Comparison of Brain Tissue Material Finite Element Models Based on Threshold for Traumatic Brain Injury

2016 ◽  
Author(s):  
Ashkan Eslaminejad ◽  
Hesam Sarvghad-Moghaddam ◽  
Asghar Rezaei ◽  
Mariusz Ziejewski ◽  
Ghodrat Karami
Keyword(s):  
Traumatic Brain Injury ◽  
Finite Element ◽  
Brain Injury ◽  
Dynamic Response ◽  
Brain Tissue ◽  
Head Model ◽  
Fe Modeling ◽  
Material Models ◽  
The Brain ◽  
Tissue Material

Blast traumatic brain injury (bTBI) may happen due to sudden blast and high-frequency loads. Due to the moral issues and the burden of experimental approaches, using computational methods such as finite element analysis (FEA) can be effective. Several finite element studies have focused on the effects of TBI to anticipate and understand the brain dynamic response. One of the most important factors in every FEA study of bTBI is the accurate modeling of brain tissue material properties. The main goal of this study is a comparison of different brain tissue constitutive models to understand the dynamic response of brain under an identical blast load. The multi-material FE modeling of the human head has several limitations such as its complexity and consequently high computational costs. Therefore, a spherical head model is modeled which suggests more straightforward observation/understanding of the FE modeling of skull (solid), CSF (fluid), and the brain tissue. Three different material models are considered for the brain tissue, namely hyperelastic, viscoelastic, and hyperviscoelastic. Brain dynamic responses are studied in terms of the head kinematics (linear acceleration), intracranial pressure (ICP), shear stress, and maximum mechanical strain. Our results showed that the hyperelastic model predicts larger ICP and shear than other constitutive brain tissue models. However, all material models predicted similar shear strain and head accelerations.

Simulation of Blast Induced Traumatic Brain Injury using Finite Element Method

2021 ◽  
Vol 13 (2) ◽  
Author(s):  
G. Krishnaveni ◽  
D. Dominic Xavier ◽  
R. Sarathkumar ◽  
G. Kavitha ◽  
M. Senbagan
Keyword(s):  
Traumatic Brain Injury ◽  
Finite Element ◽  
Brain Injury ◽  
Blast Wave ◽  
Ambient Pressure ◽  
Memory Loss ◽  
Human Head ◽  
Head Model ◽  
Stress Concentrations ◽  
The Brain

Because of increase in threat from militant groups and during war exposure to blast wave from improvised explosive devices, Traumatic Brain Injury (TBI), a signature injury is on rise worldwide. During blast, the biological system is exposed to a sudden blast over pressure which is several times higher than the ambient pressure causing the damage in the brain. The severity of TBI due to air blast may vary from brief change in mental status or consciousness (termed as mild) to extended period of unconsciousness or memory loss after injuries (termed as severe). The blast wave induced impact on head propagates as shock wave with the broad spectrum of frequencies and stress concentrations in the brain. The primary blast TBI is directly induced by pressure differentials across the skull/fluid/soft tissue interfaces and is further reinforced by the reflected stress waves within the cranial cavity, leading to stress concentrations in certain regions of the brain. In this paper, an attempt has been made to study the behaviour of a human brain model subjected to blast wave based on finite element model using LSDYNA code. The parts of a typical human head such as skull, scalp, CSF, brain are modelled using finite element with properties assumed based on available literature. The model is subjected to blast from frontal lobe, occipital lobe, temporal lobe of the brain. The interaction of the blast wave with the head and subsequent transformation of various forms of shock energy internally have been demonstrated in the human head model. The brain internal pressure levels and the shear stress distribution in the various lobes of the brain such as frontal, parietal, temporal and occipital are determined and presented.

scholarly journals Effect of Xenon Treatment on Gene Expression in Brain Tissue after Traumatic Brain Injury in Rats

2021 ◽  
Vol 11 (7) ◽  
pp. 889
Author(s):  
Anton D. Filev ◽  
Denis N. Silachev ◽  
Ivan A. Ryzhkov ◽  
Konstantin N. Lapin ◽  
Anastasiya S. Babkina ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Brain Tissue ◽  
Target Genes ◽  
Neural Function ◽  
Stress Genes ◽  
Expression Of Genes ◽  
Delayed Recovery ◽  
The Brain ◽  
Lower Expression

The overactivation of inflammatory pathways and/or a deficiency of neuroplasticity may result in the delayed recovery of neural function in traumatic brain injury (TBI). A promising approach to protecting the brain tissue in TBI is xenon (Xe) treatment. However, xenon’s mechanisms of action remain poorly clarified. In this study, the early-onset expression of 91 target genes was investigated in the damaged and in the contralateral brain areas (sensorimotor cortex region) 6 and 24 h after injury in a TBI rat model. The expression of genes involved in inflammation, oxidation, antioxidation, neurogenesis and neuroplasticity, apoptosis, DNA repair, autophagy, and mitophagy was assessed. The animals inhaled a gas mixture containing xenon and oxygen (ϕXe = 70%; ϕO2 25–30% 60 min) 15–30 min after TBI. The data showed that, in the contralateral area, xenon treatment induced the expression of stress genes (Irf1, Hmox1, S100A8, and S100A9). In the damaged area, a trend towards lower expression of the inflammatory gene Irf1 was observed. Thus, our results suggest that xenon exerts a mild stressor effect in healthy brain tissue and has a tendency to decrease the inflammation following damage, which might contribute to reducing the damage and activating the early compensatory processes in the brain post-TBI.

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

2019 ◽  
Vol 19 (3) ◽  
pp. 1109-1130 ◽  
Author(s):  
Marzieh Hajiaghamemar ◽  
Taotao Wu ◽  
Matthew B. Panzer ◽  
Susan S. Margulies
Keyword(s):  
Traumatic Brain Injury ◽  
Finite Element ◽  
Brain Injury ◽  
Strain Rate ◽  
Brain Tissue ◽  
Brain Injuries ◽  
Characteristic Curve ◽  
Strain And Strain Rate

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

scholarly journals Decompressive craniectomy of post-traumatic brain injury: an in silico modelling approach for intracranial hypertension management

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Chryso Lambride ◽  
Nicolas Christodoulou ◽  
Anna Michail ◽  
Vasileios Vavourakis ◽  
Triantafyllos Stylianopoulos
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Intracranial Pressure ◽  
Intracranial Hypertension ◽  
Brain Tissue ◽  
Decompressive Craniectomy ◽  
In Silico ◽  
Pressure Loading ◽  
Post Traumatic ◽  
The Brain

Abstract Traumatic brain injury (TBI) causes brain edema that induces increased intracranial pressure and decreased cerebral perfusion. Decompressive craniectomy has been recommended as a surgical procedure for the management of swollen brain and intracranial hypertension. Proper location and size of a decompressive craniectomy, however, remain controversial and no clinical guidelines are available. Mathematical and computational (in silico) models can predict the optimum geometric conditions and provide insights for the brain mechanical response following a decompressive craniectomy. In this work, we present a finite element model of post-traumatic brain injury and decompressive craniectomy that incorporates a biphasic, nonlinear biomechanical model of the brain. A homogenous pressure is applied in the brain to represent the intracranial pressure loading caused by the tissue swelling and the models calculate the deformations and stresses in the brain as well as the herniated volume of the brain tissue that exits the skull following craniectomy. Simulations for different craniectomy geometries (unilateral, bifrontal and bifrontal with midline bar) and sizes are employed to identify optimal clinical conditions of decompressive craniectomy. The reported results for the herniated volume of the brain tissue as a function of the intracranial pressure loading under a specific geometry and size of craniectomy are exceptionally relevant for decompressive craniectomy planning.

The Parametric Studies of Brain Materials in the Analysis of Head Impact

2006 ◽  
Author(s):  
Dalong Li ◽  
Mariusz Ziejewski ◽  
Ghodrat Karami
Keyword(s):  
Finite Element ◽  
Dynamic Response ◽  
Dynamic Behavior ◽  
Material Properties ◽  
Material Behavior ◽  
Material Models ◽  
Material Parameters ◽  
Multiple Materials ◽  
The Brain ◽  
Brain Tissues

Crash analysis and head injury biomechanics are very important fields in biomedical research due to the devastating consequences of traumatic brain injuries (TBI). Complex geometry and constitutive models of multiple materials can be combined with the loading conditions in finite element head model to study the dynamic behavior of brain and the TBI. In such a modeling, the proper regional material properties of brain tissues are important. Brain tissues material properties have not been finally determined by experiments, and large variations in the test data still exist and the data is very much situation-dependent. Therefore, parametric analysis should be performed to study the relationship between the material properties and the brain response. The main purpose of presenting this paper is to identify the influence of material constitutive properties on brain impact response, to search for an improved material model and to arrive at a better correlation between the finite element model and the cadaver tests data. In this paper a 3-D nonlinear finite element method will be used to study the dynamic response of the human head under dynamic loading. The finite element formulation includes detailed model of the skull, brain, cerebral-spinal fluid (CSF), dura mater, pia mater, falx and tentorium membranes. The brain is modeled as linear viscoelastic material, whereas linear elastic material behavior is assumed for all the other tissue components. The proper contact and compatibility conditions between different components have been implemented in the modeling procedure. The results for the direct frontal impacts will be shown for three groups of material parameters. The parametrical analysis of tissue material models allows to examines the accuracy of three different set of material parameters for brain in a comparison with the prediction of the head dynamic response of Nahum's human cadaver direct impact experiment. Three sets of suggested material parameters are examined. It is concluded that although all three groups of material models will follow the dynamic behavior of the head and brain behavior, but the parametric data considered in this paper have a closer resemblance to the experimental behavior.

scholarly journals Analysis of the Histopathology, TNF-α of Microglia Cells Expression, NRG-1/erbB Oligodendrocyte, and Ki67/Apoptosis of Dentate Gyrus Rattus novergicus Brain After Acute Traumatic Brain Injury

2017 ◽  
Vol 6 (1) ◽  
pp. 20
Author(s):  
Wibi Riawan ◽  
Putri Fitri Alfiantya ◽  
Oktavia Rahayu Adianingsih ◽  
Zulkarnaen Zulkarnaen ◽  
Alif Fariz Jazmi ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Dentate Gyrus ◽  
Brain Tissue ◽  
Microscopic Observation ◽  
Pyramidal Cells ◽  
Adult Brain ◽  
Sprague Dawley ◽  
Tnf Α ◽  
The Brain

Head trauma or traumatic brain injury (TBI) gives most serious impact on the central nervous system. Several experimental models have been established to mimic different pathogenesis characteristics of TBI. The purpose of this study was to determine whether there is evidence of hystopathological lesions in the brain tissue after Marmorou TBI models. This study uses Rattus norvegicus Sprague Dawley strain. Macroscopic and microscopic observations on the brain tissue were done. Macroscopic lesions were observed in the brain. Microscopic observation was performed with Haematoxylin-Eosin (HE) staining and immunohistochemistry on the distribution of microglia cells and pyramidal cells in the cortex. Meanwhile, the distribution of NRG-1/ErbB, proliferation, and apoptosis were observed in the hippocampus. The results of macroscopic observation showed that there were wounds caused by falling loads and vasodilatation. On microscopic observation, the TBI group showed an increase in neutrophils distribution and distribution of activated microglia to produce TNF-α, and decrease in the number of cortical pyramidal cells significantly. The distribution of NRG-1 tended to decrease after exposure of TBI and had no effect on its receptor, erbB. Exposure of TBI appears to lower the activity of neuronal cells proliferation in dentate gyrus (DG) area and significantly increase the number of apoptotic cells. Marmarou model is a physiological model of TBI that spontaneously occurs following a trauma to the head, for example trauma due to an accident. This data can be used as a preliminary data of inflammation and tissue regeneration of disrupted adult brain. Therefore, this research could be used as the basis in the studies of therapeutic agents in the process of neurogenesis of brain cells.Keywords: traumatic brain injury, ERG-1/ErbB, dentate gyrus, Ki67, TNF-a, microglia

A Finite Element Model for Estimating Axonal Damage in Traumatic Brain Injury

2012 ◽  
Author(s):  
Rika M. Wright ◽  
K. T. Ramesh
Keyword(s):  
Traumatic Brain Injury ◽  
Finite Element ◽  
Brain Injury ◽  
White Matter ◽  
Finite Element Model ◽  
Axonal Injury ◽  
Diffuse Axonal Injury ◽  
Element Model ◽  
Cellular Level ◽  
The Brain

There has been an ongoing effort to reduce the occurrence of sports-related traumatic brain injury. These injuries are caused by an impact to the head and often lead to the damage of neural axons in the brain. This type of damage is classified as diffuse axonal injury (DAI) or traumatic axonal injury (TAI) [1]. One of the difficulties in studying the progression of axonal injury is that the structural signature of DAI cannot be readily visualized with conventional medical imaging modalities since the damage occurs at the cellular level [2]. This also makes the injury difficult to diagnose. Many researchers have turned to finite element (FE) models to study the development of diffuse axonal injury. FE models provide a means for observing the mechanical process of injury development from the loads to the head at the macroscale to the damage that results at the cellular level. However, for a finite element model to be a viable tool for studying DAI, the model must be able to accurately represent the behavior of the brain tissue, and it must be able to accurately predict injury. In this work, we address both of these issues in an effort to improve the material models and injury criteria used in current FE models of TBI. We represent the white matter with an anisotropic, hyper-viscoelastic constitutive model, incorporate the microstructure of the white matter through the use of diffusion tensor imaging (DTI), and estimate injury using an axonal strain injury (ASI) criterion (Figure 1). We also develop a novel method to quantify the degree of axonal damage in the fiber tracts of the brain.

scholarly journals Mitochondrial-Protective Effects of R-Phenibut after Experimental Traumatic Brain Injury

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Einars Kupats ◽  
Gundega Stelfa ◽  
Baiba Zvejniece ◽  
Solveiga Grinberga ◽  
Edijs Vavers ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Brain Tissue ◽  
Aminobutyric Acid ◽  
Drug Candidate ◽  
H2o2 Production ◽  
Therapeutic Effects ◽  
Protective Effects ◽  
The Impact ◽  
The Brain

Altered neuronal Ca2+ homeostasis and mitochondrial dysfunction play a central role in the pathogenesis of traumatic brain injury (TBI). R-Phenibut ((3R)-phenyl-4-aminobutyric acid) is an antagonist of the α2δ subunit of voltage-dependent calcium channels (VDCC) and an agonist of gamma-aminobutyric acid B (GABA-B) receptors. The aim of this study was to evaluate the potential therapeutic effects of R-phenibut following the lateral fluid percussion injury (latFPI) model of TBI in mice and the impact of R- and S-phenibut on mitochondrial functionality in vitro. By determining the bioavailability of R-phenibut in the mouse brain tissue and plasma, we found that R-phenibut (50 mg/kg) reached the brain tissue 15 min after intraperitoneal (i.p.) and peroral (p.o.) injections. The maximal concentration of R-phenibut in the brain tissues was 0.6 μg/g and 0.2 μg/g tissue after i.p. and p.o. administration, respectively. Male Swiss-Webster mice received i.p. injections of R-phenibut at doses of 10 or 50 mg/kg 2 h after TBI and then once daily for 7 days. R-Phenibut treatment at the dose of 50 mg/kg significantly ameliorated functional deficits after TBI on postinjury days 1, 4, and 7. Seven days after TBI, the number of Nissl-stained dark neurons (N-DNs) and interleukin-1beta (IL-1β) expression in the cerebral neocortex in the area of cortical impact were reduced. Moreover, the addition of R- and S-phenibut at a concentration of 0.5 μg/ml inhibited calcium-induced mitochondrial swelling in the brain homogenate and prevented anoxia-reoxygenation-induced increases in mitochondrial H2O2 production and the H2O2/O ratio. Taken together, these results suggest that R-phenibut could serve as a neuroprotective agent and promising drug candidate for treating TBI.

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