Effect of inter-species, gender, and breeding on the mechanical behavior of brain tissue

Brain Material Properties and Integration of Arachnoid Complex for Biofidelic Impact Response for Human Head Finite Element Model

Finite element head models offer great potential to study brain-related injuries; however, at present may be limited by geometric and material property simplifications required for continuum-level human body models. Specifically, the mechanical properties of the brain tissues are often represented with simplified linear viscoelastic models, or the material properties have been optimized to specific impact cases. In addition, anatomical structures such as the arachnoid complex have been omitted or implemented in a simple lumped manner. Recent material test data for four brain regions at three strain rates in three modes of loading (tension, compression, and shear) was used to fit material parameters for a hyper-viscoelastic constitutive model. The material model was implemented in a contemporary detailed head finite element model. A detailed representation of the arachnoid trabeculae was implemented with mechanical properties based on experimental data. The enhanced head model was assessed by re-creating 11 ex vivo head impact scenarios and comparing the simulation results with experimental data. The hyper-viscoelastic model faithfully captured mechanical properties of the brain tissue in three modes of loading and multiple strain rates. The enhanced head model showed a high level of biofidelity in all re-created impacts in part due to the improved brain-skull interface associated with implementation of the arachnoid trabeculae. The enhanced head model provides an improved predictive capability with material properties based on tissue level data and is positioned to investigate head injury and tissue damage in the future.

Correlation between gyral size, brain size, and head impact risk across mammalian species

A study on primates has established that gyral size is largely independent of overall brain size. Building on this-and other research suggesting that brain gyrification may mitigate the effects of head impacts-our study aims to explore potential correlations between gyral size and the risk of head impact across a diverse range of mammalian species. Our findings corroborate the idea that gyral sizes are largely independent of brain sizes, especially among species with larger brains, thus extending this observation beyond primates. Preliminary evidence also suggests a correlation between an animal's gyral size and its lifestyle, particularly in terms of head-impact risk. For instance, goats, known for their headbutting behaviors, exhibit smaller gyral sizes. In contrast, species such as manatees and dugongs, which typically face lower risks of head impact, have lissencephalic brains. Additionally, we explore mechanisms that may explain how narrower gyral sizes could offer protective advantages against head impact. Finally, we discuss a possible trade-off associated with gyrencephaly.

Quasi-Static Mechanical Properties and Continuum Constitutive Model of the Thyroid Gland

The purpose of this study is to obtain the digital twin parameters of the thyroid gland and to build a constitutional model of the thyroid gland based on continuum mechanics, which will lay the foundation for the establishment of a surgical training system for the thyroid surgery robot and the development of the digital twin of the thyroid gland. First, thyroid parenchyma was obtained from fresh porcine thyroid tissue and subjected to quasi-static unconfined uniaxial compression tests using a biomechanical test platform with two strain rates (0.005 s^-1 and 0.05 s^-1) and two loading orientations (perpendicular to the thyroid surface and parallel to the thyroid surface). Based on this, a tensile thyroid model was established to simulate the stretching process by using the finite element method. The thyroid stretching test was carried out under the same parameters to verify the validity of the hyperelastic constitutive model. The quasi-static mechanical property parameters of the thyroid tissue were obtained by a quasi-static unconstrained uniaxial compression test, and a constitutional model that can describe the quasi-static mechanical properties of thyroid tissue was proposed based on the principle of continuum media mechanics, which is of great value for the establishment of a surgical training system for the head and neck surgery robot and for the development of the thyroid digital twin.

Correlating the microstructural architecture and macrostructural behaviour of the brain

The computational simulation of pathological conditions and surgical procedures, for example the removal of cancerous tissue, can contribute crucially to the future of medicine. Especially for brain surgery, these methods can be important, as the ultra-soft tissue controls vital functions of the body. However, the microstructural interactions and their effects on macroscopic material properties remain incompletely understood. Therefore, we investigated the mechanical behaviour of brain tissue under three different deformation modes, axial tension, compression, and semi-confined compression, in different anatomical regions, and for varying axon orientation. In addition, we characterised the underlying microstructure in terms of myelin, cells, glial cells and neuron area fraction, and density. The correlation of these quantities with the material parameters of the anisotropic Ogden model reveals a decrease in shear modulus with increasing myelin area fraction. Strikingly, the tensile shear modulus correlates positively with cell and neuronal area fraction (Spearman's correlation coefficient of r_s=0.40 and r_s=0.33), whereas the compressive shear modulus decreases with increasing glial cell area (r_s=-0.33). Our study finds that tissue non-linearity significantly depends on the myelin area fraction (r_s=0.47), cell density (r_s=0.41) and glial cell area (r_s=0.49). Our results provide an important step towards understanding the micromechanical load transfer that leads to the non-linear macromechanical behaviour of the brain. STATEMENT OF SIGNIFICANCE: Within this article, we investigate the mechanical behaviour of brain tissue under three different deformation modes, in different anatomical regions, and for varying axon orientation. Further, we characterise the underlying microstructure in terms of various constituents. The correlation of these quantities with the material parameters of the anisotropic Ogden model reveals a decrease in shear modulus with increasing myelin area fraction. Strikingly, the tensile shear modulus correlates positively with cell and neuronal area fraction, whereas the compressive shear modulus decreases with increasing glial cell area. Our study finds that tissue non-linearity significantly depends on the myelin area fraction, cell density, and glial cell area. Our results provide an important step towards understanding the micromechanical load transfer that leads to the non-linear macromechanical behaviour of the brain.

Tissue-Scale Biomechanical Testing of Brain Tissue for the Calibration of Nonlinear Material Models

Brain tissue is one of the most complex and softest tissues in the human body. Due to its ultrasoft and biphasic nature, it is difficult to control the deformation state during biomechanical testing and to quantify the highly nonlinear, time-dependent tissue response. In numerous experimental studies that have investigated the mechanical properties of brain tissue over the last decades, stiffness values have varied significantly. One reason for the observed discrepancies is the lack of standardized testing protocols and corresponding data analyses. The tissue properties have been tested on different length and time scales depending on the testing technique, and the corresponding data have been analyzed based on simplifying assumptions. In this review, we highlight the advantage of using nonlinear continuum mechanics based modeling and finite element simulations to carefully design experimental setups and protocols as well as to comprehensively analyze the corresponding experimental data. We review testing techniques and protocols that have been used to calibrate material model parameters and discuss artifacts that might falsify the measured properties. The aim of this work is to provide standardized procedures to reliably quantify the mechanical properties of brain tissue and to more accurately calibrate appropriate constitutive models for computational simulations of brain development, injury and disease. Computational models can not only be used to predictively understand brain tissue behavior, but can also serve as valuable tools to assist diagnosis and treatment of diseases or to plan neurosurgical procedures. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC.

Unconventional animal models for traumatic brain injury and chronic traumatic encephalopathy

Traumatic brain injury (TBI) is one of the main causes of death worldwide. It is a complex injury that influences cellular physiology, causes neuronal cell death, and affects molecular pathways in the brain. This in turn can result in sensory, motor, and behavioral alterations that deeply impact the quality of life. Repetitive mild TBI can progress into chronic traumatic encephalopathy (CTE), a neurodegenerative condition linked to severe behavioral changes. While current animal models of TBI and CTE such as rodents, are useful to explore affected pathways, clinical findings therein have rarely translated into clinical applications, possibly because of the many morphofunctional differences between the model animals and humans. It is therefore important to complement these studies with alternative animal models that may better replicate the individuality of human TBI. Comparative studies in animals with naturally evolved brain protection such as bighorn sheep, woodpeckers, and whales, may provide preventive applications in humans. The advantages of an in-depth study of these unconventional animals are threefold. First, to increase knowledge of the often-understudied species in question; second, to improve common animal models based on the study of their extreme counterparts; and finally, to tap into a source of biological inspiration for comparative studies and translational applications in humans.

Dynamic mechanical characterization and viscoelastic modeling of bovine brain tissue

Brain tissue is vulnerable and sensitive, predisposed to potential damage under various conditions of mechanical loading. Although its material properties have been investigated extensively, the frequency-dependent viscoelastic characterization is currently limited. Computational models can provide a non-invasive method by which to analyze brain injuries and predict the mechanical response of the tissue. The brain injuries are expected to be induced by dynamic loading, mostly in compression and measurement of dynamic viscoelastic properties are essential to improve the accuracy and variety of finite element simulations on brain tissue. Thus, the aim of this study was to investigate the compressive frequency-dependent properties of brain tissue and present a mathematical model in the frequency domain to capture the tissue behavior based on experimental results. Bovine brain specimens, obtained from four locations of corona radiata, corpus callosum, basal ganglia and cortex, were tested under compression using dynamic mechanical analysis over a range of frequencies between 0.5 and 35 Hz to characterize the regional and directional response of the tissue. The compressive dynamic properties of bovine brain tissue were heterogenous for regions but not sensitive to orientation showing frequency dependent statistical results, with viscoelastic properties increasing with frequency. The mean storage and loss modulus were found to be 12.41 kPa and 5.54 kPa, respectively. The material parameters were obtained using the linear viscoelastic model in the frequency domain and the numeric simulation can capture the compressive mechanical behavior of bovine brain tissue across a range of frequencies. The frequency-dependent viscoelastic characterization of brain tissue will improve the fidelity of the computational models of the head and provide essential information to the prediction and analysis of brain injuries in clinical treatments.

Mechanical regulation of oligodendrocyte biology

Oligodendrocytes (OL) are a subset of glial cells in the central nervous system (CNS) comprising the brain and spinal cord. The CNS environment is defined by complex biochemical and biophysical cues during development and response to injury or disease. In the last decade, significant progress has been made in understanding some of the key biophysical factors in the CNS that modulate OL biology, including their key role in myelination of neurons. Taken together, those studies offer translational implications for remyelination therapies, pharmacological research, identification of novel drug targets, and improvements in methods to generate human oligodendrocyte progenitor cells (OPCs) and OLs from donor stem cells in vitro. This review summarizes current knowledge of how various physical and mechanical cues affect OL biology and its implications for disease, therapeutic approaches, and generation of human OPCs and OLs.

Data mining the effects of testing conditions and specimen properties on brain biomechanics

Traumatic brain injury is highly prevalent in the United States. However, despite its frequency and significance, there is little understanding of how the brain responds during injurious loading. A confounding problem is that because testing conditions vary between assessment methods, brain biomechanics cannot be fully understood. Data mining techniques, which are commonly used to determine patterns in large datasets, were applied to discover how changes in testing conditions affect the mechanical response of the brain. Data at various strain rates were collected from published literature and sorted into datasets based on strain rate and tension vs. compression. Self-organizing maps were used to conduct a sensitivity analysis to rank the testing condition parameters by importance. Fuzzy C-means clustering was applied to determine if there were any patterns in the data. The parameter rankings and clustering for each dataset varied, indicating that the strain rate and type of deformation influence the role of these parameters in the datasets.

Identification of the visco-hyperelastic properties of brain white matter based on the combination of inverse method and experiment

To fully understand the brain injury mechanism and develop effective protective approaches, an accurate constitutive model of brain tissue is firstly required. Generally, the brain tissue is regarded as a kind of viscoelastic material and is simply used in the simulation of brain injury. In fact, the brain tissue has the behavior of the visco-hyperelastic property. Therefore, this paper presents an effective computational inverse method to determine the material parameters of visco-hyperelastic constitutive model of brain white matter through compression experiments. First, with the help of 3D hand scanner, 3D geometries of brain white matter specimens are obtained to make it possible to establish the accurate simulation models of the specific specimens. Then, the global sensitivity analysis is adopted to evaluate the importance of the material parameters and further determine the parameters which may be identified. Subsequently, based on the genetic algorithm, the optimal material parameters of brain white matter can be identified by minimizing the match error between the experimental and simulated responses. Finally, by comparing the experiment and simulation results on the other specific specimen, and the simulation results with the material parameters from the references, respectively, the accuracy and reliability of the constitutive model parameters of brain white matter are demonstrated. Graphical abstract The main flowchart of the computational inverse technique for determining the material parameters of specimen-specific on brain white matter. Generalization: Combining the computational inverse method and unconfined uniaxial compression experiment of the specific specimen, an effective identification method is presented to accurately determine the hyperelastic and viscoelastic parameters of brain white matter in this paper.

Sex-related responses after traumatic brain injury: Considerations for preclinical modeling

Traumatic brain injury (TBI) has historically been viewed as a primarily male problem, since men are more likely to experience a TBI because of more frequent participation in activities that increase risk of head injuries. This male bias is also reflected in preclinical research where mostly male animals have been used in basic and translational science. However, with an aging population in which TBI incidence is increasingly sex-independent due to falls, and increasing female participation in high-risk activities, the attention to potential sex differences in TBI responses and outcomes will become more important. These considerations are especially relevant in designing preclinical animal models of TBI that are more predictive of human responses and outcomes. This review characterizes sex differences following TBI with a special emphasis on the contribution of the female sex hormones, progesterone and estrogen, to these differences. This information is potentially important in developing and customizing TBI treatments.

Compressive mechanical characterization of non-human primate spinal cord white matter

The goal of developing computational models of spinal cord injury (SCI) is to better understand the human injury condition. However, finite element models of human SCI have used rodent spinal cord tissue properties due to a lack of experimental data. Central nervous system tissues in non human primates (NHP) closely resemble that of humans and therefore, it is expected that material constitutive models obtained from NHPs will increase the fidelity and the accuracy of human SCI models. Human SCI most often results from compressive loading and spinal cord white matter properties affect FE predicted patterns of injury; therefore, the objectives of this study were to characterize the unconfined compressive response of NHP spinal cord white matter and present an experimentally derived, finite element tractable constitutive model for the tissue. Cervical spinal cords were harvested from nine male adult NHPs (Macaca mulatta). White matter biopsy samples (3 mm in diameter) were taken from both lateral columns of the spinal cord and were divided into four strain rate groups for unconfined dynamic compression and stress relaxation (post-mortem <1-hour). The NHP spinal cord white matter compressive response was sensitive to strain rate and showed substantial stress relaxation confirming the viscoelastic behavior of the material. An Ogden 1st order model best captured the non-linear behavior of NHP white matter in a quasi-linear viscoelastic material model with 4-term Prony series. This study is the first to characterize NHP spinal cord white matter at high (>10/sec) strain rates typical of traumatic injury. The finite element derived material constitutive model of this study will increase the fidelity of SCI computational models and provide important insights for transferring pre-clinical findings to clinical treatments.

STATEMENT OF SIGNIFICANCE

Spinal cord injury (SCI) finite element (FE) models provide an important tool to bridge the gap between animal studies and human injury, assess injury prevention technologies (e.g. helmets, seatbelts), and provide insight into the mechanisms of injury. Although, FE model outcomes depend on the assumed material constitutive model, there is limited experimental data for fresh spinal cords and all was obtained from rodent, porcine or bovine tissues. Central nervous system tissues in non human primates (NHP) more closely resemble humans. This study characterizes fresh NHP spinal cord material properties at high strains rates and large deformations typical of SCI for the first time. A constitutive model was defined that can be readily implemented in finite strain FE analysis of SCI.

Chameleon-like elastomers with molecularly encoded strain-adaptive stiffening and coloration

Active camouflage is widely recognized as a soft-tissue feature, and yet the ability to integrate adaptive coloration and tissuelike mechanical properties into synthetic materials remains elusive. We provide a solution to this problem by uniting these functions in moldable elastomers through the self-assembly of linear-bottlebrush-linear triblock copolymers. Microphase separation of the architecturally distinct blocks results in physically cross-linked networks that display vibrant color, extreme softness, and intense strain stiffening on par with that of skin tissue. Each of these functional properties is regulated by the structure of one macromolecule, without the need for chemical cross-linking or additives. These materials remain stable under conditions characteristic of internal bodily environments and under ambient conditions, neither swelling in bodily fluids nor drying when exposed to air.

Effect of in vitro storage duration on measured mechanical properties of brain tissue

Accurate characterization of the mechanical properties of brain tissue is essential for understanding the mechanisms of traumatic brain injuries and developing protective gears or facilities. However, how storage conditions might affect the mechanical properties of brain tissue remains unclear. The objective of this study is to investigate the effect of in vitro storage duration on the mechanical performance of brain tissue since measurements are usually carried out in vitro. Differential Scanning Calorimetry (DSC) measurements and uniaxial compression mechanical experiments are carried out. The results indicate that, for brain tissue stored at 1 °C without any liquid medium, the bio-molecular interactions and the mechanical strength of both white and grey matter deteriorate with prolonged storage duration. Transmission Electron Microscopy (TEM) results reveal the degeneration of myelin sheaths and the vacuolization of cristae with prolonged storage duration, suggesting that the in vitro storage duration should be carefully controlled. The findings from this study might facilitate the development of guidelines and standards for the in vitro storage of brain tissue.

An empirical measure of nonlinear strain for soft tissue indentation

Indentation is a primary tool in the investigation of the mechanical properties of very soft tissue such as the brain. However, the usual material characterization protocols are not applicable because the resulting deformation is inhomogeneous, with even the identification of the amount of strain ambiguous and uncertain. Focusing on spherical indentation only, a standard is needed to quantify the amount of strain in terms of the probe radius and displacement so that different indentation experiments can be compared and contrasted. It is shown here that the minimum axial value of the Eulerian logarithmic strain tensor has many desirable properties of such a standard, such as invariance under the choice of material model, and experimental conditions for a given probe displacement. The disadvantage of this measure is that sophisticated finite element techniques need to be used in its determination. An empirical relation is obtained between this strain and the probe radius and displacement to circumvent this problem, and it is shown that this relationship is an excellent predictor of the strain measure. Two essential features of this empirical measure for nonlinear strains are that the exact strain measure for the linear theory is recovered on restriction to infinitesimal deformations and that the simulations use models based on reliable and accurate indentation data obtained from freshly harvested murine brains using a bespoke micro-indentation device.

Region and species dependent mechanical properties of adolescent and young adult brain tissue

Traumatic brain injuries, the leading cause of death and disability in children and young adults, are the result of a rapid acceleration or impact of the head. In recent years, a global effort to better understand the biomechanics of TBI has been undertaken, with many laboratories creating detailed computational models of the head and brain. For these models to produce realistic results they require accurate regional constitutive data for brain tissue. However, there are large differences in the mechanical properties reported in the literature. These differences are likely due to experimental parameters such as specimen age, brain region, species, test protocols, and fiber direction which are often not reported. Furthermore, there is a dearth of reported viscoelastic properties for brain tissue at large-strain and high rates. Mouse, rat, and pig brains are impacted at 10/s to a strain of ~36% using a custom-built micro-indenter with a 125 μm radius. It is shown that the resultant mechanical properties are dependent on specimen-age, species, and region, under identical experimental parameters.

Protection of cortex by overlying meninges tissue during dynamic indentation of the adolescent brain

Traumatic brain injury (TBI) has become a recent focus of biomedical research with a growing international effort targeting material characterization of brain tissue and simulations of trauma using computer models of the head and brain to try to elucidate the mechanisms and pathogenesis of TBI. The meninges, a collagenous protective tri-layer, which encloses the entire brain and spinal cord has been largely overlooked in these material characterization studies. This has resulted in a lack of accurate constitutive data for the cranial meninges, particularly under dynamic conditions such as those experienced during head impacts. The work presented here addresses this lack of data by providing for the first time, in situ large deformation material properties of the porcine dura-arachnoid mater composite under dynamic indentation. It is demonstrated that this tissue is substantially stiffer (shear modulus, μ=19.10±8.55kPa) and relaxes at a slower rate (τ₁=0.034±0.008s, τ₂=0.336±0.077s) than the underlying brain tissue (μ=6.97±2.26kPa, τ₁=0.021±0.007s, τ₂=0.199±0.036s), reducing the magnitudes of stress by 250% and 65% for strains that arise during indentation-type deformations in adolescent brains.

STATEMENT OF SIGNIFICANCE

We present the first mechanical analysis of the protective capacity of the cranial meninges using in situ micro-indentation techniques. Force-relaxation tests are performed on in situ meninges and cortex tissue, under large strain dynamic micro-indentation. A quasi-linear viscoelastic model is used subsequently, providing time-dependent mechanical properties of these neural tissues under loading conditions comparable to what is experienced in TBI. The reported data highlights the large differences in mechanical properties between these two tissues. Finite element simulations of the indentation experiments are also performed to investigate the protective capacity of the meninges. These simulations show that the meninges protect the underlying brain tissue by reducing the overall magnitude of stress by 250% and up to 65% for strains.

A viscoelastic analysis of the P56 mouse brain under large-deformation dynamic indentation

The brain is a complex organ made up of many different functional and structural regions consisting of different types of cells such as neurons and glia, as well as complex anatomical geometries. It is hypothesized that the different regions of the brain exhibit significantly different mechanical properties which may be attributed to the diversity of cells within individual brain regions. The regional viscoelastic properties of P56 mouse brain tissue, up to 70μm displacement, are presented and discussed in the context of traumatic brain injury, particularly how the different regions of the brain respond to mechanical loads. Force-relaxation data obtained from micro-indentation measurements were fit to both linear and quasi-linear viscoelastic models to determine the time and frequency domain viscoelastic response of the pons, cortex, medulla oblongata, cerebellum, and thalamus. The damping ratio of each region was also determined. Each region was found to have a unique mechanical response to the applied displacement, with the pons and thalamus exhibiting the largest and smallest force-response, respectively. All brain regions appear to have an optimal frequency for the dissipation of energies which lies between 1 and 10Hz.

STATEMENT OF SIGNIFICANCE

We present the first mechanical characterization of the viscoelastic response for different regions of mouse brain. Force-relaxation tests are performed under large strain dynamic micro-indentation, and viscoelastic models are used subsequently, providing time-dependent mechanical properties of brain tissue under loading conditions comparable to what is experienced in TBI. The unique mechanical properties of different brain regions are highlighted, with substantial variations in the viscoelastic properties and damping ratio of each region. Cortex and pons were the stiffest regions, while the thalamus and medulla were most compliant. The cerebellum and thalamus had highest damping ratio values and those of the medulla were lowest. The reported material parameters can be implemented into finite element computer models of the mouse to investigate the effects of trauma on individual brain regions.

Mechanical characterization of the P56 mouse brain under large-deformation dynamic indentation

The brain is a complex organ made up of many different functional and structural regions consisting of different types of cells such as neurons and glia, as well as complex anatomical geometries. It is hypothesized that the different regions of the brain exhibit significantly different mechanical properties, which may be attributed to the diversity of cells and anisotropy of neuronal fibers within individual brain regions. The regional dynamic mechanical properties of P56 mouse brain tissue in vitro and in situ at velocities of 0.71-4.28 mm/s, up to a deformation of 70 μm are presented and discussed in the context of traumatic brain injury. The experimental data obtained from micro-indentation measurements were fit to three hyperelastic material models using the inverse Finite Element method. The cerebral cortex elicited a stiffer response than the cerebellum, thalamus, and medulla oblongata regions for all velocities. The thalamus was found to be the least sensitive to changes in velocity, and the medulla oblongata was most compliant. The results show that different regions of the mouse brain possess significantly different mechanical properties, and a significant difference also exists between the in vitro and in situ brain.

Material properties and constitutive modeling of infant porcine cerebellum tissue in tension at high strain rate

Background

The mechanical characterization of infant porcine cerebellum tissue in tension at high strain rate is crucial for modeling traumatic cerebellum injury, which is in turn helpful for understanding the biomechanics of such injuries suffered in traffic accidents.

Material and Method

In this study, the infant porcine cerebellum tissue was given three loading velocities, ie, 2s^-1, 20s^-1 and 100s^-1 with up to 30% strain to investigate the tensile properties. At least six tensile tests for each strain rate were validly performed. Fung, Gent, Ogden and exponential models were applied to fit the constitutive equations, so as to obtain material parameters from the experimental data.

Results

The Lagrange stress of infant porcine cerebellum tissue in tension appeared to be no more than 3000Pa at each loading velocity. More specifically, the Lagrange stress at 30% strain was (393.7±84.4)Pa, (928.3±56.3)Pa and (2582.4±282.2)Pa at strain rates of 2s^-1, 20s^-1 and 100s^-1, respectively. Fung (0.833≤R²≤0.924), Gent (0.797≤R²≤0.875), Ogden (0.859≤R²≤0.944) and exponential (0.930≤R²≤0.972) models provided excellent fitting to experimental data up to 30% strain.

Conclusions

The infant cerebellum tissue shows a stiffer response with increase of the loading speed, indicating a strong strain-rate sensitivity. This study will enrich the knowledge on the material properties of infant brain tissue, which may augment the biofidelity of finite element model of human pediatric cerebellum.

An experimental study on the mechanical properties of rat brain tissue using different stress-strain definitions

There are different stress-strain definitions to measure the mechanical properties of the brain tissue. However, there is no agreement as to which stress-strain definition should be employed to measure the mechanical properties of the brain tissue at both the longitudinal and circumferential directions. It is worth knowing that an optimize stress-strain definition of the brain tissue at different loading directions may have implications for neuronavigation and surgery simulation through haptic devices. This study is aimed to conduct a comparative study on different results are given by the various definitions of stress-strain and to recommend a specific definition when testing brain tissues. Prepared cylindrical samples are excised from the parietal lobes of rats' brains and experimentally tested by applying load on both the longitudinal and circumferential directions. Three stress definitions (second Piola-Kichhoff stress, engineering stress, and true stress) and four strain definitions (Almansi-Hamel strain, Green-St. Venant strain, engineering strain, and true strain) are used to determine the elastic modulus, maximum stress and strain. The highest non-linear stress-strain relation is observed for the Almansi-Hamel strain definition and it may overestimate the elastic modulus at different stress definitions at both the longitudinal and circumferential directions. The Green-St. Venant strain definition fails to address the non-linear stress-strain relation using different definitions of stress and triggers an underestimation of the elastic modulus. The results suggest the application of the true stress-true strain definition for characterization of the brain tissues mechanics since it gives more accurate measurements of the tissue's response using the instantaneous values.

Assessing neuro-systemic & behavioral components in the pathophysiology of blast-related brain injury

Among the U.S. military personnel, blast injury is among the leading causes of brain injury. During the past decade, it has become apparent that even blast injury as a form of mild traumatic brain injury (mTBI) may lead to multiple different adverse outcomes, such as neuropsychiatric symptoms and long-term cognitive disability. Blast injury is characterized by blast overpressure, blast duration, and blast impulse. While the blast injuries of a victim close to the explosion will be severe, majority of victims are usually at a distance leading to milder form described as mild blast TBI (mbTBI). A major feature of mbTBI is its complex manifestation occurring in concert at different organ levels involving systemic, cerebral, neuronal, and neuropsychiatric responses; some of which are shared with other forms of brain trauma such as acute brain injury and other neuropsychiatric disorders such as post-traumatic stress disorder. The pathophysiology of blast injury exposure involves complex cascades of chronic psychological stress, autonomic dysfunction, and neuro/systemic inflammation. These factors render blast injury as an arduous challenge in terms of diagnosis and treatment as well as identification of sensitive and specific biomarkers distinguishing mTBI from other non-TBI pathologies and from neuropsychiatric disorders with similar symptoms. This is due to the “distinct” but shared and partially identified biochemical pathways and neuro-histopathological changes that might be linked to behavioral deficits observed. Taken together, this article aims to provide an overview of the current status of the cellular and pathological mechanisms involved in blast overpressure injury and argues for the urgent need to identify potential biomarkers that can hint at the different mechanisms involved.

Long-term changes in the material properties of brain tissue at the implant-tissue interface

OBJECTIVE

Brain tissue undergoes dramatic molecular and cellular remodeling at the implant-tissue interface that evolves over a period of weeks after implantation. The biomechanical impact of such remodeling on the interface remains unknown. In this study, we aim to assess the changes in the mechanical properties of the brain-electrode interface after chronic implantation of a microelectrode.

APPROACH

Microelectrodes were implanted in the rodent cortex at a depth of 1 mm for different durations-1 day (n = 4), 10-14 days (n = 4), 4 weeks (n = 4) and 6-8 weeks (n = 7). After the initial duration of implantation, the microelectrodes were moved an additional 1 mm downward at a constant speed of 10 µm s(-1). Forces experienced by the microelectrode were measured during movement and after termination of movement. The biomechanical properties of the interfacial brain tissue were assessed from measured force-displacement curves using two separate models-a two-parameter Mooney-Rivlin hyperelastic model and a viscoelastic model with a second-order Prony series.

MAIN RESULTS

Estimated shear moduli using a second-order viscoelastic model increased from 0.5-2.6 kPa (day 1 of implantation) to 25.7-59.3 kPa (after 4 weeks of implantation) and subsequently decreased to 0.8-7.9 kPa after 6-8 weeks of implantation in 6 of the 7 animals. The estimated elastic modulus increased from 4.1-7.8 kPa on the day of implantation to 24-44.9 kPa after 4 weeks. The elastic modulus was estimated to be 6.8-33.3 kPa in 6 of the 7 animals after 6-8 weeks of implantation. The above estimates suggest that the brain tissue surrounding the microelectrode evolves from a stiff matrix with maximal shear and elastic modulus after 4 weeks of implantation into a composite of two different layers with different mechanical properties-a stiff compact inner layer surrounded by softer brain tissue that is biomechanically similar to brain tissue-during the first week of implantation. Tissue micromotion-induced stresses on the microelectrode constituted 12-55% of the steady-state stresses on the microelectrode on the day of implantation (n = 4), 2-21% of the steady-state stresses after 4 weeks of implantation (n = 4), and 4-10% of the steady-state stresses after 6-8 weeks of implantation (n = 7).

SIGNIFICANCE

Understanding biomechanical behavior at the brain-microelectrode interface is necessary for the long-term success of implantable neuroprosthetics and microelectrode arrays. Such quantitative physical characterization of the dynamic changes in the electrode-tissue interface will (a) drive the design and development of more mechanically optimal, chronic brain implants, and (b) lead to new insights into key cellular and molecular events such as neuronal adhesion, migration and function in the immediate vicinity of the brain implant.

Mechanical characterization of brain tissue in tension at dynamic strain rates

Mechanical characterization of brain tissue at high loading velocities is crucial for modeling Traumatic Brain Injury (TBI). During severe impact conditions, brain tissue experiences compression, tension and shear. Limited experimental data is available for brain tissue in extension at dynamic strain rates. In this research, a High Rate Tension Device (HRTD) was developed to obtain dynamic properties of brain tissue in extension at strain rates of ≤90/s. In vitro tensile tests were performed to obtain properties of brain tissue at strain rates of 30, 60 and 90/s up to 30% strain. The brain tissue showed a stiffer response with increasing strain rates, showing that hyperelastic models are not adequate. Specifically, the tensile engineering stress at 30% strain was 3.1±0.49kPa, 4.3±0.86kPa, 6.5±0.76kPa (mean±SD) at strain rates of 30, 60 and 90/s, respectively. Force relaxation tests in tension were also conducted at different strain magnitudes (10-60% strain) with the average rise time of 24ms, which were used to derive time dependent parameters. One-term Ogden, Fung and Gent models were used to obtain material parameters from the experimental data. Numerical simulations were performed using a one-term Ogden model to analyze hyperelastic behavior of brain tissue up to 30% strain. The material parameters obtained in this study will help to develop biofidelic human brain finite element models, which can subsequently be used to predict brain injuries under impact conditions and as a reconstruction and simulation tool for forensic investigations.