Development of a Finite Element Model for Blast Brain Injury and the Effects of CSF Cavitation

Simulation of the Strain Amplification in Sulci Due to Blunt Impact to the Head

Traumatic brain injury (TBI) has become a concern in sports, automobile accidents and combat operations. A better understanding of the mechanics leading to a TBI is required to cope with both the short-term life-threatening effects and long-term effects of TBIs, such as the development chronic traumatic encephalopathy (CTE). Kornguth et al. (1) proposed that an inflammatory and autoimmune process initiated by a water hammer effect at the bases of the sulci of the brain is a mechanism of TBI leading to CTE. A major objective of this study is to investigate whether the water hammer effect is present due to blunt impacts through the use of computational models. Frontal blunt impacts were simulated with 2D finite element models developed to capture the biofidelic geometry of a human head. The models utilized the Arbitrary Lagrangian Eulerian (ALE) method to model a layer of cerebrospinal fluid (CSF) as a deforming fluid allowing for CSF to move in and out of sulci. During the simulated impacts, CSF was not observed to be driven into the sulci during the transient response. However, elevated shear strain levels near the base of the sulci were exhibited. Further, increased shear strain was present when differentiation between white and gray matter was taken into account. Both of the results support clinical observations of (1).

Damage to the rat cerebrum under in vitro sinusoidal translational shear deformation

Blast waves, which induce sinusoidal shear waves within brain tissue, may cause mild traumatic brain injury (mTBI). To identify damage from a shear deformation wave, sagittal slices of rat cerebra are subjected to 50 cycles of translational shear deformation at six fixed frequencies between 25 Hz and 125 Hz and displacement amplitudes of 10% or 25% of the original length of the specimen. Each deformation frequency produces transient and apparent steady shear stress states that frequency analysis describes by their harmonic wavelet and Fourier frequency components. The dominant frequency components are integer multiples of the applied deformation frequency. The morphology of the shear stress versus time curve, and probably the type of damage, changes with deformation frequency. Damage at the lower frequencies appears to be diffuse bond breaking. Imaging and histology do not clearly detect mild damage due to bond breaking that underlies mTBI, which the analysis of the shear stress response captures. Major transitions in the morphology of the stress response in the two regions occur at about 75 Hz deformation frequency, possibly due to minor damage to cerebral substructures. An increase in deformation frequency increases the drag force between the extracellular fluid and solid matter. The deformation frequency dependence of the shear stress response makes protection against blast mTBI more difficult because the frequency content of a blast wave is not known a priori.

Characterization of Astrocytic Response after Experiencing Cavitation In Vitro

When a traumatic brain injury (TBI) occurs, low-pressure regions inside the skull can cause vapor contents in the cerebral spinal fluid (CSF) to expand and collapse, a phenomenon known as cavitation. When these microbubbles (MBs) collapse, shock waves are radiated outward and are known to damage surrounding materials in other applications, like the steel foundation of boat propellers, so it is alarming to realize the damage that cavitation inflicts on vulnerable brain tissue. Using cell-laden microfibers, the longitudinal morphological response that mouse astrocytes have to surrounding cavitation in vitro is visually analyzed. Astrocytic damage is evident immediately after cavitation when compared to a control sample, as their processes retract. Forty-eight hours later, the astrocytes appeared to spread across the fibers, as normal. This study also analyzes the gene expression changes that occur post-cavitation via quantitative polymerase chain reaction (qPCR) methods. After cavitation a number of pro-inflammatory genes are upregulated, including TNFα, IL-1β, C1q, Serping1, NOS1, IL-6, and JMJD3. Taken together, these results confirm that surrounding cavitation is detrimental to astrocytic function, and yield opportunities to further the understanding of how protective headgear can minimize or eliminate the occurrence of cavitation.

Embedded axonal fiber tracts improve finite element model predictions of traumatic brain injury

With the growing rate of traumatic brain injury (TBI), there is an increasing interest in validated tools to predict and prevent brain injuries. Finite element models (FEM) are valuable tools to estimate tissue responses, predict probability of TBI, and guide the development of safety equipment. In this study, we developed and validated an anisotropic pig brain multi-scale FEM by explicitly embedding the axonal tract structures and utilized the model to simulate experimental TBI in piglets undergoing dynamic head rotations. Binary logistic regression, survival analysis with Weibull distribution, and receiver operating characteristic curve analysis, coupled with repeated k-fold cross-validation technique, were used to examine 12 FEM-derived metrics related to axonal/brain tissue strain and strain rate for predicting the presence or absence of traumatic axonal injury (TAI). All 12 metrics performed well in predicting of TAI with prediction accuracy rate of 73-90%. The axonal-based metrics outperformed their rival brain tissue-based metrics in predicting TAI. The best predictors of TAI were maximum axonal strain times strain rate (MASxSR) and its corresponding optimal fraction-based metric (AF-MASxSR7.5) that represents the fraction of axonal fibers exceeding MASxSR of 7.5 s-1. The thresholds compare favorably with tissue tolerances found in in-vitro/in-vivo measurements in the literature. In addition, the damaged volume fractions (DVF) predicted using the axonal-based metrics, especially MASxSR (DVF = 0.05-4.5%), were closer to the actual DVF obtained from histopathology (AIV = 0.02-1.65%) in comparison with the DVF predicted using the brain-related metrics (DVF = 0.11-41.2%). The methods and the results from this study can be used to improve model prediction of TBI in humans.

A Multibody Model for Predicting Spatial Distribution of Human Brain Deformation Following Impact Loading

With an increasing focus on long-term consequences of concussive brain injuries, there is a new emphasis on developing tools that can accurately predict the mechanical response of the brain to impact loading. Although finite element models (FEM) estimate the brain response under dynamic loading, these models are not capable of delivering rapid (∼seconds) estimates of the brain's mechanical response. In this study, we develop a multibody spring-mass-damper model that estimates the regional motion of the brain to rotational accelerations delivered either about one anatomic axis or across three orthogonal axes simultaneously. In total, we estimated the deformation across 120 locations within a 50th percentile human brain. We found the multibody model (MBM) correlated, but did not precisely predict, the computed finite element response (average relative error: 18.4 ± 13.1%). We used machine learning (ML) to combine the prediction from the MBM and the loading kinematics (peak rotational acceleration, peak rotational velocity) and significantly reduced the discrepancy between the MBM and FEM (average relative error: 9.8 ± 7.7%). Using an independent sports injury testing set, we found the hybrid ML model also correlated well with predictions from a FEM (average relative error: 16.4 ± 10.2%). Finally, we used this hybrid MBM-ML approach to predict strains appearing in different locations throughout the brain, with average relative error estimates ranging from 8.6% to 25.2% for complex, multi-axial acceleration loading. Together, these results show a rapid and reasonably accurate method for predicting the mechanical response of the brain for single and multiplanar inputs, and provide a new tool for quickly assessing the consequences of impact loading throughout the brain.

Predicting Concussion Outcome by Integrating Finite Element Modeling and Network Analysis

Concussion is a significant public health problem affecting 1.6-2.4 million Americans annually. An alternative to reducing the burden of concussion is to reduce its incidence with improved protective equipment and injury mitigation systems. Finite element (FE) models of the brain response to blunt trauma are often used to estimate injury potential and can lead to improved helmet designs. However, these models have yet to incorporate how the patterns of brain connectivity disruption after impact affects the relay of information in the injured brain. Furthermore, FE brain models typically do not consider the differences in individual brain structural connectivities and their purported role in concussion risk. Here, we use graph theory techniques to integrate brain deformations predicted from FE modeling with measurements of network efficiency to identify brain regions whose connectivity characteristics may influence concussion risk. We computed maximum principal strain in 129 brain regions using head kinematics measured from 53 professional football impact reconstructions that included concussive and non-concussive cases. In parallel, using diffusion spectrum imaging data from 30 healthy subjects, we simulated structural lesioning of each of the same 129 brain regions. We simulated lesioning by removing each region one at a time along with all its connections. In turn, we computed the resultant change in global efficiency to identify regions important for network communication. We found that brain regions that deformed the most during an impact did not overlap with regions most important for network communication (Pearson's correlation, ρ = 0.07; p = 0.45). Despite this dissimilarity, we found that predicting concussion incidence was equally accurate when considering either areas of high strain or of high importance to global efficiency. Interestingly, accuracy for concussion prediction varied considerably across the 30 healthy connectomes. These results suggest that individual network structure is an important confounding variable in concussion prediction and that further investigation of its role may improve concussion prediction and lead to the development of more effective protective equipment.

Biomechanics of Periventricular Injury

Periventricular injury is frequently noted as one aspect of severe traumatic brain injury (TBI) and the presence of the ventricles has been hypothesized to be a primary pathogenesis associated with the prevalence of periventricular injury in patients with TBI. Although substantial endeavors have been made to elucidate the potential mechanism, a thorough explanation for this hypothesis appears lacking. In this study, a three-dimensional (3D) finite element (FE) model of the human head with an accurate representation of the cerebral ventricles is developed accounting for the fluid properties of the intraventricular cerebrospinal fluid (CSF) as well as its interaction with the brain. An additional model is developed by replacing the intraventricular CSF with a substitute with brain material. Both models are subjected to rotational accelerations with magnitudes suspected to induce severe diffuse axonal injury. The results reveal that the presence of the ventricles leads to increased strain in the periventricular region, providing a plausible explanation for the vulnerability of the periventricular region. In addition, the strain-exacerbation effect associated with the presence of the ventricles is also noted in the paraventricular region, although less pronounced than that in the periventricular region. The current study advances the understanding of the periventricular injury mechanism as well as the detrimental effects that the ventricles exert on the periventricular and paraventricular brain tissue.

Material properties of the skull layers of the primate parietal bone: A single-subject study

The outer cortical table of the parietal bone has been commonly used as a calvarial bone graft site for the craniofacial reconstruction. However, little is known about how removing the outer table may affect the function and structure of the inner table, and how the knowledge of the biomechanics and material properties of cortical bones will help the calvarial graft to better integrate into the biological and mechanical functions of its surrounding native tissues. In this study, it was hypothesized that there were significant differences in both density and material properties between inner and outer cortical plates in cranial bones. Twelve cylindrical specimens, including inner-outer layers, of cortical parietal bone of a female baboon were collected. Cortical thicknesses and densities were measured, and elastic properties were assessed using an ultrasonic technique. Results demonstrated remarkable difference in both thickness (t = 8.248, p ≤0.05) and density (t = 4.926, p≤0.05) between inner and outer cortical paired samples. Orthotropic characteristics of the cortical plates were detected as well, these findings suggest that there are differences in biomechanical properties between two surfaces of cranial bones at both tissue and organ levels. How these differences are linked to the stress environments of the inner and outer cranial cortical layers awaits further studies. Further study will greatly enhance our ability to address questions derived from both morphological and craniofacial medicine fields about the development and biomechanics of craniofacial skeletons.

Primary blast wave protection in combat helmet design: A historical comparison between present day and World War I

Since World War I, helmets have been used to protect the head in warfare, designed primarily for protection against artillery shrapnel. More recently, helmet requirements have included ballistic and blunt trauma protection, but neurotrauma from primary blast has never been a key concern in helmet design. Only in recent years has the threat of direct blast wave impingement on the head-separate from penetrating trauma-been appreciated. This study compares the blast protective effect of historical (World War I) and current combat helmets, against each other and 'no helmet' or bare head, for realistic shock wave impingement on the helmet crown. Helmets included World War I variants from the United Kingdom/United States (Brodie), France (Adrian), Germany (Stahlhelm), and a current United States combat variant (Advanced Combat Helmet). Helmets were mounted on a dummy head and neck and aligned along the crown of the head with a cylindrical shock tube to simulate an overhead blast. Primary blast waves of different magnitudes were generated based on estimated blast conditions from historical shells. Peak reflected overpressure at the open end of the blast tube was compared to peak overpressure measured at several head locations. All helmets provided significant pressure attenuation compared to the no helmet case. The modern variant did not provide more pressure attenuation than the historical helmets, and some historical helmets performed better at certain measurement locations. The study demonstrates that both historical and current helmets have some primary blast protective capabilities, and that simple design features may improve these capabilities for future helmet systems.

An assessment of blast modelling techniques for injury biomechanics research

Blast-induced traumatic brain injury (TBI) has been affecting combatants and civilians. The blast pressure wave is thought to have a significant contribution to blast-related TBI. Due to the limitations and difficulties of conducting blast tests on surrogates, computational modelling has been used as a key method for exploring this field. However, the blast wave modelling methods reported in current literature have drawbacks. They either cannot generate the desirable blast pressure wave history or they are unable to accurately simulate the blast wave/structure interaction. In addition, boundary conditions, which can have significant effects on model predictions, have not been described adequately. Here, we critically assess the commonly used methods for simulating blast wave propagation in air (open-field blast) and its interaction with the human body. We investigate the predicted blast wave time history, blast wave transmission, and the effects of various boundary conditions in three-dimensional (3D) models of blast prediction. We propose a suitable meshing topology, which enables accurate prediction of blast wave propagation and interaction with the human head and significantly decreases the computational cost in 3D simulations. Finally, we predict strain and strain rate in the human brain during blast wave exposure and show the influence of the blast wave modelling methods on the brain response. The findings presented here can serve as guidelines for accurately modelling blast wave generation and interaction with the human body for injury biomechanics studies and design of prevention systems.

Cavitation threshold evaluation of porcine cerebrospinal fluid using a Polymeric Split Hopkinson Pressure Bar-Confinement chamber apparatus

Studies investigating mild Traumatic Brain Injury (mTBI) in the military population using experimental head surrogates and Finite Element (FE) head models have demonstrated the existence of transient negative pressures occurring within the head at the contrecoup location to the blast wave impingement. It has been hypothesized that this negative pressure may cause cavitation of cerebrospinal fluid (CSF) and possibly lead to brain tissue damage from cavitation bubble collapse. The cavitation pressure threshold of human CSF is presently unknown, although existing FE studies in the literature have assumed a value of -100 kPa. In the present study, the cavitation threshold of degassed porcine CSF at body temperature (37 °C) was measured using a unique modified Polymeric Split Hopkinson Pressure Bar apparatus, and compared to thresholds of distilled water at various conditions. The loading pulse generated in the apparatus was comparable to experimentally measured pressures resulting from blast exposure, and those predicted by an FE model. The occurrence of cavitation was identified using high-speed imaging and the corresponding pressures were determined using a computational model of the apparatus that was previously developed and validated. The probability of cavitation was calculated (ISO/TS, 18506) from forty-one experimental tests on porcine CSF, representing an upper bound for in vivo CSF. The 50% probability of cavitation for CSF (-0.467 MPa ± 7%) was lower than that of distilled water (-1.37 MPa ± 16%) under the same conditions. The lesser threshold of CSF could be related to the constituents such as blood cells and proteins. The results of this study can be used to inform FE head models subjected to blast exposure and improve prediction of the potential for CSF cavitation and response of brain tissue.

Development of a Single-Degree-of-Freedom Mechanical Model for Predicting Strain-Based Brain Injury Responses

Linking head kinematics to injury risk has been the focus of numerous brain injury criteria. Although many early forms were developed using mechanics principles, recent criteria have been developed using empirical methods based on subsets of head impact data. In this study, a single-degree-of-freedom (sDOF) mechanical analog was developed to parametrically investigate the link between rotational head kinematics and brain deformation. Model efficacy was assessed by comparing the maximum magnitude of displacement to strain-based brain injury predictors from finite element (FE) human head models. A series of idealized rotational pulses covering a broad range of acceleration and velocity magnitudes (0.1-15 krad/s2 and 1-100 rad/s) with durations between 1 and 3000 ms were applied to the mechanical models about each axis of the head. Results show that brain deformation magnitude is governed by three categories of rotational head motion each distinguished by the duration of the pulse relative to the brain's natural period: for short-duration pulses, maximum brain deformation depended primarily on angular velocity magnitude; for long-duration pulses, brain deformation depended primarily on angular acceleration magnitude; and for pulses relatively close to the natural period, brain deformation depended on both velocity and acceleration magnitudes. These results suggest that brain deformation mechanics can be adequately explained by simple mechanical systems, since FE model responses and experimental brain injury tolerances exhibited similar patterns to the sDOF model. Finally, the sDOF model was the best correlate to strain-based responses and highlighted fundamental limitations with existing rotational-based brain injury metrics.

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.

Current playground surface test standards underestimate brain injury risk for children

Playgrounds surface test standards have been introduced to reduce the number of fatal and severe injuries. However, these test standards have several simplifications to make it practical, robust and cost-effective, such as the head is represented with a hemisphere, only the linear kinematics is evaluated and the body is excluded. Little is known about how these simplifications may influence the test results. The objective of this study was to evaluate the effect of these simplifications on global head kinematics and head injury prediction for different age groups. The finite element human body model PIPER was used and scaled to seven different age groups from 1.5 up to 18 years old, and each model was impacted at three different playground surface stiffness and three head impact locations. All simulations were performed in pairs, including and excluding the body. Linear kinematics and skull bone stress showed small influence if excluding the body while head angular kinematics and brain tissue strain were underestimated by the same simplification. The predicted performance of the three different playground surface materials, in terms of head angular kinematics and brain tissue strain, was also altered when including the body. A body and biofidelic neck need to be included, together with suitable head angular kinematics based injury thresholds, in future physical or virtual playground surface test standards to better prevent brain injuries.

A reanalysis of football impact reconstructions for head kinematics and finite element modeling

BACKGROUND

Head kinematics generated by laboratory reconstructions of professional football helmet impacts have been applied to computational models to study the biomechanics of concussion. Since the original publication of this data, techniques for evaluating accelerometer consistency and error correction have been developed. This study applies these techniques to the original reconstruction data and reanalyzes the results given the current state of concussion biomechanics.

METHODS

Consistency checks were applied to the sensor data collected in the head of each test dummy. Inconsistent data were corrected using analytical techniques, and head kinematics were recalculated from the corrected data. Reconstruction videos were reviewed to identify artefactual impacts during the reconstruction to establish the region of applicability for simulations. Corrected head kinematics were input into finite element brain models to investigate strain response to the corrected dataset.

FINDINGS

Multiple reconstruction cases had inconsistent sensor arrays caused by a problematic sensor; corrections to the arrays caused changes in calculated rotational head motion. These corrections increased median peak angular velocity for the concussion cases from 35.6 to 41.5 rad/s. Using the original kinematics resulted in an average error of 20% in maximum principal strain results for each case. Simulations of the reconstructions also demonstrated that simulation lengths less than 40 ms did not capture the entire brain strain response and under-predicted strain.

INTERPRETATION

This study corrects data that were used to determine concussion risk, and indicates altered head angular motion and brain strain response for many reconstructions. Conclusions based on the original data should be re-examined based on this new study.

Biomechanical simulation of traumatic brain injury in the rat

BACKGROUND

Traumatic brain injury poses an enormous clinical challenge. Rats are the animals most widely used in pre-clinical experiments. Biomechanical simulations of these experiments predict the distribution of mechanical stress and strain across key tissues. It is in theory possible to dramatically increase our understanding of traumatic brain injury pathophysiology by correlating stress and strain with histological and functional injury outcomes. This review summarizes the state of the art in biomechanical simulation of traumatic brain injury in the rat. It also places this body of knowledge in the context of the wider effort to understand traumatic brain injury in rats and in humans.

METHODS

Peer-reviewed research articles on biomechanical simulation of traumatic brain injury in the rat were reviewed and summarized.

FINDINGS

When mathematical models of traumatic brain injury in the rat first emerged, they relied on scant data regarding biomechanical properties. The data on relevant biomechanical properties has increased recently. However, experimental models of traumatic brain injury in the rat have also become less homogeneous. New and modified models have emerged that are biomechanically distinct from traditional models.

INTERPRETATION

Important progress in mathematical modeling and measurement of biomechanical properties has led to credible, predictive simulations of traditional, experimental models of traumatic brain injury in the rat, such as controlled cortical impact. However, recent trends such as the increasing popularity of closed head models and blast models create new biomechanical challenges. Investigators studying rat brain biomechanics must continue to innovate to keep pace with these developments.

Brain tissue strains vary with head impact location: A possible explanation for increased concussion risk in struck versus striking football players

BACKGROUND

On-field football helmet impacts over a large range of severities have caused concussions in some players but not in other players. One possible explanation for this variability is the struck player's helmet impact location.

METHODS

We examined the effect of impact location on regional brain tissue strain when input energy was held constant. Laboratory impacts were performed at 12 locations distributed over the helmet and the resulting head kinematics were simulated in two finite element models of the brain: the Simulated Injury Monitor and the Global Human Body Model Consortium brain model.

FINDINGS

Peak kinematics, injury metrics and brain strain varied significantly with impact location. Differences in impact location explained 33 to 37% of the total variance in brain strain for the whole brain and cerebrum, considerably more than the variance explained by impact location for the peak resultant head kinematics (8 to 23%) and slightly more than half of the variance explained by the difference in closing speed (57 to 61%). Both finite element models generated similar strain results, with minor variations for impacts that generated multi-axial rotations, larger variations in brainstem strains for some impact locations and a small bias for the cerebellum.

INTERPRETATION

Based on this experimental and computational simulation study, impact location on the football helmet has a large effect on regional brain tissue strain. We also found that the lowest strains consistently occurred in impacts to the crown and forehead, helmet locations commonly associated with the striking player.

Multi-Scale Modeling of Head Kinematics and Brain Tissue Response to Blast Exposure

Injuries resulting from blast exposure have been increasingly prevalent in recent conflicts, with a particular focus on the risk of head injury. In the current study, a multibody model (GEBOD) was used to investigate the gross kinematics resulting from blast exposure, including longer duration events such as the fall and ground impact. Additionally, detailed planar head models, in the sagittal and transverse planes, were used to model the primary blast wave interaction with the head, and resulting tissue response. For severe blast load cases (scaled distance less than 2), the translational head accelerations during primary blast were found to increase as the height-of-burst (HOB) was lowered, while the HOB was found to have no effect for cases with scaled distance greater than 2. The HOB was found to affect both the magnitude and direction of rotational accelerations, with increasing magnitudes as the HOB deviated from the height of the head. The choice of ground contact stiffness was found to greatly affect the predicted head accelerations during ground impact. For a medium soil ground material, the kinematics during ground impact were greater for scaled distances exceeding 1.5, below which the primary blast produced greater kinematic head response.

Evaluation of Brain Response during Head Impact in Youth Athletes Using an Anatomically Accurate Finite Element Model

During normal participation in football, players are exposed to repetitive subconcussive head impacts, or impacts that do not result in signs and symptoms of concussion. To better understand the effects of repetitive subconcussive impacts, the biomechanics of on-field head impacts and resulting brain deformation need to be well characterized. The current study evaluates local brain response to typical youth football head impacts using the atlas-based brain model (ABM), an anatomically accurate brain finite element (FE) model. Head impact kinematic data were collected from three local youth football teams using the Head Impact Telemetry (HIT) System. The azimuth and elevation angles were used to identify impacts near six locations of interest, and low, moderate, and high acceleration magnitudes (5th, 50th, and 95th percentiles, respectively) were calculated from the grouped impacts for FE simulation. Strain response in the brain was evaluated by examining the range and peak maximum principal strain (MPS) values in each element. A total of 40,538 impacts from 119 individual athletes were analyzed. Impacts to the facemask resulted in 0.18 MPS for the high magnitude impact category. This was 1.5 times greater than the oblique impact location, which resulted in the lowest strain value of 0.12 for high magnitude impacts. Overall, higher strains resulted from a 95th percentile lateral impact (41.0g, 2556 rad/sec²) with two predominant axes of rotation than from a 95th percentile frontal impact (67.6g, 2641 rad/sec²) with a single predominant axis of rotation. These findings highlight the importance of accounting for directional dependence and relative contribution of axes of rotation when evaluating head impact response.

Development of a Second-Order System for Rapid Estimation of Maximum Brain Strain

Diffuse brain injuries are assessed with deformation-based criteria that utilize metrics based on rotational head kinematics to estimate brain injury severity. Although numerous metrics have been proposed, many are based on empirically-derived models that use peak kinematics, which often limit their applicability to a narrow range of head impact conditions. However, over a broad range of impact conditions, brain deformation response to rotational head motion behaves similarly to a second-order mechanical system, which utilizes the full kinematic time history of a head impact. This study describes a new brain injury metric called Diffuse Axonal Multi-Axis General Evaluation (DAMAGE). DAMAGE is based on the equations of motion of a three-degree-of-freedom, coupled 2nd-order system, and predicts maximum brain strain using the directionally dependent angular acceleration time-histories from a head impact. Parameters for the effective mass, stiffness, and damping were determined using simplified rotational pulses which were applied multiaxially to a 50th percentile adult human male finite element model. DAMAGE was then validated with a separate database of 1747 head impacts including helmet, crash, and sled tests and human volunteer responses. Relative to existing rotational brain injury metrics that were evaluated in this study, DAMAGE was found to be the best predictor of maximum brain strain.

Improved safety standards are needed to better protect younger children at playgrounds

Playground-related traumatic brain injuries (TBIs) in children remain a considerable problem world-wide and current safety standards are being questioned due to historical reasons where the injury thresholds had been perpetuated from automobile industry. Here we investigated head injury mechanisms due to falls on playgrounds using a previously developed and validated age-scalable and positionable whole body child model impacted at front, back and side of the head simulating head-first falls from 1.59 meters (m). The results show that a playground material passing the current testing standards (HIC < 1000 and resultant linear acceleration <200 g) resulted in maximum strain in the brain higher than known injury thresholds, thus not offering sufficient protection especially for younger children. The analysis highlights the age dependence of head injuries in children due to playground falls and the youngest have a higher risk of brain injury and skull fracture. Further, the results provide the first biomechanical evidence guiding age-dependent injury thresholds for playground testing standards. The results also have direct implications for novel designs of playground materials for a better protection of children from TBIs. Only making the playground material thicker and more compliant is not sufficient. This study represents the first initiative of using full body human body models of children as a new tool to improve playground testing standards and to better protect the children at playgrounds.

Effect of human head morphological variability on the mechanical response of blast overpressure loading

A methodology is introduced to investigate the effect of intersubject head morphological variability on the mechanical response of the brain when subjected to blast overpressure loading. Nonrigid image registration techniques are leveraged to warp a manually segmented template model to an arbitrary number of subjects following a procedure to coarsely segment the subjects in batch. Finite element meshes are autogenerated, and blast analysis is conducted. The template model is initially constructed to enable the full automated implementation and application of the proposed methodology. The application of the proposed approach for an anterior-oriented blast has been demonstrated, and the results reveal that the pressure response in the brain does exhibit some dependence on head morphological variability. While the magnitude of the peak pressure response can vary by more than 30%, its location within the brain is unaffected by head morphological variability. A linear least squares analysis was conducted to demonstrate that the peak magnitude of pressure is uncorrelated with head volume while it is correlated with aspect ratio relating to the amount of exposed surface area to the blast. These features of the pressure response are likely due to the peak pressure occurring during the early stages of stress wave transmission and reflection. As a result, the pressure response due to blast overpressure loading is predominantly loading dependent while morphological variability has a secondary effect.

Fluid-structure interaction simulation of the brain-skull interface for acute subdural haematoma prediction

Traumatic brain injury is a leading cause of disability and mortality. Finite element-based head models are promising tools for enhanced head injury prediction, mitigation and prevention. The reliability of such models depends heavily on adequate representation of the brain-skull interaction. Nevertheless, the brain-skull interface has been largely simplified in previous three-dimensional head models without accounting for the fluid behaviour of the cerebrospinal fluid (CSF) and its mechanical interaction with the brain and skull. In this study, the brain-skull interface in a previously developed head model is modified as a fluid-structure interaction (FSI) approach, in which the CSF is treated on a moving mesh using an arbitrary Lagrangian-Eulerian multi-material formulation and the brain on a deformable mesh using a Lagrangian formulation. The modified model is validated against brain-skull relative displacement and intracranial pressure responses and subsequently imposed to an experimentally determined loading known to cause acute subdural haematoma (ASDH). Compared to the original model, the modified model achieves an improved validation performance in terms of brain-skull relative motion and is able to predict the occurrence of ASDH more accurately, indicating the superiority of the FSI approach for brain-skull interface modelling. The introduction of the FSI approach to represent the fluid behaviour of the CSF and its interaction with the brain and skull is crucial for more accurate head injury predictions.

Damage and Failure of Axonal Microtubule under Extreme High Strain Rate: An In-Silico Molecular Dynamics Study

As a major cytoskeleton element of the axon, the breaking of microtubules (MTs) has been considered as a major cause of the axon degeneration. High strain rate loading is considered as one of the key factors in microtubule breaking. Due to the small size of microtubule, the real-time behavior of microtubule breaking is hard to capture. This study employs fully-atomistic molecular dynamics (MD) simulation to determine the failure modes of microtubule under different loadings conditions such as, unidirectional stretching, bending and hydrostatic expansion. For each loading conditions, MT is subjected to extreme high strain rate (108-109 s-1) loading. We argue that such level of high strain rate may be realized during cavitation bubble implosion. For each loading type, we have determined the critical energy for MT rupture. The associated rupture mechanisms are also discussed. We observed that the stretching has the lowest energy barrier to break the MT at the nanosecond time scale. Moreover, the breakage between the dimers starts at ~16% of total strain when stretched, which is much smaller compared to the reported strain-at-failure (50%) for lower strain rate loading. It suggests that MT fails at a significantly smaller strain states when loaded at higher strain rates.

Cognition based bTBI mechanistic criteria; a tool for preventive and therapeutic innovations

Blast-induced traumatic brain injury has been associated with neurodegenerative and neuropsychiatric disorders. To date, although damage due to oxidative stress appears to be important, the specific mechanistic causes of such disorders remain elusive. Here, to determine the mechanical variables governing the tissue damage eventually cascading into cognitive deficits, we performed a study on the mechanics of rat brain under blast conditions. To this end, experiments were carried out to analyse and correlate post-injury oxidative stress distribution with cognitive deficits on a live rat exposed to blast. A computational model of the rat head was developed from imaging data and validated against in vivo brain displacement measurements. The blast event was reconstructed in silico to provide mechanistic thresholds that best correlate with cognitive damage at the regional neuronal tissue level, irrespectively of the shape or size of the brain tissue types. This approach was leveraged on a human head model where the prediction of cognitive deficits was shown to correlate with literature findings. The mechanistic insights from this work were finally used to propose a novel protective device design roadmap and potential avenues for therapeutic innovations against blast traumatic brain injury.

Development of a Metric for Predicting Brain Strain Responses Using Head Kinematics

Diffuse brain injuries are caused by excessive brain deformation generated primarily by rapid rotational head motion. Metrics that describe the severity of brain injury based on head motion often do not represent the governing physics of brain deformation, rendering them ineffective over a broad range of head impact conditions. This study develops a brain injury metric based on the response of a second-order mechanical system, and relates rotational head kinematics to strain-based brain injury metrics: maximum principal strain (MPS) and cumulative strain damage measure (CSDM). This new metric, universal brain injury criterion (UBrIC), is applicable over a broad range of kinematics encountered in automotive crash and sports. Efficacy of UBrIC was demonstrated by comparing it to MPS and CSDM predicted in 1600 head impacts using two different finite element (FE) brain models. Relative to existing metrics, UBrIC had the highest correlation with the FE models, and performed better in most impact conditions. While UBrIC provides a reliable measurement for brain injury assessment in a broad range of head impact conditions, and can inform helmet and countermeasure design, an injury risk function was not incorporated into its current formulation until validated strain-based risk functions can be developed and verified against human injury data.

Do blast induced skull flexures result in axonal deformation?

Subject-specific computer models (male and female) of the human head were used to investigate the possible axonal deformation resulting from the primary phase blast-induced skull flexures. The corresponding axonal tractography was explicitly incorporated into these finite element models using a recently developed technique based on the embedded finite element method. These models were subjected to extensive verification against experimental studies which examined their pressure and displacement response under a wide range of loading conditions. Once verified, a parametric study was developed to investigate the axonal deformation for a wide range of loading overpressures and directions as well as varying cerebrospinal fluid (CSF) material models. This study focuses on early times during a blast event, just as the shock transverses the skull (< 5 milliseconds). Corresponding boundary conditions were applied to eliminate the rotation effects and the resulting axonal deformation. A total of 138 simulations were developed– 128 simulations for studying the different loading scenarios and 10 simulations for studying the effects of CSF material model variance–leading to a total of 10,702 simulation core hours. Extreme strains and strain rates along each of the fiber tracts in each of these scenarios were documented and presented here. The results suggest that the blast-induced skull flexures result in strain rates as high as 150–378 s^-1. These high-strain rates of the axonal fiber tracts, caused by flexural displacement of the skull, could lead to a rate dependent micro-structural axonal damage, as pointed by other researchers.

Impact & Blast Traumatic Brain Injury: Implications for Therapy

Traumatic brain injury (TBI) is one of the most frequent causes of combat casualties in Operations Iraqi Freedom (OIF), Enduring Freedom (OEF), and New Dawn (OND). Although less common than combat-related blast exposure, there have been significant numbers of blast injuries in civilian populations in the United States. Current United States Department of Defense (DoD) ICD-9 derived diagnoses of TBI in the DoD Health Care System show that, for 2016, severe and moderate TBIs accounted for just 0.7% and 12.9%, respectively, of the total of 13,634 brain injuries, while mild TBIs (mTBIs) accounted for 86% of the total. Although there is a report that there are differences in the frequency of long-term complications in mTBI between blast and non-blast TBIs, clinical presentation is classified by severity score rather than mechanism because severity scoring is associated with prognosis in clinical practice. Blast TBI (bTBI) is unique in its pathology and mechanism, but there is no treatment specific for bTBIs-these patients are treated similarly to TBIs in general and therapy is tailored on an individual basis. Currently there is no neuroprotective drug recommended by the clinical guidelines based on evidence.

Primary Blast Brain Injury Mechanisms: Current Knowledge, Limitations, and Future Directions

Mild blast traumatic brain injury (bTBI) accounts for the majority of brain injury in United States service members and other military personnel worldwide. The mechanisms of primary blast brain injury continue to be disputed with little evidence to support one or a combination of theories. The main hypotheses addressed in this review are blast wave transmission through the skull orifices, direct cranial transmission, skull flexure dynamics, thoracic surge, acceleration, and cavitation. Each possible mechanism is discussed using available literature with the goal of focusing research efforts to address the limitations and challenges that exist in blast injury research. Multiple mechanisms may contribute to the pathology of bTBI and could be dependent on magnitudes and orientation to blast exposure. Further focused biomechanical investigation with cadaver, in vivo, and finite element models would advance our knowledge of bTBI mechanisms. In addition, this understanding could guide future research and contribute to the greater goal of developing relevant injury criteria and mandates to protect our soldiers on the battlefield.

An injectable hydrogel enhances tissue repair after spinal cord injury by promoting extracellular matrix remodeling

The cystic cavity that develops following injuries to brain or spinal cord is a major obstacle for tissue repair in central nervous system (CNS). Here we report that injection of imidazole-poly(organophosphazenes) (I-5), a hydrogel with thermosensitive sol–gel transition behavior, almost completely eliminates cystic cavities in a clinically relevant rat spinal cord injury model. Cystic cavities are bridged by fibronectin-rich extracellular matrix. The fibrotic extracellular matrix remodeling is mediated by matrix metalloproteinase-9 expressed in macrophages within the fibrotic extracellular matrix. A poly(organophosphazenes) hydrogel lacking the imidazole moiety, which physically interacts with macrophages via histamine receptors, exhibits substantially diminished bridging effects. I-5 injection improves coordinated locomotion, and this functional recovery is accompanied by preservation of myelinated white matter and motor neurons and an increase in axonal reinnervation of the lumbar motor neurons. Our study demonstrates that dynamic interactions between inflammatory cells and injectable biomaterials can induce beneficial extracellular matrix remodeling to stimulate tissue repair following CNS injuries.

The cystic cavity that develops following injuries to brain or spinal cord is a major obstacle. Here the authors show an injection of imidazole poly(organophosphazenes), a hydrogel with thermosensitive sol–gel transition behavior, almost completely eliminates cystic cavities in a clinically relevant rat spinal cord injury model.

Evaluation of Head and Brain Injury Risk Functions Using Sub-Injurious Human Volunteer Data

Risk assessment models are developed to estimate the probability of brain injury during head impact using mechanical response variables such as head kinematics and brain tissue deformation. Existing injury risk functions have been developed using different datasets based on human volunteer and scaled animal injury responses to impact. However, many of these functions have not been independently evaluated with respect to laboratory-controlled human response data. In this study, the specificity of 14 existing brain injury risk functions was assessed by evaluating their ability to correctly predict non-injurious response using previously conducted sled tests with well-instrumented human research volunteers. Six degrees-of-freedom head kinematics data were obtained for 335 sled tests involving subjects in frontal, lateral, and oblique sled conditions up to 16 Gs peak sled acceleration. A review of the medical reports associated with each individual test indicated no clinical diagnosis of mild or moderate brain injury in any of the cases evaluated. Kinematic-based head and brain injury risk probabilities were calculated directly from the kinematic data, while strain-based risks were determined through finite element model simulation of the 335 tests. Several injury risk functions substantially over predict the likelihood of concussion and diffuse axonal injury; proposed maximum principal strain-based injury risk functions predicted nearly 80 concussions and 14 cases of severe diffuse axonal injury out of the 335 non-injurious cases. This work is an important first step in assessing the efficacy of existing brain risk functions and highlights the need for more predictive injury assessment models.

Modeling the mechanics of axonal fiber tracts using the embedded finite element method

A subject-specific human head finite element model with embedded axonal fiber tractography obtained from diffusion tensor imaging was developed. The axonal fiber tractography finite element model was coupled with the volumetric elements in the head model using the embedded element method. This technique enables the calculation of axonal strains and real-time tracking of the mechanical response of the axonal fiber tracts. The coupled model was then verified using pressure and relative displacement-based (between skull and brain) experimental studies and was employed to analyze a head impact, demonstrating the applicability of this method in studying axonal injury. Following this, a comparison study of different injury criteria was performed. This model was used to determine the influence of impact direction on the extent of the axonal injury. The results suggested that the lateral impact loading is more dangerous compared to loading in the sagittal plane, a finding in agreement with previous studies. Through this analysis, we demonstrated the viability of the embedded element method as an alternative numerical approach for studying axonal injury in patient-specific human head models.

Blast Scaling Parameters: Transitioning from Lung to Skull Base Metrics

Neurotrauma from blast exposure is one of the single most characteristic injuries of modern warfare. Understanding blast traumatic brain injury is critical for developing new treatment options for warfighters and civilians exposed to improvised explosive devices. Unfortunately, the pre-clinical models that are widely utilized to investigate blast exposure are based on archaic lung based parameters developed in the early 20th century. Improvised explosive devices produce a different type of injury paradigm than the typical mortar explosion. Protective equipment for the chest cavity has also improved over the past 100 years. In order to improve treatments, it is imperative to develop models that are based more on skull-based parameters. In this mini-review, we discuss the important anatomical and biochemical features necessary to develop a skull-based model.

Evaluation of brain tissue responses because of the underwash overpressure of helmet and faceshield under blast loading

Head protective tools such as helmets and faceshields can induce a localized high pressure region on the skull because of the underwash of the blast waves. Whether this underwash overpressure can affect the brain tissue response is still unknown. Accordingly, a computational approach was taken to confirm the incidence of underwash with regards to blast direction, as well as examine the influence of this effect on the mechanical responses of the brain. The variation of intracranial pressure (ICP) as one of the major injury predictors, as well as the maximum shear stress were mainly addressed in this study. Using a nonlinear finite element (FE) approach, generation and interaction of blast waves with the unprotected, helmeted, and fully protected (helmet and faceshield protected) FE head models were modeled using a multi-material arbitrary Lagrangian-Eulerian (ALE) method and a fluid-structure interaction (FSI) coupling algorithm. The underwash incidence overpressure was found to greatly change with the blast direction. Moreover, while underwash induced ICP (U-ICP) did not exceed the peak ICP of the unprotected head, it was comparable and even more than the peak ICP imposed on the protected heads by the primary shockwaves (Coup-ICP). It was concluded that while both helmet and faceshield protected the head against blast waves, the underwash overpressure affected the brain tissue response and altered the dynamic load experienced by the brain as it led to increased ICP levels at the countercoup site, imparted elevated skull flexure, and induced high negative pressure regions. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Effect of pillow height on the biomechanics of the head-neck complex: investigation of the cranio-cervical pressure and cervical spine alignment

BACKGROUND

While appropriate pillow height is crucial to maintaining the quality of sleep and overall health, there are no universal, evidence-based guidelines for pillow design or selection. We aimed to evaluate the effect of pillow height on cranio-cervical pressure and cervical spine alignment.

METHODS

Ten healthy subjects (five males) aged 26 ± 3.6 years were recruited. The average height, weight, and neck length were 167 ± 9.3 cm, 59.6 ± 11.9 kg, and 12.9 ± 1.2 cm respectively. The subjects lay on pillows of four different heights (H0, 110 mm; H1, 130 mm; H2, 150 mm; and H3, 170 mm). The cranio-cervical pressure distribution over the pillow was recorded; the peak and average pressures for each pillow height were compared by one-way ANOVA with repeated measures. Cervical spine alignment was studied using a finite element model constructed based on data from the Visible Human Project. The coordinate of the center of each cervical vertebra were predicted for each pillow height. Three spine alignment parameters (cervical angle, lordosis distance and kyphosis distance) were identified.

RESULTS

The average cranial pressure at pillow height H3 was approximately 30% higher than that at H0, and significantly different from those at H1 and H2 (p < 0.05). The average cervical pressure at pillow height H0 was 65% lower than that at H3, and significantly different from those at H1 and H2 (p < 0.05). The peak cervical pressures at pillow heights H2 and H3 were significantly different from that at H0 (p < 0.05). With respect to cervical spine alignment, raising pillow height from H0 to H3 caused an increase of 66.4% and 25.1% in cervical angle and lordosis distance, respectively, and a reduction of 43.4% in kyphosis distance.

DISCUSSION

Pillow height elevation significantly increased the average and peak pressures of the cranial and cervical regions, and increased the extension and lordosis of the cervical spine. The cranio-cervical pressures and cervical spine alignment were height-specific, and they were believed to reflect quality of sleep. Our results provide a quantitative and objective evaluation of the effect of pillow height on the biomechanics of the head-neck complex, and have application in pillow design and selection.

Untangling the Effect of Head Acceleration on Brain Responses to Blast Waves

Multiple injury-causing mechanisms, such as wave propagation, skull flexure, cavitation, and head acceleration, have been proposed to explain blast-induced traumatic brain injury (bTBI). An accurate, quantitative description of the individual contribution of each of these mechanisms may be necessary to develop preventive strategies against bTBI. However, to date, despite numerous experimental and computational studies of bTBI, this question remains elusive. In this study, using a two-dimensional (2D) rat head model, we quantified the contribution of head acceleration to the biomechanical response of brain tissues when exposed to blast waves in a shock tube. We compared brain pressure at the coup, middle, and contre-coup regions between a 2D rat head model capable of simulating all mechanisms (i.e., the all-effects model) and an acceleration-only model. From our simulations, we determined that head acceleration contributed 36-45% of the maximum brain pressure at the coup region, had a negligible effect on the pressure at the middle region, and was responsible for the low pressure at the contre-coup region. Our findings also demonstrate that the current practice of measuring rat brain pressures close to the center of the brain would record only two-thirds of the maximum pressure observed at the coup region. Therefore, to accurately capture the effects of acceleration in experiments, we recommend placing a pressure sensor near the coup region, especially when investigating the acceleration mechanism using different experimental setups.

Deficits in Visual System Functional Connectivity after Blast-Related Mild TBI are Associated with Injury Severity and Executive Dysfunction

INTRODUCTION

Approximately, 275,000 American service members deployed to Iraq or Afghanistan have sustained a mild traumatic brain injury (mTBI), with 75% of these incidents involving an explosive blast. Visual processing problems and cognitive dysfunction are common complaints following blast-related mTBI.

METHODS

In 127 veterans, we examined resting fMRI functional connectivity (FC) of four key nodes within the visual system: lateral geniculate nucleus (LGN), primary visual cortex (V1), lateral occipital gyrus (LO), and fusiform gyrus (FG). Regression analyses were performed (i) to obtain correlations between time-series from each seed and all voxels in the brain, and (ii) to identify brain regions in which FC variability was related to blast mTBI severity. Blast-related mTBI severity was quantified as the sum of the severity scores assigned to each of the three most significant blast-related injuries self-reported by subjects. Correlations between FC and performance on executive functioning tasks were performed across participants with available behavioral data (n = 94).

RESULTS

Greater blast mTBI severity scores were associated with lower FC between: (A) LGN seed and (i) medial frontal gyrus, (ii) lingual gyrus, and (iii) right ventral anterior nucleus of thalamus; (B) V1 seed and precuneus; (C) LO seed and middle and superior frontal gyri; (D) FG seed and (i) superior and medial frontal gyrus, and (ii) left middle frontal gyrus. Finally, lower FC between visual network regions and frontal cortical regions predicted worse performance on the WAIS digit-symbol coding task.

CONCLUSION

These are the first published results that directly illustrate the relationship between blast-related mTBI severity, visual pathway neural networks, and executive dysfunction - results that highlight the detrimental relationship between blast-related brain injury and the integration of visual sensory input and executive processes.