The performance of equestrian helmets to protect against brain injuries caused by fall impacts against compliant surfaces such as turf has not been studied widely. We characterise the kinematic response of simulated fall impacts to turf through field tests on horse racetracks and laboratory experiments. The kinematic response characteristics and ground stiffness at different Going Ratings (standard measurement of racetrack condition) were obtained from 1m and 2m drop tests of an instrumented hemispherical impactor onto a turf racetrack. The 'Hard' rating resulted in higher peak linear accelerations and stiffness, and shorter impact durations than the 'Soft' and 'Heavy' ratings. Insignificant differences were found among the other Going Ratings, but a strong overall relationship was evident between the 'Going Rating' and the kinematic response. This relationship was used to propose a series of three synthetic foam anvils as turf surrogates in equestrian falls corresponding to ranges of Going Ratings of (i) Heavy-Soft, (ii) Good-Firm, and (iii) Firm-Hard. Laboratory experiments consisted of a helmeted headform being dropped onto natural turf and the turf surrogate anvils using a monorail drop rig. These experiments revealed that the magnitudes and durations of the linear and rotational accelerations for helmeted impacts to turf/turf surrogates were similar to those in concussive sports falls and collisions. Since the compliance of an impacted surface influences the dynamic response of a jockey's head during a fall impact against the ground, it is important that this is considered during both accident reconstructions and helmet certification tests.

In studying traumatic brain injury (TBI), it has been long hypothesized that the head is more vulnerable to injury from impacts in certain directions or locations, as the relationship between impact force and the resulting neurological outcome is complex and can vary significantly between individual cases. Many studies have identified head angular acceleration to be the putative cause of brain trauma, but it is not well understood how impact location can affect the resulting head kinematics and tissue strain. Here, we identify the susceptibility of the head to accelerations and brain strain from normal forces at contact points across the surface of the skull and jaw using a three-dimensional, 20-degree-of-freedom rigid-body head and cervical spine model. We find that head angular acceleration and brain tissue strain resulting from an input force can vary by orders of magnitude based on impact location on the skull, with the mandible as the most vulnerable region. Conversely, head linear acceleration is not sensitive to contact location. Using these analyses, we present an optimization scheme to distribute helmet padding thickness to minimize angular acceleration, resulting in a reduction of angular acceleration by an estimated 25% at the most vulnerable contact point compared to uniform thickness padding. This work gives intuition behind the relationship between input force and resulting brain injury risk, and presents a framework for developing and evaluating novel head protection gear.

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

Military personnel sustain head and brain injuries as a result of ballistic, blast, and blunt impact threats. Combat helmets are meant to protect the heads of these personnel during injury events. Studies show peak kinematics and kinetics are attenuated using protective headgear during impacts; however, there is limited experimental biomechanical literature that examines whether or not helmets mitigate peak mechanics delivered to the head and brain during blast. While the mechanical links between blast and brain injury are not universally agreed upon, one hypothesis is that blast energy can be transmitted through the head and into the brain. These transmissions can lead to rapid skull flexure and elevated pressures in the cranial vault, and, therefore, may be relevant in determining injury likelihood. Therefore, it could be argued that assessing a helmet for the ability to mitigate mechanics may be an appropriate paradigm for assessing the potential protective benefits of helmets against blast. In this work, we use a surrogate model of the head and brain to assess whether or not helmets and eye protection can alter mechanical measures during both head-level face-on blast and high forehead blunt impact events. Measurements near the forehead suggest head protection can attenuate brain parenchyma pressures by as much as 49% during blast and 52% during impact, and forces on the inner table of the skull by as much as 80% during blast and 84% during impact, relative to an unprotected head.

Causes of autism spectrum disorders (ASD) are understood poorly, making diagnosis and treatment challenging. While many studies have investigated the biochemical and genetic aspects of ASD, whether and how mechanical characteristics of the autistic brain can modulate neuronal connectivity and cognition in ASD are unknown. Previously, it has been shown that ASD brains are characterized by abnormal white matter and disorganized neuronal connectivity; we hypothesized that these significant cellular-level structural changes may translate to changes in the mechanical properties of the autistic brain or regions therein. Here, we focused on tuberous sclerosis complex (TSC), a genetic disorder with a high penetrance of ASD. We investigated mechanical differences between murine brains obtained from control and TSC cohorts at various deformation length- and time-scales. At the microscale, we conducted creep-compliance and stress relaxation experiments using atomic force microscope(AFM)-enabled indentation. At the mesoscale, we conducted impact indentation using a pendulum-based instrumented indenter to extract mechanical energy dissipation metrics. At the macroscale, we used oscillatory shear rheology to quantify the frequency-dependent shear moduli. Despite significant changes in the cellular organization of TSC brain tissue, we found no corresponding changes in the quantified mechanical properties at every length- and time-scale explored. This investigation of the mechanical characteristics of the brain has broadened our understanding of causes and markers of TSC/ASD, while raising questions about whether any mechanical differences can be detected in other animal models of ASD or other disease models that also feature abnormal brain structure.

Concussions are among the most common injuries sustained by goaltenders. Concussive injuries are characterized by impairment to neurological function which can affect many different brain regions. Understanding how different impact loading conditions (event type and impact site) affect the brain tissue response may help identify what kind of impacts create a high risk of injury to specific brain regions. The purpose of this study was to examine the influence of different impact conditions on the distribution of brain strain for ice hockey goaltender impacts. An instrumented headform was fitted with an ice hockey goaltender mask and impacted under a protocol which was developed using video analysis of real world ice hockey goaltender concussions for three different impact events (collision, puck, and fall). The resulting kinematic response served as input into the University College Dublin Brain Trauma Model (UCDBTM), which calculated maximum principal strain (MPS) in the cerebrum. Strain subsets were then determined and analyzed. Resulting peak strains (0.124–0.328) were found to be within the range for concussion reported in the literature. The results demonstrated that falls and collisions produced larger strain subsets in the cerebrum than puck impacts which is likely a reflection of longer impact duration for falls and collisions than puck impacts. For each impact event, impact site was also found to produce strain subsets of varying size and configuration. The results of this study suggest that the location and number of brain regions which can be damaged depend on the loading conditions of the impact.

Understanding of in vivo brain biomechanical behavior is critical in the study of traumatic brain injury (TBI) mechanisms and prevention. Using tagged magnetic resonance imaging, we measured spatiotemporal brain deformations in 34 healthy human volunteers under mild angular accelerations of the head. Two-dimensional (2D) Lagrangian strains were examined throughout the brain in each subject. Strain metrics peaked shortly after contact with a padded stop, corresponding to the inertial response of the brain after head deceleration. Maximum shear strain of at least 3% was experienced at peak deformation by an area fraction (median±standard error) of 23.5±1.8% of cortical gray matter, 15.9±1.4% of white matter, and 4.0±1.5% of deep gray matter. Cortical gray matter strains were greater in the temporal cortex on the side of the initial contact with the padded stop and also in the contralateral temporal, frontal, and parietal cortex. These tissue-level deformations from a population of healthy volunteers provide the first in vivo measurements of full-volume brain deformation in response to known kinematics. Although strains differed in different tissue type and cortical lobes, no significant differences between male and female head accelerations or strain metrics were found. These cumulative results highlight important kinematic features of the brain's mechanical response and can be used to facilitate the evaluation of computational simulations of TBI.

Intrinsic cardiac-induced deformation of brain tissue is thought to be important in the pathophysiology of various neurological disorders. In this study, we evaluated the feasibility of utilizing displacement encoding with stimulated echoes (DENSE) magnetic resonance imaging (MRI) to quantify two-dimensional (2D) neural tissue strain using cardiac-driven brain pulsations. We examined eight adult healthy volunteers with an electrocardiogram-gated spiral DENSE sequence performed at the midsagittal plane on a 3 Tesla MRI scanner. Displacement, pixel-wise trajectories, and principal strains were determined in seven regions of interest (ROI): the brain stem, cerebellum, corpus callosum, and four cerebral lobes. Quantification of small neural tissue motion and strain along with their spatial and temporal variations in different brain regions was found to be feasible using DENSE. The medial and inferior brain structures (brain stem, cerebellum, and corpus callosum) had significantly larger motion and strain compared to structures located more peripherally. The brain stem had the largest peak mean displacement (PMD) (187 ± 50 μ m, mean ± SD). The largest mean principal strains in compression and extension were observed in the brain stem (0.38 ± 0.08%) and the corpus callosum (0.37 ± 0.08%), respectively. Measured values in percent strain were altered by as much as 0.1 between repeated scans. This study showed that DENSE can quantify regional variations in brain tissue motion and strain and has the potential to be utilized as a tool to evaluate the changes in brain tissue dynamics resulting from alterations in biomechanical stresses and tissue properties.

Linking head kinematics to injury risk has been the focus of numerous brain injury criteria. Although many early forms were developed using mechanics principles, recent criteria have been developed using empirical methods based on subsets of head impact data. In this study, a single-degree-of-freedom (sDOF) mechanical analog was developed to parametrically investigate the link between rotational head kinematics and brain deformation. Model efficacy was assessed by comparing the maximum magnitude of displacement to strain-based brain injury predictors from finite element (FE) human head models. A series of idealized rotational pulses covering a broad range of acceleration and velocity magnitudes (0.1–15 krad/s 2 and 1–100 rad/s) with durations between 1 and 3000 ms were applied to the mechanical models about each axis of the head. Results show that brain deformation magnitude is governed by three categories of rotational head motion each distinguished by the duration of the pulse relative to the brain's natural period: for short-duration pulses, maximum brain deformation depended primarily on angular velocity magnitude; for long-duration pulses, brain deformation depended primarily on angular acceleration magnitude; and for pulses relatively close to the natural period, brain deformation depended on both velocity and acceleration magnitudes. These results suggest that brain deformation mechanics can be adequately explained by simple mechanical systems, since FE model responses and experimental brain injury tolerances exhibited similar patterns to the sDOF model. Finally, the sDOF model was the best correlate to strain-based responses and highlighted fundamental limitations with existing rotational-based brain injury metrics.

Mild blast traumatic brain injury (bTBI) accounts for the majority of brain injury in United States service members and other military personnel worldwide. The mechanisms of primary blast brain injury continue to be disputed with little evidence to support one or a combination of theories. The main hypotheses addressed in this review are blast wave transmission through the skull orifices, direct cranial transmission, skull flexure dynamics, thoracic surge, acceleration, and cavitation. Each possible mechanism is discussed using available literature with the goal of focusing research efforts to address the limitations and challenges that exist in blast injury research. Multiple mechanisms may contribute to the pathology of bTBI and could be dependent on magnitudes and orientation to blast exposure. Further focused biomechanical investigation with cadaver, in vivo, and finite element models would advance our knowledge of bTBI mechanisms. In addition, this understanding could guide future research and contribute to the greater goal of developing relevant injury criteria and mandates to protect our soldiers on the battlefield.

Neural recording and stimulation with high spatial and temporal resolution are highly desirable in the study of neurocommunication and diseases. Planar multiple microelectrode arrays (MEA) or quasi-three-dimensional (3D) MEA with fixed height have been proposed by many researchers and become commercially available. In this paper, we present the design, fabrication, and test of a novel true 3D multiple electrode array for brain slice stimulation and recording. This MEA is composed of 105 microelectrodes with 50 μ m diameter and 125 μ m center-to-center spacing integrated in a 1.2 × 1.2 mm 2 area. This “true” 3D MEA allows us to precisely position the individual electrodes by piezoelectric-based actuators to penetrate the inactive tissue layer and to approach the active neurons so as to optimize the recording and stimulation of electrical field potential. The capability to stimulate nerve fibers and record postsynaptic field potentials was demonstrated in an experiment using mouse brain hippocampus slice.

Indentation experiments offer a robust, fast, and repeatable testing method for evaluating the mechanical properties of the solid-state materials in a wide stiffness range. With the advantage of requiring a minimal sample preparation and multiple tests on a small piece of specimen, this method has recently become a popular technique for measuring the elastic properties of the biological materials, especially the brain tissue whose ultrasoft nature makes its mechanical characterization very challenging. Nevertheless, some limitations are associated with the indentation of the brain tissue, such as improper surface detection, negative initial contact force due to tip-tissue moisture interaction, and partial contact between the tip and the sample. In this study, an indirect indentation scheme is proposed to overcome the aforementioned difficulties. In this way, the indentation force is transferred from a sharp tip to the surface of the tissue slices via a rigid coverslip. To demonstrate the accuracy of this method, the linear viscoelastic properties of the white and gray matters of the bovine brain samples are measured by imposing small cyclic loads at different frequencies. The rate, regional, directional, and postmortem time dependence of the viscoelastic moduli are investigated and compared with the previous results from cyclic shear and monotonic experiments on the brain tissue. While findings of this research present a comprehensive set of information for the viscoelastic properties of the brain at a wide frequency range, the central goal of this paper is to introduce a novel experimentation technique with noticeable advantages for biomechanical characterization of the soft tissue.

Tissue cooling has been proven as a viable therapy for multiple conditions and injuries and has been applied to the brain to treat epilepsy and concussions, leading to improved long-term outcomes. To facilitate the study of temperature reduction as a function of various cooling methods, a thermal brain phantom was developed and analyzed. The phantom is composed of a potassium-neutralized, superabsorbent copolymer hydrogel. The phantom was tested in a series of cooling trials using a cooling block and 37 deg water representing nondirectional blood flow ranging up to 6 gph, a physiologically representative range based on the prototype volume. Results were compared against a validated finite difference (FD) model. Two sets of parameters were used in the FD model: one set to represent the phantom itself and a second set to represent brain parenchyma. The model was then used to calculate steady-state cooling at a depth of 5 mm for all flow rates, for both the phantom and a model of the brain. This effort was undertaken to (1) validate the FD model against the phantom results and (2) evaluate how similar the thermal response of the phantom is to that of a perfused brain. The FD phantom model showed good agreement with the empirical phantom results. Furthermore, the empirical phantom agreed with the predicted brain response within 3.5% at physiological flow, suggesting a biofidelic thermal response. The phantom will be used as a platform for future studies of thermally mediated therapies applied to the cerebral cortex.

In traumatic brain injury (TBI), membranes such as the dura mater, arachnoid mater, and pia mater play a vital role in transmitting motion from the skull to brain tissue. Magnetic resonance elastography (MRE) is an imaging technique developed for noninvasive estimation of soft tissue material parameters. In MRE, dynamic deformation of brain tissue is induced by skull vibrations during magnetic resonance imaging (MRI); however, skull motion and its mode of transmission to the brain remain largely uncharacterized. In this study, displacements of points in the skull, reconstructed using data from an array of MRI-safe accelerometers, were compared to displacements of neighboring material points in brain tissue, estimated from MRE measurements. Comparison of the relative amplitudes, directions, and temporal phases of harmonic motion in the skulls and brains of six human subjects shows that the skull–brain interface significantly attenuates and delays transmission of motion from skull to brain. In contrast, in a cylindrical gelatin “phantom,” displacements of the rigid case (reconstructed from accelerometer data) were transmitted to the gelatin inside (estimated from MRE data) with little attenuation or phase lag. This quantitative characterization of the skull–brain interface will be valuable in the parameterization and validation of computer models of TBI.

Most studies on football helmet performance focus on lowering head acceleration-related parameters to reduce concussions. This has resulted in an increase in helmet size and mass. The objective of this paper was to study the effect of helmet mass on head and upper neck responses. Two independent test series were conducted. In test series one, 90 pendulum impact tests were conducted with four different headform and helmet conditions: unhelmeted Hybrid III headform, Hybrid III headform with a football helmet shell, Hybrid III headform with helmet shell and facemask, and Hybrid III headform with the helmet and facemask with mass added to the shell (n = 90). The Hybrid III neck was used for all the conditions. For all the configurations combined, the shell only, shell and facemask, and weighted helmet conditions resulted in 36%, 43%, and 44% lower resultant head accelerations (p < 0.0001), respectively, when compared to the unhelmeted condition. Head delta-V reductions were 1.1%, 4.5%, and 4.4%, respectively. In contrast, the helmeted conditions resulted in 26%, 41%, and 49% higher resultant neck forces (p < 0.0001), respectively. The increased neck forces were dominated by neck tension. In test series two, testing was conducted with a pneumatic linear impactor (n = 178). Fourteen different helmet makes and models illustrate the same trend. The increased neck forces provide a possible explanation as to why there has not been a corresponding reduction in concussion rates despite improvements in helmets ability to reduce head accelerations.

Stroke caused by an embolism accounts for about a third of all stroke cases. Understanding the source and cause of the embolism is critical for diagnosis and long-term treatment of such stroke cases. The complex nature of the transport of an embolus within large arteries is a primary hindrance to a clear understanding of embolic stroke etiology. Recent advances in medical image-based computational hemodynamics modeling have rendered increasing utility to such techniques as a probe into the complex flow and transport phenomena in large arteries. In this work, we present a novel, patient-specific, computational framework for understanding embolic stroke etiology, by combining image-based hemodynamics with discrete particle dynamics and a sampling-based analysis. The framework allows us to explore the important question of how embolism source manifests itself in embolus distribution across the various major cerebral arteries. Our investigations illustrate prominent numerical evidence regarding (i) the size/inertia-dependent trends in embolus distribution to the brain; (ii) the relative distribution of cardiogenic versus aortogenic emboli among the anterior, middle, and posterior cerebral arteries; (iii) the left versus right brain preference in cardio-emboli and aortic-emboli transport; and (iv) the source–destination relationship for embolisms affecting the brain.

Convection enhanced delivery (CED) is a promising novel technology to treat neural diseases, as it can transport macromolecular therapeutic agents greater distances through tissue by direct infusion. To minimize off-target delivery, our group has developed 3D computational transport models to predict infusion flow fields and tracer distributions based on magnetic resonance (MR) diffusion tensor imaging data sets. To improve the accuracy of our voxelized models, generalized anisotropy (GA), a scalar measure of a higher order diffusion tensor obtained from high angular resolution diffusion imaging (HARDI) was used to improve tissue segmentation within complex tissue regions of the hippocampus by capturing small feature fissures. Simulations were conducted to reveal the effect of these fissures and cerebrospinal fluid (CSF) boundaries on CED tracer diversion and mistargeting. Sensitivity analysis was also conducted to determine the effect of dorsal and ventral hippocampal infusion sites and tissue transport properties on drug delivery. Predicted CED tissue concentrations from this model are then compared with experimentally measured MR concentration profiles. This allowed for more quantitative comparison between model predictions and MR measurement. Simulations were able to capture infusate diversion into fissures and other CSF spaces which is a major source of CED mistargeting. Such knowledge is important for proper surgical planning.

Shear waves that propagate in soft solids, such as the brain, are strongly nonlinear and can develop into shock waves in less than one wavelength. We hypothesize that these shear shock waves could be responsible for certain types of traumatic brain injuries (TBI) and that the spherical geometry of the skull bone could focus shear waves deep in the brain, generating diffuse axonal injuries. Theoretical models and numerical methods that describe nonlinear polarized shear waves in soft solids such as the brain are presented. They include the cubic nonlinearities that are characteristic of soft solids and the specific types of nonclassical attenuation and dispersion observed in soft tissues and the brain. The numerical methods are validated with analytical solutions, where possible, and with self-similar scaling laws where no known solutions exist. Initial conditions based on a human head X-ray microtomography (CT) were used to simulate focused shear shock waves in the brain. Three regimes are investigated with shock wave formation distances of 2.54 m , 0.018 m , and 0.0064 m . We demonstrate that under realistic loading scenarios, with nonlinear properties consistent with measurements in the brain, and when the shock wave propagation distance and focal distance coincide, nonlinear propagation can easily overcome attenuation to generate shear shocks deep inside the brain. Due to these effects, the accelerations in the focal are larger by a factor of 15 compared to acceleration at the skull surface. These results suggest that shock wave focusing could be responsible for diffuse axonal injuries.

Multiple injury-causing mechanisms, such as wave propagation, skull flexure, cavitation, and head acceleration, have been proposed to explain blast-induced traumatic brain injury (bTBI). An accurate, quantitative description of the individual contribution of each of these mechanisms may be necessary to develop preventive strategies against bTBI. However, to date, despite numerous experimental and computational studies of bTBI, this question remains elusive. In this study, using a two-dimensional (2D) rat head model, we quantified the contribution of head acceleration to the biomechanical response of brain tissues when exposed to blast waves in a shock tube. We compared brain pressure at the coup, middle, and contre-coup regions between a 2D rat head model capable of simulating all mechanisms (i.e., the all-effects model) and an acceleration-only model. From our simulations, we determined that head acceleration contributed 36–45% of the maximum brain pressure at the coup region, had a negligible effect on the pressure at the middle region, and was responsible for the low pressure at the contre-coup region. Our findings also demonstrate that the current practice of measuring rat brain pressures close to the center of the brain would record only two-thirds of the maximum pressure observed at the coup region. Therefore, to accurately capture the effects of acceleration in experiments, we recommend placing a pressure sensor near the coup region, especially when investigating the acceleration mechanism using different experimental setups.