzed a publicly available database of brain imaging data and selected five distinct network architectures, seven different brain sizes, and three uniaxial head rotational conditions to study the consequences of 74 virtual impact scenarios. Results show impact direction produces the most significant change in connections across brain areas (structural connectome) and the functional coupling of activity across these brain areas (functional connectivity). Axial rotations were more injurious than those with sagittal and coronal rotations when the head kinematics were the same for each condition. When the impact direction was held constant, brain network architecture showed a significantly different vulnerability across axial and sagittal, but not coronal rotations. As expected, brain size significantly affected the expected change in structural and functional connectivity after impact. Together, these results provided groupings of predicted vulnerability to impact-a subgroup of male brain architectures exposed to axial impacts were most vulnerable, while a subgroup of female brain architectures was the most tolerant to the sagittal impacts studied. These findings lay essential groundwork for subject-specific analyses of concussion and provide invaluable guidance for designing personalized protection equipment.

Quantifying the Effect of Sex and Neuroanatomical Biomechanical Features on Brain Deformation Response in Finite Element Brain Models

Recent automotive epidemiology studies have concluded that females have significantly higher odds of sustaining a moderate brain injury or concussion than males in a frontal crash after controlling for multiple crash and occupant variables. Differences in neuroanatomical features, such as intracranial volume (ICV), have been shown between male and female subjects, but how these sex-specific neuroanatomical differences affect brain deformation is unknown. This study used subject-specific finite element brain models, generated via registration-based morphing using both male and female magnetic resonance imaging scans, to investigate sex differences of a variety of neuroanatomical features and their effect on brain deformation; additionally, this study aimed to determine the relative importance of these neuroanatomical features and sex on brain deformation metrics for a single automotive loading environment. Based on the Bayesian linear mixed models, sex had a significant effect on ICV, white matter volume and gray matter volume, as well as a section of cortical gray matter regions' thicknesses and volumes; however, after these neuroanatomical features were accounted for in the statistical model, sex was not a significant factor in predicting brain deformation. ICV had the highest relative effect on the brain deformation metrics assessed. Therefore, ICV should be considered when investigating both brain injury biomechanics and injury risk.

Brain architecture-based vulnerability to traumatic injury

The white matter tracts forming the intricate wiring of the brain are subject-specific; this heterogeneity can complicate studies of brain function and disease. Here we collapse tractography data from the Human Connectome Project (HCP) into structural connectivity (SC) matrices and identify groups of similarly wired brains from both sexes. To characterize the significance of these architectural groupings, we examined how similarly wired brains led to distinct groupings of neural activity dynamics estimated with Kuramoto oscillator models (KMs). We then lesioned our networks to simulate traumatic brain injury (TBI) and finally we tested whether these distinct architecture groups’ dynamics exhibited differing responses to simulated TBI. At each of these levels we found that brain structure, simulated dynamics, and injury susceptibility were all related to brain grouping. We found four primary brain architecture groupings (two male and two female), with similar architectures appearing across both sexes. Among these groupings of brain structure, two architecture types were significantly more vulnerable than the remaining two architecture types to lesions. These groups suggest that mesoscale brain architecture types exist, and these architectural differences may contribute to differential risks to TBI and clinical outcomes across the population.

Mechanical and morphological properties of parietal bone in patients with sagittal craniosynostosis

Limited information is available on the effect of sagittal craniosynostosis (CS) on morphological and material properties of the parietal bone. Understanding these properties would not only provide an insight into bone response to surgical procedures but also improve the accuracy of computational models simulating these surgeries. The aim of the present study was to characterise the mechanical and microstructural properties of the cortical table and diploe in parietal bone of patients affected by sagittal CS. Twelve samples were collected from pediatric patients (11 males, and 1 female; age 5.2 ± 1.3 months) surgically treated for sagittal CS. Samples were imaged using micro-computed tomography (micro-CT); and mechanical properties were extracted by means of micro-CT based finite element modelling (micro-FE) of three-point bending test, calibrated using sample-specific experimental data. Reference point indentation (RPI) was used to validate the micro-FE output. Bone samples were classified based on their macrostructure as unilaminar or trilaminar (sandwich) structure. The elastic moduli obtained using RPI and micro-FE approaches for cortical tables (E_RPI 3973.33 ± 268.45 MPa and E_micro-FE 3438.11 ± 387.38 MPa) in the sandwich structure and diploe (E_RPI1958.17 ± 563.79 MPa and E_micro-FE 1960.66 ± 492.44 MPa) in unilaminar samples were in strong agreement (r = 0.86, p < .01). We found that the elastic modulus of cortical tables and diploe were correlated with bone mineral density. Changes in the microstructure and mechanical properties of bone specimens were found to be irrespective of patients' age. Although younger patients are reported to benefit more from surgical intervention as skull is more malleable, understanding the material properties is critical to better predict the surgical outcome in patients <1 year old since age-related changes were minimal.

Subject-Specific Head Model Generation by Mesh Morphing: A Personalization Framework and Its Applications

Finite element (FE) head models have become powerful tools in many fields within neuroscience, especially for studying the biomechanics of traumatic brain injury (TBI). Subject-specific head models accounting for geometric variations among subjects are needed for more reliable predictions. However, the generation of such models suitable for studying TBIs remains a significant challenge and has been a bottleneck hindering personalized simulations. This study presents a personalization framework for generating subject-specific models across the lifespan and for pathological brains with significant anatomical changes by morphing a baseline model. The framework consists of hierarchical multiple feature and multimodality imaging registrations, mesh morphing, and mesh grouping, which is shown to be efficient with a heterogeneous dataset including a newborn, 1-year-old (1Y), 2Y, adult, 92Y, and a hydrocephalus brain. The generated models of the six subjects show competitive personalization accuracy, demonstrating the capacity of the framework for generating subject-specific models with significant anatomical differences. The family of the generated head models allows studying age-dependent and groupwise brain injury mechanisms. The framework for efficient generation of subject-specific FE head models helps to facilitate personalized simulations in many fields of neuroscience.

Mechanical characterisation of the human dura mater, falx cerebri and superior sagittal sinus

The cranial meninges have been shown to play a pivotal role in traumatic brain injury mechanopathology. However, while the mechanical response of the brain and its many subregions have been studied extensively, the meninges have conventionally been overlooked. This paper presents the first comparative mechanical analysis of human dura mater, falx cerebri and superior sagittal sinus tissues. Biaxial tensile analysis identified that these tissues are mechanically heterogeneous, in contrast to the assumption that the tissues are mechanically homogeneous which is typically employed in FE model design. A thickness of 0.91 ± 0.05 (standard error) mm for the falx cerebri was also identified. This data can aid in improving the biofidelity of the influential falx structure in FE models. Additionally, the use of a collagen hybridizing peptide on the superior sagittal sinus suggests this structure is particularly susceptible to the effects of circumferential stretch, which may have important implications for clinical treatment of dural venous sinus pathologies. Collectively, this research progresses understanding of meningeal mechanical and structural characteristics and may aid in elucidating the behaviour of these tissues in healthy and diseased conditions. STATEMENT OF SIGNIFICANCE: This study presents the first evaluation of human falx cerebri and superior sagittal sinus mechanical, geometrical and structural properties, along with a comparison to cranial dura mater. To mechanically characterise the tissues, biaxial tensile testing is conducted on the tissues. This analysis identifies, for the first time, mechanical stiffness differences between these tissues. Additionally, geometrical analysis identifies that there are thickness differences between the tissues. The evaluation of human meningeal tissues allows for direct implementation of the novel data to finite element head injury models to enable improved biofidelity of these influential structures in traumatic brain injury simulations. This work also identifies that the superior sagittal sinus may be easily damaged during clinical angioplasty procedures, which may inform the treatment of dural sinus pathologies.

Toward subject-specific evaluation: methods of evaluating finite element brain models using experimental high-rate rotational brain motion

Computational models of the brain have become the gold standard in biomechanics to understand, predict, and mitigate traumatic brain injuries. Many models have been created and evaluated with limited experimental data and without accounting for subject-specific morphometry of the specimens in the dataset. Recent advancements in the measurement of brain motion using sonomicrometry allow for a comprehensive evaluation of brain model biofidelity using a high-rate, rotational brain motion dataset. In this study, four methods were used to determine the best technique to compare nodal displacement to experimental brain motion, including a new morphing method to match subject-specific inner skull geometry. Three finite element brain models were evaluated in this study: the isotropic GHBMC and SIMon models, as well as an anisotropic model with explicitly embedded axons (UVA-EAM). Using a weighted cross-correlation score (between 0 and 1), the anisotropic model yielded the highest average scores across specimens and loading conditions ranging from 0.53 to 0.63, followed by the isotropic GHBMC with average scores ranging from 0.46 to 0.58, and then the SIMon model with average scores ranging from 0.36 to 0.51. The choice of comparison method did not significantly affect the cross-correlation score, and differences of global strain up to 0.1 were found for the morphed geometry relative to baseline models. The morphed or scaled geometry is recommended when evaluating computational brain models to capture the subject-specific skull geometry of the experimental specimens.

Vibration-based elastic parameter identification of the diploë and cortical tables in dry cranial bones

Various human skull models feature a layered cranial structure composed of homogeneous cortical tables and the inner diploë. However, there is a lack of fundamental validation work of such three-layer cranial bone models by combining high-fidelity computational modeling and rigorous experiments. Here, non-contact vibration experiments are conducted on an assortment of dry bone segments from the largest cranial bone regions (parietal, frontal, occipital, and temporal) to estimate the first handful of modal frequencies and damping ratios, as well as mode shapes, in the audio frequency regime. Numerical models that consider the cortical tables and the diploë as domains with separate isotropic material properties are constructed for each bone segment using a routine that identifies the cortical table-diploë boundaries from micro-computed tomography scan images, and reconstructs a three-dimensional geometry layer by layer. The material properties for cortical tables and diploë are obtained using a Hounsfield Unit-based mass density calculation combined with a parameter identification scheme for Young's modulus estimation. With the identified parameters, the average error between experimental and numerical modal frequencies is 1.3% and the modal assurance criterion values for most modes are above 0.90, indicating that the layered model is suitable for predicting the vibrational behavior of cranial bone. The proposed layered modeling and identified elastic parameters are also useful to support computational modeling of cranial guided waves and mode conversion in medical ultrasound. Additionally, the diploë elastic properties are rarely reported in the literature, making this work a fundamental characterization effort that can guide in the selection of material properties for human head models that consider layered cranial bone.

Head and Neck Injury Patterns among American Football Players

IMPORTANCE

American football is a popular high-impact sport, leading to 2.7 million injuries in the United States annually. Recent evidence in football-related neurological damage has spurred national interest in player-safety. Football players injure their head and neck in up to 26% of total injuries. Variation in injury patterns between age groups and correlated hospitalizations for football-related head and neck injury has yet to be characterized.

OBJECTIVE

Our aim is to evaluate injury patterns among American-football related head and neck trauma.

METHODS

A retrospective cohort study of patients with football-related head and neck injury in the National Electronic Injury Surveillance System (NEISS).

RESULTS

Nearly 100 000 ED visits for football-related head and neck injuries occur annually. Males comprised 95% of patients, with a median age of 13. The head comprised 70% of injuries followed by the face (13%). The most common diagnoses were concussions (39%), internal organ injury (26%), and lacerations (11%). Pediatric patients were more likely to sustain concussions while adults experienced more lacerations (P < .05%). Fractures and nerve damage were rare injuries but caused a disproportionate share of hospitalizations.

CONCLUSION

Pediatric males are most likely to present for emergency care from football-related injury to the head and neck. Evaluating physicians can anticipate concussions, internal organ injury, and lacerations among presenting patients. Concussions, facial fractures, and nerve damage are injuries most likely to lead to hospitalization.

Calibration of a Heterogeneous Brain Model Using a Subject-Specific Inverse Finite Element Approach

Central to the investigation of the biomechanics of traumatic brain injury (TBI) and the assessment of injury risk from head impact are finite element (FE) models of the human brain. However, many existing FE human brain models have been developed with simplified representations of the parenchyma, which may limit their applicability as an injury prediction tool. Recent advances in neuroimaging techniques and brain biomechanics provide new and necessary experimental data that can improve the biofidelity of FE brain models. In this study, the CAB-20MSym template model was developed, calibrated, and extensively verified. To implement material heterogeneity, a magnetic resonance elastography (MRE) template image was leveraged to define the relative stiffness gradient of the brain model. A multi-stage inverse FE (iFE) approach was used to calibrate the material parameters that defined the underlying non-linear deviatoric response by minimizing the error between model-predicted brain displacements and experimental displacement data. This process involved calibrating the infinitesimal shear modulus of the material using low-severity, low-deformation impact cases and the material non-linearity using high-severity, high-deformation cases from a dataset of in situ brain displacements obtained from cadaveric specimens. To minimize the geometric discrepancy between the FE models used in the iFE calibration and the cadaveric specimens from which the experimental data were obtained, subject-specific models of these cadaveric brain specimens were developed and used in the calibration process. Finally, the calibrated material parameters were extensively verified using independent brain displacement data from 33 rotational head impacts, spanning multiple loading directions (sagittal, coronal, axial), magnitudes (20–40 rad/s), durations (30–60 ms), and severity. Overall, the heterogeneous CAB-20MSym template model demonstrated good biofidelity with a mean overall CORA score of 0.63 ± 0.06 when compared to in situ brain displacement data. Strains predicted by the calibrated model under non-injurious rotational impacts in human volunteers (N = 6) also demonstrated similar biofidelity compared to in vivo measurements obtained from tagged magnetic resonance imaging studies. In addition to serving as an anatomically accurate model for further investigations of TBI biomechanics, the MRE-based framework for implementing material heterogeneity could serve as a foundation for incorporating subject-specific material properties in future models.

An anatomically detailed and personalizable head injury model: Significance of brain and white matter tract morphological variability on strain

Finite element head (FE) models are important numerical tools to study head injuries and develop protection systems. The generation of anatomically accurate and subject-specific head models with conforming hexahedral meshes remains a significant challenge. The focus of this study is to present two developmental works: first, an anatomically detailed FE head model with conforming hexahedral meshes that has smooth interfaces between the brain and the cerebrospinal fluid, embedded with white matter (WM) fiber tracts; second, a morphing approach for subject-specific head model generation via a new hierarchical image registration pipeline integrating Demons and Dramms deformable registration algorithms. The performance of the head model is evaluated by comparing model predictions with experimental data of brain-skull relative motion, brain strain, and intracranial pressure. To demonstrate the applicability of the head model and the pipeline, six subject-specific head models of largely varying intracranial volume and shape are generated, incorporated with subject-specific WM fiber tracts. DICE similarity coefficients for cranial, brain mask, local brain regions, and lateral ventricles are calculated to evaluate personalization accuracy, demonstrating the efficiency of the pipeline in generating detailed subject-specific head models achieving satisfactory element quality without further mesh repairing. The six head models are then subjected to the same concussive loading to study the sensitivity of brain strain to inter-subject variability of the brain and WM fiber morphology. The simulation results show significant differences in maximum principal strain and axonal strain in local brain regions (one-way ANOVA test, p < 0.001), as well as their locations also vary among the subjects, demonstrating the need to further investigate the significance of subject-specific models. The techniques developed in this study may contribute to better evaluation of individual brain injury and the development of individualized head protection systems in the future. This study also contains general aspects the research community may find useful: on the use of experimental brain strain close to or at injury level for head model validation; the hierarchical image registration pipeline can be used to morph other head models, such as smoothed-voxel models.

Analysis of HIC and Hydrostatic Pressure in the Human Head during NOCSAE Tests of American Football Helmets

Brain damage is a serious economic and social burden. Contact sports such as American football, are one of the most common sources of concussions. The biomechanical response of the head-helmet system caused by dynamic loading plays a major role. The literature has focused on measuring the resultant kinematics that act on the head and helmet during tackles. However, few studies have focused on helmet validation tests, supported by recent findings and emerging numerical approaches. The future of helmet standards could benefit from insights at the level of injury mechanisms, using numerical tools to assess the helmets. Therefore, in this work, a numerical approach is employed to investigate the influence of intracranial pressure (ICP) on brain pathophysiology during and after helmeted impacts, which are common in American football. The helmeted impacts were performed at several impact locations according to the NOCSAE standard (configurations A, AP, B, C, D, F, R, UT). In order to evaluate the ICP levels, the αHEAD finite element head and brain model was combined with a Hybrid III-neck structure and then coupled with an American football helmet to simulate the NOCSAE impacts. In addition, the ICP level was analyzed together with the resulting HIC value, since the latter is commonly used, in this application and others, as the injury criterion. The obtained results indicate that ICP values exceed the common threshold of head injury criteria and do not correlate with HIC values. Thus, this work raises concern about applying the HIC to predict brain injury in American football direct head impacts, since it does not correlate with ICP predicted with the FE head model.

The importance of modeling the human cerebral vasculature in blunt trauma

BACKGROUND

Multiple studies describing human head finite element (FE) models have established the importance of including the major cerebral vasculature to improve the accuracy of the model predictions. However, a more detailed network of cerebral vasculature, including the major veins and arteries as well as their branch vessels, can further enhance the model-predicted biomechanical responses and help identify correlates to observed blunt-induced brain injury.

METHODS

We used an anatomically accurate three-dimensional geometry of a 50th percentile U.S. male head that included the skin, eyes, sinuses, spine, skull, brain, meninges, and a detailed network of cerebral vasculature to develop a high-fidelity model. We performed blunt trauma simulations and determined the intracranial pressure (ICP), the relative displacement (RD), the von Mises stress, and the maximum principal strain. We validated our detailed-vasculature model by comparing the model-predicted ICP and RD values with experimental measurements. To quantify the influence of including a more comprehensive network of brain vessels, we compared the biomechanical responses of our detailed-vasculature model with those of a reduced-vasculature model and a no-vasculature model.

RESULTS

For an inclined frontal impact, the predicted ICP matched well with the experimental results in the fossa, frontal, parietal, and occipital lobes, with peak-pressure differences ranging from 2.4% to 9.4%. For a normal frontal impact, the predicted ICP matched the experimental results in the frontal lobe and lateral ventricle, with peak-pressure discrepancies equivalent to 1.9% and 22.3%, respectively. For an offset parietal impact, the model-predicted RD matched well with the experimental measurements, with peak RD differences of 27% and 24% in the right and left cerebral hemispheres, respectively. Incorporating the detailed cerebral vasculature did not influence the ICP but redistributed the brain-tissue stresses and strains by as much as 30%. In addition, our detailed-vasculature model predicted strain reductions by as much as 28% when compared to current reduced-vasculature FE models that only include the major cerebral vessels.

CONCLUSIONS

Our study highlights the importance of including a detailed representation of the cerebral vasculature in FE models to more accurately estimate the biomechanical responses of the human brain to blunt impact.

Mechanical and structural characterisation of the dural venous sinuses

The dural venous sinuses play an integral role in draining venous blood from the cranial cavity. As a result of the sinuses anatomical location, they are of significant importance when evaluating the mechanopathology of traumatic brain injury (TBI). Despite the importance of the dural venous sinuses in normal neurophysiology, no mechanical analyses have been conducted on the tissues. In this study, we conduct mechanical and structural analysis on porcine dural venous sinus tissue to help elucidate the tissues’ function in healthy and diseased conditions. With longitudinal elastic moduli values ranging from 33 to 58 MPa, we demonstrate that the sinuses exhibit higher mechanical stiffness than that of native dural tissue, which may be of interest to the field of TBI modelling. Furthermore, by employing histological staining and a colour deconvolution protocol, we show that the sinuses have a collagen-dominant extracellular matrix, with collagen area fractions ranging from 84 to 94%, which likely explains the tissue’s large mechanical stiffness. In summary, we provide the first investigation of the dural venous sinus mechanical behaviour with accompanying structural analysis, which may aid in understanding TBI mechanopathology.

Hyper-viscoelastic mechanical behavior of cranial pia mater in tension

BACKGROUND

Cranial pia mater, the innermost layer of the meninges, protects the central nervous system by tightly wrapping the brain and damping the external impact force to the brain. Accurate experimental data of the mechanical property of the cranial pia mater can enhance the theoretical prediction of traumatic brain injury or the scientific surgery design for brain disease. The aim of this study is to characterize the mechanical behavior of the cranial pia mater.

METHODS

In vitro tensile and stress-relaxation experiments of ovine cranial pia mater specimens were conducted at eight strain rates to characterize the rate-dependent viscoelastic property. The tensile and stress-relaxation experimental data were fitted by an Ogden hyper-viscoelastic model with a strain rate function to describe the mechanical behavior of the cranial pia mater.

FINDINGS

The elastic modulus and the ultimate stress are significantly increased from 5.545 MPa and 0.535 MPa at 0.00167 s^-1 to 18.345 MPa and 2.547 MPa at 0.83 s^-1 (p < .0001), respectively. The initial stress and the long-term stress (300 s) are also increased significantly with the increasing strain rates (p < .0001). A good fit of the experimental data with the Ogden hyper-viscoelastic model incorporated with a strain rate function was achieved (R² > 0.93).

INTERPRETATION

The cranial pia mater exhibits as a rate-dependent hyper-viscoelastic material in the tensile and stress-relaxation experiments. Compared with the brain, the stiffer nature of the cranial pia mater indicates its essential role in brain protection. The rate-dependent constitutive model provides a proper description of the hyper-viscoelastic characteristics of the cranial pia mater in tension and may provide a basic constitutive relationship for numerical simulations of traumatic brain injury.

An anatomically detailed and personalizable head injury model: Significance of brain and white matter tract morphological variability on strain

Finite element head (FE) models are important numerical tools to study head injuries and develop protection systems. The generation of anatomically accurate and subject-specific head models with conforming hexahedral meshes remains a significant challenge. The focus of this study is to present two developmental works: first, an anatomically detailed FE head model with conforming hexahedral meshes that has smooth interfaces between the brain and the cerebrospinal fluid, embedded with white matter (WM) fiber tracts; second, a morphing approach for subject-specific head model generation via a new hierarchical image registration pipeline integrating Demons and Dramms deformable registration algorithms. The performance of the head model is evaluated by comparing model predictions with experimental data of brain-skull relative motion, brain strain, and intracranial pressure. To demonstrate the applicability of the head model and the pipeline, six subject-specific head models of largely varying intracranial volume and shape are generated, incorporated with subject-specific WM fiber tracts. DICE similarity coefficients for cranial, brain mask, local brain regions, and lateral ventricles are calculated to evaluate personalization accuracy, demonstrating the efficiency of the pipeline in generating detailed subject-specific head models achieving satisfactory element quality without further mesh repairing. The six head models are then subjected to the same concussive loading to study the sensitivity of brain strain to inter-subject variability of the brain and WM fiber morphology. The simulation results show significant differences in maximum principal strain and axonal strain in local brain regions (one-way ANOVA test, p < 0.001), as well as their locations also vary among the subjects, demonstrating the need to further investigate the significance of subject-specific models. The techniques developed in this study may contribute to better evaluation of individual brain injury and the development of individualized head protection systems in the future. This study also contains general aspects the research community may find useful: on the use of experimental brain strain close to or at injury level for head model validation; the hierarchical image registration pipeline can be used to morph other head models, such as smoothed-voxel models.

Biomechanical Comparison of Real World Concussive Impacts in Children, Adolescents, and Adults

Accidental falls occur to people of all ages, with some resulting in concussive injury. At present, it is unknown whether children and adolescents are at a comparable risk of sustaining a concussion compared to adults. This study reconstructed the impact kinematics of concussive falls for children, adolescents, and adults and simulated the associated brain tissue deformations. Patients included in this study were diagnosed with a concussion as defined by the Zurich Consensus guidelines. Eleven child, 10 adolescent, and 11 adult falls were simulated using mathematical dynamic models(MADYMO), with three ellipsoid pedestrian models sized to each age group. Laboratory impact reconstruction was conducted using Hybrid III head forms, with finite element model simulations of the brain tissue response using recorded impact kinematics from the reconstructions. The results of the child group showed lower responses than the adolescent group for impact variables of impact velocity, peak linear acceleration, and peak rotational acceleration but no statistical differences existed for any other groups. Finite element model simulations showed the child group to have lower strain values than both the adolescent and adult groups. There were no statistical differences between the adolescent and adult groups for any variables examined in this study. With the cases included in this study, young children sustained concussive injuries at lower modeled brain strains than adolescents and adults, supporting the theory that children may be more susceptible to concussive impacts than adolescents or adults.

Three-dimensional finite element analysis of the dural folds and the human skull under head acceleration

Bone and collagen fiber architecture adapt to external mechanical loads. In humans, due to the low insertion of the temporal muscle, mastication does not lead to a physiological loading of the calvaria. Forces applied to the skull by the dural folds can lead to compressive stresses in the calvaria. To investigate the relationship between mechanical loads and form in the skull and its membranes, in a finite element three-dimensional model of the human skull, loads due to head acceleration in daily activities are applied to the falx cerebri and the tentorium cerebelli. The dural folds are modeled as membranes. The stress paths in the dural folds correlate with anatomical fiber direction. Head accelerations of 9 g lead to compressive stress in the calvaria. Finite element analysis of the falx cerebri and the tentorium cerebelli can be used to study the influence of mechanical stresses on the ossification of the dural folds and their impact on calvarial growth. This study presents an example of functional loading of bone by fibrous membranes and describes a possible mechanism by which Wolff's law works on the bone of the calvaria creating evolutionarily beneficial lightweight constructions.

Certified Motorcycle Helmets: Computational Evaluation of the Efficacy of Standard Requirements with Finite Element Models

Every year, thousands of people die in the European Union as a direct result of road accidents. Helmets are one of the most important types of personal safety gear. The ECE R22.05 standard, adopted in 2000, is responsible for the certification of motorcycle helmets in the European Union and in many other countries. Two decades later, it is still being used with the same requirements, without any update. The aim of this work is to evaluate the efficacy of a motorcycle helmet certified by such standard, using computational models as an assessment tool. First, a finite element model of a motorcycle helmet available on the market was developed and validated by simulating the same impacts required by the standard. Then, a finite element model of the human head is used as an injury prediction tool to assess its safety performance. Results indicate a significant risk of brain injury, which is in accordance with previous studies available in the literature. Therefore, this work underlines and emphasizes the need of improving the requirements of ECE R22.05.

A novel repetitive head impact exposure measurement tool differentiates player position in National Football League

American-style football participation poses a high risk of repetitive head impact (RHI) exposure leading to acute and chronic brain injury. The complex nature of symptom expression, human predisposition, and neurological consequences of RHI limits our understanding of what constitutes as an injurious impact affecting the integrity of brain tissue. Video footage of professional football games was reviewed and documentation made of all head contact. Frequency of impact, tissue strain magnitude, and time interval between impacts was used to quantify RHI exposure, specific to player field position. Differences in exposure characteristics were found between eight different positions; where three unique profiles can be observed. Exposure profiles provide interpretation of the relationship between the traumatic event(s) and how tissue injury is manifested and expressed. This study illustrates and captures an objective measurement of RHI on the field, a critical component in guiding public policy and guidelines for managing exposure.

Investigation of wave propagation through head layers with focus on understanding blast wave transmission

Blast-induced traumatic brain injury (bTBI) is a critical health concern. This issue is being addressed in terms of identifying a cause-effect relationship between the mechanical insult in the form of a blast and resulting injury to the brain. Understanding wave propagation through the head is an important aspect in this regard. The objective of this work was to study the blast wave propagation through the layered architecture of the head with an emphasis on understanding the wave transmission mechanism. Toward this end, one-dimensional (1D) finite element head model is built for a simplified surrogate, human, and rat. Motivated from experimental investigations, four different head layer configurations have been considered. These configurations are: (A) Skull-Brain, (B) Skin-Skull-Brain, (C) Skin-Skull-Dura-Arachnoid-CSF-Pia-Brain, (D) Skin-Skull-Dura-Arachnoid-AT-Pia-Brain. The validated head model is subjected to flattop and Friedlander loading implied in the blast, and the resulting response is evaluated in terms of brain pressures. Our results suggest that wave propagation through head parenchyma plays an important role in blast wave transmission. The thickness, material properties of head layers, and rise time of an input pulse govern the temporal evolution of pressure in the brain. The key findings of this work are: (a) Skin and meninges amplify the applied input pressure, whereas air sinus has an attenuation effect. (b) Model is able to describe experimentally recorded peak pressures and rise times in the brain, including variations within the aforementioned experimental head models of TBI. This reinforces that the wave transmission is an important loading pathway to the brain. (c) Equivalent layer theory for modeling meningeal layers as a single layer has been proposed, and it gives reasonable agreement with each meningeal layer modeled explicitly. This modeling approach has a great utility in 3D head models. The potential applications of 1D head model in evaluation of new helmet materials, brain sensor calibration, and brain pressure estimation for a given explosive strength have also been demonstrated. Overall, these results provide important insights into the understanding of mechanics of blast wave transmission in the head.

Suitability of enhanced head injury criteria for vehicle rating

Objective: Euro NCAP is considering the implementation of a new head injury assessment with the introduction of THOR in the mobile progressive deformable barrier frontal impact crash test. The objective of this study is to assess the suitability of enhanced head injury criteria for practical application in consumer rating programs.Method: AIS2+ risk predictions from nine selected head injury criteria where calculated for 27 pairs of crash test results representing small and moderate overlap frontal crashes. The capability of each injury criteria to predict the real-world injury rates of these crash modes was evaluated. Next, the correlation coefficients between the head injury candidates were calculated and individual predictions were compared for all tests in scatter plots.Results: The results show that none of the crash tests head injury assessment predicted the four-times higher head injury rates observed in the accident data for small overlap crashes compared to moderate overlap crashes. Poor correlation was demonstrated between many leading brain injury metrics, and the risk predictions for individual vehicles differ quite substantially depending on the criterion considered. Conclusions: While preliminary, the results of this study demonstrate that more evaluation of the most suitable brain injury criteria is necessary before consideration into a consumer evaluation program. Convergence of the head injury criteria risks for individual cases should be part of the validation process for enhanced head injury criteria, since identical head signals should yield similar injury risks.

The Influence of Shear Anisotropy in mTBI: A White Matter Constitutive Model

We examine the influence of shear anisotropy of brain tissue on the potential for mild traumatic brain injury. First we develop a new constitutive description for the white matter in the brain that can capture the anisotropic behavior of the white matter in both tension and shear. The material parameters for the models are determined using a set of three experiments already published in the literature. The calibrated and parameterized model is then implemented in a computational (finite element) model of the head. This computational model is two-dimensional and is used to simulate a previously published injury-causing event in the National Hockey League, using axonal strain as criterion to assess the level of diffuse axonal injury. It is demonstrated that the inclusion of shear anisotropy affects both the nature and the extent of predicted injury. Further, the locations of the predicted injury are more consistent with observations in the literature.

Fast Robust Dejitter and Interslice Discontinuity Removal in MRI Phase Acquisitions: Application to Magnetic Resonance Elastography

MRI phase contrast imaging methods that assemble slice-wise acquisitions into volumes can contain interslice phase discontinuities (IPDs) over the course of the scan from sources, including unavoidable physiological activity. In magnetic resonance elastography (MRE), this can alter wavelength and tissue stiffness estimates, invalidating the analysis. We first model this behavior as jitter along the z-axis of the phase of 3D complex-valued wave volumes. A two-step image processing pipeline is then proposed that removes IPDs. First, constant slicewise phase shift is removed with a novel, non-convex dejittering algorithm. Then, regional physiological noise artifacts are removed with novel filtering of 3D wavelet coefficients. Calibration of two pipeline coefficients, the dejitter parameter α and the wavelet band high-pass coefficient ω_c , was first performed on a finite-element method brain phantom. A comparative investigation was then performed, on a cohort of 48 brain acquisitions, of four approaches to IPDs: 1) the proposed method; 2) a "control" condition of neglect of IPDs; 3) an anisotropic wavelet-based method; and 4) a method of in-plane (2D) processing. The present method showed medians of [Formula: see text] Pa for a multifrequency wave inversion centered at 40 Hz which was within 6% of methods 3) and 4), while neglect produced [Formula: see text] estimates a mean of 17% lower. The proposed method reduced the value range of the cohort against methods 3) and 4) by 29% and 31%, respectively. Such reduction in variance enhances the ability of brain MRE to predict subtler physiological changes. Our theoretical approach further enables more powerful applications of fundamental findings in noise and denoising to MRE.

Lateral impacts correlate with falx cerebri displacement and corpus callosum trauma in sports-related concussions

Corpus callosum trauma has long been implicated in mild traumatic brain injury (mTBI), yet the mechanism by which forces penetrate this structure is unknown. We investigated the hypothesis that coronal and horizontal rotations produce motion of the falx cerebri that damages the corpus callosum. We analyzed previously published head kinematics of 115 sports impacts (2 diagnosed mTBI) measured with instrumented mouthguards and used finite element (FE) simulations to correlate falx displacement with corpus callosum deformation. Peak coronal accelerations were larger in impacts with mTBI (8592 rad/s² avg.) than those without (1412 rad/s² avg.). From FE simulations, coronal acceleration was strongly correlated with deep lateral motion of the falx center (r = 0.85), while horizontal acceleration was correlated with deep lateral motion of the falx periphery (r > 0.78). Larger lateral displacement at the falx center and periphery was correlated with higher tract-oriented strains in the corpus callosum body (r = 0.91) and genu/splenium (r > 0.72), respectively. The relationship between the corpus callosum and falx was unique: removing the falx from the FE model halved peak strains in the corpus callosum from 35% to 17%. Consistent with model results, we found indications of corpus callosum trauma in diffusion tensor imaging of the mTBI athletes. For a measured alteration of consciousness, depressed fractional anisotropy and increased mean diffusivity indicated possible damage to the mid-posterior corpus callosum. Our results suggest that the corpus callosum may be sensitive to coronal and horizontal rotations because they drive lateral motion of a relatively stiff membrane, the falx, in the direction of commissural fibers below.

On the Development of Interspecies Traumatic Brain Injury Correspondence Rules

Traumatic brain injury analysis in human is exceedingly difficult due to the methods in which data can be collected, thus many researchers commonly implement animal surrogates. However, use of these surrogates is costly and restricted by ethical concerns and test logistics. Computational models and simulations do not have these constraints and can produce significant amounts of data in relatively short periods. This paper shows the development of a human head and neck model and a full body porcine model. Both models are developed from high-resolution CT and MRI scans and the latest low-to-high strain rate mechanical data available in the literature to represent tissue component material behaviors. Both models are validated against experiments from the literature and used to complete an initial interspecies correspondence rule development study for blast overpressure effects. The results indicate the similarities in the way injury develops in the pig brain and human brain but these similarities occur at very different insult levels. These results are extended by a study, which shows that blast peak pressure is the driving factor in injury prediction and, depending on the injury metric used, significantly different injuries could be predicted.

Homogenization of heterogeneous brain tissue under quasi-static loading: a visco-hyperelastic model of a 3D RVE

Researches, in the recent years, reveal the utmost importance of brain tissue assessment regarding its mechanical properties, especially for automatic robotic tools, surgical robots and helmet producing. For this reason, experimental and computational investigation of the brain behavior under different conditions seems crucial. However, experiments do not normally show the distribution of stress and injury in microscopic scale, and due to various factors are costly. Development of micromechanical methods, which could predict the brain behavior more appropriately, could highly be helpful in reducing these costs. This study presents computational analysis of heterogeneous part of the brain tissue under quasi-static loading. Heterogeneity is created by irregular distribution of neurons in a representative volume element (RVE). Considering time-dependent behavior of the tissue, a visco-hyperelastic constitutive model is developed to predict the RVE behavior more realistically. The RVE is studied in different loads and load rates; 1, 2, 3, 10 and 15% strain load are applied at 0.03 and 0.2 s on the RVE as tensile and shear loads. Due to complexity in geometry, self-consistent approximation method is employed to increase the volume fraction of neurons and analyze RVE behavior in various NVFs. The results show increasing the load rate leads to a raise in the maximum stress that indicates the tissue is more vulnerable at higher rates. Moreover, stiffness of the tissue is enhanced in higher NVFs. Additionally, it is found that axons undergo higher stresses; hence, they are more sensitive in accidents which lead to axonal death and would cause TBI and DAI.

Material and Structural Modeling Aspects of Brain Tissue Deformation under Dynamic Loads

The aim of this work was to assess the numerous approaches to structural and material modeling of brain tissue under dynamic loading conditions. The current technological improvements in material modeling have led to various approaches described in the literature. However, the methods used for the determination of the brain’s characteristics have not always been stated or clearly defined and material data are even more scattered. Thus, the research described in this paper explicitly underlines directions for the development of numerical brain models. An important element of this research is the development of a numerical model of the brain based on medical imaging methods. This approach allowed the authors to assess the changes in the mechanical and geometrical parameters of brain tissue caused by the impact of mechanical loads. The developed model was verified through comparison with experimental studies on post-mortem human subjects described in the literature, as well as through numerical tests. Based on the current research, the authors identified important aspects of the modeling of brain tissue that influence the assessment of the actual biomechanical response of the brain for dynamic analyses.

Mesh Convergence Behavior and the Effect of Element Integration of a Human Head Injury Model

Numerous head injury models exist that vary in mesh density by orders of magnitude. A careful study of the mesh convergence behavior is necessary, especially in terms of strain most relevant to brain injury. To this end, as well as to investigate the effect of element integration scheme on simulated strains, we re-meshed the Worcester Head Injury Model at five mesh densities (~ 7.2-1000 k high-quality hexahedral elements of the brain). Results from explicit dynamic simulations of three cadaveric impacts and an in vivo head rotation were compared. First, scalar metrics of the whole brain only considering magnitude were used, including peak maximum principal strain and population-based median strain. They were further extended to deep white matter regions and the entire brain elements, respectively, to form two "response vectors" to account for both magnitude and distribution. Using benchmark enhanced full-integration elements (C3D8I), a minimum of 202.8 k brain elements were necessary to converge for response vectors of the deep white matter regions. This model was further used to simulate with reduced integration (C3D8R). We found that hourglass energy higher than the common rule of thumb (e.g., up to 44.38% vs. < 10% of internal energy) was necessary to maintain comparable strain relative to C3D8I. Based on these results, it is recommended that a human head injury model should have a minimum number of 202.8 k elements, or an average element size of no larger than 1.8 mm, for the brain. C3D8R formulation with relax stiffness hourglass control using a high scaling factor is also recommended to achieve sufficient accuracy without substantial computational cost.

An assessment of the role of the falx cerebri and tentorium cerebelli in the cranium of the cat (Felis silvestris catus)

The falx cerebri and the tentorium cerebelli are two projections of the dura mater in the cranial cavity which ossify to varying degrees in some mammalian species. The idea that the ossification of these structures may be necessary to support the loads arising during feeding has been proposed and dismissed in the past, but never tested quantitatively. To address this, a biomechanical model of a domestic cat (Felis silvestris catus) skull was created and the material properties of the falx and tentorium were varied for a series of loading regimes incorporating the main masticatory and neck muscles during biting. Under these loading conditions, ossification of the falx cerebri does not have a significant impact on the stress in the cranial bones. In the case of the tentorium, however, a localized increase in stress was observed in the parietal and temporal bones, including the tympanic bulla, when a non-ossified tentorium was modelled. These effects were consistent across the different analyses, irrespective of loading regime. The results suggest that ossification of the tentorium cerebelli may play a minor role during feeding activities by decreasing the stress in the back of the skull.