Development of a Biofidelic Material Model for Brain Tissue

2011 ◽  
Author(s):  
Sandeep Kulathu ◽  
David L. Littlefield
Keyword(s):  
Brain Tissue ◽  
Grey Matter ◽  
Mechanical Response ◽  
Constitutive Models ◽  
Material Model ◽  
Small Sample ◽  
Material Models ◽  
Computational Mesh ◽  
Injury Mechanisms ◽  
The Brain

Computational simulations of brain injury mechanisms have advanced to a level of sophistication where in addition to capturing different anatomic regions, the computational mesh is capable of distinguishing white and grey matter in the brain. Brain tissue is typically modeled as an isotropic, viscoelastic material. Experiments have shown that the mechanical response of brain tissue to an external load varies depending on the location from which the tissue is harvested and also the direction of loading. Some researchers have developed anisotropic constitutive models by appealing to the composite material case wherein cylindrical axon fibers are immersed in a cellular matrix. Though such material models have been developed over a small sample, they have not been applied over the entire brain for simulation purposes.

Constitutive Modeling of Brain Tissue: Current Perspectives

2016 ◽  
Vol 68 (1) ◽  
Author(s):  
Rijk de Rooij ◽  
Ellen Kuhl
Keyword(s):  
Brain Tissue ◽  
Mechanical Response ◽  
Deformation Gradient ◽  
Constitutive Models ◽  
Time Dependent ◽  
Elastic Behavior ◽  
Integral Approach ◽  
Mechanical Stimuli ◽  
The Past ◽  
The Brain

Modeling the mechanical response of the brain has become increasingly important over the past decades. Although mechanical stimuli to the brain are small under physiological conditions, mechanics plays a significant role under pathological conditions including brain development, brain injury, and brain surgery. Well calibrated and validated constitutive models for brain tissue are essential to accurately simulate these phenomena. A variety of constitutive models have been proposed over the past three decades, but no general consensus on these models exists. Here, we provide a comprehensive and structured overview of state-of-the-art modeling of the brain tissue. We categorize the different features of existing models into time-independent, time-dependent, and history-dependent contributions. To model the time-independent, elastic behavior of the brain tissue, most existing models adopt a hyperelastic approach. To model the time-dependent response, most models either use a convolution integral approach or a multiplicative decomposition of the deformation gradient. We evaluate existing constitutive models by their physical motivation and their practical relevance. Our comparison suggests that the classical Ogden model is a well-suited phenomenological model to characterize the time-independent behavior of the brain tissue. However, no consensus exists for mechanistic, physics-based models, neither for the time-independent nor for the time-dependent response. We anticipate that this review will provide useful guidelines for selecting the appropriate constitutive model for a specific application and for refining, calibrating, and validating future models that will help us to better understand the mechanical behavior of the human brain.

Simulation of Brain Response to Noncontact Impacts Using Coupled Eulerian–Lagrangian Method

2020 ◽  
Vol 142 (5) ◽  
Author(s):  
Miao Na ◽  
Timothy J. Beavers ◽  
Abhijit Chandra ◽  
Sarah A. Bentil
Keyword(s):  
Brain Tissue ◽  
Mechanical Response ◽  
Brain Regions ◽  
Von Mises Stress ◽  
Fe Model ◽  
Brain Response ◽  
Fe Method ◽  
Angular Velocities ◽  
Von Mises ◽  
The Brain

Abstract Finite element (FE) method has been widely used for gaining insights into the mechanical response of brain tissue during impacts. In this study, a coupled Eulerian−Lagrangian (CEL) formulation is implemented in impact simulations of a head system to overcome the mesh distortion difficulties due to large deformation in the cerebrospinal fluid (CSF) region and provide a biofidelic model of the interaction between the brain and skull. The head system used in our FE model is constructed from the transverse section of the human brain, with CSF modeled by Eulerian elements. Spring connectors are applied to represent the pia-arachnoid connection between the brain and skull. Validations of the CEL formulation and the FE model are performed using the experimental results. The dynamic response of brain tissue under noncontact impacts and the brain regions susceptible to injury are evaluated based on the intracranial pressure (ICP), maximum principal strain (MPS), and von Mises stress. While tracking the critical MPS location on the brain, higher likelihood of contrecoup injury than coup injury is found when sudden brain−skull motion takes place. The accumulation effect of CSF in the ventricle system, under large relative brain−skull motion, is also identified. The FE results show that adding relative angular velocities, to the translational impact model, not only causes a diffuse high strain area, but also cause the temporal lobes to be susceptible to cerebral contusions since the protecting CSF is prone to be squeezed away at the temporal sites due to the head rotations.

scholarly journals The importance of intervertebral disc material model on the prediction of mechanical function of the cervical spine

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Amin Komeili ◽  
Akbar Rasoulian ◽  
Fatemeh Moghaddam ◽  
Marwan El-Rich ◽  
Le Ping Li
Keyword(s):  
Intervertebral Disc ◽  
Mechanical Response ◽  
Fluid Pressure ◽  
Material Model ◽  
Load Sharing ◽  
Disc Height ◽  
Loading Conditions ◽  
Material Models ◽  
Linear Elastic ◽  
Disc Material

Abstract Background Linear elastic, hyperelastic, and multiphasic material constitutive models are frequently used for spinal intervertebral disc simulations. While the characteristics of each model are known, their effect on spine mechanical response requires a careful investigation. The use of advanced material models may not be applicable when material constants are not available, model convergence is unlikely, and computational time is a concern. On the other hand, poor estimations of tissue’s mechanical response are likely if the spine model is oversimplified. In this study, discrepancies in load response introduced by material models will be investigated. Methods Three fiber-reinforced C2-C3 disc models were developed with linear elastic, hyperelastic, and biphasic behaviors. Three different loading modes were investigated: compression, flexion and extension in quasi-static and dynamic conditions. The deformed disc height, disc fluid pressure, range of motion, and stresses were compared. Results Results indicated that the intervertebral disc material model has a strong effect on load-sharing and disc height change when compression and flexion were applied. The predicted mechanical response of three models under extension had less discrepancy than its counterparts under flexion and compression. The fluid-solid interaction showed more relevance in dynamic than quasi-static loading conditions. The fiber-reinforced linear elastic and hyperelastic material models underestimated the load-sharing of the intervertebral disc annular collagen fibers. Conclusion This study confirmed the central role of the disc fluid pressure in spinal load-sharing and highlighted loading conditions where linear elastic and hyperelastic models predicted energy distribution different than that of the biphasic model.

Effect of Cerebral Vasculatures on the Mechanical Response of Brain Tissue: A Preliminary Study

2000 ◽  
Author(s):  
Kiyoshi Omori ◽  
Liying Zhang ◽  
King H. Yang ◽  
Albert I. King
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Brain Tissue ◽  
Mechanical Response ◽  
Clinical Symptoms ◽  
Anatomical Structure ◽  
Causal Mechanism ◽  
Injury Biomechanics ◽  
Preliminary Study ◽  
The Brain

Abstract Traumatic brain injury (TBI) constitutes a significant portion of all injuries occurring as a result of automotive, motorcycle and sports related injuries. Over the years, a large amount of literature has been devoted to an increased understanding of clinical symptoms, pathological evidence and injury biomechanics for such injuries. However, the precise causal mechanism, which accounts for complex mechanical interactions and responses in an anatomical structure as complex as the brain, is not fully understood.

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.

The Effect of Material Constitutive Models on Stress Wave Propagation Calculations

1978 ◽  
Vol 100 (1) ◽  
pp. 84-95 ◽  
Author(s):  
W. Herrmann ◽  
R. J. Lawrence
Keyword(s):  
Wave Propagation ◽  
Finite Difference ◽  
Stress Wave ◽  
Constitutive Models ◽  
Material Model ◽  
Infinite Medium ◽  
Stress Wave Propagation ◽  
Material Models ◽  
One Dimensional ◽  
Design Calculations

Material models which have been successfully used for describing experimental observations of stress wave propagation in metals, polymers, composites, and porous materials are used in a series of one-dimensional finite-difference calculations of stress pulses propagating in a semi-infinite medium. These calculations show the effect of the material model on pulse attenuation. Parametric variations indicate the sensitivity of the attenuation to the parameters of each model. A simple conceptual description based on the hysteretic energy loss experienced by the material in a loading-unloading cycle is used to explain the results. Relevance of the results to the prediction of damage in specific engineering design calculations is developed. The results and conceptual description should aid the stress analyst in assessing which effects to include in the material model used in specific multidimensional calculations.

scholarly journals Insights into the Microstructural Origin of Brain Viscoelasticity

2021 ◽  
Author(s):  
Nina Reiter ◽  
Biswaroop Roy ◽  
Friedrich Paulsen ◽  
Silvia Budday
Keyword(s):  
Brain Tissue ◽  
Computational Models ◽  
Mechanical Response ◽  
Constitutive Models ◽  
Brain Regions ◽  
Tissue Mechanics ◽  
Linear Functions ◽  
Model Parameters ◽  
Microstructural Parameters ◽  
Viscoelastic Constitutive Model

AbstractMechanical aspects play an important role in brain development, function, and disease. Therefore, continuum-mechanics-based computational models are a valuable tool to advance our understanding of mechanics-related physiological and pathological processes in the brain. Currently, mainly phenomenological material models are used to predict the behavior of brain tissue numerically. The model parameters often lack physical interpretation and only provide adequate estimates for brain regions which have a similar microstructure and age as those used for calibration. These issues can be overcome by establishing advanced constitutive models that are microstructurally motivated and account for regional heterogeneities through microstructural parameters.In this work, we perform simultaneous compressive mechanical loadings and microstructural analyses of porcine brain tissue to identify the microstructural mechanisms that underlie the macroscopic nonlinear and time-dependent mechanical response. Based on experimental insights into the link between macroscopic mechanics and cellular rearrangements, we propose a microstructure-informed finite viscoelastic constitutive model for brain tissue. We determine a relaxation time constant from cellular displacement curves and introduce hyperelastic model parameters as linear functions of the cell density, as determined through histological staining of the tested samples. The model is calibrated using a combination of cyclic loadings and stress relaxation experiments in compression. The presented considerations constitute an important step towards microstructure-based viscoelastic constitutive models for brain tissue, which may eventually allow us to capture regional material heterogeneities and predict how microstructural changes during development, aging, and disease affect macroscopic tissue mechanics.

Liquid Chromatography Analysis of Clozapine in Rat Brain Tissue, Using its Molecularly Imprinted Polymer after Administration of Toxic Dose of Drug and Lipid Emulsion Therapy

2019 ◽  
Vol 15 (3) ◽  
pp. 251-257
Author(s):  
Bahareh Sadat Yousefsani ◽  
Seyed Ahmad Mohajeri ◽  
Mohammad Moshiri ◽  
Hossein Hosseinzadeh
Keyword(s):  
Rat Brain ◽  
Brain Tissue ◽  
Molecularly Imprinted Polymer ◽  
Lipid Emulsion ◽  
Limit Of Detection ◽  
Imprinted Polymer ◽  
Toxic Dose ◽  
Molecularly Imprinted ◽  
The Brain ◽  
Rat Brain Tissue

Background:Molecularly imprinted polymers (MIPs) are synthetic polymers that have a selective site for a given analyte, or a group of structurally related compounds, that make them ideal polymers to be used in separation processes.Objective:An optimized molecularly imprinted polymer was selected and applied for selective extraction and analysis of clozapine in rat brain tissue.Methods:A molecularly imprinted solid-phase extraction (MISPE) method was developed for preconcentration and cleanup of clozapine in rat brain samples before HPLC-UV analysis. The extraction and analytical process was calibrated in the range of 0.025-100 ppm. Clozapine recovery in this MISPE process was calculated between 99.40 and 102.96%. The limit of detection (LOD) and the limit of quantification (LOQ) of the assay were 0.003 and 0.025 ppm, respectively. Intra-day precision values for clozapine concentrations of 0.125 and 0.025 ppm were 5.30 and 3.55%, whereas inter-day precision values of these concentrations were 9.23 and 6.15%, respectively. In this study, the effect of lipid emulsion infusion in reducing the brain concentration of drug was also evaluated.Results:The data indicated that calibrated method was successfully applied for the analysis of clozapine in the real rat brain samples after administration of a toxic dose to animal. Finally, the efficacy of lipid emulsion therapy in reducing the brain tissue concentration of clozapine after toxic administration of drug was determined.Conclusion:The proposed MISPE method could be applied in the extraction and preconcentration before HPLC-UV analysis of clozapine in rat brain tissue.

scholarly journals Safety profile of the transcription factor EB (TFEB)-based gene therapy through intracranial injection in mice

2020 ◽  
Vol 11 (1) ◽  
pp. 241-250
Author(s):  
Zhenyu Li ◽  
Guangqian Ding ◽  
Yudi Wang ◽  
Zelong Zheng ◽  
Jianping Lv
Keyword(s):  
Gene Therapy ◽  
Transcription Factor ◽  
Neurodegenerative Diseases ◽  
Brain Tissue ◽  
Inflammatory Responses ◽  
Tissue Samples ◽  
Protein Levels ◽  
Virus Serotype ◽  
Transcription Factor Eb ◽  
The Brain

AbstractTranscription factor EB (TFEB)-based gene therapy is a promising therapeutic strategy in treating neurodegenerative diseases by promoting autophagy/lysosome-mediated degradation and clearance of misfolded proteins that contribute to the pathogenesis of these diseases. However, recent findings have shown that TFEB has proinflammatory properties, raising the safety concerns about its clinical application. To investigate whether TFEB induces significant inflammatory responses in the brain, male C57BL/6 mice were injected with phosphate-buffered saline (PBS), adeno-associated virus serotype 8 (AAV8) vectors overexpressing mouse TFEB (pAAV8-CMV-mTFEB), or AAV8 vectors expressing green fluorescent proteins (GFPs) in the barrel cortex. The brain tissue samples were collected at 2 months after injection. Western blotting and immunofluorescence staining showed that mTFEB protein levels were significantly increased in the brain tissue samples of mice injected with mTFEB-overexpressing vectors compared with those injected with PBS or GFP-overexpressing vectors. pAAV8-CMV-mTFEB injection resulted in significant elevations in the mRNA and protein levels of lysosomal biogenesis indicators in the brain tissue samples. No significant changes were observed in the expressions of GFAP, Iba1, and proinflammation mediators in the pAAV8-CMV-mTFEB-injected brain compared with those in the control groups. Collectively, our results suggest that AAV8 successfully mediates mTFEB overexpression in the mouse brain without inducing apparent local inflammation, supporting the safety of TFEB-based gene therapy in treating neurodegenerative diseases.

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