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.     

A proposed tolerance criterion for diffuse axonal injury in man.

The head injury criterion (HIC) is currently the government-accepted head injury indicator. The HIC is not injury-specific, does not relate to injury severity, nor does it take into account variations in the brain mass or load direction. This report focuses on one type of inertial brain injury, diffuse axonal injury (DAI), and utilizes animal studies, physical model experiments, and analytical model simulations to determine the kinematics of DAI in the subhuman primate and to scale these results to man. A human injury tolerance for moderate to severe DAI, which includes the influences of rotational loads and brain mass, is proposed.     

The mechanical behaviour of brain tissue: large strain response and constitutive modelling

The non-linear mechanical behaviour of porcine brain tissue in large shear deformations is determined. An improved method for rotational shear experiments is used, producing an approximately homogeneous strain field and leading to an enhanced accuracy. Results from oscillatory shear experiments with a strain amplitude of 0.01 and frequencies ranging from 0.04 to 16 Hz are given. The immediate loss of structural integrity, due to large deformations, influencing the mechanical behaviour of brain tissue, at the time scale of loading, is investigated. No significant immediate mechanical damage is observed for these shear deformations up to strains of 0.45. Moreover, the material behaviour during complex loading histories (loading-unloading) is investigated. Stress relaxation experiments for strains up to 0.2 and constant strain rate experiments for shear rates from 0.01 to 1 s(-1) and strains up to 0.15 are presented. A new differential viscoelastic model is used to describe the mechanical response of brain tissue. The model is formulated in terms of a large strain viscoelastic framework and considers non-linear viscous deformations in combination with non-linear elastic behaviour. This constitutive model is readily applicable in three-dimensional head models in order to predict the mechanical response of the intra-cranial contents due to an impact.     

Design and numerical implementation of a 3-D non-linear viscoelastic constitutive model for brain tissue during impact

Finite Element (FE) head models are often used to understand mechanical response of the head and its contents during impact loading in the head. Current FE models do not account for non-linear viscoelastic material behavior of brain tissue. We developed a new non-linear viscoelastic material model for brain tissue and implemented it in an explicit FE code. To obtain sufficient numerical accuracy for modeling the nearly incompressible brain tissue, deviatoric and volumetric stress contributions are separated. Deviatoric stress is modeled in a non-linear viscoelastic differential form. Volumetric behavior is assumed linearly elastic. Linear viscoelastic material parameters were derived from published data on oscillatory experiments, and from ultrasonic experiments. Additionally, non-linear parameters were derived from stress relaxation (SR) experiments at shear strains up to 20%. The model was tested by simulating the transient phase in the SR experiments not used in parameter determination (strains up to 20%, strain rates up to 8s(-1)). Both time- and strain-dependent behavior were predicted accurately (R2>0.96) for strain and strain rates applied. However, the stress was overestimated systematically by approximately 31% independent of strain(rate) applied. This is probably caused by limitations of the experimental data at hand.     

Constitutive model for brain tissue under finite compression

While advances in computational models of mechanical phenomena have made it possible to simulate dynamically complex problems in biomechanics, accurate material models for soft tissues, particularly brain tissue, have proven to be very challenging. Most studies in the literature on material properties of brain tissue are performed in shear loading and very few tackle the behavior of brain in compression. In this study, a viscoelastic constitutive model of bovine brain tissue under finite step-and-hold uniaxial compression with 10 s(-1) ramp rate and 20 s hold time has been developed. The assumption of quasi-linear viscoelasticity (QLV) was validated for strain levels of up to 35%. A generalized Rivlin model was used for the isochoric part of the deformation and it was shown that at least three terms (C(10), C(01) and C(11)) are needed to accurately capture the material behavior. Furthermore, for the volumetric deformation, a two parameter Ogden model was used and the extent of material incompressibility was studied. The hyperelastic material parameters were determined through extracting and fitting to two isochronous curves (0.06 s and 14 s) approximating the instantaneous and steady-state elastic responses. Viscoelastic relaxation was characterized at five decay rates (100, 10, 1, 0.1, 0 s(-1)) and the results in compression and their extrapolation to tension were compared against previous models.     

Proposing a Radial Basis Function and CSDM Indices to Predict the Traumatic Brain Injury Risk

BackgroundMany head injury indices and finite element (FE) head models have been proposed to predict traumatic brain injury (TBI). Although FE head models are suitable methods with high accuracy, they are computationally intensive. Head motion-based brain injury criteria are usually fast tools with lower accuracy. So, the objective of this study is to propose new criteria along with an artificial neural network model to predict TBI risks, which can be fast and accurate.MethodsFor this purpose, 250 FE head simulations have been carried out at 5 magnitudes and 50 rotational impact directions using the SIMon model. The effects of directions and magnitudes of rotational impacts were assessed for cumulative strain damage measure (CSDM) values. Next, statistical analysis and neural network were applied to predict CSDM values.ResultsThe results of the present research showed that the direction of rotation in the sagittal and frontal planes had a considerable effect on the CSDM values. Furthermore, new brain injury indices and a radial basis function neural network have been proposed to predict CSDM values which having high correlation coefficients with SIMon responses.ConclusionsThe results of this research demonstrated that rotational impact directions should be used to develop new head injury criteria being able to predict CSDM values. However, findings of present research proved that head motion-based brain injury criteria and RBF network can be used to predict FE head model responses with high speed and accuracy.     

Measurement of strain in physical models of brain injury: a method based on HARP analysis of tagged magnetic resonance images (MRI)

Two-dimensional (2-D) strain fields were estimated non-invasively in two simple experimental models of closed-head brain injury. In the first experimental model, shear deformation of a gel was induced by angular acceleration of its spherical container In the second model the brain of a euthanized rat pup was deformed by indentation of its skull. Tagged magnetic resonance images (MRI) were obtained by gated image acquisition during repeated motion. Harmonic phase (HARP) images corresponding to the spectral peaks of the original tagged MRI were obtained, following procedures proposed by Osman, McVeigh and Prince. Two methods of HARP strain analysis were applied, one based on the displacement of tag line intersections, and the other based on the gradient of harmonic phase. Strain analysis procedures were also validated on simulated images of deformed grids. Results show that it is possible to visualize deformation and to quantify strain efficiently in animal models of closed head injury.     

Helmet liner evaluation to mitigate head response from primary blast exposure

Head injury resulting from blast loading, including mild traumatic brain injury, has been identified as an important blast-related injury in modern conflict zones. A study was undertaken to investigate potential protective ballistic helmet liner materials to mitigate primary blast injury using a detailed sagittal plane head finite element model, developed and validated against previous studies of head kinematics resulting from blast exposure. Five measures reflecting the potential for brain injury that were investigated included intracranial pressure, brain tissue strain, head acceleration (linear and rotational) and the head injury criterion. In simulations, these measures provided consistent predictions for typical blast loading scenarios. Considering mitigation, various characteristics of foam material response were investigated and a factor analysis was performed which showed that the four most significant were the interaction effects between modulus and hysteretic response, stress–strain response, damping factor and density. Candidate materials were then identified using the predicted optimal material values. Polymeric foam was found to meet the density and modulus requirements; however, for all significant parameters, higher strength foams, such as aluminum foam, were found to provide the highest reduction in the potential for injury when compared against the unprotected head.     

Mechanical properties of bovine pia-arachnoid complex in shear

Traumatic brain injury (TBI) has become a major public health and socioeconomic problem that affects 1.5 million Americans annually. Finite element methods have been widely used to investigate TBI mechanisms. The pia-arachnoid complex (PAC) covering the brain plays an important role in the mechanical response of the brain during impact or inertial loading. Existing finite element brain models have tended to oversimplify the response of the PAC due to a lack of accurately defined material properties of this structure, possibly resulting in a loss of accuracy in the model predictions. The objectives of this study were to experimentally determine the material properties of the PAC under shear loading. Bovine PAC was selected in the current study in view of its availability and comparability with previous studies. Tangential shear tests were conducted at 0.8, 7.3, and 72 s(-1). The mean shear moduli were 11.73, 20.04, and 22.37 kPa at the three strain rates tested. The ultimate stress, at the three strain rates, was 9.21, 17.01, and 22.26 kPa, while the ultimate strain was 1.52, 1.58, and 1.81. Results from the current study provide essential information to properly model the PAC membrane, an important component in the skull/brain interface, in a computational model of the human/animal head. Such an improved representation of the in vivo skull/brain interface will enhance future studies investigating brain injury mechanisms under various loading conditions.     

Development of a Finite Element Model of Decompressive Craniectomy

Decompressive craniectomy (DC), an operation whereby part of the skull is removed, is used in the management of patients with brain swelling. While the aim of DC is to reduce intracranial pressure, there is the risk that brain deformation and mechanical strain associated with the operation could damage the brain tissue. The nature and extent of the resulting strain regime is poorly understood at present. Finite element (FE) models of DC can provide insight into this applied strain and hence assist in deciding on the best surgical procedures. However there is uncertainty about how well these models match experimental data, which are difficult to obtain clinically. Hence there is a need to validate any modelling approach outside the clinical setting. This paper develops an axisymmetric FE model of an idealised DC to assess the key features of such an FE model which are needed for an accurate simulation of DC. The FE models are compared with an experimental model using gelatin hydrogel, which has similar poro-viscoelastic material property characteristics to brain tissue. Strain on a central plane of the FE model and the front face of the experimental model, deformation and load relaxation curves are compared between experiment and FE. Results show good agreement between the FE and experimental models, providing confidence in applying the proposed FE modelling approach to DC. Such a model should use material properties appropriate for brain tissue and include a more realistic whole head geometry.     

Strain relief from the cerebral ventricles during head impact: experimental studies on natural protection of the brain

Physical models of the parasagittal human skull/brain have been tested to investigate whether the cerebral ventricles provide natural protection of the brain by relieving strain during head rotation. A sophisticated model included anatomical structures, and a semicircular model consisted of a cylinder divided into two semicircles. Silicone gel simulated the brain and was detached from the vessel by a layer of liquid paraffin simulating the cerebrospinal fluid. Both models were run with and without an elliptical inclusion filled with liquid paraffin simulating a cerebral ventricle. The 2D models were exposed to angular acceleration by a pendulum impact causing 7600 rad/s2 peak rotational acceleration with 6 ms pulse duration. After rotating 100 degrees, the models were decelerated during 30 ms. The trajectory of grid markers was analyzed from high-speed video (1000 frames/s). Rigid-body displacement, shear strain and principal strain were determined from the displacement of three-point sets inferior and superior to the ventricle. For the subventricular (inferior) region in the sophisticated model, approximately 40% lower peak strain values were obtained in the model with ventricle than in the one without. Subcortical displacement was reduced by 12%. Corresponding strain reduction in the subcortical (superior) region was approximately 40% following the acceleration and 25% following the deceleration. Similar but less pronounced effects were found for the semicircular model. The lateral ventricles play an important role as strain relievers and provide natural protection against brain injury.     

Anomalous rate dependence of the preconditioned response of soft tissue during load controlled deformation

It has been observed in load controlled laboratory tests of myocardium and skin that the tissues can exhibit a decrease in nonlinear stiffness with an increase in loading rate: the faster a test is performed, the more compliant is the preconditioned material behavior. This response seems to conflict with what is generally expected of soft tissues based on stretch or strain controlled tests, in which an increased rate of deformation results in a stiffer material response. It is hypothesized that this anomalous behavior has not been observed previously due to the small number of cyclic load controlled mechanical characterization tests that are geared specifically towards viscoelastic tissue response. The goal of this paper is to examine the preconditioned response of soft tissue to load controlled deformation using nonlinear viscoelastic material models including quasi-linear viscoelasticity, and to determine under what conditions this anomalous behavior becomes apparent. Results from this study suggest that this behavior is a true phenomenon unique to load controlled deformations that results from the interplay of nonlinear effects and creep behavior. These results call for increased attention to experimental parameters when testing and modeling nonlinear viscoelastic material behavior.     

A study of rotational brain injury

Of concern in the paper is an investigation on brain injuries which may occur owing to an input angular acceleration of the head. The study is based on the use of an improved mathematical model for the cranium. The eccentricity of the braincase is incorporated through the consideration of a prolate spheroidal shell as the representative of the skull. Also the dissipative mechanical behaviour of the brain material (as per the observations of experimenters) has been accounted for by considering the material contained in the shell as viscoelastic. The problem is formulated in terms of prolate spheroidal coordinates. The singularities of the governing equations of motion (when expressed in the prolate coordinate system) are removed by a suitable transformation of the concerned dependent variable, viz. the one that stands for the angular displacement of a representative point of the system. In the first place the solution of the boundary value problem is sought in the Laplace transform space, by employing a finite difference technique. Use of the alternating-direction-implicit method together with Thomas algorithm was made for obtaining the angular acceleration in the transformed space. The Laplace inversion is also carried out with the help of numerical procedures (Gauss quadrature formula is used for this purpose). The results of the parametric study are presented through graphs. The plots illustrate the shear stresses and strains in the brain medium. A meaningful comparison of the computational results with those of previous investigations indicate that the eccentricity of the braincase plays a significant role in causing injury to the brain.     

Large deformation shear properties of liver tissue

Characterization of the mechanical properties of soft biological tissues is important for establishing the mechanical tolerances of the tissues, and for input to computational models. In this work, the viscoelastic properties of bovine liver tissue in shear loading have been measured using relaxation and constant shear rate loading. The tissue is nonlinearly viscoelastic for strains greater than 0.2%, has a yield strain of approximately 10, and shows moderate strain-rate sensitivity. The response can be modelled using a nonlinear viscoelastic differential model previously developed for brain tissue.     

Dynamic response of the brain with vasculature: a three-dimensional computational study

To date, the influence of the vasculature on the dynamic response of the brain has not been studied with a complete three-dimensional (3D) finite element head model. In this study, short duration rotational (10,000 rad/s(2) with a duration of 5 ms) and translational (100G with a duration of 5 ms) acceleration impulses were applied to the 3D finite element models to study the dynamic response of the brain. The hypothesis of this study was that due to the convoluted organization and non-linear material properties of cerebral vasculature, the difference in maximum principle strain between models with and without vasculature should be minimal. The effects of non-linear material properties and the convoluted structure of the vasculature were examined by comparing the results from the 3D finite element models. The peak average strain reduction in a model with non-linear elastic vasculature and a model with linear elastic vasculature compared to a model without vasculature was 2% and 5%, respectively, indicating that the influence of the vasculature on the dynamic response of the brain is minimal.     

Global/local head models to analyse cerebral blood vessel rupture leading to ASDH and SAH

Blunt and rotational head impacts due to vehicular collisions, falls and contact sports cause relative motion between the brain and skull. This increases the normal and shear stresses in the (skull/brain) interface region consisting of cerebrospinal fluid (CSF) and subarachnoid space (SAS) trabeculae. The relative motion between the brain and skull can explain many types of traumatic brain injuries (TBI) including acute subdural hematomas (ASDH) and subarachnoid hemorrhage (SAH) which is caused by the rupture of bridging veins that transverse from the deep brain tissue to the superficial meningeal coverings. The complicated geometry of the SAS trabeculae makes it impossible to model all the details of the region. Investigators have compromised this layer with solid elements, which may lead to inaccurate results. In this paper, the failure of the cerebral blood vessels due to the head impacts have been investigated. This is accomplished through a global/local modelling approach. Two global models, namely a global solid model (GSM) of the skull/brain and a global fluid model (GFM) of the SAS/CSF, were constructed and were validated. The global models were subjected to two sets of impact loads (head injury criterion, HIC = 740 and 1044). The relative displacements between the brain and skull were determined from GSM. The CSF equivalent fluid pressure due to the impact loads were determined by the GFM. To locally study the mechanism of the injury, the relative displacement between the brain and skull along with the equivalent fluid pressure were implemented into a new local solid model (LSM). The strains of the cerebral blood vessels were determined from LSM. These values were compared with their relevant experimental ultimate strain values. The results showed an agreement with the experimental values indicating that the second impact (HIC = 1044) was strong enough to lead to severe injury. The global/local approach provides a reliable tool to study the cerebral blood vessel ruptures leading to ASDH and/or SAH.     

Validation of an efficient method of assigning material properties in finite element analysis of pelvic bone

Bone in the pelvis is a composite material with a complex anatomical structure that is difficult to model computationally. Rather than assigning material properties to increasingly smaller elements to capture detail in three-dimensional finite element (FE) models, properties can be assigned to Gauss points within larger elements. As part of a validation process, we compared experimental and analytical results from a composite beam under four-point load to FE models with material properties assigned to refined elements and Gauss points within larger elements. Both FE models accurately predicted deformation and the analytical predictions of internal shear stress.     

A strain-hardening bi-power law for the nonlinear behaviour of biological soft tissues

Biological soft tissues exhibit a strongly nonlinear viscoelastic behaviour. Among parenchymous tissues, kidney and liver remain less studied than brain, and a first goal of this study is to report additional material properties of kidney and liver tissues in oscillatory shear and constant shear rate tests. Results show that the liver tissue is more compliant but more strain hardening than kidney. A wealth of multi-parameter mathematical models has been proposed for describing the mechanical behaviour of soft tissues. A second purpose of this work is to develop a new constitutive law capable of predicting our experimental data in the both linear and nonlinear viscoelastic regime with as few parameters as possible. We propose a nonlinear strain-hardening fractional derivative model in which six parameters allow fitting the viscoelastic behaviour of kidney and liver tissues for strains ranging from 0.01 to 1 and strain rates from 0.0151 s^?1 to 0.7 s^?1.     

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.     

On the use of a patient-specific rapid-prototyped model to simulate the response of the human head to impact and comparison with analytical and finite element models

Every year, thousands of fatalities result from head injuries, the majority of which are sustained in automotive accidents. In this paper, an experimental study of the response of the human head to impact is presented. A rapid prototyped model of a human head was generated based on high-resolution magnetic resonance imaging (MRI) scan data. The physical model was subjected to low velocity impacts using a metallic pendulum and a sensitivity study was performed to explore the influence of various parameters, including mass and velocity of the impactor, on the response. The experimental response characteristics are compared with predictions from an analytical model as well as with numerical predictions from finite element (FE) models generated from the same MRI data set. The results from the experimental tests closely match those predicted by both the analytical and the FE models and thus provide us with substantive corroboration of all three approaches. The remarkable agreement obtained between the measured response characteristics of rapid-prototyped skulls and numerical (FE) models obtained from in vivo MRI data clearly demonstrates the potential use of rapid-prototyping to generate experimental models for head impact studies, and, more generally, for the study of the response of complex bio-structures to loading. In addition, the quantitative and qualitative accuracy of the predictions from the analytical model is clearly demonstrated by the FE and experimental corroboration. In particular, the analytical prediction that, as impact mass drops the impact duration becomes increasingly short, appears to be substantiated, which has important implications for the onset of high pressure and shear strain gradients in the brain with potentially deleterious effects.