Article

Application of a finite element model of the brain to study traumatic brain injury mechanisms in the rat

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Abstract

Complete validation of any finite element (FE) model of the human brain is very difficult due to the lack of adequate experimental data. However, more animal brain injury data, especially rat data, obtained under well-defined mechanical loading conditions, are available to advance the understanding of the mechanisms of traumatic brain injury. Unfortunately, internal response of the brain in these experimental studies could not be measured. The aim of this study was to develop a detailed FE model of the rat brain for the prediction of intracranial responses due to different impact scenarios. Model results were used to elucidate possible brain injury mechanisms. A FE model, consisting of more than 250,000 hexahedral elements with a typical element size of 100 to 300 microns, was developed to represent the brain of a rat. The model was first validated locally against peak brain deformation data obtained from nine unique dynamic cortical deformation (vacuum) tests. The model was then used to predict biomechanical responses within the brain due to controlled cortical impacts (CCI). A total of six different series of CCI studies, four with unilateral craniotomy and two with bilateral craniotomy, were simulated and the results were systematically analyzed, including strain, strain rate and pressure within the rat brain. In the four unilateral CCI studies, approximately 150 rats were subjected to velocities ranging from 2.25 to 4 m/s, and cortical deformations of 1, 2 or 3 mm, with impactor diameters of 2.5 or 5 mm. Moreover, the impact direction varied from lateral 23 degrees to vertical. For the bilateral craniotomy CCI studies, about 70 rats were injured at 4.7 or 6 m/s, with deformations of 1.5 or 2.5 mm and impactor diameters of 3 or 5 mm, and at an impact direction of about 23-30 degrees laterally. Simulation results indicate that intracranial strains best correlate with experimentally obtained injuries.

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... All FE simulations were performed using a non-linear, dynamic, explicit FE solver LS-DYNA R6.1 (LSTC, CA, United States). The material properties assigned to each component of the rat head model were based on the published experimental data and the values used by the other FE head models (Shreiber et al., 1997;Gefen et al., 2003;Pena et al., 2005;Levchakov et al., 2006;Mao et al., 2006;Fijalkowski et al., 2009;Zhu et al., 2010;Wright and Ramesh, 2012;Lamy et al., 2013;Antona-Makoshi et al., 2014). ...
... Previous FE rat head models (Mao et al., 2006;Lamy et al., 2013) only validated the brain response in terms of the peak cortical displacement against the experimental DCD results. The current FE rat head model is the first FE model that has been validated against the peak cortical displacement values and also the temporal responses of the cortical displacement. ...
... The characteristics of the skull-brain interface was reported to be an significant factor affecting the brain displacement (Baumgartner and Willinger, 2004;Mao et al., 2006). To properly model this interface, three contact interface types available in the FE solver were investigated and the model results showed that the cortex surface displacement profile was influenced by the type of the interface. ...
Article
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Diffuse axonal injury (DAI) is a severe form of traumatic brain injury and often induced by blunt trauma. The closed head impact acceleration (IA) model is the most widely used rodent DAI model. However, this model results in large variations of injury severity. Recently, the impact device/system was modified to improve the consistency of the impact energy, but variations of the head kinematics and subsequent brain injuries were still observed. This study was aimed to utilize a Finite Element (FE) model of a rat head/body and simulation to investigate the potential biomechanical factors influencing the impact energy transfer to the head. A detailed FE rat head model containing detailed skull and brain anatomy was developed based on the MRI, microCT and atlas data. The model consists of over 722,000 elements, of which 310,000 are in the brain. The white matter structures consisting of highly aligned axonal fibers were simulated with transversely isotropic material. The rat body was modeled to provide a realistic boundary at the spine-medulla junction. Rodent experiments including dynamic cortical deformation, brain-skull displacement, and IA kinematics were simulated to validate the FE model. The model was then applied to simulate the rat IA experiments. Parametric studies were conducted to investigate the effect of the helmet inclination angles (0°–5°) and skull stiffness (varied 20%) on the resulting head kinematics and maximum principal strain in the brain. The inclination angle of the helmet at 5° could vary head linear acceleration by 8–31%. The change in head rotational velocity was inversely related to the change in linear acceleration. Varying skull stiffness resulted in changes in head linear acceleration by 3% but with no effect on rotational velocity. The brain strain in the corpus callosum was only affected by head rotation while the strain in the brainstem was influenced by the combined head kinematics, local skull deformation, and head-neck position. Validated FE models of rat impact head injury can assist in exploring various biomechanical factors influencing the head impact response and internal brain response. Identification of these variables may help explain the variability of injury severity observed among experiments and across different labs.
... Hrapko et al. and Forte et al. reported a comprehensive overview [94,136]. This leads to a large variety of material models used to describe the brain tissue [35,36,92,93,94,95,104,132,135,136,137,149,153,163,188,198,256,258,268,273,274,301,338,379,380], with viscoelastic and hyper-viscoelastic material models being the predominant ones. Table 1.4 gives a summary. ...
... The peak was selected by taking the maximum across all the elements in the FE model over time [125]. Reported thresholds ranged from 0.19 to 0.30 for a variety of injuries, based on animal experiments, accident reconstructions and clinical data [17,163,198,301,381], see Figure 1.6. Coats et al. used a spring connector and solid element representation of the pia-arachnoid complex to predict intracranial haemorrhage. ...
... Parameter Author Threshold Predicted Injury εpeak or εmax Shreiber et al. [301] 0.19 50 % probability of contusion Kleiven et al. [163] 0.21 -0.26 50 % probability of concussion Bain et al. [17] 0.21 DAI Zhang et al. [381] 0.19 50 % probability of mild TBI Mao et al. [198] 0.30 contusion Mao et al. [195] 0.265 contusion σv ...
Thesis
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Head injury (HI) is the fourth leading cause of death in the Western world and a major source of post-traumatic disability. It is the result of a fierce acceleration or an impact to the head, which can be caused by falls, vehicle accidents, accidental hits in sport and recreation, and assaults. Over the last decade, approximately 4 million people suffered yearly from Traumatic Brain Injury (TBI) in Europe. The epidemiology, social and economical burden of HI proves that we need research in this area. Only with complete understanding of the head injury mechanisms and mechanical ethiogenesis, we will be able to prevent and protect against these injuries. Controversy still exists within the biomechanics community regarding head injury mechanisms. Nevertheless, we widely accept that rotational and translational acceleration and velocity can cause injury if sufficiently large in absolute value and / or impulse duration. However, we need further research on experimental and numerical models to validate these hypotheses. It is a demanding challenge to combine subject-specific mechanical properties of the human head and evaluate tissue-level thresholds for head injuries. This dissertation focuses on the study of tissue tolerances in crash-related head injuries combining experimental and numerical approaches. The challenge in the identification of these tissue-level tolerance criteria comes from, among other things, the anatomical complexity of the human head. This thesis focused on the lower tissue-level threshold for cerebral contusions. For this purpose, we developed an \textit{in vivo} porcine model of cerebral contusion. It evaluated the minimal levels of strain resulting in cerebral contusion and related the mechanical loading input to contusion characteristics. These results reveal a lower tissue threshold for cerebral contusion development at an impact velocity of 0.5 - 2 m/s and impact depth of 1 - 2 mm. In combination with a Finite Element (FE) model, we evaluated the stress and strain patterns during induced cerebral contusions. The internal response of the brain tissue can be analysed in-depth and related to the ethiogenesis of cerebral contusions. Results affirm the feasibility to evaluate the internal brain response with the proposed methodology. Additionally, this thesis evaluated the implication of subject-specificity of soft and hard tissues in human head FE models. Doing so, this thesis analysed case-specific head impacts, as well as provided subject-specific soft tissue material models. First, we characterised human cranial vault dura mater \textit{in vitro} using planar biaxial tensile tests. We obtained stress-stretch curves and a constitutive model succesfully captured the tissue's material behaviour. Results reveal that the Gasser-Ogden-Holzapfel model most successfully captures the behaviour of the dura mater. Secondly, we implemented experimental data of skull fractures in case-specific FE models, combining both a subject-specific skull geometry and a subject-specific material model for cranial bone based on Hounsfield Units. We analysed the influence of the local geometry at the impact site and the material model on the internal skull strain energy. These subject-specific models predict the fracture lines with high precision. The results reveal influencing factors on the skull strain energy such as contact area, scalp thickness and impactor positioning. Finally, this PhD presents engineering contributions to the mechanopathogenesis of head injuries, particularly in fronto-temporal cerebral contusions and skull fractures. This thesis objectively demonstrates the challenges, limitations and opportunities in head injury research, hopefully leading to an improved design of protective headgear.
... For weight drop experiments, there are literature studies that combine exper- imental measurements of rat head kinematics and development of a finite element (FE) rat head model to analyze brain strain/stress responses and their correlations to axonal injury ( Li et al., 2011a,b). For CCI, we have used a validated rat brain model ( Mao et al., 2006) and quantitatively analyzed how different impact depth, velocity, impactor size, impactor shape, and craniotomy affect brain strains ( Mao et al., 2010). Understanding brain biomechanics of CCI helped researchers develop new experimental setting that better mimic real-world mild TBI in laboratory (Chen et al., 2014). ...
... A previously developed finite element (FE) rat brain model ( Mao et al., 2006) was improved by incorporating a layer of cere- brospinal fluid (CSF) determined from MRI scans of four Sprague Dawley adult rats. Furthermore, one-layer rigid shell elements of the skull were improved as three-layer solid elements, represent- ing the inner cortical bone, middle cancellous bone, and outer cor- tical bone. ...
... These moduli were assumed based on our previous experimental studies on rat skull material prop- erty ( ). Brain material properties remain same as our previous descriptions ( Mao et al., 2006). The rat brain model included major brain components such as the cortex, corpus callo- sum, hippocampus, thalamus, cerebellum, and brainstem, repre- sented by hexahedral elements. ...
... Some head-brain models include direct representation of key anatomical structures/tissues (cerebral meninges and CSF) of the brain-skull interface. Examples include the model by Yang [24], Total HUman Model for Safety THUMS by Toyota Motor Corporation and Toyota Central R&D Labs [25,26], models developed at Wayne State University [4,27], and SIMon model [28]. ...
... Building on the previous research effort by Kleiven et al. [6] and Wittek and Omori [15], this study contributes to answering this question by quantifying the effects of approach for modelling the brain-skull interface and constitutive model of the brain tissues on predicting the brain deformations due to transient loads compatible with automotive impacts. We focus on the maximum principal strain and shear strain within the brain as they were proposed as possible measures/criteria for evaluation of brain injury risk [27]. We used the head-brain model from Total HUman Model for Safety THUMS Version 4.0 by Toyota Motor Corporation and Toyota Central R&D Labs [25,26]. ...
... As strains within the brain have been proposed in the literature [27] as possible measures/criteria for evaluation of brain injury risk, we analysed the effects of the constitutive model of the brain tissues and approach for modelling the brainskull interface on the maximum principal strain and shear strain within the brain parenchyma predicted using the computational biomechanics model. Although in biomechanical engineering studies, maximum values of strain or stress are often used to evaluate the risk of tissue rupture, prediction of the maximum strain values with computational biomechanics models implemented using finite element method can be mesh dependent and may be affected by localised phenomena/modelling artefacts. ...
Chapter
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The objective of this study is to quantify the effects of approach for modelling the brain-skull interface and constitutive model of the brain parenchyma on predicting the brain deformations using a previously validated finite element head-brain model (Total HUman Model for Safety, THUMS, was used). Four approaches for modelling of the brain-skull interface and two constitutive models (linear viscoelastic and Odgen hyperviscoelastic) of the brain tissue were employed in computer simulations of the experiments reported in the literature. Comparison of the predicted and experimentally determined magnitude and shape of trajectories of selected points within the brain as well as the maximum principal and shear strain within the brain was conducted. The comparison indicates that the predicted brain responses were strongly affected by both analysed factors. The results suggest that accurate prediction of brain deformations due to violent impact requires a model of the brain-skull interface that allows for movement between the brain outer surface and skull, while preventing complete separation between the brain and skull, and constitutive model that accounts for non-linear stress-strain relationship of the brain tissues.
... And translating the FPI to a computational model is difficult because of variability in fluid loading at the dural surface (Dixon et al., 1988). While DCD has been simulated and used for other 3D FE model validation (Lamy et al., 2013;Mao et al., 2006;Shreiber et al., 1997), this method of injury induces hemorrhage in the shape of the craniotomy, likely from the bone cutting into the cortex References used: FE-Human (Cloots et al., 2012;Ho and Kleiven, 2007;Kleiven and Hardy, 2002;McAllister et al., 2012;Zhang et al., 2001Zhang et al., , 2002Zhang et al., , 2003; FE-Round (Yoganandan et al., 2008); FE-Porcine (Miller et al., 1998); PM-Human (Meaney and Thibault, 1990); PM-Primate (Margulies et al., 1990); PM-Porcine ; FE CCI-Rodent (Mao et al., 2006(Mao et al., , 2010a; PM CCI-Cat ; PM FPI-Cat . FE = Finite Element; PM = Physical Model. ...
... And translating the FPI to a computational model is difficult because of variability in fluid loading at the dural surface (Dixon et al., 1988). While DCD has been simulated and used for other 3D FE model validation (Lamy et al., 2013;Mao et al., 2006;Shreiber et al., 1997), this method of injury induces hemorrhage in the shape of the craniotomy, likely from the bone cutting into the cortex References used: FE-Human (Cloots et al., 2012;Ho and Kleiven, 2007;Kleiven and Hardy, 2002;McAllister et al., 2012;Zhang et al., 2001Zhang et al., , 2002Zhang et al., , 2003; FE-Round (Yoganandan et al., 2008); FE-Porcine (Miller et al., 1998); PM-Human (Meaney and Thibault, 1990); PM-Primate (Margulies et al., 1990); PM-Porcine ; FE CCI-Rodent (Mao et al., 2006(Mao et al., , 2010a; PM CCI-Cat ; PM FPI-Cat . FE = Finite Element; PM = Physical Model. ...
... However, CCI loading conditions do not generate similar biomechanics to human TBI. Currently, even at slower speeds, CCI produces strain rates of 400s -1 and over (Mao et al., 2006), well over the higher strain rates of moderate to severe human TBI (Figure 2.1). ...
Article
Traumatic brain injury (TBI) is a major and costly epidemic in the United States and around the world. There are little treatment options and currently no cure. Past research aimed at treating neurons as a therapeutic target have not been successful treatments clinically. Recent interest has turned to another cell type, the astrocyte, as a potential therapeutic target. In this dissertation, we expand upon past findings by further exploring the role of astrocytes and astrocytic signaling in TBI in vivo. Creating a new mild TBI model based on human mild TBI biomechanics, we produced behavioral deficits and histopathological changes similar to mild human TBI. We modified and applied the new TBI model to see if the in vitro astrocytic response to mild mechanical injury could be reproduced in vivo. By imaging the intracellular calcium in cortical astrocytes after mechanical impact in vivo with a 2-photon microscope, we found that mild mechanical injury produced a strong intercellular calcium wave originating from the site of injury. Drug applications to determine the mechanism of calcium wave showed that ATP signaling, and not gap junction coupling among the astrocytes, was responsible for this immediate effect of mild mechanical injury. Next we tested two transgenic animals, each with a different aspect of inhibited astrocyte signaling to determine the effect on TBI recovery. The first transgenic line, VIPP, had an over expression of IP3 phosphatase and was able to reduce the injury induced intercellular calcium wave in astrocytes. Reducing IP3 signaling specifically in astrocytes led to a worse behavioral outcome in a more severe TBI model and no significant difference in the mild TBI model. The second transgenic line, dnSNARE, was used to study the role of inhibited vesicular release from astrocytes. Reducing gliotransmission in this manner improved outcome in both the severe and the mild TBI models. In both cases, baseline behavior did not differ from wildtype littermates suggesting that targeting either pathway may have limited side effects. Histopathologies revealed significant reduction of astrogliosis in both VIPP and dnSNARE injured mice compared to WT. Together these results suggest that injury level can affect the effectiveness of a particular pathway as a therapeutic target and that overall targeting gliotransmission is an effective strategy.
... Finite element method (FEM)-based numerical models of the brain have been widely used to predict the effects of primary insult after a TBI. These efforts involve developing either a simplified model including only the salient anatomical features, like the skull, cerebellum and the cerebral hemispheres, allowing for a relatively quicker analysis (Anderson 2000; Pena et al. 2005;Levchakov et al. 2006), or an elaborate 3D model which make detailed predictions of local and global response to different external loads Mao et al. 2006;Takhounts et al. 2008). The output of finite element analysis in the form of principal strain, principal stress, shear strain, pressure and acceleration distribution in the brain is correlated with the occurrence of TBIs in the real world situation. ...
... Practical clinical applications may require a higher accuracy in the stress predictions of the model, which can be obtained by using a non-linear viscoelastic, or rate-dependent hyperelastic material model. The spatial calcium kinetics model can and must be made much more accurate by coupling it with a more detailed 3D FEM analysis Levchakov et al. 2006;Mao et al. 2006;Takhounts et al. 2008;Kimpara and Iwamoto 2012), and other similar studies for developing a comprehensive mathematical tool. Such functionality for predicting both primary and secondary injuries after the occurrence of a TBI will be very useful in the hands of healthcare professionals, especially considering the fact that the effects of TBI manifest long after the actual occurrence of the injury. ...
Article
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Accurate modelling of intracellular calcium ion (Ca2+Ca^{2+}) concentration evolution is valuable as it is known to rapidly increase during a Traumatic Brain Injury. In the work presented here, our older non-spatial model dealing with the effect of mechanical stress upon the Ca2+Ca^{2+} transportation in a neuron is spatialized by considering the brain tissue as a solid continuum with the Ca2+Ca^{2+} activity occurring at every material point. Starting with one-dimensional representation, the brain tissue geometry is progressively made realistic and under the action of pressure or kinematic impulses, the effect of dimensionality and material behaviour on the correlation between the stress and concomitant Ca2+Ca^{2+} concentration is investigated. The spatial calcium kinetics model faithfully captures the experimental observations concerning the Ca2+Ca^{2+} concentration, load rate, magnitude and duration and most importantly shows that the critical location for primary injury may not be the most important location as far as secondary injury is concerned.
... The maximum principal strain (MPS) and cumulative strain damage measure (CSDM) were calculated and assigned as the injury indexes for the proper prediction of cerebral contusion and diffuse brain injury, respectively. The MPS has been suggested as an efficient injury index of cerebral contusion under blunt impact [32,33]. In this study, 18 elements in a cube region in which the To simulate the same risk of brain injuries in models of three impact locations at the same impact velocity, different impact angles of the head were designed. ...
... The maximum principal strain (MPS) and cumulative strain damage measure (CSDM) were calculated and assigned as the injury indexes for the proper prediction of cerebral contusion and diffuse brain injury, respectively. The MPS has been suggested as an efficient injury index of cerebral contusion under blunt impact [32,33]. In this study, 18 elements in a cube region in which the maximum strain response appeared in the brain impact region were selected for a calculation of average peak MPS. ...
Article
Full-text available
This study is aimed at investigating the influence of skull fractures on traumatic brain injury induced by blunt impact via numerous studies of head-ground impacts. First, finite element (FE) damage modeling was implemented in the skull of the Total HUman Model for Safety (THUMS), and the skull fracture prediction performance was validated against a head-ground impact experiment. Then, the original head model of the THUMS was assigned as the control model without skull element damage modeling. Eighteen (18) head-ground impact models were established using these two FE head models, with three head impact locations (frontal, parietal, and occipital regions) and three impact velocities (25, 35, and 45 km/h). The predicted maximum principal strain and cumulative strain damage measure of the brain tissue were employed to evaluate the effect of skull fracture on the cerebral contusion and diffuse brain injury risks, respectively. Simulation results showed that the skull fracture could reduce the risk of diffuse brain injury risk under medium and high velocities significantly, while it could increase the risk of brain contusion under high-impact velocity.
... Finite element (FE) modeling and simulations have been used to predict the responses of biological structures under various mechanical conditions, including air and liquid flow conditions, transmission and pressure distribution of blast wave. This approach could provide us an increasing reliability and more detailed biomechanical information based on distribution diagram and statistics, which might be helpful in further predictive analysis of injuries 13,14 . Researchers have used this computational modeling to investigate the pressure distribution of blast injuries 13,15 . ...
... This approach could provide us an increasing reliability and more detailed biomechanical information based on distribution diagram and statistics, which might be helpful in further predictive analysis of injuries 13,14 . Researchers have used this computational modeling to investigate the pressure distribution of blast injuries 13,15 . Wang et al. simulated blast waves at five blast intensities from the anterior, right lateral and posterior directions one meter from the detonation center and found that the intracranial pressure wave went through the posterior fossa and vertebral column, causing high pressure levels 15 . ...
Article
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Blast lung injury (BLI) caused by both military and civilian explosions has become the main cause of death for blast injury patients. By building three-dimensional (3D) models of rat explosion regions, we simulated the surface pressure of the skin and lung. The pressure distributions were performed at 5 distances from the detonation center to the center of the rat. When the distances were 40 cm, 50 cm, 60 cm, 70 cm and 80 cm, the maximum pressure of the body surface were 634.77kPa, 362.46kPa, 248.11kPa, 182.13kPa and 109.29kPa and the surfaces lung pressure ranges were 928–2916 Pa, 733–2254 Pa, 488–1236 Pa, 357–1189 Pa and 314–992 Pa. After setting 6 virtual points placed on the surface of each lung lobe model, simulated pressure measurement and corresponding pathological autopsies were then conducted to validate the accuracy of the modeling. For the both sides of the lung, when the distance were 40 cm, 50 cm and 60 cm, the Pearson’s values showed strong correlations. When the distances were 70 cm and 80 cm, the Pearson’s values showed weak linear correlations. This computational simulation provided dynamic anatomy as well as functional and biomechanical information.
... Kleiven and Hardy (2002) and Haines et al. (1993) Wittek and Omori (2003) suggested that for accurate modelling of the brain-skull interface, direct representation of the subarachnoidal space/cerebrospinal fluid as a water-like medium is needed. This approach has been also used in the head/brain model developed by Yang (2011), Total HUman Model for Safety (THUMS) by Toyota Motor Corporation and Toyota Central R&D Labs (Shigeta et al. 2009;Watanabe et al. 2011), the models developed at Wayne State University (Mao et al. 2006;Zhang et al 2001), and Simulated Injury Monitor (SIMon) model (Takhounts et al. 2013). ...
... • Stage 1 As many recently proposed brain injury criteria rely on information about the strain within the brain (Hernandez et al. 2015;Mao et al. 2006), we analysed the predicted maximum principal strain and maximum shear strain within the brain parenchyma. As prediction of the maximum strain values using models implemented using finite element method may be affected by localised phenomena/modelling artefacts, following Garlapati et al. (2014) and Wang et al. (2017), we used quantile plots of the maximum principal strain and shear strain at the time when the maximum strain value was observed. ...
Article
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In this study, we investigate the effects of modelling choices for the brain–skull interface (layers of tissues between the brain and skull that determine boundary conditions for the brain) and the constitutive model of brain parenchyma on the brain responses under violent impact as predicted using computational biomechanics model. We used the head/brain model from Total HUman Model for Safety (THUMS)—extensively validated finite element model of the human body that has been applied in numerous injury biomechanics studies. The computations were conducted using a well-established nonlinear explicit dynamics finite element code LS-DYNA. We employed four approaches for modelling the brain–skull interface and four constitutive models for the brain tissue in the numerical simulations of the experiments on post-mortem human subjects exposed to violent impacts reported in the literature. The brain–skull interface models included direct representation of the brain meninges and cerebrospinal fluid, outer brain surface rigidly attached to the skull, frictionless sliding contact between the brain and skull, and a layer of spring-type cohesive elements between the brain and skull. We considered Ogden hyperviscoelastic, Mooney–Rivlin hyperviscoelastic, neo–Hookean hyperviscoelastic and linear viscoelastic constitutive models of the brain tissue. Our study indicates that the predicted deformations within the brain and related brain injury criteria are strongly affected by both the approach of modelling the brain–skull interface and the constitutive model of the brain parenchyma tissues. The results suggest that accurate prediction of deformations within the brain and risk of brain injury due to violent impact using computational biomechanics models may require representation of the meninges and subarachnoidal space with cerebrospinal fluid in the model and application of hyperviscoelastic (preferably Ogden-type) constitutive model for the brain tissue.
... Compared with the large body of strain-based studies, there are relatively fewer investigations on brain strain rate. It is ubiquitous in the literature that the strain rate values are directly reported without any clarification on how they are calculated [9,[28][29][30][31][32][33]. Even when limiting to the handful of studies with the strain rate computational schemes elaborated, alarming inconsistency existed. ...
Article
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Traumatic brain injury (TBI) is an alarming global public health issue with high morbidity and mortality rates. Although the causal link between external insults and consequent brain injury remains largely elusive, both strain and strain rate are generally recognized as crucial factors for TBI onsets. With respect to the flourishment of strain-based investigation, ambiguity and inconsistency are noted in the scheme for strain rate calculation within the TBI research community. Furthermore, there is no experimental data that can be used to validate the strain rate responses of finite element (FE) models of the human brain. The current work presented a theoretical clarification of two commonly used strain rate computational schemes: the strain rate was either calculated as the time derivative of strain or derived from the rate of deformation tensor. To further substantiate the theoretical disparity, these two schemes were respectively implemented to estimate the strain rate responses from a previous-published cadaveric experiment and an FE head model secondary to a concussive impact. The results clearly showed scheme-dependent responses, both in the experimentally determined principal strain rate and model-derived principal and tract-oriented strain rates. The results highlight that cross-scheme comparison of strain rate responses is inappropriate, and the utilized strain rate computational scheme needs to be reported in future studies. The newly calculated experimental strain rate curves in the supplementary material can be used for strain rate validation of FE head models.
... Bandak and Eppinger believe that DAI is related to the cumulative volume of the brain above tensile strain, and proposed cumulative strain damage measure (CSDM) for predicting the risk of DAI injury 25,26 . Subsequently, research scholars further validated the correlation between the criteria of maximum principal strain (MPS), CSDM, and the risk of DAI injury through nite element models 15,27,28 . However, whether global kinematic-based injury criteria or brain tissue level-based injury criteria, it is di cult for a single injury criterion to effectively evaluate the risks of severe brain injury (means AIS 4 + in this study) caused by different injury types during a tra c accident. ...
Preprint
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In traffic accidents, multiple head injury types often occur simultaneously and cause severe brain injury for vulnerable road users (VRUs). In this study, a head-weighted injury criterion was developed to assess the risk of severe brain injury considering various injury types. Firstly, 50 in-depth accidents were reconstructed using a high-precision reconstruction method to reconstruct the overall kinematic response and head injury severity of VRUs and analyze the correlation between various head injury criteria and severe brain injury. Then, four injury criteria were selected that correlated well with severe brain injury, namely HIC 15 , angular acceleration, coup pressure, and maximum principal strain (MPS). Finally, weighted head injury criteria (WIC 4 ) of severe injuries were established based on the four selected injury criteria, and the correlation between WIC 4 and severe brain injury was validated based on the area under of receiver operating characteristic curve (AUROC) and the reconstructed results of another 10 selected accidents. The results showed that WIC 4 had a good predictive capability for both severe and non-severe brain injury cases, and the AUROC was 0.983, which was significantly higher than that of the single head injury criterion. This study further improved the correlation between head injury criteria and severe brain injury.
... In comparison to the FPI model, CCI is more useful for biomechanical studies of TBI because of the controllable pneumatic and electromagnetic devices [48][49][50]. ...
Article
Following traumatic brain injury (TBI), excess reactive oxygen species (ROS) and other free radicals are released, inducing the cascade of secondary injury that exacerbate the outcomes of TBI. Antioxidant nanoparticles (ANPs) have shown promising outcomes in reducing the progression of TBI, which may be due to the higher accumulation and retention of ANPs in the injured brain. However, there is limited knowledge of: 1) antioxidant activities needed in TBI treatment, 2) correlation between longer retention, bioavailability, and target engagement with antioxidant treatments, and 3) sexual dimorphism to ANP treatments. This dissertation assesses multiple ANPs with various scavenging activities and durations to overcome the current limitations in reducing the secondary injury of TBI. First, an ROS scavenger NP (NP1) with thioether bonds that react within hours was utilized, and showed reductions in oxidative stress in the acute phase of injury and neuroinflammation in the chronic phase of injury in female mice. Next, a large size ANP (Pro-NP™) with multiple antioxidant enzymes and scavenging activity of more than 24 hours was tested in male and female TBI mice. Pro-NP™ showed more benefit in reducing the secondary injury in males than females in the acute phase, but exacerbate the TBI progression in the subacute phase of injury in males. Next, a small size ANP (NPC3) with multiple free radical scavenging capabilities that react within minutes was tested in male and female TBI mice. We found a reduction in secondary injury at 1-day post-injury, but the progression returned at 3-day post-injury. NPC3 also showed more reduction in oxidative stress biomarkers in males. Finally, a ligand to target disrupted blood-brain barrier was assessed for multiple administrations of ANPs. The results suggested ANPs with multiple free radical scavengers were more effective in mitigating the TBI progression than ANPs with ROS-only scavengers, minimal benefit from longer retention and scavenging activity when antioxidants were administered immediately following an injury, and males benefited more from ANPs treatment than females. Advisor: Forrest M. Kievit
... Several computational studies have also reported strain rate as an appropriate predictor for brain injury [27,29,32,36,71]. However, most TBI studies didn't report details of strain rate calculation [8,21,22,[71][72][73][74], making an appropriate interpretation of strain rate results impossible. For the handful of investigations with the strain rate calculation procedures elaborated, disparate inconsistency was noted in the computational scheme, posing inevitable challenges while comparing strain rate-related finding across studies. ...
Preprint
Full-text available
Traumatic brain injury (TBI) is an alarming global public health issue with high morbidity and mortality rates. Although the causal link between external insults and consequent brain injury remains largely elusive, both strain and strain rate are generally recognized as crucial factors for TBI onsets. With respect to the flourishment of strain-based investigation, ambiguity and inconsistency are noted in the scheme for strain rate calculation within the TBI research community. Furthermore, there is no experimental data that can be used to validate the strain rate responses of finite element (FE) models of the human brain. Thus, the current work presented a theoretical clarification of two commonly used strain rate computational schemes: the strain rate was either calculated as the time derivative of strain or derived from the rate of deformation tensor. To further substantiate the theoretical disparity, these two schemes were respectively implemented to estimate the strain rate responses from a previous-published cadaveric experiment and an FE head model secondary to a concussive impact. The results clearly showed scheme-dependent responses, both in the experimentally determined principal strain rate and FE model-derived principal and tract-oriented strain rates. The results highlight that cross-scheme comparison of strain rate responses is inappropriate, and the utilized strain rate computational scheme needs to be reported in future studies. The newly calculated experimental strain rate curves in the supplementary material can be used for strain rate validation of FE head models.
... found strong correlation between the area of Fibrinogen extravasation and the area of brain with vessels under axial stresses in excess of 200 kPa, equivalent to 0.14 axial strain considering the linear elastic model used for vessels. Shear stress and strain in the parenchyma have been suggested as predictors of BBB damage in previous studies 24, [35][36][37] . For instance, it has been shown that the BBB breakdown in a rat model can occur at maximum principal logarithmic strains in the parenchyma larger than 0.19. ...
Article
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Neurovascular injury is often observed in traumatic brain injury (TBI). However, the relationship between mechanical forces and vascular injury is still unclear. A key question is whether the complex anatomy of vasculature plays a role in increasing forces in cerebral vessels and producing damage. We developed a high-fidelity multiscale finite element model of the rat brain featuring a detailed definition of the angioarchitecture. Controlled cortical impacts were performed experimentally and in-silico. The model was able to predict the pattern of blood–brain barrier damage. We found strong correlation between the area of fibrinogen extravasation and the brain area where axial strain in vessels exceeds 0.14. Our results showed that adjacent vessels can sustain profoundly different axial stresses depending on their alignment with the principal direction of stress in parenchyma, with a better alignment leading to larger stresses in vessels. We also found a strong correlation between axial stress in vessels and the shearing component of the stress wave in parenchyma. Our multiscale computational approach explains the unrecognised role of the vascular anatomy and shear stresses in producing distinct distribution of large forces in vasculature. This new understanding can contribute to improving TBI diagnosis and prevention.
... The advantage of this injury model is the ease at which mechanical factors, such as time, velocity, and depth of impact, can be controlled. This makes the CCI model more reproducible than the FPI model for biomechanical studies of TBI (Cernak, 2005;Mao et al., 2006;Wang & Ma, 2010). Unlike FPI, however, the damage resulting from CCI is focal in nature and mainly models contusions (i.e., non-mild TBI) (Bruce et al., 2015;Osier & Dixon, 2016). ...
Article
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Traumatic brain injuries (TBIs) are common with an estimated 27.1 million cases per year. Approximately 80% of TBIs are categorized as mild TBI (mTBI) based on initial symptom presentation. While in most individuals, symptoms resolve within days to weeks, in some, symptoms become chronic. Advanced neuroimaging has the potential to characterize brain morphometric, microstructural, biochemical, and metabolic abnormalities following mTBI. However, translational studies are needed for the interpretation of neuroimaging findings in humans with respect to the underlying pathophysiological processes, and, ultimately, for developing novel and more targeted treatment options. In this review, we introduce the most commonly used animal models for the study of mTBI. We then summarize the neuroimaging findings in humans and animals after mTBI and, wherever applicable, the translational aspects of studies available today. Finally, we highlight the importance of translational approaches and outline future perspectives in the field of translational neuroimaging in mTBI.
... Our results show that all but one strains, and all strain rates predict a lesion volume that falls within 1 SD of the mean value of the lesion volumes across all animals and both severities. This is in keeping with previous computational work (Mao et al., 2006) and shows a reasonable prediction of lesion size from our computational model. The root mean square error of FE prediction of the contusion volume fraction versus mean value of experimental results was determined and provided evidence that a strain threshold of 0.3 and a strain rate threshold of 2.5/ms better predict the contusion volume. ...
Article
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The relationship between biomechanical forces and neuropathology is key to understanding traumatic brain injury. White matter tracts are damaged by high shear forces during impact, resulting in axonal injury, a key determinant of long-term clinical outcomes. However, the relationship between biomechanical forces and patterns of white matter injuries, associated with persistent diffusion MRI abnormalities, is poorly understood. This limits the ability to predict the severity of head injuries and the design of appropriate protection. Our previously developed human finite element model of head injury predicted the location of post-traumatic neurodegeneration. A similar rat model now allows us to experimentally test whether strain patterns calculated by the model predicts in vivo MRI and histology changes. Using a controlled cortical impact, mild and moderate injuries (1 and 2 mm) were performed. Focal and axonal injuries were quantified with volumetric and diffusion 9.4 T MRI at 2 weeks post injury. Detailed analysis of the corpus callosum was conducted using multi-shell diffusion MRI and histopathology. Microglia and astrocyte density, including process parameters, along with white matter structural integrity and neurofilament expression were determined by quantitative immunohistochemistry. Linear mixed effects regression analyses for strain and strain rate with the employed outcome measures were used to ascertain how well immediate biomechanics could explain MRI and histology changes. The spatial pattern of mechanical strain and strain rate in the injured cortex shows good agreement with the probability maps of focal lesions derived from volumetric MRI. Diffusion metrics showed abnormalities in the corpus callosum, indicating white matter changes in the segments subjected to high strain, as predicted by the model. The same segments also exhibited a severity-dependent increase in glia cell density, white matter thinning and reduced neurofilament expression. Linear mixed effects regression analyses showed that mechanical strain and strain rate were significant predictors of in vivo MRI and histology changes. Specifically, strain and strain rate respectively explained 33% and 28% of the reduction in fractional anisotropy, 51% and 29% of the change in neurofilament expression and 51% and 30% of microglia density changes. The work provides evidence that strain and strain rate in the first milliseconds after injury are important factors in determining patterns of glial and axonal injury and serve as experimental validators of our computational model of traumatic brain injury. Our results provide support for the use of this model in understanding the relationship of biomechanics and neuropathology and can guide the development of head protection systems, such as airbags and helmets.
... As brain tissue has a low shear modulus, shear strain has been proposed as a likely mechanism of damage that results in concussion (Meaney and Smith 2011). Researchers have examined the influence of strain and strain rate on the resulting cell death caused by physiological cascades (Gray and Ritchie 1954, Haftek 1970, Koike 1987, Galbraith et al. 1993, Saatman 1994, Morrison III et al. 2000, 2006, Geddes, LaPlaca and Cargill 2003, Mao et al. 2006, Elkin and Morrison III 2007, Mao et al. 2010 Research using cadavers has informed most current head and brain injury research. Early cadaveric research has investigated the relationships between linear acceleration and intracranial pressure (Thomas et al. 1967). ...
Thesis
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Brain injuries are one of the most common type of injuries sustained by riders in equestrian sports. The most common cause of brain injuries in equestrian sports are oblique impacts to a compliant surface; equestrian helmets are not currently designed to protect against such impacts. There is a paucity of research into the mechanics associated with these types of impacts; studying the impact mechanics can provide insight to reduce the risk of brain injury by improving helmet designs. The main objective of this thesis was to analyse real-world equestrian accidents and associated helmets in order to provide a unique set of primary data that can be used to characterise brain injuries and helmet performance in equestrian sports. Real-world accidents in equestrian sports were investigated to examine the associated impact mechanics and helmet damage. Video analysis of head injury incidents found that all cases involved the head impacting turf or sand surfaces and that 30% of racing accidents involved secondary and tertiary impacts from either a horse kick, collision with a horse, or the rider being crushed or stomped on by the horse. These secondary and tertiary impacts all resulted in helmet damage, however, for the majority of fall incidents no helmet damage was found. These results raised the question of whether equestrian helmets provide adequate head protection against falls for riders? Concussive thresholds for equestrian sports were found to be within the range reported in the literature but represented a unique combination of head kinematics. These unique biomechanical aspects of concussion should be considered when developing new approaches to reduce the risk of brain injury in equestrian sports. A parametric study was performed in order to examine the main effects and interactions of impact parameters on head kinematics and brain tissue response for falls in equestrian sports. Impact velocity and trajectory angle had the largest effect on head kinematics and brain tissue response. Impact surface compliance and impact location also influenced head kinematics and brain tissue response but were less influential than impact velocity and fall trajectory angle. Significant interactions such as those between fall trajectory angle and impact surface compliance were found to greatly influence head kinematics and brain tissue response. The suitability of current and proposed equestrian helmet test methods to represent realistic equestrian falls was also assessed. Impacts representing the equestrian helmet standards and the proposed EN13097-11 standard were found to produce higher acceleration magnitudes and shorter durations compared to actual concussive reconstructions due to the use of a rigid anvil instead of one that was compliant. Finally, the protective capacity of an equestrian helmet was assessed for impacts to turf. The helmet was found to offer little to no protection for linear impact falls as helmeted impacts resulted in minimal reduction in head kinematics and brain tissue response compared to unhelmeted impacts. For oblique falls, however, the use of a helmet significantly reduced rotational kinematics and brain tissue stress and strain, although the values commonly remained above the 50% risk of sustaining a concussion. This suggests that an opportunity exists to improve the protective capacity of equestrian helmets. The implementation of rotational attenuating technologies in equestrian helmets may reduce the occurrence of brain injury, as rotational acceleration has been found to be a significant predictor of concussion and was commonly reported as the best predictor of brain tissue response.
... Hence, the CSDM metric can be used to predict the DAI by calculating the volume fraction of the brain, where the experienced strain is greater than the critical levels. Mao et al. (2006) investigated the injury of the rat brain using the CSDM and found the simulation results were in good agreement with the experimental measurements for the prediction of contusions when a critical value of 0.3 was assumed. Takhounts et al. (2011Takhounts et al. ( , 2013 further expounded on the concept of the CSDM and summarized the calculation process of the CSDM by using the SIMon model. ...
Article
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The brain is one of the most critical parts of the human body, and it is vulnerable in vehicle collision accidents. Statistically, traumatic brain injuries (TBIs) account for about half of the 1.3 million deaths and 50 million injuries in annual road traffic accidents around the world. However, there are currently no universally accepted and specialized criteria for the different types of brain injuries, even though a series of injury criteria has been presented using mathematical combinations of kinematic parameters. To reduce TBIs and improve the safety performance of vehicles, we established a new brain injury index (BII) by maximizing the correlation between the kinematic parameters and strain-based measures such as cumulative strain damage measure (CSDM) and maximum principal strain (MPS), which employed 218 crash test data and the simulated injury monitor (SIMon) model from the National Highway Traffic Safety Administration website. In the process of establishing the BII, we combined the K-Nearest Neighbor with quadratic regression to enhance the correlation between the kinematic metrics and CSDM/MPS by eliminating the influence of some outlier data and used the genetic algorithm to obtain the optimal weight ratios of several kinematic parameters with strong correlations. The assessment capability of the proposed BII was more superior and reliable than other indexes when compared with 15 existing kinematic-based criteria. Finally, we developed a simple BII (SBII), which ignored the influence of the translational velocity and acceleration, and used it to establish three prediction models of brain injury based on artificial neural network learning, which achieved the quantitative description of the relationship between the kinematic parameters and CSDM/MPS.
... While direct measurement of cell and tissue level strain during mechanical loading is technically challenging, computer simulations of TBI are quite useful in creating a spatial map of stress and strain at the millisecond time scale (Dixit and Liu, 2016;Kleiven, 2006;Mao et al., 2006;Yang and King, 2003). The brain has a complex organization and cell density and organization, in addition to tissue composition, can affect the mechanical response to a high rate traumatic load. ...
Article
Background: An increases in plasma membrane permeability is part of the acute pathology of traumatic brain injury and may be a function of excessive membrane force. This membrane damage, or mechanoporation, allows non-specific flux of ions and other molecules across the plasma membrane, and may ultimately lead to cell death. The relationships among tissue stress and strain, membrane permeability, and subsequent cell degeneration, however, are not fully understood. Methods: Fluorescent molecules of different sizes were introduced to the cerebrospinal fluid space prior to injury and animals were sacrificed at either 10 min or 24 h after injury. We compared the spatial distribution of plasma membrane damage following controlled cortical impact in the rat to the stress and strain tissue patterns in a 3-D finite element simulation of the injury parameters. Findings: Permeable cells were located primarily in the ipsilateral cortex and hippocampus of injured rats at 10 min post-injury; however by 24 h there was also a significant increase in the number of permeable cells. Analysis of colocalization of permeability marker uptake and Fluorojade staining revealed a subset of permeable cells with signs of degeneration at 24 h, but plasma membrane damage was evident in the vast majority of degenerating cells. The regional and subregional distribution patterns of the maximum principal strain and shear stress estimated by the finite element model were comparable to the cell membrane damage profiles following a compressive impact. Interpretation: These results indicate that acute membrane permeability is prominent following traumatic brain injury in areas that experience high shear or tensile stress and strain due to differential mechanical properties of the cell and tissue organization, and that this mechanoporation may play a role in the initiation of secondary injury, contributing to cell death.
... Each craniotomy was 6 mm in diameter and was centered approximately 2 mm posterior to the bregma and 1 mm from the midline. Bilateral craniotomies were used because they increase contralateral axonal damage and the chances of contralateral hippocampal damage [34][35][36][37][38]. A representative example of the injury is shown in Figure 2a 2c illustrates how the bilateral craniotomy results in mechanical stress upon the contralesional hemisphere. ...
Article
The leading cause of death in the juvenile population is trauma, and in particular neurotrauma. The juvenile brain response to neurotrauma is not completely understood. Endoplasmic reticulum (ER) stress has been shown to contribute to injury expansion and behavioral deficits in adult rodents and furthermore has been seen in adult postmortem human brains diagnosed with chronic traumatic encephalopathy. Whether endoplasmic reticulum stress is increased in juveniles with traumatic brain injury (TBI) is poorly delineated. We investigated this important topic using a juvenile rat controlled cortical impact (CCI) model. We proposed that ER stress would be significantly increased in juvenile rats following TBI and that this would correlate with behavioral deficits using a juvenile rat model. A juvenile rat (postnatal day 28) CCI model was used. Binding immunoglobulin protein (BiP) and C/EBP homologous protein (CHOP) were measured at 4 h in the ipsilateral pericontusion cortex. Hypoxia-inducible factor (HIF)-1α was measured at 48 h and tau kinase measured at 1 week and 30 days. At 4 h following injury, BiP and CHOP (markers of ER stress) were significantly elevated in rats exposed to TBI. We also found that HIF-1α was significantly upregulated 48 h following TBI showing delayed hypoxia. The early ER stress activation was additionally asso­ciated with the activation of a known tau kinase, glycogen synthase kinase-3β (GSK-3β), by 1 week. Tau oligomers measured by R23 were significantly increased by 30 days following TBI. The biochemical changes following TBI were associated with increased impulsive-like or anti-anxiety behavior measured with the elevated plus maze, deficits in short-term memory measured with novel object recognition, and deficits in spatial memory measured with the Morris water maze in juvenile rats exposed to TBI. These results show that ER stress was increased early in juvenile rats exposed to TBI, that these rats developed tau oligomers over the course of 30 days, and that they had significant short-term and spatial memory deficits following injury.
... Such models tend to rely on various simplifications and assumptions for modelling the brain-skull interface. Direct representation of the key anatomical components (such as dura, arachnoid, CSF and pia) of the brain-skull interface was used in some brain FE models, including the models developed at Wayne State University [26,31], Total HUman Model for Safety THUMS by Toyota Central R&D Labs [32,33], model by Yang [34], model by Al-Bsharat et al. [35], and SIMon model [8]. Examples of more simplified approaches include modelling the brain-skull interface using a sliding contact allowing no separation between the brain and skull [20], frictionless sliding contact between the brain and skull [12,15], and no-slip interface allowing no relative movement between the brain and skull [14]. ...
Chapter
In the current study, the effects of the approach for modelling the brain–skull interface on prediction of the brain injury risk are investigated using a previously validated computational head-brain model. Four types of brain–skull interface modelling approaches (1): the method used in original Total HUman Model for Safety THUMS Head-brain model, (2): brain rigidly attached to the skull, (3): frictionless contact between the brain and skull, and (4): cohesive layer (spring-type) between the brain and skull are employed in numerical reconstruction of a real-world car-to-pedestrian impact accident. The results indicate that the predicted brain injury risk is strongly affected by the approach for modelling the brain–skull interface. The comparison of the predicted risk of diffuse axonal injury DAI and brain contusions with the injuries sustained by the pedestrian involved in the accident seems to suggest that accurate prediction of the brain injury risk using computational biomechanics models requires direct representation of the meninges and subarachnoidal space with the CSF.
... effort has been directed toward the development of finite element (FE) models, which represent a promising approach to robustly simulate the precise deformations during blunt impact without the use of human and animal tissues, dummies, and automobiles [12,[18][19][20][21][22][23][24]. Over the years, there has been much progress in the development of FE models for impact and injury predictions. ...
Article
In this study, the damage evolution of liver tissue was quantified at the microstructural level under tensile, compression, and shear loading conditions using an interrupted mechanical testing method. To capture the internal microstructural changes in response to global deformation, the tissue samples were loaded to different strain levels and chemically fixed to permanently preserve the deformed tissue geometry. Tissue microstructural alterations were analyzed to quantify the accumulated damages, with damage-related parameters such as number density, area fraction, mean area, and mean nearest neighbor distance (NND). All three loading states showed a unique pattern of damage evolution, in which the damages were found to increase in number and size, but decrease in NND as strain level increased. To validate the observed damage features as true tissue microstructural damages, more samples were loaded to the above-mentioned strain levels and then unloaded back to their reference state, followed by fixation. The most major damage-relevant features at higher strain levels remained after the release of the external loading, indicating the occurrence of permanent inelastic deformation. This study provides a foundation for future structure-based constitutive material modeling that can capture and predict the stress-state dependent damage evolution in liver tissue.
... Controlled cortical impact (CCI), producing compression injury with a piston, is a widely used animal model of contusion; 132-134 vacuum loading has also been applied to create a focal, contusion-type injury. 69,[135][136][137] Both approaches have been studied with accompanying computational models, 135,[138][139][140][141] and mechanical measures have been correlated with contusion and BBB disruption. As with other computer models, however, blood vessels have not been modeled explicitly. ...
Article
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Traumatic brain injury is a devastating cause of death and disability. Although injury of brain tissue is of primary interest in head trauma, nearly all significant cases include damage of the cerebral blood vessels. Because vessels are critical to the maintenance of the healthy brain, any injury or dysfunction of the vasculature puts neural tissue at risk. It is well known that these vessels commonly tear and bleed as an immediate consequence of traumatic brain injury. It follows that other vessels experience deformations that are significant though not severe enough to produce bleeding. Recent data show that such subfailure deformations damage the microstructure of the cerebral vessels, altering both their structure and function. Little is known about the prognosis of these injured vessels and their potential contribution to disease development. The objective of this review is to describe the current state of knowledge on the mechanics of cerebral vessels during head trauma and how they respond to the applied loads. Further research on these topics will clarify the role of blood vessels in the progression of traumatic brain injury and is expected to provide insight into improved strategies for treatment of the disease.
... For simulations of controlled cortical impact experiments (Mao et al., 2006(Mao et al., , 2010Chen et al., 2014), strain levels can be as high as 60 %. This strongly suggests the use of a nonlinear description for dura mater in head impact simulations. ...
... Understanding the mechanism of primary bTBI requires evaluation of head kinematics and brain tissue responses. Researchers have attempted to employ experimental and computational models to describe bTBI through several different injury mechanisms such as direct shock wave propagation inside the cranium [1][2][3], head acceleration [4], skull flexure [5,6], and cavitation [7]. While measurement of head kinematics can be performed using sensors inside either helmets or on the skull surface, tissue-level mechanical responses such as intracranial pressure, shear stress, and strain are nearly impossible to be measured in live humans and very challenging in cadavers. ...
Article
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Upon impingement of blast waves on the head, stress waves generated at the interface of the skull are transferred into the cranium and the brain tissue and may cause mild to severe blast traumatic brain injury. The intensity of the shock front, defined by the blast overpressure (BoP), that is, the blast-induced peak static overpressure, significantly affects head kinematics as well as the tissue responses of the brain. While evaluation of global linear and rotational accelerations may be feasible, an experimental determination of dynamic responses of the brain in terms of intracranial pressure (ICP), maximum shear stress (MSS), and maximum principal strain (MPS) is almost impossible. The main objective of this study is to investigate possible correlations between head accelerations and the brain’s ICP, MSS, and MPS. To this end, three different blasts were simulated by modeling the detonation of 70, 200, and 500 g of TNT at a fixed distance from the head, corresponding to peak BoPs of 0.52, 1.2, and 2 MPa, respectively. A nonlinear multi-material finite element algorithm was implemented in the LS-DYNA explicit solver. Fluid–solid interaction between the blast waves and head was modeled using a penalty-based method. Strong correlations were found between the brain’s dynamic responses and both global linear and rotational accelerations at different blast intensities (R2≥ 98%), implying that global kinematic parameters of the head might be strong predictors of brain tissue biomechanical parameters.
... We believe that latter approach will provide interesting insights into the change of Ca 2+ kinetics due to external injuries. The current models which predict TBI based on local stresses are purely mechanical in nature and hence do not take into consideration the damage done due to secondary injuries (Bandak et al. 2001;Zhang et al. 2001;Mao et al. 2006). Such a mechanical model integrated with our kinetic model for ion transport can provide a pathway toward creating a single model to holistically predict the consequence of TBI, via both primary and secondary insults. ...
Article
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Accurate modeling of the mechanobiological response of a Traumatic Brain Injury is beneficial toward its effective clinical examination, treatment and prevention. Here, we present a stress history-dependent non-spatial kinetic model to predict the microscale phenomena of secondary insults due to accumulation of excess calcium ions (Ca2+^{2+}) induced by the macroscale primary injuries. The model is able to capture the experimentally observed increase and subsequent partial recovery of intracellular Ca2+^{2+} concentration in response to various types of mechanical impulses. We further establish the accuracy of the model by comparing our predictions with key experimental observations.
... These five tests were selected because they vary in impact direction and magnitude (Table 1). Additionally, three of these tests (C755-T2, C383-T1, and C291-T1) are commonly used in brain model validation (Zhang et al. 2001, King et al. 2003, Kimpara et al. 2006, Kleiven 2006, Mao et al. 2006, Takhounts et al. 2008, Ji et al. 2015. In the cadaver impact experiments, local displacements were evaluated throughout the brain using a high-speed biplanar X-ray system to track the relative motion of implanted radio-opaque neutral density targets (NDTs) (Hardy et al. 2001). ...
Article
The objective of this study was to compare the performance of six validated brain finite element (FE) models to localized brain motion validation data in five experimental configurations. Model performance was measured using the objective metric CORA (CORrelation and Analysis), where higher ratings represent better correlation. The KTH model achieved the highest average CORA rating, and the ABM received the highest average rating among models robustly validated against five cadaver impacts in three directions. This technique can be more frequently employed to build better models and, when associated limitations are well understood, to compare inter-model performance under similar conditions.
... A number of rat brain FE models have also been developed. Mao et al. (2006) developed an anatomically detailed rat brain FE model. The cortical motion of the model was partially validated with in-vivo indentation test data. ...
Thesis
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Traumatic Brain Injuries (TBIs) account for about half of the 1 300 000 annual traffic related deaths and the 50 000 000 injuries worldwide. The burden of TBI is ethically unacceptable and economically unsustainable. Recognising the efforts and achievements in reducing TBI conducted by the vehicle industry, research institutions and academy worldwide, the problem still call for additional research that lead to prevention of TBI. The main aim of this thesis is to develop a brain injury criterion and associated injury thresholds that can be used with crash test dummies in the design of safer cars. The craniocervical motion that produces diffuse brain injuries in experimental settings with animals was investigated by introducing finite element (FE) models of the animals. One rat and one monkey brain FE model were developed from medical images of the animals and validated using experimental data. The validated rat model was applied to simulate sagittal head rotational acceleration experiments with rats. Sequential analysis of the trauma progression indicated that acute subdural haematoma occurred at an early stage of the trauma, while diffuse axonal injury likely occurred at a later stage. The validated monkey model was applied to simulate past head impact experiments with primates that typically produced concussion symptoms. The analysis revealed large brainstem strains supporting the hypothesis that concussions are produced due to mechanical loading of the brainstem. These results also indicate the need to incorporate the craniocervical motion in human FE models and physical test devices in the development of countermeasures for concussive injury prevention. A method to make primate brain injury experimental data applicable for humans was also investigated. The monkey FE model was used to simulate 43 primate head impact experiments. Brain tissue injury risk curves that relate probability of injury, obtained in the experiments, with brain strains estimated in the simulations were developed. By assuming comparable mechanical properties of the brain tissues in monkeys and humans, these risk curves were applied to estimate injury risk in 76 impacts simulated with a human head-neck FE model which was also developed and validated for the purpose of this investigation. Overall, the investigated method proved to be technically feasible and to provide biomechanically justifiable means to related craniocervical kinematics and brain strains. This method accounts for contact phenomena typical from vehicle crash like head impacts, which past scaling techniques did not. Finally, new conceptual global brain injury criterion and injury risk functions that have the potential to predict the risk of diffuse brain injuries, were developed. The concept, denoted as Brain Injury Threshold Surface (BITS), establishes equal brain injury risk surfaces as a function of time-dependent and combined translational and rotational head kinematics typical in head impacts in car crashes. BITS appeared to explain the variance seen in both concussion from the monkey experiments and brain strains levels from the simulations with the monkey and the human brain FE models. Although evaluations of the new criteria and associated risk surfaces are pending, these have the potential to guide the development of superior restraints which would reduce the number and severity of brain injuries in future traffic accidents.
... These mathematical models, which combine an accurate representation of the head anatomy and sophisticated material properties, have the potential to simulate tissue loads and deformation patterns of brain structures. Local mechanical parameters derived from strain and stress tensors can be extracted and used as injury predictors (Zhang et al. 2004;Mao et al. 2006;Kleiven 2007;Takhounts et al. 2008;. Moreover, in vitro research showed that the occurrence of TBI is related to both viscoelastic properties and highly organized structure of the brain tissue (Bain and Meaney 2000;Smith and Meaney 2000;Bain et al. 2001;Elkin and Morrison 2007). ...
Article
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Computational models incorporating anisotropic features of brain tissue have become a valuable tool for studying the occurrence of traumatic brain injury. The tissue deformation in the direction of white matter tracts (axonal strain) was repeatedly shown to be an appropriate mechanical parameter to predict injury. However, when assessing the reliability of axonal strain to predict injury in a population, it is important to consider the predictor sensitivity to the biological inter-subject variability of the human brain. The present study investigated the axonal strain response of 485 white matter subject-specific anisotropic finite element models of the head subjected to the same loading conditions. It was observed that the biological variability affected the orientation of the preferential directions (coefficient of variation of 39.41% for the elevation angle—coefficient of variation of 29.31% for the azimuth angle) and the determination of the mechanical fiber alignment parameter in the model (gray matter volume 55.55–70.75%). The magnitude of the maximum axonal strain showed coefficients of variation of 11.91%. On the contrary, the localization of the maximum axonal strain was consistent: the peak of strain was typically located in a 2 cm³ volume of the brain. For a sport concussive event, the predictor was capable of discerning between non-injurious and concussed populations in several areas of the brain. It was concluded that, despite its sensitivity to biological variability, axonal strain is an appropriate mechanical parameter to predict traumatic brain injury.
... Willinger et al. 1999;Zhang et al. 2001;Kleiven 2002;Horgan & Gilchrist 2003;Moore et al. 2009;Yan & Pangestu 2011) and rat head injury (e.g. Levchakov et al. 2006;Mao et al. 2006;Lamy et al. 2013). The downside of the finite element method is the complexity needed to construct the 3D geometric details of different parts of the head and the difficulty in obtaining many of the material properties of these parts. ...
Article
Traumatic brain injury (TBI), induced by impact of an object with the head, is a major health problem worldwide. Rats are a well-established animal analogue for study of TBI and the weight-drop impact-acceleration (WDIA) method is a well-established model in rats for creating diffuse TBI, the most common form of TBI seen in humans. However, little is known of the biomechanics of the WDIA method and, to address this, we have developed a four-degrees-of-freedom multi-body mass-spring-damper model for the WDIA test in rats. An analytical expression of the maximum skull acceleration, one of the important head injury predictor, was derived and it shows that the maximum skull acceleration is proportional to the impact velocity but independent of the impactor mass. Furthermore, a dimensional analysis disclosed that the maximum force on the brain and maximum relative displacement between brain and skull are also linearly proportional to impact velocity. Additionally, the effects of the impactor mass were examined through a parametric study from the developed multi-body dynamics model. It was found that increasing impactor mass increased these two brain injury predictors.
... This model uses a pneumatic impact device to drive a rigid impactor onto the exposed intact dura, and mimics cortical tissue loss, acute subdural hematoma, brain edema, and even coma (Dixon et al. 1991;Lighthall et al. 1990). The advantage of this injury model is that it can control mechanical factors, such as time, velocity, and depth of impact (Cernak 2005;Mao et al. 2006). Body temperature, heart rate, blood PH, and partial pressure of oxygen were monitored during surgery, and there was no significant difference in these parameters between the perampanel-treated and the -untreated animals (data not shown). ...
Article
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Perampanel is a novel α-amino-3-hydroxy-5-methyl-4-isoxazole propionate receptor (AMPAR) antagonist, approved in over 35 countries as an adjunctive therapy for the treatment of seizures. Recently, it was found to exert protective effects against ischemic neuronal injury in vitro. In the present study, we investigated the potential protective effects of perampanel in a traumatic brain injury (TBI) model in rats. Oral administration with perampanel at a dose of 5 mg/kg exerted no major organ-related toxicities. We found that perampanel significantly attenuated TBI-induced brain edema, brain contusion volume, and gross motor dysfunction. The results of Morris water maze test demonstrated that perampanel treatment also improved cognitive function after TBI. These neuroprotective effects were accompanied by reduced neuronal apoptosis, as evidenced by decreased TUNEL-positive cells in brain sections. Moreover, perampanel markedly inhibited lipid peroxidation and obviously preserved the endogenous antioxidant system after TBI. In addition, enzyme-linked immunosorbent assay (ELISA) was performed at 4 and 24 h after TBI to evaluate the expression of inflammatory cytokines. The results showed that perampanel suppressed the expression of pro-inflammatory cytokines TNF-α and IL-1β, whereas increased the levels of anti-inflammatory cytokines IL-10 and TGF-β1. These data show that the orally active AMPAR antagonist perampanel affords protection against TBI-induced neuronal damage and neurological dysfunction through anti-oxidative and anti-inflammatory activity.
... To develop the mesh of the brain, a different technique was used aiming at a mesh of quality good enough to sustain severe loading conditions. The contours of the brain regions of interest in 58 coronal 1 mm equidistant sections of the brain, obtained from the Rhesus monkey brain Atlas [14], were identified and digitised in a similar way as described by [17] for the development of a rat brain FE model. The digitised contours were imported as point data into the meshing software. ...
Article
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A new method has been applied to develop a Finite Element (FE) model of the head- neck complex of Macaque monkey from medical images. The skull, brain and flesh have been validated based on tissue and component experimental data from literature. The kinematics of the head during occipital impacts have been validated against a sub-set of head impact experiments carried out in the past at the Japan Automobile Research Institute (JARI). The validated model has been used to simulate 19 occipital impacts case-by-case. The correlation between obtained peak values for a number of mechanical parameters of the different brain regions and the occurrence of concussion in the experiments was analysed. Maximum principal strain in the brainstem showed significant correlation to concussion; 21% strain was associated with a probability of 50% risk for concussion. The developed model and the presented results constitute the first step towards the development of a tissue level injury criterion for humans that is based on experimental animal data.
... . La ventaja de este método con respecto a otros modelos animales de TCE es el fácil manejo y control de las variables mecánicas, tales como: el tiempo, la velocidad y la profundidad del impacto. Por tal razón, este método pudiera ser más útil que el modelo de FPI para estudios biomecánicos del TCE50 . Una fortaleza adicional de este método comparado con los modelos por caída libre de un peso, es que no existe riesgo de daño por rebote, lo cual podría modular los resultados esperados por parte del investigador21 . ...
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Resumen El traumatismo craneoencefálico es uno de los problemas de salud pública más relevantes, afecta anualmente a más del 2% de la población de Estados Unidos y representa una de las causas más importantes de morbi-mortalidad, especialmente en la población joven. Los modelos experimentales suponen en este momento la mejor herramienta que disponemos para estudiar las múltiples alteraciones fisiopatológicas asociadas al daño cerebral traumático así como para la investigación de nuevas estrategias terapéuticas. El objetivo del trabajo es proporcionar una revisión de los diversos modelos experimentales de TCE que se han desarrollado para la investigación del daño cerebral traumático en condiciones in vivo, además de detallar los principales conocimientos fisiopatológicos y neuroconductuales obtenidos a partir de su aplicación. Palabras clave: traumatismo craneoencefálico, modelos experimentales in vivo Animal Models for Traumatic Brain Injury Abstract Traumatic brain injury is one of the most important problems of public health, annually affects more than 2% of the U.S. population and represents one of the major causes of morbidity and mortality, especially in young people. Experimental models assume at this point the best tool we have to study the multiple pathophysiological alterations associated with traumatic brain injury as well as research into new therapeutic strategies. The objective of this work is to provide a review of the various experimental models of TBI have been developed for the investigation of traumatic brain injury in vivo, as well as detailing the major pathophysiological and neurobehavioral knowledge gained from its application.
... The predominantly focal brain injury results in better understanding of the secondary processes of TBI pathophysiology. Mechanical factors like time, velocity, and controlled depth of impact may be more easy to induce and more useful than the FPI model for biomechanical studies of TBI (Mao et al., 2006;Wang and Ma, 2010). ...
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Traumatic brain injury (TBI) is a complex neurotrauma in civilian life and the battlefield with a broad spectrum of symptoms, long-term neuropsychological disability, as well as mortality worldwide. Posttraumatic epilepsy (PTE) is a common outcome of TBI with unknown mechanisms, followed by posttraumatic epileptogenesis. There are numerous rodent models of TBI available with varying pathomechanisms of head injury similar to human TBI, but there is no evidence for an adequate TBI model that can properly mimic all aspects of clinical TBI and the first successive spontaneous focal seizures follow a single episode of neurotrauma with respect to epileptogenesis. This review aims to provide current information regarding the various experimental animal models of TBI relevant to clinical TBI. Mossy fiber sprouting, loss of dentate hilar neurons along with recurrent seizures, and epileptic discharge similar to human PTE have been studied in fluid percussion injury, weight-drop injury, and cortical impact models, but further refinement of animal models and functional test is warranted to better understand the underlying pathophysiology of posttraumatic epileptogenesis. A multifaceted research approach in TBI model may lead to exploration of the potential treatment measures, which are a major challenge to the research community and drug developers. With respect to clinical setting, proper patient data collection, improved clinical trials with advancement in drug delivery strategies, blood-brain barrier permeability, and proper monitoring of level and effects of target drug are also important.
... Heterogeneity in the deficits that result from TBI may be attributed to the location, nature, and severity of primary injury, as well as pre-existing conditions and demographic characteristics (e.g. age, sex, substance abuse, and genetic differences) (32). Although studies have shown that the degree of CC involvement in TBI depends on the severity of injury, to our knowledge, no study has yet determined if there is a correlation between injuries to specific regions of the cortex and abnormalities in the corresponding subdivisonal fibers of the CC. ...
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Background: Traumatic brain injury (TBI) has been shown to predominantly affect the corpus callosum (CC). In light of the anatomical organization of cortico-callosal connections, we hypothesized that injury to the different cortical lobes may specifically affect their corresponding subdivisional fibers in the CC.
... Large and some extend along the axon model were adopted [30]. The MCSF of the rat model was assigned 0.5 kPa for the short-term shear modulus, 0.1 kPa for the long-term shear modulus, and 80 s ¡1 for the decay constant. ...
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The purpose of this study is to investigate the brain-strain-based thresholds for better prediction of the diffuse axonal injury (DAI) induced by a rotational acceleration on the rat brain. A previously developed and validated rat head finite element model was used to reconstruct 26 in vivo rat head impact experiments. DAI was produced via the high rotational acceleration applied to the rat head on the sagittal plane. Intracranial strain and strain-based injury indexes were calculated, including the maximum principal strain (MPS), the product of strain and strain rate, and the cumulative strain damage measure (CSDM). The region-specific conservative thresholds for DAI were estimated in terms of strain and strain-based injury indexes in the frontal, middle, and occipital regions of the corpus callosum. The axonal injuries observed in the experiments were used to formulate the injury risk functions, and the DAI risks were analysed via binary logistic regressions in terms of the calculated injury indexes. The logistic regression analysis demonstrated that the MPS, the product of strain and strain rate, as well as the CSDM were significantly correlated with DAI in the frontal corpus callosum. For the 50% probability of DAI in the frontal corpus callosum, it is suggested that the strain-based threshold is 0.12 for the MPS, 110 s-1 for the product of strain and strain rate, and 17% for the CSDM.
... To improve the understanding between head kinematics producing the injuries and the injury mechanisms and injury site, experiments are conducted and reconstructed with FE models of the specimens. This methodology has been conducted with different animal species and models, such as monkeys (Antona-Makoshi et al. 2013), sheep (Anderson et al. 2003), swine (Meaney et al. 1993), ferrets (Ueno et al. 1995), and rats (Antona-Makoshi et al. 2014;Lamy et al. 2009;Mao et al. 2006). However, none of these studies have considered the effect of age on injury outcome. ...
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The aim of this study was to investigate the possible effects of age-related intracranial changes on the potential outcome of diffuse axonal injuries and acute subdural hematoma under rotational head loading. A simulation-based parametric study was conducted using an updated and validated finite element model of a rat head. The validation included a comparison of predicted brain cortex sliding with respect to the skull. Further, model material properties were modified to account for aging; predicted tissue strains were compared with experimental data in which groups of rats in 2 different lifecycle stages, young adult and mature adult, were subjected to rotational trauma. For the parameter study, 2 age-dependent factors-brain volume and region-specific brain material properties-were implemented into the model. The models young adult and old age were subjected to several injurious and subinjurious sagittal plane rotational acceleration levels. Sequential analysis of the simulated trauma progression indicates that an increase in acute subdural hematoma injury risk indicator occurs at an early stage of the trauma, whereas an increase in diffuse axonal injury risk indicators occurs at a later stage. Tissue stiffening from young adult to mature adult rats produced an increase in strain-based thresholds accompanied by a wider spread of strain distribution toward the rear part of the brain, consistent with rotational trauma experiments with young adult and mature adult rats. Young adult to old age brain tissue softening and brain atrophy resulted in an increase in diffuse axonal injuries and acute subdural hematoma injury risk indicators, respectively. The findings presented in this study suggest that age-specific injury thresholds should be developed to enable the development of superior restraint systems for the elderly. The findings also motivate other further studies on age-dependency of head trauma.
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Traumatic Brain Injury (TBI) stands as a multifaceted health concern, exhibiting varying influences across human population. This study delves into the biomechanical complexities of TBI within gender-specific contexts, focusing on females. Our primary objective is to investigate distinctive injury mechanisms and risks associated with females, emphasizing the imperative for tailored investigations within this cohort. By employing Fluid-Structure Interaction (FSI) Analysis, we conducted simulations to quantify biomechanical responses to traumatic forces across diverse age groups of females. The study utilized a scaling technique to create finite element models (FEMs). The young female FEM, based on anthropometric data, showcased a 15 % smaller head geometry compared to the young male FEM. Moreover, while the elderly female FEM closely mirrored the young female FEM in most structural aspects, it showed distinctive features such as brain atrophy and increased cerebrospinal fluid (CSF) layer thickness. Notably, the child female FEM (ages 7–11 years) replicated around 95 % of the young female FEM's geometry. These structural distinctions meticulously captured age-specific variations across our modeled female age groups. It's noteworthy that identical conditions, encompassing impact intensity, loading type, and boundary conditions, were maintained across all FEMs in this biomechanical finite element analysis, ensuring comparative results. The findings unveiled significant variations in frontal and occipital pressures among diverse age groups, highlighting potential age-related discrepancies in TBI susceptibility among females. These variations were primarily linked to differences in anatomical features, including brain volume, CSF thickness, and brain condition, as the same material properties were used in the FEMs. These results were approximately 4.70, 6.33 and 6.43 % in frontal area of brain in diverse age groups of females (young, elderly, and child) respectively compared to young male FEM. Comparing the FEM results between the young female and the elderly female, we observed a decrease in occipital brain pressure at the same point, reducing from 171,993 to 167,793 Pa, marking an approximate 2.5 % decrease. While typically the elderly exhibit greater brain vulnerability compared to the young, our findings showcase a reduction in brain pressure. Notably, upon assessing the relative movement between the brain and the skull at the point located in occipital area, we observed greater relative movement in the elderly (1.8 mm) compared to the young female (1.04 mm). Therefore, brain atrophy increases the range of motion of the brain within the cranial space. The study underscores the critical necessity for nuanced TBI risk assessment tailored to age and gender, emphasizing the importance of age-specific protective strategies in managing TBIs across diverse demographics. Future research employing individual modeling techniques and exploring a wider age spectrum holds promise in refining our understanding of TBI mechanisms and adopting targeted approaches to mitigate TBI in diverse groups.
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Background: Traumatic brain injury (TBI) is a major cause of morbidity and mortality, affecting millions annually worldwide. Although the majority of TBI patients return to premorbid baseline, a subset of patient can develop persistent and often debilitating neurocognitive and behavioral changes. The etiology of TBI within the clinical setting is inherently heterogenous, ranging from sport related injuries, fall related injuries and motor vehicle accidents in the civilian setting, to blast injuries in the military setting. Objective: Animal models of TBI, offer the distinct advantage of controlling for injury modality, duration and severity. Furthermore, preclinical models of TBI have provided the necessary temporal opportunity to study the chronic neuropathological sequelae of TBI, including neurodegenerative sequelae such as tauopathy and neuroinflammation within the finite experimental timeline. Despite the high prevalence of TBI, there are currently no disease modifying regimen for TBI, and the current clinical treatments remain largely symptom based. The preclinical models have provided the necessary biological substrate to examine the disease modifying effect of various pharmacological agents and have imperative translational value. Methods: The current review will include a comprehensive survey of well-established preclinical models, including classic preclinical models including weight drop, blast injury, fluid percussion injury, controlled cortical impact injury, as well as more novel injury models including closed-head impact model of engineered rotational acceleration (CHIMERA) models and closed-head projectile concussive impact model (PCI). In addition to rodent preclinical models, the review will include an overview of other species including large animal models and Drosophila. Results: There are major neuropathological perturbations post TBI captured in various preclinical models, which include neuroinflammation, calcium dysregulation, tauopathy, mitochondrial dysfunction and oxidative stress, axonopathy, as well as glymphatic system disruption. Conclusion: The preclinical models of TBI continue to offer valuable translational insight, as well as essential neurobiological basis to examine specific disease modifying therapeutic regimen.
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Model-based brain injury criteria can present higher potential to predict injury than global head kinematic parameters. Numerical head injury prediction tools are time consuming and require Finite Element (FE) skilled users. To address these difficulties, a deep learning technique was applied to an existing previously developed brain FE model for which an injury risk curve has been proposed in terms of maximum Von Mises stress to predict moderate diffuse axonal injury. A total of 4492 experimental head impacts coming from experimental helmet testing were considered as input for the analysis. Each input was expressed in terms of three linear accelerations and three angular velocities versus time, when the target metric was the time history Von Mises Stress (vms) curve computed within the brain via the FE analysis. The architecture used for the Deep Learning (DL) model is the U-Net and four models based on it were evaluated. The dataset was split into three datasets dedicated for learning and testing. The quality of the DL models were assessed via the Maximum Absolute Error between FE and DL models computed brain maximum vms. Further, a regression analysis of brain response with both methods was conducted. The results demonstrated that deep learning methods can be applied in the context of brain response estimation when helmet assessment is considered without any FE computation, only by considering the 6 D head kinematic vs time demonstrating that the deep learning approach should be further developed for research and industrial applications.
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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.
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Concussion, in spite of being a mild traumatic brain injury, involves serious long term consequences and can adversely affect the life of an individual, their family and the wider society. Since, diffuse axonal injury (DAI) is known to be one of the most frequent pathological features of traumatic brain injury (TBI), knowledge of the mechanical threshold for concussion in terms of axonal strain can help in developing better brain injury prediction tools in the context of head protection system optimization and the management of sport related concussions. This paper presents development, validation and utilization of an anisotropic viscous hyperelastic finite element rat brain model for investigation of the mechanical threshold for concussion in terms of axonal strain. For the investigation, twenty-six well documented cases of experimental concussion were simulated. A thorough statistical analysis of global kinematic parameters (maximum rotational acceleration and duration) and intra-cerebral parameters (maximum axonal strain, maximum strain energy, maximum von Mises stress, maximum von Mises strain, maximum shear stress, maximum shear strain, maximum principal stress, maximum principal strain, minimum pressure and maximum pressure) revealed that intra-cerebral parameters are better suited for the prediction of concussion than the global kinematic parameters. The estimated tolerance level for a 50% risk of concussion was found to be 8.97% of maximum axonal strain. The results are promising and hence, this study is not only a key step towards better understanding of concussion, but it also contributes towards concussion related investigations. Statement of significance A number of studies have identified axonal strain as one of the key metrics for the prediction of concussion through biomechanical simulations. Where infeasibility of experimentation on in-vivo human brain limits the in-depth investigation, animal models have proved to be efficient. None of the existing finite element rat brain models have taken anisotropy, based on the rat brain DTI, into account, which is rather a crucial aspect for the fidelity. The present study provides a validated anisotropic viscous hyperelastic finite element rat brain model, which was successfully applied for the simulations of experimental concussive loadings on the rat brain and furnished promising results that are in accordance with the literature. As such, it is helpful in developing more accurate brain injury prediction tools in the context of head protection system optimization and for the management of sport related concussions.
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The Veterans Health Administration determined that over 250,000 U.S. service members were diagnosed with a traumatic brain injury (TBI) between 2008 and 2018, of which a great proportion were due to blast exposure. Although the penetrating (secondary) and inertia-driven (tertiary) phases of blast-induced TBI (bTBI) have been studied thoroughly and are known to be injurious, primary blast brain injury has been less studied. We investigated the biomechanics of primary bTBI in our previously developed in vitro shock tube model with a fluid-filled sample receiver. Using stereoscopic, high-speed cameras and digital image correlation (DIC), we mapped the deformation of organotypic hippocampal slice cultures (OHSCs) following a range of blast exposures to characterize the induced strains. As blast exposure increased, tissue strain increased, although the levels remained relatively low (maximum < 9%), with strains rates between 25 and 85 s⁻¹. Both strain magnitude and rate were highly correlated with the in-air blast impulse and in-fluid peak pressure parameters. Comparing biomechanical parameters to previously reported blast-induced electrophysiological dysfunction, a threshold for deficits in long-term potentiation (LTP) was observed for strains between 3.7 and 6.7% and strain rates between 25 and 33 s⁻¹. This is the first study to experimentally determine primary blast-induced strain and strain rates in hippocampal tissue.
Chapter
Numerical modelling of the brain is essential for investigating its internal responses during blunt impacts. Extensive research, including the development, validation, improvement, and application of brain models, has been reported in recent years. These reported models are used to investigate intracranial responses, to study injury mechanisms and their associated tolerances, and to predict the risk of sustaining brain injuries upon impacts. In order to accomplish such endeavours, we recommend that researchers must utilize high-quality brain models and have thorough understanding of the underlying injury mechanisms. Otherwise, a wrong targeted mechanism may be selected and predictions made by the model may not represent the true responses of the brain. In this chapter, we discuss several essential knowledges related to the understanding of brain injury mechanisms and development of biofidelic head and brain models.
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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.
Chapter
The purpose of modeling head impact is to try to understand the effect of a blow to the brain. Thus, it is essential that the brain be modeled in as much detail as possible. Then, of course, it will be necessary to assess injury to the brain by computing its response. Based on what we know about brain injury, we hypothesize that strain in the axons is a likely cause of diffuse axonal injury (DAI) and intracranial pressure wave propagation can be a second parameter of interest. Because of the complexity of the geometry of the head and brain, the many different types of tissues involved, and the lack of data on their material properties under high strain rate conditions, the modeling task is far from being simple. In the pre-finite element era, simplifying assumptions were made to facilitate the formulation of equations that describe the impact event. For example, the first known model of head impact was proposed by Anzelius (1943) who assumed the head to be a rigid sphere and the brain to be a liquid. He solved the governing equations in closed form, and his model predicted coup and contrecoup pressures at the site of impact and at a site diametrically opposite to the site of impact, respectively.
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A combined approach of numerical modeling and animal experiments was used to study the mechanisms of traumatic brain injury (TBI). A three-dimensional finite element model (FEM) of the rat brain was submitted to experimental sagittal plane rotational acceleration pulses. The experimental setup provided histological analysis of injured brain tissues for a range of severities. The biomechanical response parameters were extracted from the FEM in the anatomical regions identified by experiments as prone to injuries. Von Mises stresses and first principal strains proved to increase with both the amplitude of acceleration loadings and the tissue injuries severities. Further comparison between mechanical responses and experimental histological scores allowed proposing tissue thresholds for the occurrence of TBI, namely 1.5 kPa and 4% approximately for Von Mises stresses and first principal strains, respectively. Those values can be used for further investigations of the mechanisms of TBI.
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The closed head impact (CHI) rat models are commonly used for studying the traumatic brain injury. The impact parameters vary considerably among different laboratories, making the comparison of research findings difficult. In this work, numerical CHI experiments were conducted to investigate the sensitivities of intracranial responses to various impact parameters (e.g., impact depth, velocity, and position; impactor diameter, material, and shape). A three-dimensional finite element rat head model with anatomical details was subjected to impact loadings. Results revealed that impact depth and impactor shape were the two leading factors affecting intracranial responses. The influence of impactor diameter was region-specific and an increase in impactor diameter could substantially increase tissue strains in the region which located directly beneath the impactor. The lateral impact could induce higher strains in the brain than the central impact. An indentation depth instead of impact depth would be appropriate to characterize the influence of a large deformed rubber impactor. The experimentally observed velocity-dependent injury severity could be attributed to the "overshoot" phenomenon. This work could be used to better design or compare CHI experiments.
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Most biomechanical models that aim to investigate traumatic brain injury consider the corona radiata as a homogeneous structure. To verify this, indentation-relaxation tests using a custom-designed indentation device were performed on the anterior, superior, and posterior region of the corona radiata in the coronal plane of the porcine brain. Using Boltzmann hereditary integral, a linear viscoelastic model with a Prony series approximation was fitted to the time-dependent shear modulus for different regions of the corona radiata, and the fit parameters were generated. The posterior region was the stiffest and the anterior region was the least stiff. A statistical analysis revealed a significant difference in biomedical properties between the anterior and superior regions, as well as between the anterior and posterior regions in the short time scale. However, the results showed that these differences faded away as the tissue approached equilibrium. No significant difference was observed between the superior and posterior regions along the total time history of relaxation. This is the first demonstration of the regional biomechanical heterogeneity of the corona radiata, and these results will improve future biomedical models of the porcine brain.
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Currently, angular acceleration is believed to be more damaging to the brain than linear acceleration, even though both are present in any head impact. In a recent experiment, it was found that a helmeted head sustained the same degree of angular acceleration as the unhelmeted head for the same impact, but its linear acceleration was decreased significantly. So, if angular acceleration is the cause of brain injury, then how is the brain protected by the helmet? This paper proposes a new hypothesis of brain injury and suggests that input acceleration limits should be replaced by response variables.
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Clinical and biomechanical evidence indicates that mechanisms and pathology of head injury in infants and young children may be different from those in adults. Biomechanical computer-based modeling, which can be used to provide insight into the thresholds for traumatic tissue injury, requires data on material properties of the brain, skull, and sutures that are specific for the pediatric population. In this study, brain material properties were determined for rats at postnatal days (PND) 13, 17, 43, and 90, and skull/suture composite (braincase) properties were determined at PND 13, 17, and 43. Controlled 1 mm indentation of a force probe into the brain was used to measure naive, non-preconditioned (NPC) and preconditioned (PC) instantaneous (G(i)) and long-term (G( infinity )) shear moduli of brain tissue both in situ and in vitro. Brains at 13 and 17 PND exhibited statistically indistinguishable shear moduli, as did brains at 43 and 90 PND. However, the immature (average of 13 and 17 PND) rat brain (G(i) = 3336 Pa NPC, 1754 Pa PC; G( infinity )= 786 Pa NPC, 626 Pa PC) was significantly stiffer (p < 0.05) than the mature (average of 43 and 90 PND) brains (G(i) = 1721 Pa NPC, 1232 Pa PC; G( infinity ) = 508 Pa NPC, 398 Pa PC). A "reverse engineering" finite element model approach, which simulated the indentation of the force probe into the intact braincase, was used to estimate the effective elastic moduli of the braincase. Although the skull of older rats was significantly thicker than that of the younger rats, there was no significant age-dependent change in the effective elastic modulus of the braincase (average value = 6.3 MPa). Thus, the increase in structural rigidity of the braincase with age (up to 43 PND) was due to an increase in skull thickness rather than stiffening of the tissue. These observations of a stiffer brain and more compliant braincase in the immature rat compared with the adult rat will aid in the development of age-specific experimental models and in computational head injury simulations. Specifically, these results will assist in the selection of forces to induce comparable mechanical stresses, strains and consequent injury profiles in brain tissues of immature and adult animals.
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The pia mater has received little attention regarding its function in the deformation of the spinal cord under compression. In this study the mechanical properties and function of the spinal pia mater were investigated using three methods. Spinal cord segments were excised from rabbits. The elastic modulus of the pia mater was measured by performing a tensile test using specimens with the pia mater intact and ones with the pia mater stripped off. The stiffness of the spinal cord was examined by performing a compression test with specimens containing an intact pia mater and ones with a pia mater that was incised at both sides. The cross-sectional area and circumference of the spinal cord were measured on axial views of magnetic resonance images in patients with cervical disc herniations before and after surgery. The pia mater had an elastic modulus of 2300 kPa, which was 460 times higher than that of spinal cord parenchyma. By covering the parenchyma, it tripled the overall elastic modulus of the spinal cord. The pia mater increased the stiffness of the spinal cord and enhanced its shape recovery after removal of the compression. The cross-sectional area of the spinal cord increased after surgery, whereas the circumference of the spinal cord changed little. The pia mater firmly covers the spinal cord and has a high elastic modulus; it therefore provides a constraint on the spinal cord surface. It prevents elongation of the circumference and produces a large strain energy that is responsible for shape restoration following decompression.
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The SIMon (Simulated Injury Monitor) software package is being developed to advance the interpretation of injury mechanisms based on kinematic and kinetic data measured in the advanced anthropomorphic test dummy (AATD) and applying the measured dummy response to the human mathematical models imbedded in SIMon. The human finite element head model (FEHM) within the SIMon environment is presented in this paper. Three-dimensional head kinematic data in the form of either a nine accelerometer array or three linear CG head accelerations combined with three angular velocities serves as an input to the model. Three injury metrics are calculated: Cumulative strain damage measure (CSDM) - a correlate for diffuse axonal injury (DAI); Dilatational damage measure (DDM) - to estimate the potential for contusions; and Relative motion damage measure (RMDM) - a correlate for acute subdural hematoma (ASDH). During the development, the SIMon FEHM was tuned using cadaveric neutral density targets (NDT) data and further validated against the other available cadaveric NDT data and animal brain injury experiments. The hourglass control methods, integration schemes, mesh density, and contact stiffness penalty coefficient were parametrically altered to investigate their effect on the model's response. A set of numerical and physical parameters was established that allowed a satisfactory prediction of the motion of the brain with respect to the skull, when compared with the NDT data, and a proper separation of injury/no injury cases, when compared with the brain injury data. Critical limits for each brain injury metric were also established. Finally, the SIMon FEHM performance was compared against HIC15 through the use of NHTSA frontal and side impact crash test data. It was found that the injury metrics in the current SIMon model predicted injury in all cases where HIC15 was greater than 700 and several cases from the side impact test data where HIC15 was relatively small. Side impact was found to be potentially more injurious to the human brain than frontal impact due to the more severe rotational kinematics.
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Traumatic brain injury (TBI) is caused by brain deformations resulting in the pathophysiological activation of cellular cascades which produce delayed cell damage and death. Understanding the consequences of mechanical injuries on living brain tissue continues to be a significant challenge. We have developed a reproducible tissue culture model of TBI which employs organotypic brain slice cultures to study the relationship between mechanical stimuli and the resultant biological response of living brain tissue. The device allows for the independent control of tissue strain (up to 100%) and strain rate (up to 150 s-1) so that tolerance criteria at the tissue level can be developed for the interpretation of computational simulations. The application of texture correlation image analysis algorithms to high speed video of the dynamic deformation allows for the direct calculation of substrate strain and strain rate which was found to be equi-biaxial and independent of radial position. Precisely controlled, mechanical injuries were applied to organotypic hippocampal slice cultures, and resultant cell death was quantified. Cell death was found to be dependent on both strain magnitude and rate and required several days to develop. An immunohistological examination of injured cultures with antibodies to amyloid precursor protein revealed the presence of traumatic axonal injury, suggesting that the model closely replicates in vivo TBI but with advantages gained in vitro. We anticipate that a combined in vitro approach with optical strain mapping will provide a more detailed understanding of the dependence of brain cell injury and death on strain and strain rate.
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Many finite element models have been developed by several research groups in order to achieve a better understanding of brain injury. Due to the lack of experimental data, validation of these models has generally been limited. Consequently, applying these models to investigate brain responses has also been limited. Over the last several years, several versions of the Wayne State University brain injury model (WSUBIM) were developed. However, none of these models is capable of simulating indirect impacts with an angular acceleration higher than 8,000 rad/s(2). Additionally, the density and quality of the mesh in the regions of interest are not detailed and sensitive enough to accurately predict the stress/strain level associated with a wide range of impact severities. In this study, WSUBIM version 2001, capable of simulating direct and indirect impacts with a combined translational and rotational acceleration of the head up to 200 g and 12,000 rad/s(2) has been developed. This new finely meshed model, consisting of more than 314,500 elements and 281,800 nodes, also simulates an anatomically detailed facial bone model. An additional new feature of the model is the damageable material property representation of the facial bone and the skull, allowing it to simulate bony fractures. The model was subjected to extensive validation using published cadaveric test data. These data include the intracranial and ventricular pressure data reported by Nahum et al. (1977) and Trosseille et al. (1992), the relative displacement data between the brain and the skull reported by King et al. (1999) and Hardy et al. (2001), and the facial impact data reported by Nyquist et al. (1986) and Allsop et al. (1988). With the enhanced accuracy of model predictions offered by this new model, along with new experimental data, it is hoped that it will become a powerful tool to further our understanding of the mechanisms of injury and the tolerance of the brain to blunt impact.
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The principal focus of this study was the measurement of relative brain motion with respect to the skull using a high-speed, biplanar x-ray system and neutral density targets (NDTs). A suspension fixture was used for testing of inverted, perfused, human cadaver heads. Each specimen was subjected to multiple tests, either struck at rest using a 152-mm-diameter padded impactor face, or stopped against an angled surface from steady-state motion. The impacts were to the frontal and occipital regions. An array of multiple NDTs was implanted in a double-column scheme of 5 and 6 targets, with 10 mm between targets in each column and 80 mm between columns. These columns were implanted in the temporoparietal and occipitoparietal regions. The impacts produced peak resultant accelerations of 10 to 150 g, and peak angular accelerations between 1000 and 8000 rad/s(2). For all but one test, the peak angular speeds ranged from 17 to 22 rad/s. The relative 3D displacements between the skull and the NDTs were analyzed. The localized motions of the brain generally followed loop or figure eight patterns, with peak displacements on the order of +/- 5 mm. These results can be used to further finite-element modeling efforts.
Article
Axonal injury is a common finding in serious head injuries in infancy and those associated with non-accidental causes. This study represents the first detailed research into the biomechanics of axonal injury specifically in infants. We investigated the material properties of infant brain tissue, thresholds for axonal injury in the infant, and the loads associated with accidental and inflicted pediatric head injures. Brain tissue properties show significant age-dependence, with infant tissue being approximately twice as stiff as adult tissue. Locations of axonal injury in 3–5 day-old piglets subjected to purely inertial, non-impact rotations were compared with tissue deformations predicted by finite element simulations. Peak maximum principal strain (pkE1) was the best overall predictor of axonal injury and the optimal pkEI threshold of 33% for axonal injury in the infant is higher than previous thresholds reported for adult axonal injury. To investigate the loading conditions in accidental and inflicted pediatric head injuries, we constructed a 1.5 month infant anthropomorphic surrogate. Vigorous shakes of this infant model had similar inertial loads experienced during minor falls, but inflicted impacts were significantly higher than even a 1.5m fall onto concrete. A 3-D finite element model of a 1 month old infant head, infant material properties, axonal tissue injury thresholds and typical loading conditions were combine to determine the incidence of axonal injury during abusive and accidental events. Shakes and moderate inflicted impact scenarios produced higher strains and stresses than the fall simulation but less than 1% of the brain volume was predicted to have axonal injury. The severe inflicted impact resulted in the largest strains and stresses predicted within the brain tissue of all events examined. Axonal injury was predicted in 11–30% of the brain with injury occurring in the subcortical and deep white matter regions. This research supports the theory that traumatic axonal damage in the infant requires an impact to the head and shaking alone will not produce traumatic axonal injury.
Article
A finite element model of cerebral contusion in the rat was developed and compared to experimental injury maps demonstrating blood-brain barrier (BBB) breakdown. The model was exercised at the nine unique loading conditions used experimentally. Logistic regressions of four variables, maximum principal logarithmic strain (LEP), maximum principal stress (SP), strain energy density (SEN), and von Mises stress (MIS) demonstrated highly significant confidence in the prediction of the 50th percentile values (chi-squared, p<0.00001). However, only values for LEP were invariant across loading conditions. These results suggest that the BBB is most sensitive to LEP, and that breakdown occurs above a strain of 0.188 +/- 0.0324.
Conference Paper
We have developed a totally new three-dimensional human head model in which the gray matter, white matter, vehicles and parasagittal bridging veins were included. This study is a continuation of the modeling efforts of the two-dimensional porcine brain models by Zhou et al. (1994) and three-dimensional human head model by Ruan et al. (1994). The paper presents some preliminary simulation results of the new three-dimensional model for a direct frontal impact and an indirect sagittal plane rotational impact ro delineate differences between the homogeneous and inhomogeneous brain models, and to study the mechanism of the subdural hematoma.
Article
Controlled cortical impact models produce brain injury by using a pneumatic impactor to impact exposed brain. This study systematically examined the effects of varying magnitudes of controlled cortical impact to the rat brain on neurological, cardiovascular, and histopathological variables. As the magnitude of injury increased, the duration of suppression of somatomotor reflexes and the duration of chronic vestibular motor deficits increased. The blood pressure response was observed to depend on injury levels; a moderate injury level produced a hypotensive response while a high injury level produced an immediate brief hypertensive response followed by hypotension. Low injury levels produced no significant macroscopic or microscopic change, but higher injury levels produced cortical contusion and intraparenchymal hemorrhage which, with increasing survival time, evolved into necrotic changes and cavitation underlying the injury site. Also with high levels of injury, axonal injury was found throughout the brain-stem with the greatest concentration of injured axons occurring in the cerebellar peduncles and pontomedullary junction. These data demonstrate that controlled cortical impact in the rat reproduces many of the features observed in other experimental animal models. This model allows independent control of many mechanical loading parameters associated with traumatic brain injury. The controlled cortical impact rat model should be an effective experimental tool to investigators of traumatic brain injury.
Article
A new experimental model of mechanical brain injury was produced in the laboratory ferret (Mustela putorius furo) using a stroke-constrained pneumatic impactor. Cortical impacts were made on vertex to the intact dura mater overlying the cerebral cortex with contact velocities ranging from 2.0 to 4.0 m/sec and with deformations of 2.0 to 5.0 mm. The dwell time of the impact and the stability of the skull during impact were verified with high speed (1000 to 3000 frames/sec) cineradiography. Systemic arterial blood pressure, heart rate, and respiration were monitored, and postinjury changes were recorded. Anatomic brain injury, including subdural hematoma, subarachnoid hemorrhage, tears or rents of the dura mater, and contusions of the cortex, brainstem, cervical spinal cord, and cerebellum was observed. Injury responses ranged from no apparent anatomic injury or alterations in the systemic physiology at low severity impact (2.0 m/sec, 2.0 mm) to immediate fatality in the highest severity impact groups (4.0 m/sec, 4.0 mm). The range of changes in systemic physiology and of pathology in the brain, brainstem, and spinal cord was a function of both contact velocity and the amount of brain deformation. In two cases where postinjury time was 8-10 h, diffuse axonal injury, indicated by beaded axons and retraction balls, was present in subcortical regions underlying the site of impact. The spectrum of anatomic injury and systemic physiologic responses closely resembled aspects of closed head injury seen clinically. This procedure complements and improves on existing techniques by allowing independent control of contact velocity and level of deformation of the brain to facilitate biomechanical and analytic modeling of brain trauma. Graded cortical contusions and subcortical injury are produced by precisely controlled brain deformations, thereby allowing questions to be addressed regarding the influence of contact velocity and level of deformation on the anatomic and functional severity of brain injury.
Article
Diffuse axonal injury (DAI) is a form of brain injury that is characterized by morphologic changes to axons throughout the brain and brainstem. Previous biomechanical studies have shown that primary axonal dysfunction, ranging from minor electrophysiologic disturbances to immediate axotomy, can be related to the rate and level of axonal deformation. Some existing rodent head injury models display varying degrees of axonal injury in the forebrain and brainstem, but the extent of axonal damage in the forebrain has been limited to the contused hemisphere. This study examined whether opening the dura mater over the contralateral hemisphere could direct mechanical deformation across the sagittal midline and produce levels of strain sufficient to cause a more widespread, bilateral forebrain axonal injury following cortical impact. Intracranial deformation patterns produced by this modified cortical impact technique were examined using surrogate skull-brain models. Modeling results revealed that the presence of a contralateral craniotomy significantly reduced surrogate tissue herniation through the foramen magnum, allowed surrogate tissue movement across the sagittal midline, and resulted in an appreciable increase in the shear strain in the contralateral cortex during the impact. To evaluate the injury pattern produced using this novel technique, rat brains were subjected to rigid indentor impact injury of their left somatosensory motor cortex (1.5 mm indentation, 4.5-4.9 m/sec velocity, and 22 msec dwell time) and examined after a 2-7 day survival period. Neurofilament immunohistochemistry revealed numerous axonal retraction balls in the subcortical white matter and overlying deep cortical layers in the right hemisphere beneath the contralateral craniotomy. Retraction balls were not seen at these positions in normals, sham controls, or animals that received cortical impact without contralateral craniotomy and dural opening. The results from these physical modeling and animal experiments indicate that opening of the contralateral dura mater permits translation of sufficient mechanical deformation across the midline to produce a more widespread pattern of axonal injury in the forebrain, a pattern that is distinct from those produced by existing fluid percussion and cortical impact techniques.
Article
Cerebrovascular disruption and cortical pathology resulting from either moderate (M-TBI) or severe (S-TBI) traumatic brain injury produced by a pneumatically-driven cortical contusion device were assessed in adult male rats sacrificed at 6 and 24 h or 8 and 30 days after injury to the right sensorimotor cortex. Epidural, subdural, subarachnoid, petechial (cortex and corpus callosum), and/or intraventricular hemorrhage was present in all animals, more extensively and severely following S-TBI. At 6 or 24 h after TBI, acidophilic (acid fuchsin-positive) neurons were numerous and widespread (S-TBI > M-TBI) in the ipsilateral contused cortex. By 8 days few acidophilic neurons were present in peri-impact regions of the ipsilateral neocortex, and none were detected in cortex 30 days postinjury. Both M-TBI and S-TBI groups had enlarged ipsilateral cortical volumes (edema) at 6 and 24 h post-contusion. Eight and 30 days after injury the mean volume of cortical necrosis was significantly larger in S-TBI than in M-TBI rats, and cortical necrosis in both TBI conditions increased between 8 to 30 days postinjury. These results indicate that this pneumatically-driven contusion device produces reliable and consistent primary and secondary cortical histopathology, the extent of which is related to the severity of initial injury.
Article
The purpose of this paper is to present results from methodologies used in our laboratory that are targeted toward identifying specific brain injury thresholds. Results from studying one form of brain injury, diffuse axonal injury, are presented in this report. Physical models, or surrogates, of the skull-brain complex are used to estimate the relationship between inertial loading and brain deformation. A porcine model of diffuse axonal injury, developed with information from these physical models and earlier in vitro tissue modeling studies, is used to correlate histologic and radiologic evidence of axonal injury to predicted regions of injury from the experimental and theoretical analysis. These results form the basis for developing improved diffuse brain injury tolerance levels, as well as identifying new means of diagnostic and treatment techniques for diffuse axonal injury.
Article
Controlled cortical impact (CCI) is a contemporary model of experimental cerebral contusion. We examined the cerebrovascular and neuropathologic effects of a severe CCI in rats. The utility of magnetic resonance imaging (MRI) for the assessment of contusion volume after severe CCI was also established. Severe CCI (3.0 mm depth, 4 m/sec velocity) to the left (L) parietal cortex was produced in anesthetized (isoflurane/N2O/O2), intubated, and mechanically ventilated male Sprague-Dawley rats (n = 58). Physiologic parameters were controlled. The time course of alterations in edema [L-R% brain water (% BW) in 3-mm coronal sections through injured and contralateral hemispheres, wet-dry weight] was evaluated at 2 h, 24 h, 48 h, and 7 days posttrauma. Local cerebral blood flow (ICBF, measured in 8 structures in each hemisphere by autoradiography) was evaluated at 2 h, 24 h, and 7 days. Contusion volume (measured by histology and image analysis) was assessed at 14 days and measured in 6 rats by both MRI and histology. The survival rate after severe CCI was 96.2%. The L-R difference in % BW increased to 1.69 +/- 0.18% at 2 h, 3.00 +/- 0.08% at 24 h, 2.69 +/- 0.09% at 48 h, and 0.94 +/- 0.21% at 7 days. These values all differed from the control (p < 0.05). The % BW was greater at 24 h and 48 h than at 2 h and 7 days (p < 0.05). Marked reductions in ICBF were limited to structures in the injured hemisphere and were observed in the parietal cortex (2 and 24 h), subcortical white matter (2 and 24 h), and hippocampus (2 h), (p < 0.05) vs control rats. In the contusion core, ICBF was 19.4 +/- 8.8 mL 100 g-1 min-1 at 24 h (p = 0.011 vs normal). Necrosis was seen in large portions of the parietal cortex and subcortical white matter, and portions of the hippocampus and thalamus. Contusion volume was 47.8 +/- 9.2 mm3, which represented 14.4 +/- 2.1% of the traumatized hemisphere. Estimates of contusion volume by MRI and histology were closely correlated (r = 0.941, p < 0.017). Severe CCI in rats is accompanied by contusion, reproducible edema, and marked hypoperfusion, involving over 14% of the injured hemisphere, and can be produced with minimal mortality. T2-weighted MRI successfully and noninvasively identifies contusion volume in this model.
Article
Clinical and experimental studies show that loss of neurons in the hippocampus and/or the entorhinal cortex can impede formation and storage of spatial memory. Using a controlled cortical impact model of traumatic brain injury (TBI) in rats, we have examined the temporal and spatial pattern of neuronal death using silver impregnation and cresyl violet staining. Dystrophic neurons can be detected in the dentate gyrus, and the CA1 and CA3 subfields of the hippocampus for up to 2 weeks following injury. These dystrophic cells appeared shrunken and possessed features of apoptosis. Areas containing the dystrophic cells suffer substantial cell loss as demonstrated by thinning of the neuronal layers. Dystrophic cells are also found in the amygdala, entorhinal and piriform cortices, thalamic and hypothalamic regions, and surrounding the contusion site. The loss of these cells may contribute to the memory deficits observed following TBI.
Article
This experiment utilized a laterally placed controlled cortical impact model of traumatic brain injury (TBI) to assess changes on spatial learning and memory in the Morris water maze (MWM). Adult rats were subjected to one of two different levels of cortical injury, mild (1 mm) or moderate (2 mm) deformation, and subsequently tested for their ability to learn (acquisition) or remember (retention) a spatial task, 7 or 14 days after injury. Results revealed an injury-dependent deficit for experimental animals compared to sham-operated controls. Not only did the TBI result in longer escape latencies, but also significant deficits in search time and relative target visits. Although the moderately injured animals demonstrated significant histopathology in the cortex and hippocampus, mildly injured subjects demonstrated no obvious tissue destruction, but did manifest significant behavioral change. These results demonstrate that a laterally placed controlled cortical impact is capable of producing significant cognitive deficits on both acquisition and retention paradigms utilizing the MWM.
Article
Although it is known that the brain can be injured by mechanical forces initiated at the moment of impact during trauma, it is not clear how the physical response of the brain dictates the injury patterns that occur in experimental models of traumatic brain injury. In this study, we investigated the mechanical response of the brain to a technique that creates a focal injury in the rat brain. Using a transient vacuum pulse applied to the exposed cortical surface, we found that the displacement of the cortex and the extent of in vivo blood-brain barrier breakdown were related significantly to the vacuum pressure level. The relationship between the response of the cortex and injury pattern points towards a new opportunity for control of the distribution and extent of injury patterns in animal models through a precise understanding of the model biomechanics, as well as potential improvements in means of preventing traumatic brain injury.
Article
We used a new approach, termed dynamic cortical deformation (DCD), to study the neuronal, vascular, and glial responses that occur in focal cerebral contusions. DCD produces experimental contusion by rapidly deforming the cerebral cortex with a transient, nonablative vacuum pulse of short duration (25 milliseconds) to mimic the circumstances of traumatic injury. A neuropathological evaluation was performed on brain tissue from adult rats sacrificed 3 days following induction of either moderate (4 psi, n = 6) or high (8 psi, n = 6) severity DCD. In all animals, DCD produced focal hemorrhagic lesions at the vacuum site without overt damage to other regions. Examination of histological sections showed localized gross tissue and neuronal loss in the cortex at the injury site, with the volume of cell loss dependent upon the mechanical loading (p < 0.001). Axonal pathology shown with neurofilament immunostaining (SMI-31 and SMI-32) was observed in the subcortical white matter inferior to the injury site and in the ipsilateral internal capsule. No axonal injury was observed in the contralateral hemisphere or in any remote regions. Glial fibrillary acidic protein (GFAP) immunostaining revealed widespread reactive astrocytosis surrounding the necrotic region in the ipsilateral cortex. This analysis confirms that rapid mechanical deformation of the cortex induces focal contusions in the absence of primary damage to remote areas 3 days following injury. Although it is suggested that massive release of neurotoxic substances from a contusion may cause damage throughout the brain, these data emphasize the importance of combined injury mechanisms, e.g. mechanical distortion and excitatory amino acid mediated damage, that underlie the complex pathology patterns observed in traumatic brain injury.
Article
In vivo, tissue-level, mechanical thresholds for axonal injury were determined by comparing morphological injury and electrophysiological impairment to estimated tissue strain in an in vivo model of axonal injury. Axonal injury was produced by dynamically stretching the right optic nerve of an adult male guinea pig to one of seven levels of ocular displacement (Nlevel = 10; Ntotal = 70). Morphological injury was detected with neurofilament immunohistochemical staining (NF68, SM132). Simultaneously, functional injury was determined by the magnitude of the latency shift of the N35 peak of the visual evoked potentials (VEPs) recorded before and after stretch. A companion set of in situ experiments (Nlevel = 5) was used to determine the empirical relationship between the applied ocular displacement and the magnitude of optic nerve stretch. Logistic regression analysis, combined with sensitivity and specificity measures and receiver operating characteristic (ROC) curves were used to predict strain thresholds for axonal injury. From this analysis, we determined three Lagrangian strain-based thresholds for morphological damage to white matter. The liberal threshold, intended to minimize the detection of false positives, was a strain of 0.34, and the conservative threshold strain that minimized the false negative rate was 0.14. The optimal threshold strain criterion that balanced the specificity and sensitivity measures was 0.21. Similar comparisons for electrophysiological impairment produced liberal, conservative, and optimal strain thresholds of 0.28, 0.13, and 0.18, respectively. With these threshold data, it is now possible to predict more accurately the conditions that cause axonal injury in human white matter.
Article
The large strain mechanical properties of adult porcine gray and white matter brain tissues were measured in shear and confirmed in compression. Consistent with local neuroarchitecture, gray matter showed the least amount of anisotropy, and corpus callosum exhibited the greatest degree of anisotropy. Mean regional properties were significantly distinct, demonstrating that brain tissue is inhomogeneous. Fresh adult human brain tissue properties were slightly stiffer than adult porcine properties but considerably less stiff than the human autopsy data in the literature. Mixed porcine gray/white matter samples were obtained from animals at "infant" and "toddler" stages of neurological development, and shear properties compared to those in the adult. Only the infant properties were significantly different (stiffer) from the adult.
Article
Several different models of brain trauma are currently used and each simulates different aspects of the clinical condition and to varying degrees of accuracy. While numerous studies have characterized the cellular pathology after weight-drop or fluid percussion injury, detailed information on the histopathology that evolves after the controlled cortical impact model is incomplete. We have determined the spatiotemporal pathologies of neuronal, axonal, vascular, and macro- and microglial elements at 1, 4, 7, and 28 days after moderate controlled cortical impact injury. Neuronal injury identified by pyknotic perikarya and disrupted neurofilament-stained axonal profiles were evident by 1 day in ipsilateral cortex and hippocampus and at later times in the thalamus. glial fibrillary acidic protein-reactive astrocytes were more widespread, reaching a maximum immunointensity at 4 days across the ipsilateral hemisphere but declining to control levels thereafter. Microglia/macrophage-OX42 staining was initially restricted to the contusion site and then later to the thalamus, consistent with the pattern of neuronal injury. Increases in nestin immunoreactivity-a postulated marker of neural progenitor cells, and in NG2 proteoglycan-a marker of oligodendrocyte precursor cells, were detected by 1 day, reaching maximal immunointensity at 4-7 days after injury. Mean density and diameter of cortical microvessels was significantly reduced and increased respectively but only at the initial time points, suggesting that some degree of vascular remodeling takes place after injury. We discuss these results in light of recent evidence that suggests there may be some degree of endogenous repair after central nervous system injury.
Article
The goal of this study was to determine the tensile strength of cranial pia mater. Samples of isolated bovine cranial pia mater were subjected to quasistatic traction to evaluate its tensile strength. The experimental curves of physiological deformation that were obtained can be subdivided into three parts that represent different mechanical properties: the nonlinear initial part of the curve demonstrates increasing stiffness, followed by a quasilinear pattern of elastic behavior, and finally a negative relationship (slope) between force and elongation, which characterizes a progressive deterioration. These three steps precede final sample rupture. The stiffness of the pia mater was calculated for both the initial and the linear (elastic) parts of the mean curve. The initial part and the elastic part of the curve show a typical stiffness value of 0.024 N/mm and 0.19 N/mm, respectively. The maximal mean force and corresponding maximal deformation that were attained were 1.1 N and 0.19, respectively. Although very thin and apparently fragile, pia mater exhibits an unexpectedly high level of stiffness and should have a significant influence on total brain mechanical properties in response to loading.
Article
Brain responses from concussive impacts in National Football League football games were simulated by finite element analysis using a detailed anatomic model of the brain and head accelerations from laboratory reconstructions of game impacts. This study compares brain responses with physician determined signs and symptoms of concussion to investigate tissue-level injury mechanisms. The Wayne State University Head Injury Model (Version 2001) was used because it has fine anatomic detail of the cranium and brain with more than 300,000 elements. It has 15 different material properties for brain and surrounding tissues. The model includes viscoelastic gray and white brain matter, membranes, ventricles, cranium and facial bones, soft tissues, and slip interface conditions between the brain and dura. The cranium of the finite element model was loaded by translational and rotational accelerations measured in Hybrid III dummies from 28 laboratory reconstructions of NFL impacts involving 22 concussions. Brain responses were determined using a nonlinear, finite element code to simulate the large deformation response of white and gray matter. Strain responses occurring early (during impact) and mid-late (after impact) were compared with the signs and symptoms of concussion. Strain concentration "hot spots" migrate through the brain with time. In 9 of 22 concussions, the early strain "hot spots" occur in the temporal lobe adjacent to the impact and migrate to the far temporal lobe after head acceleration. In all cases, the largest strains occur later in the fornix, midbrain, and corpus callosum. They significantly correlated with removal from play, cognitive and memory problems, and loss of consciousness. Dizziness correlated with early strain in the orbital-frontal cortex and temporal lobe. The strain migration helps explain coup-contrecoup injuries. Finite element modeling showed the largest brain deformations occurred after the primary head acceleration. Midbrain strain correlated with memory and cognitive problems and removal from play after concussion. Concussion injuries happen during the rapid displacement and rotation of the cranium, after peak head acceleration and momentum transfer in helmet impacts.