Recent advances in brain injury research: a new human head model development and validation

Quantitative assessment of traumatic brain injury risk in diverse age groups of females: Insights from computational biomechanics

Traumatic Brain Injury (TBI) stands as a multifaceted health concern, exhibiting varying influences across human population. This study delves into the biomechanical complexities of TBI within gender-specific contexts, focusing on females. Our primary objective is to investigate distinctive injury mechanisms and risks associated with females, emphasizing the imperative for tailored investigations within this cohort. By employing Fluid-Structure Interaction (FSI) Analysis, we conducted simulations to quantify biomechanical responses to traumatic forces across diverse age groups of females. The study utilized a scaling technique to create finite element models (FEMs). The young female FEM, based on anthropometric data, showcased a 15 % smaller head geometry compared to the young male FEM. Moreover, while the elderly female FEM closely mirrored the young female FEM in most structural aspects, it showed distinctive features such as brain atrophy and increased cerebrospinal fluid (CSF) layer thickness. Notably, the child female FEM (ages 7-11 years) replicated around 95 % of the young female FEM's geometry. These structural distinctions meticulously captured age-specific variations across our modeled female age groups. It's noteworthy that identical conditions, encompassing impact intensity, loading type, and boundary conditions, were maintained across all FEMs in this biomechanical finite element analysis, ensuring comparative results. The findings unveiled significant variations in frontal and occipital pressures among diverse age groups, highlighting potential age-related discrepancies in TBI susceptibility among females. These variations were primarily linked to differences in anatomical features, including brain volume, CSF thickness, and brain condition, as the same material properties were used in the FEMs. These results were approximately 4.70, 6.33 and 6.43 % in frontal area of brain in diverse age groups of females (young, elderly, and child) respectively compared to young male FEM. Comparing the FEM results between the young female and the elderly female, we observed a decrease in occipital brain pressure at the same point, reducing from 171,993 to 167,793 Pa, marking an approximate 2.5 % decrease. While typically the elderly exhibit greater brain vulnerability compared to the young, our findings showcase a reduction in brain pressure. Notably, upon assessing the relative movement between the brain and the skull at the point located in occipital area, we observed greater relative movement in the elderly (1.8 mm) compared to the young female (1.04 mm). Therefore, brain atrophy increases the range of motion of the brain within the cranial space. The study underscores the critical necessity for nuanced TBI risk assessment tailored to age and gender, emphasizing the importance of age-specific protective strategies in managing TBIs across diverse demographics. Future research employing individual modeling techniques and exploring a wider age spectrum holds promise in refining our understanding of TBI mechanisms and adopting targeted approaches to mitigate TBI in diverse groups.

Revealing the role of material properties in impact-related injuries: Investigating the influence of brain and skull density variations on head injury severity

Traumatic brain injuries (TBI) resulting from head impacts are a major public health concern, which prompted our research to investigate the complex relationship between the material properties of brain tissue and the severity of TBI. The goal of this research is to investigate how variations in brain and skull density influence the vulnerability of brain tissue to traumatic injury, thereby enhancing our understanding of injury mechanism. To achieve this goal, we employed a well-validated finite element head model (FEHM). The current investigation was divided into two phases: in the first one, three distinct brain viscoelastic materials that had been utilized in prior studies were analyzed. The review of the properties of these three materials has been meticulous, encompassing both the spectrum of mechanical properties and the behaviors that are relevant to the way in which brain tissue reacts to traumatic loading conditions. In the second phase, the material properties of both the brain and skull tissue, alongside the impact conditions, were held constant. After this step, the focus was directed towards the variation of density in the brain and skull, which was consistent with the results obtained from previous experimental investigations, in order to determine the precise impact of these variations in density. This approach allowed a more profound comprehension of the impacts that density had on the simulation results. In the first phase, Material No. 2 exhibited the highest maximum first principal strain value in the frontal region (ε max = 15.41 % ), indicating lower stiffness to instantaneous deformation. This characteristic suggests that Material No. 2 may deform more extensively upon impact, potentially increasing the risk of injury due to its viscoelastic behavior. In contrast, Material No. 1, with a lower maximum first principal strain in the frontal region (ε max = 7.87 % ), displayed greater stiffness to instantaneous deformation, potentially reducing the risk of brain injury upon head impact. The second phase provided quantitative findings revealing a proportional relationship between brain tissue density and the pressures experienced by the brain. A 2 % increase in brain tissue density corresponded to approximately a 1 % increase in pressure on the brain tissue. Similarly, changes in skull density exhibited a similar quantitative relationship, with a 6 % increase in skull density leading to a 2.5 % increase in brain pressure. This preliminary approximate ratio of 2 to 1 between brain and skull density variations provides an initial quantitative framework for assessing the impact of density changes on brain vulnerability. These findings have several implications for the development of protective measures and injury prevention strategies, particularly in contexts where head trauma is a major issue.

Brain Material Properties and Integration of Arachnoid Complex for Biofidelic Impact Response for Human Head Finite Element Model

Finite element head models offer great potential to study brain-related injuries; however, at present may be limited by geometric and material property simplifications required for continuum-level human body models. Specifically, the mechanical properties of the brain tissues are often represented with simplified linear viscoelastic models, or the material properties have been optimized to specific impact cases. In addition, anatomical structures such as the arachnoid complex have been omitted or implemented in a simple lumped manner. Recent material test data for four brain regions at three strain rates in three modes of loading (tension, compression, and shear) was used to fit material parameters for a hyper-viscoelastic constitutive model. The material model was implemented in a contemporary detailed head finite element model. A detailed representation of the arachnoid trabeculae was implemented with mechanical properties based on experimental data. The enhanced head model was assessed by re-creating 11 ex vivo head impact scenarios and comparing the simulation results with experimental data. The hyper-viscoelastic model faithfully captured mechanical properties of the brain tissue in three modes of loading and multiple strain rates. The enhanced head model showed a high level of biofidelity in all re-created impacts in part due to the improved brain-skull interface associated with implementation of the arachnoid trabeculae. The enhanced head model provides an improved predictive capability with material properties based on tissue level data and is positioned to investigate head injury and tissue damage in the future.

Investigation of Head Kinematics and Brain Strain Response During Soccer Heading Using a Custom-Fit Instrumented Mouthguard

Association football, also known as soccer in some regions, is unique in encouraging its participants to intentionally use their head to gain a competitive advantage, including scoring a goal. Repetitive head impacts are now being increasingly linked to an inflated risk of developing long-term neurodegenerative disease. This study investigated the effect of heading passes from different distances, using head acceleration data and finite element modelling to estimate brain injury risk. Seven university-level participants wore a custom-fitted instrumented mouthguard to capture linear and angular acceleration-time data. They performed 10 headers within a laboratory environment, from a combination of short, medium, and long passes. Kinematic data was then used to calculate peak linear acceleration, peak angular velocity, and peak angular acceleration as well as two brain injury metrics: head injury criterion and rotational injury criterion. Six degrees of freedom acceleration-time data were also inputted into a widely accepted finite element brain model to estimate strain-response using mean peak strain and cumulative strain damage measure values. Five headers were considered to have a 25% concussion risk. Mean peak linear acceleration equalled 26 ± 7.9 g, mean peak angular velocity 7.20 ± 2.18 rad/s, mean peak angular acceleration 1730 ± 611 rad/s2, and 95th percentile mean peak strain 0.0962 ± 0.252. Some of these data were similar to brain injury metrics reported from American football, which supports the need for further investigation into soccer heading.

Regional Strain Response of an Anatomically Accurate Human Finite Element Head Model Under Frontal Versus Lateral Loading

INTRODUCTION

Because brain regions are responsible for specific functions, regional damage may cause specific, predictable symptoms. However, the existing brain injury criteria focus on whole brain response. This study developed and validated a detailed human brain computational model with sufficient fidelity to include regional components and demonstrate its feasibility to obtain region-specific brain strains under selected loading.

METHODS

Model development used the Simulated Injury Monitor (SIMon) model as a baseline. Each SIMon solid element was split into 8, with each shell element split into 4. Anatomical regions were identified from FreeSurfer fsaverage neuroimaging template. Material properties were obtained from literature. The model was validated against experimental intracranial pressure, brain-skull displacement, and brain strain data. Model simulations used data from laboratory experiments with a rigid arm pendulum striking a helmeted head-neck system. Data from impact tests (6 m/s) at 2 helmet sites (front and left) were used.

RESULTS

Model validation showed good agreement with intracranial pressure response, fair to good agreement with brain-skull displacement, and good agreement for brain strain. CORrelation Analysis scores were between 0.72 and 0.93 for both maximum principal strain (MPS) and shear strain. For frontal impacts, regional MPS was between 0.14 and 0.36 (average of left and right hemispheres). For lateral impacts, MPS was between 0.20 and 0.48 (left hemisphere) and between 0.22 and 0.51 (right hemisphere). For frontal impacts, regional cumulative strain damage measure (CSDM20) was between 0.01 and 0.87. For lateral impacts, CSDM20 was between 0.36 and 0.99 (left hemisphere) and between 0.09 and 0.93 (right hemisphere).

CONCLUSIONS

Recognizing that neural functions are related to anatomical structures and most model-based injury metrics focus on whole brain response, this study developed an anatomically accurate human brain model to capture regional responses. Model validation was comparable with current models. The model provided sufficient anatomical detail to describe brain regional responses under different impact conditions.

An investigation of the effect of brain atrophy on brain injury in multiple sclerosis

Multiple sclerosis (MS) is a disease of the central nervous system (CNS) that affects the brain and spinal cord. It is estimated that the average prevalence of MS is 35.9 cases per 100,000 and a total of 2.8 million people worldwide have MS. Brain atrophy is usually seen in the early stages of MS, and its progress is faster than healthy people. The present study was a numerical study that uses the Fluid-structure interaction (FSI) model to investigate the effect of brain atrophy on brain injury in MS. Firstly, a healthy model was constructed from MRI images and validated by experimental data. Then three models with different degrees of brain atrophy, which showed the rate of brain atrophy in different years in MS patients, were developed to model the brain atrophy in MS. The models were subjected to two different types of impact conditions. Type I, which only produced a translational motion and the HIC value of 744, was applied to each model. Type II produced both translational and rotational motion. In this type of impact, the experimental kinematics, with peaks of 450 g for the translational acceleration and 26.2 krad/s2 for the rotational acceleration, were applied to the nodes that located in the center of gravity of the head models and the results were extracted from each one. According to the results of impact type I, the pressure of the frontal lobe of the brain is 149,647 Pa in the health model and 137,690 Pa in the model with severe atrophy.

Assessment of brain injury characterization and influence of modeling approaches

In this study, using computational biomechanics models, we investigated influence of the skull-brain interface modeling approach and the material property of cerebrum on the kinetic, kinematic and injury outputs. Live animal head impact tests of different severities were reconstructed in finite element simulations and DAI and ASDH injury results were compared. We used the head/brain models of Total HUman Model for Safety (THUMS) and Global Human Body Models Consortium (GHBMC), which had been validated under several loading conditions. Four modeling approaches of the skull-brain interface in the head/brain models were evaluated. They were the original models from THUMS and GHBMC, the THUMS model with skull-brain interface changed to sliding contact, and the THUMS model with increased shear modulus of cerebrum, respectively. The results have shown that the definition of skull-brain interface would significantly influence the magnitude and distribution of the load transmitted to the brain. With sliding brain-skull interface, the brain had lower maximum principal stress compared to that with strong connected interface, while the maximum principal strain slightly increased. In addition, greater shear modulus resulted in slightly higher the maximum principal stress and significantly lower the maximum principal strain. This study has revealed that using models with different modeling approaches, the same value of injury metric may correspond to different injury severity.

An investigation of cerebral bridging veins rupture due to head trauma

Subdural hematoma (SDH) is common abnormality that is caused by the rupture of cerebral bridge veins (BVs). It occurs in more than 30% of severe head injuries. The purpose of this research was to develop a numerical model to examine the effects of brain atrophy and age on the rupture of bridging veins in subdural hematoma. Three types of models were developed to simulate subdural hematoma, namely global solid, global FSI, and local solid models. In the next step, a head impact with the head injury criterion (HIC) value of 744 was applied as a loading condition to global models. For the global solid models, we measured the relative displacement between the skull and brain. We extracted the pressure distribution from the global FSI models. The data were used as boundary conditions on the local models to evaluate the damage to the cerebral bridge veins precisely The results showed that the relative displacement was greater in the atrophied model compared to the healthy one (2.64 and 2.20 mm, respectively). In addition, the pressure value was higher in atrophied models. In the healthy local model, the maximum strain on BVs was around 1.38, while in the atrophied model, it was 2.77. The head impact, which had a HIC value of 744, did not cause serious injury to a human with a healthy brain, but it caused severe damage to an atrophied brain. The degeneration of the brain and intracranial space changes are two important factors for the movement of the brain and its vulnerability to impact.

Research on Neck Response of Elderly Drivers in Rear Collision

In order to study the neck response of elderly drivers in rear collision, a finite element model for elderly neck was built. By comparing the cadaver experiment data in the literature, the simulation reliability of the head and neck model of the elderly under dynamic load was verified. Through the C-NCAP rear-end collision test on the elderly model, the study showed that the neck of the elderly driver had good dynamic response characteristics. The verified finite element model was used to analyze the head and neck collision response and injury risk of the elderly under different distances between the head and the headrest (vertical distance and horizontal distance). By analyzing the head and neck injuries of occupants at different distances, it was found that when the horizontal distance was 50 mm, and the vertical distance was between +10 and ~+20 mm, the headrest could play the best role in protecting the neck of the elderly driver and could reduce the degree of injury of the elderly driver in the process of rear collision.

Development and Validation of a New Anisotropic Visco-Hyperelastic Human Head Finite Element Model Capable of Predicting Multiple Brain Injuries

This paper reports on the latest refinement of the Finite Element Global Human Body Models Consortium 50th percentile (GHBMC M50) adult male head model by the development and incorporation of a new material model into the white matter tissue of the brain. The white matter is represented by an anisotropic visco-hyperelastic material model capable of simulating direction-dependent response of the brain tissue to further improve the bio-fidelity and injury predictive capability of the model. The parameters representing the material were optimized by comparing model responses to seven experimentally reported strain responses of brains of postmortem human subjects (PMHS) subjected to head impact. The head model was subjected to rigorous validation against experimental data on force–deflection responses in the skull and face, intracranial pressure, and brain strain responses from over 34 PMHS head impact experiments. Crash-induced injury indices (CIIs) for facial bone fracture, skull fracture, cerebral contusion, acute subdural hematomas (ASDHs), and diffuse brain injury were developed by reconstructing 32 PMHS and real-world injury cases with the model. Model predicted maximum principal strain (MPS) and stress were determined as fracture CIIs for compact bone and spongy bones, respectively, in the skull and face. Brain responses in terms of MPS, MPS rates, and pressure distribution in injury producing experimental impacts were determined using the model and analyzed with logistic regression and survival analysis to develop CIIs for brain contusions, diffuse brain injuries, and ASDH. The statistical models using logistic regression and survival analysis showed high accuracy with area under the receiver operating curve greater than 0.8. Because of lack of sufficient moderate diffuse brain injury data, a statistical model was not created, but all indications are that the MPS rate is an essential brain response that discriminates between moderate and severe brain injuries. The authors stated that the current GHBMC M50 v.6.0 is an advanced tool for injury prediction and mitigation of injuries in automotive crashes, sports, recreational, and military environments.

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.

Modeling one-handed grip strangulation: Intentionality of the gesture and age influence

Strangulation is a violent act which can be lethal and is often studied in forensic context. The neck includes several anatomical elements that can evolve with aging. We therefore created a numerical human neck model including the main anatomical elements and simulated one-handed grip strangulation cases. In addition, we created 3 models each representing age groups: 20-30 years old, 30-50 years old and over 50 years old. The main changes between the different age groups are the ossification of the cartilages and the muscles mechanical properties. Several initial and boundary conditions have been tested to perform a realistic simulation of one-handed grip strangulation. Stress analysis and fracture observation were compared with the grip strength of an average man, 552 N, to look at the intentionality of the gesture. In each age group, the results show no model fracture for a force of 552 N. It is necessary to reach a minimum of 1406 N before observing a first fracture on the hyoid bone. However, it is possible to get stresses on the hyoid bone and on the thyroid cartilage way before 552 N. It thus appears that the force created by one-handed grip strangulation is not sufficient to cause fractures of the bony elements of the neck, but it remains sufficient to compress the larynx and at least reduce airflow.

Design of 3D Additively Manufactured Hybrid Structures for Cranioplasty

A wide range of materials has been considered to repair cranial defects. In the field of cranioplasty, poly(methyl methacrylate) (PMMA)-based bone cements and modifications through the inclusion of copper doped tricalcium phosphate (Cu-TCP) particles have been already investigated. On the other hand, aliphatic polyesters such as poly(ε-caprolactone) (PCL) and polylactic acid (PLA) have been frequently investigated to make scaffolds for cranial bone regeneration. Accordingly, the aim of the current research was to design and fabricate customized hybrid devices for the repair of large cranial defects integrating the reverse engineering approach with additive manufacturing, The hybrid device consisted of a 3D additive manufactured polyester porous structures infiltrated with PMMA/Cu-TCP (97.5/2.5 w/w) bone cement. Temperature profiles were first evaluated for 3D hybrid devices (PCL/PMMA, PLA/PMMA, PCL/PMMA/Cu-TCP and PLA/PMMA/Cu-TCP). Peak temperatures recorded for hybrid PCL/PMMA and PCL/PMMA/Cu-TCP were significantly lower than those found for the PLA-based ones. Virtual and physical models of customized devices for large cranial defect were developed to assess the feasibility of the proposed technical solutions. A theoretical analysis was preliminarily performed on the entire head model trying to simulate severe impact conditions for people with the customized hybrid device (PCL/PMMA/Cu-TCP) (i.e., a rigid sphere impacting the implant region of the head). Results from finite element analysis (FEA) provided information on the different components of the model.

Development of a Subhuman Primate Brain Finite Element Model to Investigate Brain Injury Thresholds Induced by Head Rotation

An anatomically detailed rhesus monkey brain FE model was developed to simulate in vivo responses of the brain of sub-human primates subjected to rotational accelerations resulting in diffuse axonal injury (DAI). The material properties used in the monkey model are those in the GHBMC 50th percentile male head model (Global Human Body Model Consortium). The angular loading simulations consisted of coronal, oblique and sagittal plane rotations with the center of rotation in neck to duplicate experimental conditions. Maximum principal strain (MPS) and Cumulative strain damage measure (CSDM) were analyzed for various white matter structures such as the cerebrum subcortical white matter, corpus callosum and brainstem. The MPS in coronal rotation were 45% to 54% higher in the brainstem, 8% to 48% higher in the corpus callosum, 13% to 22% higher in the white matter when compared to those in oblique and sagittal rotations, suggesting that more severe DAI was expected from coronal and oblique rotations as compared to that from sagittal rotation. The level 1+ DAI was associated with 1.3 to 1.42 MPS and 50% CSDM (0.5) responses in the brainstem, corpus callosum and cerebral white matter. The mass scaling method, sometimes referred to as Holbourn's inverse 2/3 power law, used for development of human brain injury criterion was evaluated to understand the effect of geometrical and anatomical differences between human and animal head. Based on simulations conducted with the animal and human models in three different planes - sagittal, coronal and horizontal - the scaling from animal to human models are not supported due to lack of geometrical similitude between the animal and human brains. Thus, the scaling method used in the development of brain injury criterion for rotational acceleration/velocity is unreliable.

The influence of impact surface on head kinematics and brain tissue response during impacts with equestrian helmets

Current equestrian standards employ a drop test to a rigid steel anvil. However, falls in equestrian sports often result in impacts with soft ground. The purpose of this study was to compare head kinematics and brain tissue response associated with surfaces impacted during equestrian accidents and corresponding helmet certification tests. A helmeted Hybrid III headform was dropped freely onto three different anvils (steel, turf and sand) at three impact locations. Peak linear acceleration, rotational acceleration and impact duration of the headform were measured. Resulting accelerations served as input into a three-dimensional finite element head model, which calculated Maximum principal strain (MPS) and von Mises stress (VMS) in the cerebrum. The results indicated that impacts to a steel anvil produced peak head kinematics and brain tissue responses that were two to three times greater than impacts against both turf and sand. Steel impacts were less than half the duration of turf and sand impacts. The observed response magnitudes obtained in this study suggest that equestrian helmet design should be improved, not only for impacts to rigid surfaces but also to compliant surfaces as response magnitudes for impacts to soft surfaces were still within the reported range for concussion in the literature.

Biomechanical comparison of concussions with and without a loss of consciousness in elite American football: implications for prevention

Loss of consciousness (LOC) associated with concussion is no longer considered an indicator of severity of injury in concussion management protocols. Studies investigating the association between LOC and recovery time or neurophysiological performance have reported ambiguous findings and resulted in a limited understanding of the severity of LOC-inducing head impacts. Concussive injuries with and without LOC from helmet-to-helmet and shoulder collisions and falls in elite American football were reconstructed in laboratory using a hybrid III headform and finite element model to obtain peak linear and rotational acceleration and brain tissue deformation metrics in the cerebral cortex, the cerebral white matter, the corpus callosum, the thalamus and the brainstem. Impact velocity, peak linear and rotational acceleration were significantly greater in the LOC group than the no LOC group. The brain tissue deformation metrics were greater in the LOC group than the no LOC group. The best overall predictor for LOC was impact velocity. Concussions with LOC are characterised by greater magnitudes of brain tissue deformation. This was mainly the result of higher impact velocities in the LOC group providing league decision-makers with an understanding of the importance of managing impact velocity through athlete education and rule enforcement or change.

Cerebral blood vessel damage in traumatic brain injury

Traumatic brain injury is a devastating cause of death and disability. Although injury of brain tissue is of primary interest in head trauma, nearly all significant cases include damage of the cerebral blood vessels. Because vessels are critical to the maintenance of the healthy brain, any injury or dysfunction of the vasculature puts neural tissue at risk. It is well known that these vessels commonly tear and bleed as an immediate consequence of traumatic brain injury. It follows that other vessels experience deformations that are significant though not severe enough to produce bleeding. Recent data show that such subfailure deformations damage the microstructure of the cerebral vessels, altering both their structure and function. Little is known about the prognosis of these injured vessels and their potential contribution to disease development. The objective of this review is to describe the current state of knowledge on the mechanics of cerebral vessels during head trauma and how they respond to the applied loads. Further research on these topics will clarify the role of blood vessels in the progression of traumatic brain injury and is expected to provide insight into improved strategies for treatment of the disease.

The effect of impact location on brain strain

OBJECTIVE

To determine the effect of impact direction on strains within the brain.

RESEARCH DESIGN

Laboratory drop tests of hybrid III head-form and finite element simulation of impacts.

METHODS AND PROCEDURES

A head-form instrumented with accelerometers and gyroscopes was dropped from 10 different heights in four orientations: front, rear, left and right-hand side. Twelve impacts with constant impact energy were chosen to simulate, to determine the effect of the impact location. A finite element head model was used to simulate these impacts, using 6 degrees of freedom. Following this, a further set of simulations were performed, where the same acceleration profiles were applied to different head locations.

MAIN OUTCOME AND RESULTS

The angular accelerations recorded were up to 30% higher in lateral and rear impacts when compared to frontal impacts. High strains in the midbrain (41%) were recorded from severe frontal impacts where as high strains in the corpus callosum (44%) resulted from lateral impacts with the same energy.

CONCLUSION

Impact direction is very significant in determining the subsequent strains developed in the brain. Lateral impacts result in the highest strains in the corpus callosum and frontal impacts result in high strains in the mid-brain.

Injury predictors for traumatic axonal injury in a rodent head impact acceleration model

A modified Marmarou impact acceleration injury model was developed to study the kinematics of the rat head to quantify traumatic axonal injury (TAI) in the corpus callosum (CC) and brainstem pyramidal tract (Py), to determine injury predictors and to establish injury thresholds for severe TAI. Thirty-one anesthetized male Sprague-Dawley rats (392±13 grams) were impacted using a modified impact acceleration injury device from 2.25 m and 1.25 m heights. Beta-amyloid precursor protein (β-APP) immunocytochemistry was used to assess and quantify axonal changes in CC and Py. Over 600 injury maps in CC and Py were constructed in the 31 impacted rats. TAI distribution along the rostro-caudal direction in CC and Py was determined. Linear and angular responses of the rat head were monitored and measured in vivo with an attached accelerometer and angular rate sensor, and were correlated to TAI data. Logistic regression analysis suggested that the occurrence of severe TAI in CC was best predicted by average linear acceleration, followed by power and time to surface righting. The combination of average linear acceleration and time to surface righting showed an improved predictive result. In Py, severe TAI was best predicted by time to surface righting, followed by peak and average angular velocity. When both CC and Py were combined, power was the best predictor, and the combined average linear acceleration and average angular velocity was also found to have good injury predictive ability. Receiver operator characteristic curves were used to assess the predictive power of individual and paired injury predictors. TAI tolerance curves were also proposed in this study.

Simulation of human head response to impact loading using newly developed biofidelic material models for brain tissue

Brain tissue is known to exhibit regional and directional variations in its mechanical response to external loads. Material models traditionally used to simulate brain tissue deformation in the human head have been primarily region independent and limited to isotropic and linear viscoelastic. The primary goal of this research is to develop a biofidelic material model for brain tissue by accounting for the underlying microstructure of the material. A computational and analytical approach was undertaken in our attempt to develop a more realistic material model. Based on the microstructure observed at the neuron level, a mesoscale model was developed which included neurons, glial cells and Cerebro-Spinal Fluid (CSF). A semi-analytical model was first developed using a simplified geometry accounting for separate fiber and matrix (fluid) behavior of the medium. A second computational model was also constructed by developing a representative volume element (RVE) of brain tissue that includes the neurons, glial cells and CSF. Diffusion Tensor Imaging (DTI) was also utilized to capture anisotropy and directional dependence of the tissue on the continuum scale. Using the aforementioned material models, computational simulations were performed to predict the mechanical response of the brain tissue when subjected to a non-penetrating, impact load.

Investigation of traumatic brain injuries using the next generation of simulated injury monitor (SIMon) finite element head model

The objective of this study was to investigate potential for traumatic brain injuries (TBI) using a newly developed, geometrically detailed, finite element head model (FEHM) within the concept of a simulated injury monitor (SIMon). The new FEHM is comprised of several parts: cerebrum, cerebellum, falx, tentorium, combined pia-arachnoid complex (PAC) with cerebro-spinal fluid (CSF), ventricles, brainstem, and parasagittal blood vessels. The model's topology was derived from human computer tomography (CT) scans and then uniformly scaled such that the mass of the brain represents the mass of a 50th percentile male's brain (1.5 kg) with the total head mass of 4.5 kg. The topology of the model was then compared to the preliminary data on the average topology derived from Procrustes shape analysis of 59 individuals. Material properties of the various parts were assigned based on the latest experimental data. After rigorous validation of the model using neutral density targets (NDT) and pressure data, the stability of FEHM was tested by loading it simultaneously with translational (up to 400 g) combined with rotational (up to 24,000 rad/s2) acceleration pulses in both sagittal and coronal planes. Injury criteria were established in the manner shown in Takhounts et al. (2003a). After thorough validation and injury criteria establishment (cumulative strain damage measure--CSDM for diffuse axonal injuries (DAI), relative motion damage measure--RMDM for acute subdural hematoma (ASDH), and dilatational damage measure--DDM for contusions and focal lesions), the model was used in investigation of mild TBI cases in living humans based on a set of head impact data taken from American football players at the collegiate level. It was found that CSDM and especially RMDM correlated well with angular acceleration and angular velocity. DDM was close to zero for most impacts due to their mild severity implying that cavitational pressure anywhere in the brain was not reached. Maximum principal strain was found to correlate well with RMDM and angular head kinematic measures. Maximum principal stress didn't correlate with any kinematic measure or injury metric. The model was then used in the investigation of brain injury potential in NHTSA conducted side impact tests. It was also used in parametric investigations of various "what if" scenarios, such as side versus frontal impact, to establish a potential link between head kinematics and injury outcomes. The new SIMon FEHM offers an advantage over the previous version because it is geometrically more representative of the human head. This advantage, however, is made possible at the expense of additional computational time.

Age and gender based biomechanical shape and size analysis of the pediatric brain

Injuries caused by motor vehicle crashes (MVCs) are the leading cause of head injury and death for children in the United States. This study aims to describe the shape and size (morphologic) changes of the cerebrum, cerebellum, brainstem, and ventricles of the pediatric occupant to better predict injury and assess how these changes affect finite element model (FEM) response. To quantify morphologic differences in the brain, a Generalized Procrustes Analysis (GPA) with a sliding landmark method was conducted to isolate morphologic changes using magnetic resonance images of 63 normal subjects. This type of geometric morphometric analysis was selected for its ability to identify homologous landmarks on structures with few true landmarks and isolate the shape and size of the individuals studied. From the resulting landmark coordinates, the shape and size changes were regressed against age to develop a model describing morphologic changes in the pediatric brain as a function of age. The most statistically significant shape change was in the cerebrum with p-values of 0.00346 for males and 0.00829 for females. The age-based model explains over 80% of the variation in size in the cerebrum. Using size and shape models, affine transformations were applied to the SIMon FEM to determine differences in response given differences in size and size plus shape. The geometric centroid of the elements exceeding 15% strain was calculated and compared to the geometric centroid of the entire structure. Given the same Haversine pulse, the centroid location, a metric for the spatial distribution of the elements exceeding an injury threshold, varied based on which transformation was applied to the model. To assess the overall response of the model, three injury metrics were examined to determine the magnitude of the metrics each element sustained and the overall volume of elements that experienced that value. These results suggested that the overall response of the model was driven by the variation in size, with little variation due to changes in shape. This study demonstrates a new methodology to quantify the shape and size variation of the brain from infancy to adulthood. The use of the changes in shape and size when applied to a FEM suggests that there are differences in the spatial distribution of the elements that exceed a specific threshold based on shape but the overall volume of elements experiencing the specified magnitude was more dependent on the changes in the size of the model with little change due to shape.

Head injury prediction capability of the HIC, HIP, SIMon and ULP criteria

The objective of the present study is to synthesize and investigate using the same set of sixty-one real-world accidents the human head injury prediction capability of the head injury criterion (HIC) and the head impact power (HIP) based criterion as well as the injury mechanisms related criteria provided by the simulated injury monitor (SIMon) and the Louis Pasteur University (ULP) finite element head models. Each accident has been classified according to whether neurological injuries, subdural haematoma and skull fractures were reported. Furthermore, the accidents were reconstructed experimentally or numerically in order to provide loading conditions such as acceleration fields of the head or initial head impact conditions. Finally, thanks to this large statistical population of head trauma cases, injury risk curves were computed and the corresponding regression quality estimators permitted to check the correlation of the injury criteria with the injury occurrences. As different kinds of accidents were used, i.e. footballer, motorcyclist and pedestrian cases, the case-independency could also be checked. As a result, FE head modeling provides essential information on the intracranial mechanical behavior and, therefore, better injury criteria can be computed. It is clearly shown that moderate and severe neurological injuries can only be distinguished with a criterion that is computed using intracranial variables and not with the sole global head acceleration.

Region-specific tolerance criteria for the living brain

Computational models of traumatic brain injury (TBI) can predict injury-induced brain deformation. However, predicting the biological consequences (i.e. cell death or dysfunction) of induced brain deformation requires tolerance criteria. Here, we present a tolerance criterion for the cortex which exhibits important differences from that of the hippocampus. Organotypic slice cultures of the rat cortex, which maintain tissue architecture and cell content consistent with that in vivo, were mechanically injured with an in vitro model described previously. Cultures were stretched equibiaxially up to 0.35 Lagrangian strain at strain rates up to 50 s(-1). Cell death was quantified at 1, 2, 3, and 4 days following injury. Statistical analysis (repeated measures ANOVA) showed that all three factors (Strain, Strain Rate, and Time post-injury) significantly affected cell death. An equation describing cell death as a function of the significant parameters was then fit to the data. Compared to the hippocampus, the cortex was less vulnerable to stretch-induced injury and demonstrated a strain threshold below 0.20. Strain rate was also a significant factor for cortical but not hippocampal cell death. Cortical cell death began at an earlier time point than in the hippocampus, with cell death evident at 1 day post-injury versus 3 days in the hippocampus. In conclusion, different regions of the brain respond differently to identical mechanical stimuli, and this difference should be incorporated into finite element models of TBI if they are to more accurately predict in vivo consequences of TBI.

Influence of impact speed on head and brain injury outcome in vulnerable road user impacts to the car hood

EuroNCAP and regulations in Europe and Japan evaluate the pedestrian protection performance of cars. The test methods are similar and they all have requirements for the passive protection of the hood area at a pedestrian to car impact speed of 40 km/h. In Europe, a proposal for a second phase of the regulation mandates a brake-assist system along with passive requirements. The system assists the driver in optimizing the braking performance during panic braking, resulting in activation only when the driver brakes sufficiently. In a European study this was estimated to occur in about 50% of pedestrian accidents. A future system for brake assistance will likely include automatic braking, in response to a pre-crash sensor, to avoid or mitigate injuries of vulnerable road users. An important question is whether these systems will provide sufficient protection, or if a parallel, passive pedestrian protection system will be necessary. This study investigated the influence of impact speed on head and brain injury risk, in impacts to the carhood. One car model was chosen and a rigid adjustable plate was mounted under the hood. Free-flying headform impacts were carried out at 20 and 30 km/h head impact velocities at different under-hood distances, 20 to 100 mm; and were compared to earlier tests at 40 km/h. The EEVC WG17 adult pedestrian headform was used for non-rotating tests and a Hybrid III adult 50th percentile head was used for rotational tests where linear and rotational acceleration was measured. Data from the rotational tests was used as input to a validated finite element model of the human head, the Wayne State University Head Injury Model (WSUHIM). The model was utilized to assess brain injury risk and potential injury mechanism in a pedestrian-hood impact. Although this study showed that it was not necessarily true that a lower HIC value reduced the risk for brain injury, it appeared, for the tested car model, under-hood distances of 60 mm in 20 km/h and 80 mm in 30 km/h reduced head injury values for both skull fractures and brain injuries. An earlier study showed that the corresponding value for a test speed of 40 km/h is 100 mm. A 10 km/h reduction in head impact velocity, as in automatic braking, allowed 20 mm less under-hood clearance with maintained head protection of the vulnerable road user.

Development of numerical models for injury biomechanics research: a review of 50 years of publications in the Stapp Car Crash Conference

Numerical analyses frequently accompany experimental investigations that study injury biomechanics and improvements in automotive safety. Limited by computational speed, earlier mathematical models tended to simplify the system under study so that a set of differential equations could be written and solved. Advances in computing technology and analysis software have enabled the development of many sophisticated models that have the potential to provide a more comprehensive understanding of human impact response, injury mechanisms, and tolerance. In this article, 50 years of publications on numerical modeling published in the Stapp Car Crash Conference Proceedings and Journal were reviewed. These models were based on: (a) author-developed equations and software, (b) public and commercially available programs to solve rigid body dynamic models (such as MVMA2D, CAL3D or ATB, and MADYMO), and (c) finite element models. A clear trend that can be observed is the increasing use of the finite element method for model development. A review of these modeling papers clearly indicates the progression of the state-of-the-art in computational methods and technologies in injury biomechanics.

In vivo imaging of rapid deformation and strain in an animal model of traumatic brain injury

In traumatic brain injury (TBI) rapid deformation of brain tissue leads to axonal injury and cell death. In vivo quantification of such fast deformations is extremely difficult, but important for understanding the mechanisms of degeneration post-trauma and for development of numerical models of injury biomechanics. In this paper, strain fields in the brain of the perinatal rat were estimated from data obtained in vivo during rapid indentation. Tagged magnetic resonance (MR) images were obtained with high spatial (0.2 mm) and temporal (3.9 ms) resolution by gated image acquisition during and after impact. Impacts were repeated either 64 or 128 times to obtain images of horizontal and vertical tag lines in coronal and sagittal planes. Strain fields were estimated by harmonic phase (HARP) analysis of the tagged images. The original MR data was filtered and Fourier-transformed to obtain HARP images, following a method originally developed by Osman et al. (IEEE Trans. Med. Imaging 19(3) (2000) 186). The displacements of material points were estimated from intersections of HARP contours and used to generate estimates of the deformation gradient and Lagrangian strain tensors. Maximum principal Lagrangian strains of >0.20 at strain rates >40/s were observed during indentations of 2 mm depth and 21 ms duration.

Analysis of finite element models for head injury investigation: reconstruction of four real-world impacts

Previous studies have shown that both excessive linear and rotational accelerations are the cause of head injuries. Although the head injury criterion has been beneficial as an indicator of head injury risk, it only considers linear acceleration, so there is a need to consider both types of motion in future safety standards. Advanced models of the head/brain complex have recently been developed to gain a better understanding of head injury biomechanics. While these models have been verified against laboratory experimental data, there is a lack of suitable real-world data available for validation. Hence, using two computer models of the head/brain, the objective of the current study was to reconstruct four real-world crashes with known head injury outcomes in a full-vehicle crash laboratory, simulate head/brain responses using kinematics obtained during these reconstructions, and to compare the results predicted by the models against the actual injuries sustained by the occupant. Cases where the occupant sustained no head injuries (AIS 0) and head injuries of severity AIS 4, AIS 5, and multiple head injuries were selected. Data collected from a 9-accelerometer skull were input into the Wayne State University Head Injury Model (WSUHIM) and the NHTSA Simulated Injury Monitor (SIMon). The results demonstrated that both models were able to predict varying injury severities consistent with the difference in AIS injury levels in the real-world cases. The WSUHIM predicted a slightly higher injury threshold than the SIMon, probably due to the finer mesh and different software used for the simulations, and could also determine regions of the brain which had been injured. With further validation, finite element models can be used to establish an injury criterion for each type of brain injury in the future.

Concussion in Professional Football: Brain Responses by Finite Element Analysis: Part 9

OBJECTIVE

Brain responses from concussive impacts in National Football League football games were simulated by finite element analysis using a detailed anatomic model of the brain and head accelerations from laboratory reconstructions of game impacts. This study compares brain responses with physician determined signs and symptoms of concussion to investigate tissue-level injury mechanisms.

METHODS

The Wayne State University Head Injury Model (Version 2001) was used because it has fine anatomic detail of the cranium and brain with more than 300,000 elements. It has 15 different material properties for brain and surrounding tissues. The model includes viscoelastic gray and white brain matter, membranes, ventricles, cranium and facial bones, soft tissues, and slip interface conditions between the brain and dura. The cranium of the finite element model was loaded by translational and rotational accelerations measured in Hybrid III dummies from 28 laboratory reconstructions of NFL impacts involving 22 concussions. Brain responses were determined using a nonlinear, finite element code to simulate the large deformation response of white and gray matter. Strain responses occurring early (during impact) and mid-late (after impact) were compared with the signs and symptoms of concussion.

RESULTS

Strain concentration "hot spots" migrate through the brain with time. In 9 of 22 concussions, the early strain "hot spots" occur in the temporal lobe adjacent to the impact and migrate to the far temporal lobe after head acceleration. In all cases, the largest strains occur later in the fornix, midbrain, and corpus callosum. They significantly correlated with removal from play, cognitive and memory problems, and loss of consciousness. Dizziness correlated with early strain in the orbital-frontal cortex and temporal lobe. The strain migration helps explain coup-contrecoup injuries.

CONCLUSION

Finite element modeling showed the largest brain deformations occurred after the primary head acceleration. Midbrain strain correlated with memory and cognitive problems and removal from play after concussion. Concussion injuries happen during the rapid displacement and rotation of the cranium, after peak head acceleration and momentum transfer in helmet impacts.

Finite element modelling of human head injuries caused by a fall

Finite element models (FEMs) can be used as prediction tools for human head injuries caused by falls. The purpose of this paper is to demonstrate the relevance of using human head FEM to assess the possible mechanism for the origin of head injuries. The FEM of the human head used in this study was developed in the late 1990s at the University Louis Pasteur of Strasbourg (ULP) and has been validated for human head impacts for simulating human head injuries caused by car accidents. Its use in legal medicine appears to be very useful for comparing different injury mechanisms. We present the simulation obtained for two witnessed falls of the same individual, and compare our results to tolerance limits of the main human head injuries. We show that this tool can be used to discuss the possible mechanism of injury encountered for the observed lesions in a forensic case. It can also help to distinguish between possible and impossible human head injury mechanisms.

Measurement of strain in physical models of brain injury: a method based on HARP analysis of tagged magnetic resonance images (MRI)

Two-dimensional (2-D) strain fields were estimated non-invasively in two simple experimental models of closed-head brain injury. In the first experimental model, shear deformation of a gel was induced by angular acceleration of its spherical container In the second model the brain of a euthanized rat pup was deformed by indentation of its skull. Tagged magnetic resonance images (MRI) were obtained by gated image acquisition during repeated motion. Harmonic phase (HARP) images corresponding to the spectral peaks of the original tagged MRI were obtained, following procedures proposed by Osman, McVeigh and Prince. Two methods of HARP strain analysis were applied, one based on the displacement of tag line intersections, and the other based on the gradient of harmonic phase. Strain analysis procedures were also validated on simulated images of deformed grids. Results show that it is possible to visualize deformation and to quantify strain efficiently in animal models of closed head injury.

In vivo measurements of human brain displacement

Finite element models are increasingly important in understanding head injury mechanisms and designing new injury prevention equipment. Although boundary conditions strongly influence model responses, only limited quantitative data are available. While experimental studies revealed some motion between brain and skull, little data exists regarding the base of the skull. Using magnetic resonance images (MRI) of the caudal brain regions, we measured in vivo, quasi-static angular displacement of the cerebellum (CB) and brainstem (BS) relative to skull, and axial displacement of BS at the foramen magnum in supine human subjects (N=5). Images were obtained in flexion (7 degrees - 54 degrees ) and neutral postures using SPAMM tagging technique (N=47 pairs). Rigid body skull rotation angle from neutral posture (theta, degrees) was determined by extracting the edge feature points of the skull, and rotating and displacing the coordinates in one image until they matched those in the other. Tissue rotation was obtained by comparing tag lines in image pairs before and after flexion, and the motion of BS and CB were expressed relative to skull rotation and displacement. During flexion, the CB rotated in the flexion direction, exceeding the skull rotation, but relative BS rotations were negligible. Meanwhile, the BS moved caudally toward the foramen magnum. With a flexion angle of 54 degrees , the 95% confidence interval for the relative CB rotation was 2.7 degrees - 4.3 degrees , and 0.8 - 1.6mm for the relative BS axial displacement. Albeit quasi-static, this study provides important data that can be implemented to create more life-like boundary conditions in human finite element models.

Shear Properties of Brain Tissue over a Frequency Range Relevant for Automotive Impact Situations: New Experimental Results

This research aims at improving the definition of the shear linear material properties of brain tissue. A comparison between human and porcine white and gray matter samples was carried out over a new large frequency range associated with both traffic road and non-penetrating ballistic impacts. Oscillatory experiments were performed by using an original custom-designed oscillatory shear testing device. The findings revealed that no significant difference occured between the linear viscoelastic behavior of the porcine and the human brain tissue. On the average, the storage modulus (G') and the loss modulus (G") of the white matter increased respectively from 2.1 +/- 0.9 kPa to 16.8 +/- 2.0 kPa and from 0.4 +/- 0.2 kPa to 18.7 +/- 2.3 kPa between 0.1 and 6300 Hz at 37 degrees C. In addition, the gray and white matter behaviors seemed to be similar at small strains. The reliability of the data and the robustness of the experimental protocol were checked using a standard rheometer (Bohlin C-VOR 150). A good agreement was found between the data obtained in the frequency and time field. As a result, the linear relaxation modulus was determined over an extensive time range (from 10(-5) s to 300 s). In a first approach, the nonlinear behavior of brain tissue was studied using stress relaxation tests. Brain tissue showed significant shear softening for strains above 1% and the time relaxation behavior was independent of the applied strain. On this basis, a visco-hyperelastic model was proposed using the generalized Maxwell model and the Ogden hyperelastic model. These models respectively describe the linear relaxation modulus and the strain dependence of the shear stress.

On the importance of nonlinearity of brain tissue under large deformations

Linear shear properties of human and bovine brain tissue were determined from transient stress-relaxation experiments and their material functions were compared. Quasi-linear viscoelastic theory was then utilized to determine material constants for bovine brain tissue subjected to large deformations. The range of applicability for linear and quasi-linear constitutive models of brain tissue was determined. A nonlinear Green-Rivlin constitutive model was subsequently applied to characterize temporal nonlinearity of bovine brain tissue in shear. Overall, 10 brain specimens from 5 fresh human cadavers and 156 brain specimens from 26 fresh bovine cadaver brains were used to quantify and compare shear brain responses under various loading conditions. The assumptions of homogeneity, isotropy, and incompressibility of brain material were made in order to reduce the required number of experiments. A series of single-, two-, and three-step strain inputs was applied to one end of a cylindrical brain specimen and the stress-time histories were measured at the other end. The time delays between the applied strain step inputs were altered in order to determine the temporal nonlinearity of brain tissue. The study resulted in linear constitutive models for human and bovine brain tissue, and quasi-linear and nonlinear constitutive equations for bovine brain tissue in shear. It was found that human brain is somewhat stiffer than bovine brain; the difference, however, was not statistically significant and bovine brain may be a good substitute in studying nonlinear human brain response. A linear constitutive model was found to be sufficient to characterize brain tissue response when Lagrangian shear strains do not exceed 0.2 (advised to limit the range to the shear strain of 0.175), a quasi-linear constitutive model can then be used for loading conditions of up to 0.5 of Lagrangian shear strains (advised to limit the range to the shear strain of 0.325). For any shear strain magnitudes and histories a fully nonlinear Green-Rivlin viscoelastic constitutive model may be utilized.

On the Development of the SIMon Finite Element Head Model

The SIMon (Simulated Injury Monitor) software package is being developed to advance the interpretation of injury mechanisms based on kinematic and kinetic data measured in the advanced anthropomorphic test dummy (AATD) and applying the measured dummy response to the human mathematical models imbedded in SIMon. The human finite element head model (FEHM) within the SIMon environment is presented in this paper. Three-dimensional head kinematic data in the form of either a nine accelerometer array or three linear CG head accelerations combined with three angular velocities serves as an input to the model. Three injury metrics are calculated: Cumulative strain damage measure (CSDM) - a correlate for diffuse axonal injury (DAI); Dilatational damage measure (DDM) - to estimate the potential for contusions; and Relative motion damage measure (RMDM) - a correlate for acute subdural hematoma (ASDH). During the development, the SIMon FEHM was tuned using cadaveric neutral density targets (NDT) data and further validated against the other available cadaveric NDT data and animal brain injury experiments. The hourglass control methods, integration schemes, mesh density, and contact stiffness penalty coefficient were parametrically altered to investigate their effect on the model's response. A set of numerical and physical parameters was established that allowed a satisfactory prediction of the motion of the brain with respect to the skull, when compared with the NDT data, and a proper separation of injury/no injury cases, when compared with the brain injury data. Critical limits for each brain injury metric were also established. Finally, the SIMon FEHM performance was compared against HIC15 through the use of NHTSA frontal and side impact crash test data. It was found that the injury metrics in the current SIMon model predicted injury in all cases where HIC15 was greater than 700 and several cases from the side impact test data where HIC15 was relatively small. Side impact was found to be potentially more injurious to the human brain than frontal impact due to the more severe rotational kinematics.

Computational study of the contribution of the vasculature on the dynamic response of the brain

Brain tissue architecture consists of a complex network of neurons and vasculature interspersed within a matrix of supporting cells. The role of the relatively stiffer blood vessels on the more compliant brain tissues during rapid loading has not been properly investigated. Two 2-D finite element models of the human head were developed. The basic model (Model I) consisted of the skull, dura matter, cerebral spinal fluid (CSF), tentorium, brain tissue and the parasagittal bridging veins. The pia mater was also included but in a simplified form which does not correspond to the convolutions of the brain. In Model II, major branches of the cerebral arteries were added to Model I. Material properties for the brain tissues and vasculature were taken from those reported in the literature. The model was first validated against intracranial pressure and brain/skull relative motion data from cadaveric tests. Two loading conditions, an anterior-posterior linear acceleration and a flexion-extension angular velocity pulse, were applied to both models. Resulting maximum principal strain, shear strain and intracranial pressure throughout the intracranial tissue were calculated and compared. Overall, the maximum principal strain/stress in the brain was lower in the model that included simulated blood vessels. The inclusion of the cerebral vessels added regional strength to the brain substance, and thereby contributed to the load bearing capacity of this composite brain model during head impact, analogous to reinforcing bars in a reinforced concrete structure. In addition to the neurovasculature, the pia membrane, which conforms to the numerous gyri and sulci not modeled in this study, may add to the structural strength of the brain. Results from this investigation suggest that the fine anatomical substructures of the brain should not be ignored in traumatic brain injury modeling. However, incorporation of blood vessels in a 3-D FE head model is not practical at this stage due to the lack of computing power.