Brain Material Properties Research Articles

Preservatives for postmortem brain tissue in biomechanical testing: A pilot study.

Postmortem human subject (PMHS) studies are essential to brain injury research in motor vehicle safety. However, postmortem deterioration reduces the similarity between postmortem test results and invivo response in material testing of brain tissue and in biomechanical testing of the whole head. This pilot study explores the effect of potential preservatives on brain tissue breakdown to identify promising preservatives that warrant further investigation. To identify preservatives with potential to slow postmortem degradation, samples from an initial PMHS were refrigerated at 10°C to qualitatively compare tissue breakdown from 58 to 152 h postmortem after storage in candidate solutions. On brain tissue samples from a second PMHS, compressive stiffness was measured on six samples immediately after harvest for comparison to the stiffness of 23 samples that were stored at 10°C in candidate solutions for 24 h after harvest. The candidate solutions were artificial cerebrospinal fluid (ACSF) without preservatives; ACSF with a combination of antibiotics and antifungal agents; ACSF with added sodium bicarbonate; and ACSF with both the antibiotic/antifungal combination and sodium bicarbonate. Results were analyzed using multiple linear regression of specimen stiffness on harvest lobe and storage solution to investigate potential differences in tissue stiffness. Qualitative evaluation suggested that samples stored in a solution that contained both the antibiotic/antifungal combination and sodium bicarbonate exhibited less evidence of tissue breakdown than the samples stored without preservatives or with only one of those preservatives. In compression testing, samples tested immediately after harvest were significantly stiffer than samples tested after 24 h of storage at 10°C in ACSF (difference: -0.27 N/mm, 95% confidence interval (CI): -0.50, -0.05) or ACSF with antibiotics/antifungal agents (difference: -0.32 N/mm, 95% CI: -0.59, -0.04), controlling for harvest lobe. In contrast, the stiffness of samples tested after storage in either solution containing sodium bicarbonate was not significantly different from the stiffness of samples tested at harvest. There was no significant overall difference in the mean tissue stiffness between samples from the frontal and parietal lobes, controlling for storage solution. Given the importance of PMHS studies to brain injury research, any strategy that shows promise for helping to maintain invivo brain material properties has the potential to improve understanding of brain injury mechanisms and tolerance to head injury and warrants further investigation. These pilot study results suggest that sodium bicarbonate has the potential to reduce the deterioration of brain tissue in biomechanical testing. The results motivate further evaluation of sodium bicarbonate as a preservative for biomechanical testing using additional test subjects, more comprehensive material testing, and evaluation under a broader set of test conditions including in whole-head testing. The effect of antibiotics and antifungal agents on brain tissue stiffness was minimal but may have been limited by the cold storage conditions in this study. Further exploration of the potential for microbial agents to preserve tissue postmortem would benefit from evaluation of the effects of storage temperature.

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.

Analysis of the pattern of microstructural changes in the brain after mTBI with diffusion tensor imaging and subject-specific FE models

Traumatic brain injury (TBI) is a major public health challenge. Up to 90 % of TBIs are on the mild spectrum of TBI (mTBI), where diagnosis is a major challenge. Majority of studies in this field have been conducted on human subjects, which inherently suffer from the lack of appropriate control group, selection bias, and individual differences in patients. To overcome these limitations, animal studies have been used as an alternative approach to provide deeper insights into the underlying mechanism related to the injury. Therefore our aim is to investigate various quantitative imaging biomarkers acquired from T1-W and diffusion tensor imaging (DTI) sequences to provide more information about the microstructural changes in the brain after mTBI. We then use this to generate subject-specific finite element models of the brain and examine how the changes in the brain material properties reflected in MR images affects strain distribution patterns on a subsequent head hit. Our study revealed a decrease in FA and an increase in diffusivity indices (MD, AD, RD) in the white matter tracts of the brain. This finding may represent the axonal damage, demyelination and gliosis after mild TBI, which have been shown in other animal and human studies. Moreover, our FE analysis showed that microstructural changes in the brain after mTBI might have weakened the structural integrity of the brain as the subsequent head hit led to wider and more severe brain deformations. SignificanceAnimal models have been used to investigate biomechanical and pathophysiological aspects of mild traumatic brain injuries in the past. Still, most of them used small animals such as rats and mice. These models provided valuable insight into the pathophysiology of mTBI, but their findings have limitations due to their inherent differences to human brains. We have developed a large animal model of mTBI with sheep brains by combining advanced MRI and finite element analysis as they mimic the human brain better. To the best of our knowledge, this study is the first mTBI neuroimaging study conducted on large animal brains to investigate the diffusional changes in the white matter tracts after mTBI. Our FE analysis revealed that such microstructural changes resulted in tissue softening as the extent of brain deformation increased on a subsequent head hit, indicating increased brain vulnerability after head impacts.

In vivo measurement of human brain material properties under quasi-static loading.

Computational modelling of the brain requires accurate representation of the tissues concerned. Mechanical testing has numerous challenges, in particular for low strain rates, like neurosurgery, where redistribution of fluid is biomechanically important. A finite-element (FE) model was generated in FEBio, incorporating a spring element/fluid-structure interaction representation of the pia-arachnoid complex (PAC). The model was loaded to represent gravity in prone and supine positions. Material parameter identification and sensitivity analysis were performed using statistical software, comparing the FE results to human in vivo measurements. Results for the brain Ogden parameters µ, α and k yielded values of 670 Pa, -19 and 148 kPa, supporting values reported in the literature. Values of the order of 1.2 MPa and 7.7 kPa were obtained for stiffness of the pia mater and out-of-plane tensile stiffness of the PAC, respectively. Positional brain shift was found to be non-rigid and largely driven by redistribution of fluid within the tissue. To the best of our knowledge, this is the first study using in vivo human data and gravitational loading in order to estimate the material properties of intracranial tissues. This model could now be applied to reduce the impact of positional brain shift in stereotactic neurosurgery.

Mind the gap: A mechanobiological hypothesis for the role of gap junctions in the mechanical properties of injured brain tissue

Despite more than half a century of work on the brain biomechanics, there are still significant unknowns about this tissue. Since the brain is highly susceptible to injury, damage biomechanics has been one of the main areas of interest to the researchers in the field of brain biomechanics. In many previous studies, mechanical properties of brain tissue under sub-injury and injury level loading conditions have been addressed; however, to the best of our knowledge, the role of cell-cell interactions in the mechanical behavior of brain tissue has not been well examined yet. This note introduces the hypothesis that gap junctions as the major type of cell-cell junctions in the brain tissue play a pivotal role in the mechanical properties of the tissue and their failure during injury leads to changes in brain's material properties. According to this hypothesis, during an injury, the gap junctions are damaged, leading to a decrease in tissue stiffness, whereas following the injury, new junction proteins are expressed, leading to an increase in tissue stiffness. We suggest that considering the mechanobiological effect of gap junctions in the material properties of brain tissue may help better understand the brain injury mechanism.

Analyzing the changes in the brain material properties after a mild traumatic brain injury—A pilot study

AbstractTraumatic brain injury (TBI) is a major health challenge, is very difficult to diagnose, and currently has no accepted treatment options. The difficulty in diagnosis is due to the complex pathophysiology of TBI, where the damage mechanisms span multiple spatial and temporal scales and ultimately manifest as diverse cognitive impairments in brain function. The speed and dynamic nature with which the mechanical insults occur in TBI means that computational models are the best candidate to mimic the in vivo event and to investigate the injury progression in detail. A current weakness in TBI computational models is the poor understanding of how material properties within different regions of the brain change after damage. Here, we developed an animal experiment pipeline where a controlled and reproducible mechanical insult can be applied to a sheep brain in vivo followed by ex vivo compression mechanical testing. For each brain, the compression mechanical testing was conducted across the length of the brain to assess baseline regional variations in material properties and how these properties changed after mechanical impact. Using this pipeline, we have characterized locational variations in the brain material properties both pre and post‐TBI. Our preliminary results confirm that there exist locational variations in the brain material properties across all regions of cerebrum. The analysis of post‐TBI tissues showed that compressive strength was reduced in the area nearest the direct impact.

Viscoelastic properties of shock wave exposed brain tissue subjected to unconfined compression experiments

Traumatic brain injuries (TBI) affect millions of people each year. While research has been dedicated to determining the mechanical properties of the uninjured brain, there has been a lack of investigation on the mechanical properties of the brain after experiencing a primary blast-induced TBI. In this paper, whole porcine brains were exposed to a shock wave to simulate blast-induced TBI. First, ten (10) brains were subjected to unconfined compression experiments immediately following shock wave exposure. In addition, 22 brains exposed to a shock wave were placed in saline solution and refrigerated between 30 minutes and 6.0 hours before undergoing unconfined compression experiments. This study aimed to investigate the effect of a time delay on the viscoelastic properties in the event that an experiment cannot be completed immediately. Samples from both soaked and freshly extracted brains were subjected to compressive rates of 5, 50, and 500 mm/min during the unconfined compression experiments. The fractional Zener (FZ) viscoelastic model was applied to obtain the brain's material properties. The length of time in the solution statistically influenced three of the four FZ coefficients, E0 (instantaneous elastic response), τ0 (relaxation time), and α (fractional order). Further, the compressive rate statistically influenced τ0 and α.

Optimization of a Multifrequency Magnetic Resonance Elastography Protocol for the Human Brain.

The brain's stiffness measurements from magnetic resonance elastography (MRE) strongly depend on actuation frequencies, which makes cross-study comparisons challenging. We performed a preliminary study to acquire optimal sets of actuation frequencies to accurately obtain rheological parameters for the whole brain (WB), white matter (WM), and gray matter (GM). Six healthy volunteers aged between 26 and 72 years old went through MRE with a modified single-shot spin-echo echo planar imaging pulse sequence embedded with motion encoding gradients on a 3T scanner. Frequency-independent brain material properties and best-fit material model were determined from the frequency-dependent brain tissue response data (20 -80 Hz), by comparing four different linear viscoelastic material models (Maxwell, Kelvin-Voigt, Springpot, and Zener). During the material fitting, spatial averaging of complex shear moduli (G*) obtained under single actuation frequency was performed, and then rheological parameters were acquired. Since clinical scan time is limited, a combination of three actuation frequencies that would provide the most accurate approximation and lowest fitting error was determined for WB, WM, and GM by optimizing for the lowest Bayesian information criterion (BIC). BIC scores for the Zener and Springpot models showed these models approximate the multifrequency response of the tissue best. The best-fit frequency combinations for the reference Zener and Springpot models were identified to be 30-60-70 and 30-40-80 Hz, respectively, for the WB. Optimal sets of actuation frequencies to accurately obtain rheological parameters for WB, WM, and GM were determined from shear moduli measurements obtained via 3-dimensional direct inversion. We believe that our study is a first-step in developing a region-specific multifrequency MRE protocol for the human brain.

A 3-D Rat Brain Model for Blast-Wave Exposure: Effects of Brain Vasculature and Material Properties

Exposure to blast waves is suspected to cause primary traumatic brain injury. However, existing finite-element (FE) models of the rat head lack the necessary fidelity to characterize the biomechanical responses in the brain due to blast exposure. They neglect to represent the cerebral vasculature, which increases brain stiffness, and lack the appropriate brain material properties characteristic of high strain rates observed in blast exposures. To address these limitations, we developed a high-fidelity three-dimensional FE model of a rat head. We explicitly represented the rat’s cerebral vasculature and used high-strain-rate material properties of the rat brain. For a range of blast overpressures (100 to 230 kPa) the brain-pressure predictions matched experimental results and largely overlapped with and tracked the incident pressure–time profile. Incorporating the vasculature decreased the average peak strain in the cerebrum, cerebellum, and brainstem by 17, 33, and 18%, respectively. When compared with our model based on rat-brain properties, the use of human-brain properties in the FE model led to a three-fold reduction in the strain predictions. For simulations of blast exposure in rats, our findings suggest that representing cerebral vasculature and species-specific brain properties has a considerable influence in the resulting brain strain but not the pressure predictions.

Material properties of the brain in injury-relevant conditions - Experiments and computational modeling.

Material properties of the brain have been extensively studied but remain poorly characterized. The vast variations in constitutive models and material constants are well documented. However, no study exists to translate the variations into disparities in impact-induced brain strains most relevant to brain injury. Here, we reviewed a subset of injury-relevant brain material properties either characterized in experiments or adopted in recent head injury models. To highlight how variations in measured brain material properties manifested in simulated brain strains, we selected six experiments that have provided a complete set of brain material model and constants to implement a common head injury model. Responses resulting from two extreme events representing a high-rate cadaveric head impact and a low-rate in vivo head rotation, respectively, varied substantially. We hypothesized, and further confirmed, that the time-varying shear moduli at the appropriate time scales (e.g., ~5 ms and ~40 ms corresponding to the impulse durations of the major acceleration peaks for the two impacts, respectively), rather than the initial or long-term shear moduli, were the most indicative of impact-induced brain strains. These results underscored the need to implement measured brain material properties into an actual head injury model for evaluation. They may also provide guidelines to better characterize brain material properties in future experiments and head injury models. Finally, our finding provided a practical solution to satisfy head injury model validation requirements at both ends of the impact severity spectrum. This would improve the confidence in model simulation performance across a range of time scales relevant to concussion and sub-concussion in the real-world.

Dynamic analysis of the human brain with complex cerebral sulci

ABSTRACTThe brain is one of the most vulnerable organs inside the human body. Head accidents often appear in daily life and are easy to cause different level of brain damage inside the skull. Once the brain suffered intense locomotive impact, external injuries, falls, or other accidents, it will result in different degrees of concussion. This study employs finite element analysis to compare the dynamic characteristics between the geometric models of an assumed simple brain tissue and a brain tissue with complex cerebral sulci. It is aimed to understand the free vibration of the internal brain tissue and then to protect the brain from injury caused by external influences. Reverse engineering method is used for a Classic 5-Part Brain (C18) model produced by 3B Scientific Corporation. 3D optical scanner is employed to scan the human brain structure model with complex cerebral sulci and imported into 3D graphics software to construct a solid brain model to simulate the real complex brain tissue. Obtaining the normal mode analysis by inputting the material properties of the true human brain into finite element analysis software, and then to compare the simplified and the complex of brain models.

Modeling the Insertion Mechanics of Flexible Neural Probes Coated with Sacrificial Polymers for Optimizing Probe Design

Single-unit recording neural probes have significant advantages towards improving signal-to-noise ratio and specificity for signal acquisition in brain-to-computer interface devices. Long-term effectiveness is unfortunately limited by the chronic injury response, which has been linked to the mechanical mismatch between rigid probes and compliant brain tissue. Small, flexible microelectrodes may overcome this limitation, but insertion of these probes without buckling requires supporting elements such as a stiff coating with a biodegradable polymer. For these coated probes, there is a design trade-off between the potential for successful insertion into brain tissue and the degree of trauma generated by the insertion. The objective of this study was to develop and validate a finite element model (FEM) to simulate insertion of coated neural probes of varying dimensions and material properties into brain tissue. Simulations were performed to predict the buckling and insertion forces during insertion of coated probes into a tissue phantom with material properties of brain. The simulations were validated with parallel experimental studies where probes were inserted into agarose tissue phantom, ex vivo chick embryonic brain tissue, and ex vivo rat brain tissue. Experiments were performed with uncoated copper wire and both uncoated and coated SU-8 photoresist and Parylene C probes. Model predictions were found to strongly agree with experimental results (<10% error). The ratio of the predicted buckling force-to-predicted insertion force, where a value greater than one would ideally be expected to result in successful insertion, was plotted against the actual success rate from experiments. A sigmoidal relationship was observed, with a ratio of 1.35 corresponding to equal probability of insertion and failure, and a ratio of 3.5 corresponding to a 100% success rate. This ratio was dubbed the “safety factor”, as it indicated the degree to which the coating should be over-designed to ensure successful insertion. Probability color maps were generated to visually compare the influence of design parameters. Statistical metrics derived from the color maps and multi-variable regression analysis confirmed that coating thickness and probe length were the most important features in influencing insertion potential. The model also revealed the effects of manufacturing flaws on insertion potential.

Development and validation of an atlas-based finite element brain model.

Traumatic brain injury is a leading cause of disability and injury-related death. To enhance our ability to prevent such injuries, brain response can be studied using validated finite element (FE) models. In the current study, a high-resolution, anatomically accurate FE model was developed from the International Consortium for Brain Mapping brain atlas. Due to wide variation in published brain material parameters, optimal brain properties were identified using a technique called Latin hypercube sampling, which optimized material properties against three experimental cadaver tests to achieve ideal biomechanics. Additionally, falx pretension and thickness were varied in a lateral impact variation. The atlas-based brain model (ABM) was subjected to the boundary conditions from three high-rate experimental cadaver tests with different material parameter combinations. Local displacements, determined experimentally using neutral density targets, were compared to displacements predicted by the ABM at the same locations. Error between the observed and predicted displacements was quantified using CORrelation and Analysis (CORA), an objective signal rating method that evaluates the correlation of two curves. An average CORA score was computed for each variation and maximized to identify the optimal combination of parameters. The strongest relationships between CORA and material parameters were observed for the shear parameters. Using properties obtained through the described multiobjective optimization, the ABM was validated in three impact configurations and shows good agreement with experimental data. The final model developed in this study consists of optimized brain material properties and was validated in three cadaver impacts against local brain displacement data.

1006 脳と脊髄の材料特性の異方性(バイオエンジニアリングI)

1006 脳と脊髄の材料特性の異方性(バイオエンジニアリングI)

Ventriculostomy Simulation Using Patient-Specific Ventricular Anatomy, 3D Printing, and Hydrogel Casting

Educational simulators provide a means for students and experts to learn and refine surgical skills. Educators can leverage the strengths of medical simulators to effectively teach complex and high-risk surgical procedures, such as placement of an external ventricular drain. Our objective was to develop a cost-effective, patient-derived medical simulacrum for cerebral lateral ventriculostomy. A cost-effective, patient-derived medical simulacrum was developed for placement of an external lateral ventriculostomy. Elastomeric and gel casting techniques were used to achieve realistic brain geometry and material properties. 3D printing technology was leveraged to develop accurate cranial properties and dimensions. An economical, gravity-driven pump was developed to provide normal and abnormal ventricular pressures. A small pilot study was performed to gauge simulation efficacy using a technology acceptance model. An accurate geometric representation of the brain was developed with independent lateral cerebral ventricular chambers. A gravity-driven pump pressurized the ventricular cavities to physiologic values. A qualitative study illustrated that the simulation has potential as an educational tool to train medical professionals in the ventriculostomy procedure. The ventricular simulacrum can improve learning in a medical education environment. Rapid prototyping and multi-material casting techniques can produce patient-derived models for cost-effective and realistic surgical training scenarios.

Effect of Aging on Brain Injury Prediction in Rotational Head Trauma—A Parameter Study with a Rat Finite Element Model

Objective: The aim of this study was to investigate the possible effects of age-related intracranial changes on the potential outcome of diffuse axonal injuries and acute subdural hematoma under rotational head loading.Methods: A simulation-based parametric study was conducted using an updated and validated finite element model of a rat head. The validation included a comparison of predicted brain cortex sliding with respect to the skull. Further, model material properties were modified to account for aging; predicted tissue strains were compared with experimental data in which groups of rats in 2 different lifecycle stages, young adult and mature adult, were subjected to rotational trauma. For the parameter study, 2 age-dependent factors—brain volume and region-specific brain material properties—were implemented into the model. The models young adult and old age were subjected to several injurious and subinjurious sagittal plane rotational acceleration levels.Results: Sequential analysis of the simulated trauma progression indicates that an increase in acute subdural hematoma injury risk indicator occurs at an early stage of the trauma, whereas an increase in diffuse axonal injury risk indicators occurs at a later stage. Tissue stiffening from young adult to mature adult rats produced an increase in strain-based thresholds accompanied by a wider spread of strain distribution toward the rear part of the brain, consistent with rotational trauma experiments with young adult and mature adult rats. Young adult to old age brain tissue softening and brain atrophy resulted in an increase in diffuse axonal injuries and acute subdural hematoma injury risk indicators, respectively.Conclusions: The findings presented in this study suggest that age-specific injury thresholds should be developed to enable the development of superior restraint systems for the elderly. The findings also motivate other further studies on age-dependency of head trauma.

Material Characterization of in Vivo and in Vitro Porcine Brain Using Shear Wave Elasticity

Realistic computer simulation of closed head trauma requires accurate mechanical properties of brain tissue, ideally in vivo. A substantive deficiency of most existing experimental brain data is that properties were identified through in vitro mechanical testing. This study develops a novel application of shear wave elasticity imaging to assess porcine brain tissue shear modulus in vivo. Shear wave elasticity imaging is a quantitative ultrasound technique that has been used here to examine changes in brain tissue shear modulus as a function of several experimental and physiologic parameters. Animal studies were performed using two different ultrasound transducers to explore the differences in physical response between closed skull and open skull arrangements. In vivo intracranial pressure in four animals was varied over a relevant physiologic range (2–40 mmHg) and was correlated with shear wave speed and stiffness estimates in brain tissue. We found that stiffness does not vary with modulation of intracranial pressure. Additional in vitro porcine specimens (n = 14) were used to investigate variation in brain tissue stiffness with temperature, confinement, spatial location and transducer orientation. We observed a statistically significant decrease in stiffness with increased temperature (23%) and an increase in stiffness with decreasing external confinement (22–37%). This study determined the feasibility of using shear wave elasticity imaging to characterize porcine brain tissue both in vitro and in vivo. Our results underline the importance of temperature- and skull-derived boundary conditions to brain stiffness and suggest that physiologic ranges of intracranial pressure do not significantly affect in situ brain tissue properties. Shear wave elasticity imaging allowed for brain material properties to be experimentally characterized in a physiologic setting and provides a stronger basis for assessing brain injury in computational models.

Human head–neck computational model for assessing blast injury

A human head finite element model (HHFEM) was developed to study the effects of a blast to the head. To study both the kinetic and kinematic effects of a blast wave, the HHFEM was attached to a finite element model of a Hybrid III ATD neck. A physical human head surrogate model (HSHM) was developed from solid model files of the HHFEM, which was then attached to a physical Hybrid III ATD neck and exposed to shock tube overpressures. This allowed direct comparison between the HSHM and HHFEM. To develop the temporal and spatial pressures on the HHFEM that would simulate loading to the HSHM, a computational fluid dynamics (CFD) model of the HHFEM in front of a shock tube was generated. CFD simulations were made using loads equivalent to those seen in experimental studies of the HSHM for shock tube driver pressures of 517, 690 and 862kPa. Using the selected brain material properties, the peak intracranial pressures, temporal and spatial histories of relative brain–skull displacements and the peak relative brain–skull displacements in the brain of the HHFEM compared favorably with results from the HSHM. The HSHM sensors measured the rotations of local areas of the brain as well as displacements, and the rotations of the sensors in the sagittal plane of the HSHM were, in general, correctly predicted from the HHFEM. Peak intracranial pressures were between 70 and 120kPa, while the peak relative brain–skull displacements were between 0.5 and 3.0mm.

MATERIAL PROPERTIES OF ADULT RAT SKULL

Development of advanced computational rat head models requires accurate material properties of the rat brain, meninges, skull, and other soft tissues. This study investigated adult rat skull material properties, which are very limited in the current literature. A total of 20 skull specimens were harvested from 10 adult rats. High resolution (16 μm) microcomputed tomography scans were performed for each specimen to observe dimensional changes within each specimen and internal porosities through the cross sections. The specimens were tested in three-point bending at loading velocities of 0.02 and 200 mm/s. The elastic modulus, energy absorbed to failure, energy density, and bending stress were calculated using classical beam theory. Results demonstrated that bending velocity (strain rate) had significant effect on elastic modulus and bending stress, but not on energy and energy density. The Young's moduli of rat skull measured in this study were comparable to those measured from the adult human skull.

Material property influences on the modelling of child brain injuries

Finite element simulations of a human head are often used to enhance our knowledge of injury mechanisms, assist in injury prediction and to develop preventative devices such as helmets and seatbelts. While many adult models have been developed and validated, few child models have been developed due to a lack of material data and experimental studies of which to validate the model. Therefore, many child head injuries are investigated via dimensionally scaled adult head models without the replacement of the adult material properties by the child material properties. This study aims to evaluate whether applying the child material properties to a dimensionally scaled adult head significantly influences the predicted risk of brain injury of a child head due to impact accidents. The adult model of Horgan & Gilchrist (2003) was scaled to the size of a 6-month old child’s head and then this model was compared to the one with child material properties appended. Frontal, lateral and occipital impacts were simulated, and the use of the child material properties was found to decrease the peak von Mises stress in the brain by up to 58.2%. Applying this result to the University Louis Pasteur criterion (Marjoux et al, 2008) yielded a maximum decrease of 90% in the relative risks of severe brain injury. Therefore, when analysing child brain injuries with a scaled adult model, the child material properties should be applied in order to more accurately predict the extent of brain injury. Our further numerical study explored the sensitivity of the skull and brain material properties on head injuries. The results showed that the impact force is mainly affected by the skull material properties and the brain material properties have negligible influence on the impact force. However, the maximum von Mises stress in the brain is mainly affected by the brain material properties.