Micromechanical analysis of brain’s diffuse axonal injury

Computational models are important tools which help researchers understand traumatic brain injury (TBI). A mechanistic multi-scale numerical approach is introduced to quantify diffuse axonal injury (DAI), the most important mechanism of TBI, induced by a mechanical insult at micro-scale regions of the white matter or voxels where fiber orientations are the same. Using the mechanical properties of a single axon with a viscoelastic constitutive relation and its functional failure in terms of electrophysiological impairment, a numerical 2D micro-level lattice method is implemented to directly analyze the percentage of injured axons in a voxel containing a bundle of axons all with the same orientation under biaxial stretches. Reference micro-injury maps are then developed with the input parameters based on the principal strain or stretch values and their direction with respect to axons, which provide the percentage of injured axons in the voxel of interest as the output. The methodology is independent of any statistical analyses of the accident data and medical reports to derive probabilistic injury risk curves for DAI. Avoiding a structurally detailed full finite element head model, this study proposes a micro-mechanical approach which considers the anatomical structure of neural axons in the white matter together with their mechanical properties using a numerical lattice method to analyze the brain’s diffuse axonal injury. This work has the potential to help develop safer prevention tools and more effective diagnosis methods for DAI.     

Anisotropic finite element models for brain injury prediction: the sensitivity of axonal strain to white matter tract inter-subject variability

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.     

The peculiar properties of the falx and tentorium in brain injury biomechanics

The influence of the falx and tentorium on brain injury biomechanics during impact was studied with finite element (FE) analysis. Three detailed 3D FE head models were created based on the images of a healthy, normal size head. Two of the models contained the addition of falx and tentorium with material properties from previously published experiments. Impact loadings from a reconstructed concussive case in a sport accident were applied to the two players involved. The results suggested that the falx and tentorium could induce large strains to the surrounding brain tissues, especially to the corpus callosum and brainstem. The tentorium seemed to constrain the motion of the cerebellum while inducing large strain in the brainstem in both players involved in the accident (one player had mainly coronal head rotation and the other had both coronal and transversal rotations). Since changed strain levels were observed in the brainstem and corpus callosum, which are classical sites for diffuse axonal injuries (DAI), we confirmed the importance of using accurate material properties for falx and tentorium in a FE head model when studying traumatic brain injuries.     

Modeling of microstructural kinematics during simple elongation of central nervous system tissue

Damage to axons and glial cells in the central nervous system (CNS) white matter is a nearly universal feature of traumatic brain injury, yet it is not clear how the tissue mechanical deformations are transferred to the cellular components of the CNS. Defining how cellular deformations relate to the applied tissue deformation field can both highlight cellular populations at risk for mechanical injury, and define the fraction of cells in a specific population that will exhibit damage. In this investigation, microstructurally based models of CNS white matter were developed and tested against measured transformations of the CNS tissue microstructure under simple elongation. Results show that axons in the unstretched optic nerves were significantly wavy or undulated, where the measured axonal path length was greater than the end-to-end distance of the axon. The average undulation parameter--defined as the true axonal length divided by the end-to-end length--was 1.13. In stretched nerves, mean axonal undulations decreased with increasing applied stretch ratio (lambda)--the mean undulation values decreased to 1.06 at lambda = 1.06, 1.04 at lambda = 1.12, and 1.02 at lambda = 1.25. A model describing the gradual coupling, or tethering, of the axons to the surrounding glial cells best fit the experimental data. These modeling efforts indicate the fraction of the axonal and glial populations experiencing deformation increases with applied elongation, consistent with the observation that both axonal and glial cell injury increases at higher levels of white matter injury. Ultimately, these results can be used in conjunction with computational simulations of traumatic brain injury to aid in establishing the relative risk of cellular structures in the CNS white matter to mechanical injury.     

Combining the Finite Element Method with Structural Connectome-based Analysis for Modeling Neurotrauma: Connectome Neurotrauma Mechanics

This article presents the integration of brain injury biomechanics and graph theoretical analysis of neuronal connections, or connectomics, to form a neurocomputational model that captures spatiotemporal characteristics of trauma. We relate localized mechanical brain damage predicted from biofidelic finite element simulations of the human head subjected to impact with degradation in the structural connectome for a single individual. The finite element model incorporates various length scales into the full head simulations by including anisotropic constitutive laws informed by diffusion tensor imaging. Coupling between the finite element analysis and network-based tools is established through experimentally-based cellular injury thresholds for white matter regions. Once edges are degraded, graph theoretical measures are computed on the "damaged" network. For a frontal impact, the simulations predict that the temporal and occipital regions undergo the most axonal strain and strain rate at short times (less than 24 hrs), which leads to cellular death initiation, which results in damage that shows dependence on angle of impact and underlying microstructure of brain tissue. The monotonic cellular death relationships predict a spatiotemporal change of structural damage. Interestingly, at 96 hrs post-impact, computations predict no network nodes were completely disconnected from the network, despite significant damage to network edges. At early times ([Formula: see text]) network measures of global and local efficiency were degraded little; however, as time increased to 96 hrs the network properties were significantly reduced. In the future, this computational framework could help inform functional networks from physics-based structural brain biomechanics to obtain not only a biomechanics-based understanding of injury, but also neurophysiological insight.     

The influence of anisotropy on brain injury prediction

Traumatic Brain Injury (TBI) occurs when a mechanical insult produces damage to the brain and disrupts its normal function. Numerical head models are often used as tools to analyze TBIs and to measure injury based on mechanical parameters. However, the reliability of such models depends on the incorporation of an appropriate level of structural detail and accurate representation of the material behavior. Since recent studies have shown that several brain regions are characterized by a marked anisotropy, constitutive equations should account for the orientation-dependence within the brain. Nevertheless, in most of the current models brain tissue is considered as completely isotropic. To study the influence of the anisotropy on the mechanical response of the brain, a head model that incorporates the orientation of neural fibers is used and compared with a fully isotropic model. A simulation of a concussive impact based on a sport accident illustrates that significantly lowered strains in the axonal direction as well as increased maximum principal strains are detected for anisotropic regions of the brain. Thus, the orientation-dependence strongly affects the response of the brain tissue. When anisotropy of the whole brain is taken into account, deformation spreads out and white matter is particularly affected. The introduction of local axonal orientations and fiber distribution into the material model is crucial to reliably address the strains occurring during an impact and should be considered in numerical head models for potentially more accurate predictions of brain injury.     

An anatomically detailed and personalizable head injury model: Significance of brain and white matter tract morphological variability on strain

Finite element head (FE) models are important numerical tools to study head injuries and develop protection systems. The generation of anatomically accurate and subject-specific head models with conforming hexahedral meshes remains a significant challenge. The focus of this study is to present two developmental works: first, an anatomically detailed FE head model with conforming hexahedral meshes that has smooth interfaces between the brain and the cerebrospinal fluid, embedded with white matter (WM) fiber tracts; second, a morphing approach for subject-specific head model generation via a new hierarchical image registration pipeline integrating Demons and Dramms deformable registration algorithms. The performance of the head model is evaluated by comparing model predictions with experimental data of brain–skull relative motion, brain strain, and intracranial pressure. To demonstrate the applicability of the head model and the pipeline, six subject-specific head models of largely varying intracranial volume and shape are generated, incorporated with subject-specific WM fiber tracts. DICE similarity coefficients for cranial, brain mask, local brain regions, and lateral ventricles are calculated to evaluate personalization accuracy, demonstrating the efficiency of the pipeline in generating detailed subject-specific head models achieving satisfactory element quality without further mesh repairing. The six head models are then subjected to the same concussive loading to study the sensitivity of brain strain to inter-subject variability of the brain and WM fiber morphology. The simulation results show significant differences in maximum principal strain and axonal strain in local brain regions (one-way ANOVA test, p < 0.001), as well as their locations also vary among the subjects, demonstrating the need to further investigate the significance of subject-specific models. The techniques developed in this study may contribute to better evaluation of individual brain injury and the development of individualized head protection systems in the future. This study also contains general aspects the research community may find useful: on the use of experimental brain strain close to or at injury level for head model validation; the hierarchical image registration pipeline can be used to morph other head models, such as smoothed-voxel models.

     

An axonal strain injury criterion for traumatic brain injury

Computational models are often used as tools to study traumatic brain injury. The fidelity of such models depends on the incorporation of an appropriate level of structural detail, the accurate representation of the material behavior, and the use of an appropriate measure of injury. In this study, an axonal strain injury criterion is used to estimate the probability of diffuse axonal injury (DAI), which accounts for a large percentage of deaths due to brain trauma and is characterized by damage to neural axons in the deep white matter regions of the brain. We present an analytical and computational model that treats the white matter as an anisotropic, hyperelastic material. Diffusion tensor imaging is used to incorporate the structural orientation of the neural axons into the model. It is shown that the degree of injury that is predicted in a computational model of DAI is highly dependent on the incorporation of the axonal orientation information and the inclusion of anisotropy into the constitutive model for white matter.     

Atomic force microscopy reveals important differences in axonal resistance to injury

Axonal degeneration after traumatic brain injury and nerve compression is considered a common underlying cause of temporary as well as permanent disability. Because a proper functioning of neural network requires phase coherence of all components, even subtle changes in circuitry may lead to network failure. However, it is still not possible to determine which axons will recover or degenerate after injury. Several groups have studied the pressure threshold for axonal injury within a nerve, but difficulty accessing the injured region; insufficient imaging methods and the extremely small dimensions involved have prevented the evaluation of the response of individual axons to injury. We combined microfluidics with atomic force microscopy and in vivo imaging to estimate the threshold force required to 1), uncouple axonal transport without impairing axonal survival, and 2), compromise axonal survival in both individual and bundled axons. We found that rat hippocampal axons completely recover axonal transport with no detectable axonal loss when compressed with pressures up to 65 ± 30 Pa for 10 min, while dorsal root ganglia axons can resist to pressures up to 540 ± 220 Pa. We investigated the reasons for the differential susceptibility of hippocampal and DRG axons to mechanical injury and estimated the elasticity of live axons. We found that dorsal root ganglia axons have a 20% lower elastic modulus than hippocampal axons. Our results emphasize the importance of the integrity of the axonal cytoskeleton in deciding the axonal fate after damage and open up new avenues to improve injury diagnosis and to identify ways to protect axons.     

Computational Study of Human Head Response to Primary Blast Waves of Five Levels from Three Directions

Human exposure to blast waves without any fragment impacts can still result in primary blast-induced traumatic brain injury (bTBI). To investigate the mechanical response of human brain to primary blast waves and to identify the injury mechanisms of bTBI, a three-dimensional finite element head model consisting of the scalp, skull, cerebrospinal fluid, nasal cavity, and brain was developed from the imaging data set of a human female. The finite element head model was partially validated and was subjected to the blast waves of five blast intensities from the anterior, right lateral, and posterior directions at a stand-off distance of one meter from the detonation center. Simulation results show that the blast wave directly transmits into the head and causes a pressure wave propagating through the brain tissue. Intracranial pressure (ICP) is predicted to have the highest magnitude from a posterior blast wave in comparison with a blast wave from any of the other two directions with same blast intensity. The brain model predicts higher positive pressure at the site proximal to blast wave than that at the distal site. The intracranial pressure wave invariably travels into the posterior fossa and vertebral column, causing high pressures in these regions. The severities of cerebral contusions at different cerebral locations are estimated using an ICP based injury criterion. Von Mises stress prevails in the cortex with a much higher magnitude than in the internal parenchyma. According to an axonal injury criterion based on von Mises stress, axonal injury is not predicted to be a cause of primary brain injury from blasts.     

Viscoelasticity of Tau Proteins Leads to Strain Rate-Dependent Breaking of Microtubules during Axonal Stretch Injury: Predictions from a Mathematical Model

The unique viscoelastic nature of axons is thought to underlie selective vulnerability to damage during traumatic brain injury. In particular, dynamic loading of axons has been shown to mechanically break microtubules at the time of injury. However, the mechanism of this rate-dependent response has remained elusive. Here, we present a microstructural model of the axonal cytoskeleton to quantitatively elucidate the interaction between microtubules and tau proteins under mechanical loading. Mirroring the axon ultrastructure, the microtubules were arranged in staggered arrays, cross-linked by tau proteins. We found that the viscoelastic behavior specifically of tau proteins leads to mechanical breaking of microtubules at high strain rates, whereas extension of tau allows for reversible sliding of microtubules without any damage at small strain rates. Based on the stiffness and viscosity of tau proteins inferred from single-molecule force spectroscopy studies, we predict the critical strain rate for microtubule breaking to be in the range 22–44 s⁻¹, in excellent agreement with recent experiments on dynamic loading of micropatterned neuronal cultures. We also identified a characteristic length scale for load transfer that depends on microstructural properties and have derived a phase diagram in the parameter space spanned by loading rate and microtubule length that demarcates those regions where axons can be loaded and unloaded reversibly and those where axons are injured due to breaking of the microtubules.     

Primary paranode demyelination modulates slowly developing axonal depolarization in a model of axonal injury

Neurological sequelae of mild traumatic brain injury are associated with the damage to white matter myelinated axons. In vitro models of axonal injury suggest that the progression to pathological ruin is initiated by the mechanical damage to tetrodotoxin-sensitive voltage-gated sodium channels that breaches the ion balance through alteration in kinetic properties of these channels. In myelinated axons, sodium channels are concentrated at nodes of Ranvier, making these sites vulnerable to mechanical injury. Nodal damage can also be inflicted by injury-induced partial demyelination of paranode/juxtaparanode compartments that flank the nodes and contain high density of voltage-gated potassium channels. Demyelination-induced potassium deregulation can further aggravate axonal damage; however, the role of paranode/juxtaparanode demyelination in immediate impairment of axonal function, and its contribution to the development of axonal depolarization remain elusive. A biophysically realistic computational model of myelinated axon that incorporates ion exchange mechanisms and nodal/paranodal/juxtaparanodal organization was developed and used to study the impact of injury-induced demyelination on axonal signal transmission. Injured axons showed alterations in signal propagation that were consistent with the experimental findings and with the notion of reduced axonal excitability immediately post trauma. Injury-induced demyelination strongly modulated the rate of axonal depolarization, suggesting that trauma-induced damage to paranode myelin can affect axonal transition to degradation. Results of these studies clarify the contribution of paranode demyelination to immediate post trauma alterations in axonal function and suggest that partial paranode demyelination should be considered as another “injury parameter” that is likely to determine the stability of axonal function.     

Viscoelasticity of Tau Proteins Leads to Strain Rate-Dependent Breaking of?Microtubules during Axonal Stretch Injury: Predictions from a Mathematical Model

The unique viscoelastic nature of axons is thought to underlie selective vulnerability to damage during traumatic brain injury. In particular, dynamic loading of axons has been shown to mechanically break microtubules at the time of injury. However, the mechanism of this rate-dependent response has remained elusive. Here, we present a microstructural model of the axonal cytoskeleton to quantitatively elucidate the interaction between microtubules and tau proteins under mechanical loading. Mirroring the axon ultrastructure, the microtubules were arranged in staggered arrays, cross-linked by tau proteins. We found that the viscoelastic behavior specifically of tau proteins leads to mechanical breaking of microtubules at high strain rates, whereas extension of tau allows for reversible sliding of microtubules without any damage at small strain rates. Based on the stiffness and viscosity of tau proteins inferred from single-molecule force spectroscopy studies, we predict the critical strain rate for microtubule breaking to be in the range 22–44 s⁻¹, in excellent agreement with recent experiments on dynamic loading of micropatterned neuronal cultures. We also identified a characteristic length scale for load transfer that depends on microstructural properties and have derived a phase diagram in the parameter space spanned by loading rate and microtubule length that demarcates those regions where axons can be loaded and unloaded reversibly and those where axons are injured due to breaking of the microtubules.     

White matter tract-oriented deformation predicts traumatic axonal brain injury and reveals rotational direction-specific vulnerabilities

A systematic correlation between finite element models (FEMs) and histopathology is needed to define deformation thresholds associated with traumatic brain injury (TBI). In this study, a FEM of a transected piglet brain was used to reverse engineer the range of optimal shear moduli for infant (5 days old, 553–658 Pa) and 4-week-old toddler piglet brain (692–811 Pa) from comparisons with measured in situ tissue strains. The more mature brain modulus was found to have significant strain and strain rate dependencies not observed with the infant brain. Age-appropriate FEMs were then used to simulate experimental TBI in infant (\(n=36\)) and preadolescent (\(n=17\)) piglets undergoing a range of rotational head loads. The experimental animals were evaluated for the presence of clinically significant traumatic axonal injury (TAI), which was then correlated with FEM-calculated measures of overall and white matter tract-oriented tissue deformations, and used to identify the metric with the highest sensitivity and specificity for detecting TAI. The best predictors of TAI were the tract-oriented strain (6–7 %), strain rate (38–40 s\(^{-1})\), and strain times strain rate (1.3–1.8 s\(^{-1})\) values exceeded by 90 % of the brain. These tract-oriented strain and strain rate thresholds for TAI were comparable to those found in isolated axonal stretch studies. Furthermore, we proposed that the higher degree of agreement between tissue distortion aligned with white matter tracts and TAI may be the underlying mechanism responsible for more severe TAI after horizontal and sagittal head rotations in our porcine model of nonimpact TAI than coronal plane rotations.     

Shear Injuries of the Brain

A blow to the head will impart rotational velocity to the brain and, depending on its magnitude, will produce effects ranging from concussion to profound neurological dysfunction. Resultant shear strains distort and rupture axons, blood vessels and major fibre tracts. Thirty-seven patients with head injury that was not complicated by significant hemorrhage or superficial laceration of the brain had coma or severe dementia, spastic quadriparesis, incontinence and autonomic dysfunction. These patients survived 24 hours to 243 days. Gross pathological examination revealed little, but there was microscopic evidence of axonal and small vessel injury in all; this was localized to the basal and midsagittal areas of the diencephalon and mesencephalon, particularly in those less severely injured. Such changes represent the basic pathology of all head injury. Data from this study suggest that concussion depends upon varying degrees of damage to the axon as well as the neuron. The current definition of concussion—immediate loss of consciousness with rapid and complete recovery of cerebral function—should not exclude the fact that a small number of neurons may have been permanently disconnected or have perished.     

Computational modeling of axonal microtubule bundles under tension

Microtubule bundles cross-linked by tau protein serve a variety of neurological functions including maintaining mechanical integrity of the axon, promoting axonal growth, and facilitating cargo transport. It has been observed that axonal damage in traumatic brain injury leads to bundle disorientation, loss of axonal viability, and cognitive impairment. This study investigates the initial mechanical response of axonal microtubule bundles under uniaxial tension using a discrete bead-spring representation. Mechanisms of failure due to traumatic stretch loading and their impact on the mechanical response and stability are also characterized. This study indicates that cross-linked axonal microtubule bundles in tension display stiffening behavior similar to a power-law relationship from nonaffine network deformations. Stretching of cross-links and microtubule bending were the primary deformation modes at low stresses. Microtubule stretch was negligible up to tensile stresses of ～1 MPa. Bundle failure occurred by failure of cross-links leading to pull-out of microtubules and loss of bundle integrity. This may explain the elongation, undulation, and delayed elasticity of axons following traumatic stretch loading. More extensively cross-linked bundles withstood higher tensile stresses before failing. The bundle mechanical behavior uncovered by these computational techniques should guide future experiments on stretch-injured axons.     

Image-based multi-scale mechanical analysis of strain amplification in neurons embedded in collagen gel

A general multi-scale strategy is presented for modeling the mechanical environment of a group of neurons that were embedded within a collagenous matrix. The results of the multi-scale simulation are used to estimate the local strains that arise in neurons when the extracellular matrix is deformed. The distribution of local strains was found to depend strongly on the configuration of the embedded neurons relative to the loading direction, reflecting the anisotropic mechanical behavior of the neurons. More importantly, the applied strain on the surrounding extracellular matrix is amplified in the neurons for all loading configurations that are considered. In the most severe case, the applied strain is amplified by at least a factor of 2 in 10% of the neurons' volume. The approach presented in this paper provides an extension to the capability of past methods by enabling the realistic representation of complex cell geometry into a multi-scale framework. The simulation results for the embedded neurons provide local strain information that is not accessible by current experimental techniques.     

Physical model simulations of brain injury in the primate

Diffuse brain injuries resulting from non-impact rotational acceleration are investigated with the aid of physical models of the skull-brain structure. These models provide a unique insight into the relationship between the kinematics of head motion and the associated deformation of the surrogate brain material. Human and baboon skulls filled with optically transparent surrogate brain tissue are subjected to lateral rotations like those shown to produce diffuse injury to the deep white matter in the brain of the baboon. High-speed cinematography captures the deformations of the grids embedded within the surrogate brain tissue during the applied load. The overall deformation pattern is compared to the pathological portrait of diffuse brain injury as determined from animal studies and autopsy reports. Shear strain and pathology spatial distributions mirror each other. Load levels and resulting surrogate brain tissue deformations are related from one species to the other. Increased primate brain mass magnified the strain amplified without significantly altering the spatial distribution. An empirically-derived value for a critical shear strain associated with the onset of severe diffuse axonal injury in primates is determined, assuming constitutive similarity between baboon and human brain tissue. The primate skull physical model data and the critical shear strain associated with the threshold for severe diffuse axonal injury were used to scale data obtained from previous studies to man, and thus derive a diffuse axonal injury tolerance for rotational acceleration for humans.     

Estimating axonal strain and failure following white matter stretch using contactin-associated protein as a fiduciary marker

Axonal injury occurs during trauma when tissue-scale loads are transferred to individual axons. Computational models are used to understand this transfer and predict the circumstances that cause injury. However, these findings are limited by a lack of validating experimental work examining the mechanics of axons in their in situ state. As a first step towards validation for dynamic stretch, we use contactin-associated protein (Caspr), expressed at the nodes of Ranvier, as a fiduciary marker of quasistatic axonal stretch. We measured changes in the distance between immunolabled Caspr pairs along axons as a function of tissue-level stretch in chick embryo spinal cords harvested from different developmental periods. We then identified and characterized broken axons and adapted a kinematic model published previously by our group (Singh et al., 2015) to estimate average strain thresholds for axon mechanical failure. The distance between Caspr pairs increased with stretch, though not as much as predicted by simple continuum mechanics. For equivalent tissue stretch, greater numbers of broken axons were found at later stages of development. In adapting our kinematic model to predict a breaking threshold strain, we found that breaking thresholds decrease with development stage. When thresholds were split and classified based on kinematic behavior, non-affine, uncoupled axons had higher strain thresholds than affine, coupled axons, corroborating thresholds predicted from in vitro and in vivo preparations. These results provide a valuable launching point for generating more accurate multi-scale models in primary central nervous system injury.