Biomechanical responses of a pig head under blast loading: a computational simulation

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

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

A 3-D Finite-Element Minipig Model to Assess Brain Biomechanical Responses to Blast Exposure

Despite years of research, it is still unknown whether the interaction of explosion-induced blast waves with the head causes injury to the human brain. One way to fill this gap is to use animal models to establish “scaling laws” that project observed brain injuries in animals to humans. This requires laboratory experiments and high-fidelity mathematical models of the animal head to establish correlates between experimentally observed blast-induced brain injuries and model-predicted biomechanical responses. To this end, we performed laboratory experiments on Göttingen minipigs to develop and validate a three-dimensional (3-D) high-fidelity finite-element (FE) model of the minipig head. First, we performed laboratory experiments on Göttingen minipigs to obtain the geometry of the cerebral vasculature network and to characterize brain-tissue and vasculature material properties in response to high strain rates typical of blast exposures. Next, we used the detailed cerebral vasculature information and species-specific brain tissue and vasculature material properties to develop the 3-D high-fidelity FE model of the minipig head. Then, to validate the model predictions, we performed laboratory shock-tube experiments, where we exposed Göttingen minipigs to a blast overpressure of 210 kPa in a laboratory shock tube and compared brain pressures at two locations. We observed a good agreement between the model-predicted pressures and the experimental measurements, with differences in maximum pressure of less than 6%. Finally, to evaluate the influence of the cerebral vascular network on the biomechanical predictions, we performed simulations where we compared results of FE models with and without the vasculature. As expected, incorporation of the vasculature decreased brain strain but did not affect the predictions of brain pressure. However, we observed that inclusion of the cerebral vasculature in the model changed the strain distribution by as much as 100% in regions near the interface between the vasculature and the brain tissue, suggesting that the vasculature does not merely decrease the strain but causes drastic redistributions. This work will help establish correlates between observed brain injuries and predicted biomechanical responses in minipigs and facilitate the creation of scaling laws to infer potential injuries in the human brain due to exposure to blast waves.

A Machine Learning Approach to Investigate the Uncertainty of Tissue-Level Injury Metrics for Cerebral Contusion

Controlled cortical impact (CCI) on porcine brain is often utilized to investigate the pathophysiology and functional outcome of focal traumatic brain injury (TBI), such as cerebral contusion (CC). Using a finite element (FE) model of the porcine brain, the localized brain strain and strain rate resulting from CCI can be computed and compared to the experimentally assessed cortical lesion. This way, tissue-level injury metrics and corresponding thresholds specific for CC can be established. However, the variability and uncertainty associated with the CCI experimental parameters contribute to the uncertainty of the provoked cortical lesion and, in turn, of the predicted injury metrics. Uncertainty quantification via probabilistic methods (Monte Carlo simulation, MCS) requires a large number of FE simulations, which results in a time-consuming process. Following the recent success of machine learning (ML) in TBI biomechanical modeling, we developed an artificial neural network as surrogate of the FE porcine brain model to predict the brain strain and the strain rate in a computationally efficient way. We assessed the effect of several experimental and modeling parameters on four FE-derived CC injury metrics (maximum principal strain, maximum principal strain rate, product of maximum principal strain and strain rate, and maximum shear strain). Next, we compared the in silico brain mechanical response with cortical damage data from in vivo CCI experiments on pig brains to evaluate the predictive performance of the CC injury metrics. Our ML surrogate was capable of rapidly predicting the outcome of the FE porcine brain undergoing CCI. The now computationally efficient MCS showed that depth and velocity of indentation were the most influential parameters for the strain and the strain rate-based injury metrics, respectively. The sensitivity analysis and comparison with the cortical damage experimental data indicate a better performance of maximum principal strain and maximum shear strain as tissue-level injury metrics for CC. These results provide guidelines to optimize the design of CCI tests and bring new insights to the understanding of the mechanical response of brain tissue to focal traumatic brain injury. Our findings also highlight the potential of using ML for computationally efficient TBI biomechanics investigations.

Animal models of traumatic brain injury: a review of pathophysiology to biomarkers and treatments

Traumatic brain injury (TBI) is one of the main causes of death and disability in both civilian and military population. TBI may occur via a variety of etiologies, all of which involve trauma to the head. However, the neuroprotective drugs which were found to be very effective in animal TBI models failed in phase II or phase III clinical trials, emphasizing a compelling need to review the current status of animal TBI models and therapeutic strategies. No single animal model can adequately mimic all aspects of human TBI owing to the heterogeneity of clinical TBI. However, due to the ethical limitations, it is difficult to precisely emulate the TBI mechanisms that occur in humans. Therefore, many animal models with varying severity and mechanisms of brain injury have been developed, and each model has its own pros and cons in its implementation for TBI research. These challenges pose a need for study of continued TBI mechanisms, brain injury severity, duration, treatment strategies, and optimization of animal models across the neurotrauma research community. The aim of this review is to discuss (1) causes of TBI, (2) its prevalence in military and civilian population, (3) classification and pathophysiology of TBI, (4) biomarkers and detection methods, (5) animal models of TBI, and (6) the advantages and disadvantages of each model and the species used, as well as possible treatments.

Effect of blast loading on the risk of rib fractures: a preliminary 3D numerical investigation

Blast is a complex phenomenon which needs to be understood, especially in a military framework, where this kind of loading can have severe consequences on the human body. Indeed, the literature lists a number of studies which try to investigate the dangerousness of such a phenomenon, both at experimental and numerical level, and the injuries that could occur when the fighters or police officers are stroke by blast wave. When focusing on primary blast effect, this paper analyses the effect of this loading on the occurrence of rib fracture, using previously developed injury risk curves.

Deformation of an airfoil-shaped brain surrogate under shock wave loading

Improvised explosive devices (IEDs), during military operations, has increased the incidence of blast-induced traumatic brain injuries (bTBI). The shock wave is created following detonation of the IED. This shock wave propagates through the atmosphere and may cause bTBI. As a result, bTBI research has gained increased attention since this injury's mechanism is not thoroughly understood. To develop better protection and treatment against bTBI, further studies of soft material (e.g. brain and brain surrogate) deformation due to shock wave exposure are essential. However, the dynamic mechanical behavior of soft materials, subjected to high strain rates from shock wave exposure, remains unknown. Thus, an experimental approach was applied to study the interaction between the shock wave and an unconfined brain surrogate fabricated from a biomaterial (i.e. polydimethylsiloxane (PDMS)). The 1:70 ratio of curing agent-to-base determined the stiffness of the PDMS (Sylgard 184, Dow Corning Corporation). A stretched NACA 2414 (upper airfoil surface) geometry was utilized to resemble the shape of a porcine brain. Digital image correlation (DIC) technique was applied to measure the deformation on the brain surrogate's surface following shock wave exposure. A shock tube was utilized to create the shock wave and pressure transducers measured the pressure in the vicinity of the brain surrogate. A transient structural analysis using ANSYS Workbench was performed to predict the elastic modulus of 1:70 airfoil-shaped PDMS, at a strain rate on the order of 6 × 10³ s^-1. Both compression and protrusion of the PDMS surface were found due to the shock wave exposure. Negative pressure was found in a semi-ring area, which was the cause of protrusion. Oscillation of the brain surrogate, due to the shock wave loading, was found. The frequency of oscillation does not depend on the geometry. This work will add to the limited data describing the dynamic behavior of soft materials due to shock wave loading.

Variations in Constitutive Properties of the Fluid Elicit Divergent Vibrational and Pressure Response Under Shock Wave Loading

We performed a characterization of the shock wave loading on the response of the specimen representing a simplified head model. A polycarbonate cylinder (2-in. outer diameter, wall thickness: 0.06 or 0.12 in.) was filled with two fluids: pure de-ionized water and 40% glycerol in water, which differ only slightly in their constitutive material properties. These two fluids were selected to represent the cerebrospinal fluid and cerebral blood, using their high strain rate viscosity as a primary selection criterion. The model specimen was exposed to a single shock wave with two nominal intensities: 70 and 130 kPa overpressure. The response of the model was measured using three strain gauges and three pressure sensors, one mounted on the front face of the cylinder and two embedded in the cylinder to measure the pressure inside of the fluid. We noted several discriminant characteristics in the collected data, which indicate that the type of fluid is strongly influencing the response. The vibrations of the cylinder walls are strongly correlated with the fluid kind. The similarity analysis via the Pearson coefficient indicated that the pressure waveforms in the fluid are only moderately correlated, and these results were further corroborated by Euclidean distance analysis. Continuous wavelet transform of pressure waveforms revealed that the frequency response is strongly correlated with the properties of the fluid. The observed differences in strain and pressure modalities stem from relatively small differences in the properties of the fluids used in this study.

The effects of explosion sound on the brain based on electroencephalogram signals

In this paper, the brain reactions to explosion sound are investigated. Electroencephalogram (EEG) signals of 17 people were recorded. Subjects were selected from three groups: staff who did not face explosion before, blasting employees of surface, and underground mining workers. Routine EEG signals, also called explosion sounds, were recorded. Explosion sound was broadcasted without any previous alarm. Then it was repeated with their pre-awareness. Gradient and time duration of Delta band of EEG signals were extracted as features. Results showed that for blasting employees, especially underground ones, an increase of mean amplitude of delta band power of EEG signals of motor, speech, auditory and visual sensations were occurred, while in the case of staff it was decreased. This shows consciousness arising of blasting employees with hearing explosion sound. The reaction of somatosensory sense was dropped for all three groups. In general, reaction time for blasting employees has been longer than staff.

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.

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

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

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.

On the Development of Interspecies Traumatic Brain Injury Correspondence Rules

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

Modeling the Long-Term Consequences of Repeated Blast-Induced Mild Traumatic Brain Injuries

Repeated mild traumatic brain injury (rmTBI) caused by playing collision sports or by exposure to blasts during military operations can lead to late onset, chronic diseases such as chronic traumatic encephalopathy (CTE), a progressive neurodegenerative condition that manifests in increasingly severe neuropsychiatric abnormalities years after the last injury. Currently, because of the heterogeneity of the clinical presentation, confirmation of a CTE diagnosis requires post-mortem examination of the brain. The hallmarks of CTE are abnormal accumulation of phosphorylated tau protein, TDP-43 immunoreactive neuronal cytoplasmic inclusions, and astroglial abnormalities, but the pathomechanism leading to these terminal findings remains unknown. Animal modeling can play an important role in the identification of CTE pathomechanisms, the development of early stage diagnostic and prognostic biomarkers, and pharmacological interventions. Modeling the long-term consequences of blast rmTBI in animals is especially challenging because of the complexities of blast physics and animal-to-human scaling issues. This review summarizes current knowledge about the pathobiologies of CTE and rmbTBI and discusses problems as well as potential solutions related to high-fidelity modeling of rmbTBI and determining its long-term consequences.

Considerations for Experimental Animal Models of Concussion, Traumatic Brain Injury, and Chronic Traumatic Encephalopathy-These Matters Matter

Animal models of concussion, traumatic brain injury (TBI), and chronic traumatic encephalopathy (CTE) are widely available and routinely deployed in laboratories around the world. Effective animal modeling requires careful consideration of four basic principles. First, animal model use must be guided by clarity of definitions regarding the human disease or condition being modeled. Concussion, TBI, and CTE represent distinct clinical entities that require clear differentiation: concussion is a neurological syndrome, TBI is a neurological event, and CTE is a neurological disease. While these conditions are all associated with head injury, the pathophysiology, clinical course, and medical management of each are distinct. Investigators who use animal models of these conditions must take into account these clinical distinctions to avoid misinterpretation of results and category mistakes. Second, model selection must be grounded by clarity of purpose with respect to experimental questions and frame of reference of the investigation. Distinguishing injury context ("inputs") from injury consequences ("outputs") may be helpful during animal model selection, experimental design and execution, and interpretation of results. Vigilance is required to rout out, or rigorously control for, model artifacts with potential to interfere with primary endpoints. The widespread use of anesthetics in many animal models illustrates the many ways that model artifacts can confound preclinical results. Third, concordance between key features of the animal model and the human disease or condition being modeled is required to confirm model biofidelity. Fourth, experimental results observed in animals must be confirmed in human subjects for model validation. Adherence to these principles serves as a bulwark against flawed interpretation of results, study replication failure, and confusion in the field. Implementing these principles will advance basic science discovery and accelerate clinical translation to benefit people affected by concussion, TBI, and CTE.

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.

Development of a new biomechanical indicator for primary blast-induced brain injury

Primary blast-induced traumatic brain injury (bTBI) has been observed at the boundary of brain tissue and cerebrospinal fluid (CSF). Such injury can hardly be explained by using the theory of compressive wave propagation, since both the solid and fuid materials have similar compressibility and thus the intracranial pressure (ICP) has a continuous distribution across the boundary. Since they have completely different shear properties, it is hypothesized the injury at the interface is caused by shear wave. In the present study, a preliminary combined numerical and theoretical analysis was conducted based on the theory of shear wave propagation/reflection. Simulation results show that higher lateral acceleration of brain tissue particles is concentrated in the boundary region. Based on this fnding, a new biomechanical vector, termed as strain gradient, was suggested for primary bTBI. The subsequent simple theoretical analysis reveals that this parameter is proportional to the value of lateral acceleration. At the boundary of lateral ventricles, high spatial strain gradient implies that the brain tissue in this area (where neuron cells may be contained) undergo significantly different strains and large velocity discontinuity, which may result in mechanical damage of the neuron cells.

Quantitative electroencephalography in a swine model of blast-induced brain injury

OBJECTIVE

Electroencephalography (EEG) was used to examine brain activity abnormalities earlier after blast exposure using a swine model to develop a qEEG data analysis protocol.

METHODS

Anaesthetized swine were exposed to 420-450 Kpa blast overpressure and survived for 3 days after blast. EEG recordings were performed at 15 minutes before the blast and 15 minutes, 30 minutes, 2 hours and 1, 2 and 3 days post-blast using surface recording electrodes and a Biopac 4-channel data acquisition system. Off-line quantitative EEG (qEEG) data analysis was performed to determine qEEG changes.

RESULTS

Blast induced qEEG changes earlier after blast exposure, including a decrease of mean amplitude (MAMP), an increase of delta band power, a decrease of alpha band root mean square (RMS) and a decrease of 90% spectral edge frequency (SEF90).

CONCLUSIONS

This study demonstrated that qEEG is sensitive for cerebral injury. The changes of qEEG earlier after the blast indicate the potential of utilization of multiple parameters of qEEG for diagnosis of blast-induced brain injury. Early detection of blast induced brain injury will allow early screening and assessment of brain abnormalities in soldiers to enable timely therapeutic intervention.

Biomechanical Responses of the Brain in Swine Subject to Free-Field Blasts

Blast-induced traumatic brain injury (bTBI) is a signature wound of modern warfare. The current incomplete understanding of its injury mechanism impedes the development of strategies for effective protection of bTBI. Despite a considerable amount of experimental animal studies focused on the evaluation of brain neurotrauma caused by blast exposure, there is very limited knowledge on the biomechanical responses of the gyrenecephalic brain subjected to primary free-field blast waves imposed in vivo. This study aims to evaluate the external and internal mechanical responses of the brain against different levels of blast loading with Yucatan swine in free field. The incident overpressure (IOP) was generated using 3.6 kg of C4 charge placed at three standoff distances from the swine. Five swine were exposed to a total of 19 blasts. The three average peak IOP pressure levels in this study were 148.8, 278.9, and 409.2 kPa as measured by a pencil probe. The duration of the first positive wave was in the range of 2.1–3 ms. Pressure changes in the brain and head kinematics were recorded with intracranial pressure (ICP) sensors, linear accelerometers, and angular rate sensors. The corresponding average peak ICPs were in the range of 79–143, 210–281, and 311–414 kPa designated as low, medium, and high blast level, respectively. Peak head linear accelerations were in the range of 120–412 g. A positive correlation between IOP and its corresponding biomechanical responses of the brain was also observed. These experimental data can be used to validate computer models of bTBI.

When physics meets biology: low and high-velocity penetration, blunt impact, and blast injuries to the brain

The incidence of traumatic brain injuries (TBI) in the US has reached epidemic proportions with well over 2 million new cases reported each year. TBI can occur in both civilians and warfighters, with head injuries occurring in both combat and non-combat situations from a variety of threats, including ballistic penetration, acceleration, blunt impact, and blast. Most generally, TBI is a condition in which physical loads exceed the capacity of brain tissues to absorb without injury. More specifically, TBI results when sufficient external force is applied to the head and is subsequently converted into stresses that must be absorbed or redirected by protective equipment. If the stresses are not sufficiently absorbed or redirected, they will lead to damage of extracranial soft tissue and the skull. Complex interactions and kinematics of the head, neck and jaw cause strains within the brain tissue, resulting in structural, anatomical damage that is characteristic of the inciting insult. This mechanical trauma then initiates a neuro-chemical cascade that leads to the functional consequences of TBI, such as cognitive impairment. To fully understand the mechanisms by which TBI occurs, it is critically important to understand the effects of the loading environments created by these threats. In the following, a review is made of the pertinent complex loading conditions and how these loads cause injury. Also discussed are injury thresholds and gaps in knowledge, both of which are needed to design improved protective systems.

Altering endoplasmic reticulum stress in a model of blast-induced traumatic brain injury controls cellular fate and ameliorates neuropsychiatric symptoms

Neuronal injury following blast-induced traumatic brain injury (bTBI) increases the risk for neuropsychiatric disorders, yet the pathophysiology remains poorly understood. Blood-brain-barrier (BBB) disruption, endoplasmic reticulum (ER) stress, and apoptosis have all been implicated in bTBI. Microvessel compromise is a primary effect of bTBI and is postulated to cause subcellular secondary effects such as ER stress. What remains unclear is how these secondary effects progress to personality disorders in humans exposed to head trauma. To investigate this we exposed male rats to a clinically relevant bTBI model we have recently developed. The study examined initial BBB disruption using Evan's blue (EB), ER stress mechanisms, apoptosis and impulsive-like behavior measured with elevated plus maze (EPM). Large BBB openings were observed immediately following bTBI, and persisted for at least 6 h. Data showed increased mRNA abundance of stress response genes at 3 h, with subsequent increases in the ER stress markers C/EBP homologous protein (CHOP) and growth arrest and DNA damage-inducible protein 34 (GADD34) at 24 h. Caspase-12 and Caspase-3 were both cleaved at 24 h following bTBI. The ER stress inhibitor, salubrinal (SAL), was administered (1 mg/kg i.p.) to investigate its effects on neuronal injury and impulsive-like behavior associated with bTBI. SAL reduced CHOP protein expression, and diminished Caspase-3 cleavage, suggesting apoptosis attenuation. Interestingly, SAL also ameliorated impulsive-like behavior indicative of head trauma. These results suggest SAL plays a role in apoptosis regulation and the pathology of chronic disease. These observations provide evidence that bTBI involves ER stress and that the unfolded protein response (UPR) is a promising molecular target for the attenuation of neuronal injury.

Computational simulation of the mechanical response of brain tissue under blast loading

In the present study, numerical simulations of nonlinear wave propagation and shock formation in brain tissue have been presented and a new mechanism of injury for blast-induced neurotrauma (BINT) is proposed. A quasilinear viscoelastic (QLV) constitutive material model was used that encompasses the nonlinearity as well as the rate dependence of the tissue relevant to BINT modeling. A one-dimensional model was implemented using the discontinuous Galerkin finite element method and studied with displacement- and pressure-input boundary conditions. The model was validated against LS-DYNA finite element code and theoretical results for specific conditions that resulted in shock wave formation. It was shown that a continuous wave can become a shock wave as it propagates in the QLV brain tissue when the initial changes in acceleration are beyond a certain limit. The high spatial gradient of stress and strain at the shock front cause large relative motions at the cellular scale at high temporal rates even when the maximum stresses and strains are relatively low. This gradient-induced local deformation may occur away from the boundary and is proposed as a contributing factor to the diffuse nature of BINT.

A theoretical analysis of stress wave propagation in the head under primary blast loading

Traumatic brain injury due to primary blast loading has become a signature injury in recent military conflicts. Efforts have been made to study the stress wave propagation in the head. However, the relationship of incident pressure, reflected pressure and intracranial pressure is still not clear, and the experimental findings reported in the literature are contradictory. In this article, an analytical model is developed to calculate the stress wave transfer through a multiple-layered structure which is used to mimic the head. The model predicts stress at the scalp-skull and skull-brain interfaces as the functions of reflected pressure, which is further dependent on incident pressure. A numerical model is used to corroborate the theoretical predictions. It is concluded that scalp has an amplification effect on intracranial pressure. If scalp is absent, there exists a critical incident pressure, defined as P _cr at approximately 16 kPa. When peak incident pressure σ _in is higher than 16 kPa, the pressure at the skull-brain interface is greater than σ _in; otherwise, it is lower than σ _in.

Head and brain response to blast using sagittal and transverse finite element models

Mild traumatic brain injury caused by blast exposure from Improvised Explosive Devices has become increasingly prevalent in modern conflicts. To investigate head kinematics and brain tissue response in blast scenarios, two solid hexahedral blast-head models were developed in the sagittal and transverse planes. The models were coupled to an Arbitrary Lagrangian-Eulerian model of the surrounding air to model blast-head interaction, for three blast load cases (5 kg C4 at 3, 3.5 and 4 m). The models were validated using experimental kinematic data, where predicted accelerations were in good agreement with experimental tests, and intracranial pressure traces at four locations in the brain, where the models provided good predictions for frontal, temporal and parietal, but underpredicted pressures at the occipital location. Brain tissue response was investigated for the wide range of constitutive properties available. The models predicted relatively low peak principal brain tissue strains from 0.035 to 0.087; however, strain rates ranged from 225 to 571 s-1. Importantly, these models have allowed us to quantify expected strains and strain rates experienced in brain tissue, which can be used to guide future material characterization. These computationally efficient and predictive models can be used to evaluate protection and mitigation strategies in future analysis.

The mechanics of traumatic brain injury: a review of what we know and what we need to know for reducing its societal burden

Traumatic brain injury (TBI) is a significant public health problem, on pace to become the third leading cause of death worldwide by 2020. Moreover, emerging evidence linking repeated mild traumatic brain injury to long-term neurodegenerative disorders points out that TBI can be both an acute disorder and a chronic disease. We are at an important transition point in our understanding of TBI, as past work has generated significant advances in better protecting us against some forms of moderate and severe TBI. However, we still lack a clear understanding of how to study milder forms of injury, such as concussion, or new forms of TBI that can occur from primary blast loading. In this review, we highlight the major advances made in understanding the biomechanical basis of TBI. We point out opportunities to generate significant new advances in our understanding of TBI biomechanics, especially as it appears across the molecular, cellular, and whole organ scale.

Using anesthetics and analgesics in experimental traumatic brain injury

Valid modeling of traumatic brain injury (TBI) requires accurate replication of both the mechanical forces that cause the primary injury and the conditions that lead to secondary injuries observed in human patients. The use of animals in TBI research is justified by the lack of in vitro or computer models that can sufficiently replicate the complex pathological processes involved. Measures to reduce nociception and distress must be implemented, but the administration of anesthetics and analgesics can influence TBI outcomes, threatening the validity of the research. In this review, the authors present evidence for the interference of anesthetics and analgesics in the natural course of brain injury in animal models of TBI. They suggest that drugs should be selected for or excluded from experimental TBI protocols on the basis of IACUC-approved experimental objectives in order to protect animal welfare and preserve the validity of TBI models.

Mathematical Models of Blast-Induced TBI: Current Status, Challenges, and Prospects

Blast-induced traumatic brain injury (TBI) has become a signature wound of recent military activities and is the leading cause of death and long-term disability among U.S. soldiers. The current limited understanding of brain injury mechanisms impedes the development of protection, diagnostic, and treatment strategies. We believe mathematical models of blast wave brain injury biomechanics and neurobiology, complemented with in vitro and in vivo experimental studies, will enable a better understanding of injury mechanisms and accelerate the development of both protective and treatment strategies. The goal of this paper is to review the current state of the art in mathematical and computational modeling of blast-induced TBI, identify research gaps, and recommend future developments. A brief overview of blast wave physics, injury biomechanics, and the neurobiology of brain injury is used as a foundation for a more detailed discussion of multiscale mathematical models of primary biomechanics and secondary injury and repair mechanisms. The paper also presents a discussion of model development strategies, experimental approaches to generate benchmark data for model validation, and potential applications of the model for prevention and protection against blast wave TBI.