The dynamic response characteristics of traumatic brain injury

Volumetric MRI Findings in Mild Traumatic Brain Injury (mTBI) and Neuropsychological Outcome

Region of interest (ROI) volumetric assessment has become a standard technique in quantitative neuroimaging. ROI volume is thought to represent a coarse proxy for making inferences about the structural integrity of a brain region when compared to normative values representative of a healthy sample, adjusted for age and various demographic factors. This review focuses on structural volumetric analyses that have been performed in the study of neuropathological effects from mild traumatic brain injury (mTBI) in relation to neuropsychological outcome. From a ROI perspective, the probable candidate structures that are most likely affected in mTBI represent the target regions covered in this review. These include the corpus callosum, cingulate, thalamus, pituitary-hypothalamic area, basal ganglia, amygdala, and hippocampus and associated structures including the fornix and mammillary bodies, as well as whole brain and cerebral cortex along with the cerebellum. Ventricular volumetrics are also reviewed as an indirect assessment of parenchymal change in response to injury. This review demonstrates the potential role and limitations of examining structural changes in the ROIs mentioned above in relation to neuropsychological outcome. There is also discussion and review of the role that post-traumatic stress disorder (PTSD) may play in structural outcome in mTBI. As emphasized in the conclusions, structural volumetric findings in mTBI are likely just a single facet of what should be a multimodality approach to image analysis in mTBI, with an emphasis on how the injury damages or disrupts neural network integrity. The review provides an historical context to quantitative neuroimaging in neuropsychology along with commentary about future directions for volumetric neuroimaging research in mTBI.

A Methodology to Compare Biomechanical Simulations With Clinical Brain Imaging Analysis Utilizing Two Blunt Impact Cases

According to the US Defense and Veterans Brain Injury Center (DVBIC) and Centers for Disease Control and Prevention (CDC), mild traumatic brain injury (mTBI) is a common form of head injury. Medical imaging data provides clinical insight into tissue damage/injury and injury severity, and helps medical diagnosis. Computational modeling and simulation can predict the biomechanical characteristics of such injury, and are useful for development of protective equipment. Integration of techniques from computational biomechanics with medical data assessment modalities (e.g., magnetic resonance imaging or MRI) has not yet been used to predict injury, support early medical diagnosis, or assess effectiveness of personal protective equipment. This paper presents a methodology to map computational simulations with clinical data for interpreting blunt impact TBI utilizing two clinically different head injury case studies. MRI modalities, such as T1, T2, diffusion-weighted imaging (DWI) and apparent diffusion coefficient (ADC), were used for simulation comparisons. The two clinical cases have been reconstructed using finite element analysis to predict head biomechanics based on medical reports documented by a clinician. The findings are mapped to simulation results using image-based clinical analyses of head impact injuries, and modalities that could capture simulation results have been identified. In case 1, the MRI results showed lesions in the brain with skull indentation, while case 2 had lesions in both coup and contrecoup sides with no skull deformation. Simulation data analyses show that different biomechanical measures and thresholds are needed to explain different blunt impact injury modalities; specifically, strain rate threshold corresponds well with brain injury with skull indentation, while minimum pressure threshold corresponds well with coup–contrecoup injury; and DWI has been found to be the most appropriate modality for MRI data interpretation. As the findings from these two cases are substantiated with additional clinical studies, this methodology can be broadly applied as a tool to support injury assessment in head trauma events and to improve countermeasures (e.g., diagnostics and protective equipment design) to mitigate these injuries.

Injury Biomechanics of a Child’s Head: Problems, Challenges and Possibilities with a New aHEAD Finite Element Model

Traumatic brain injury (TBI) is a major public health problem among children. The predominant causes of TBI in young children are motor vehicle accidents, firearm incidents, falls, and child abuse. The limitation of in vivo studies on the human brain has made the finite element modelling an important tool to study brain injury. Numerical models based on the finite element approach can provide valuable data on biomechanics of brain tissues and help explain many pathological conditions. This work reviews the existing numerical models of a child’s head. However, the existing literature is very limited in reporting proper geometric representation of a small child’s head. Therefore, an advanced 2-year-old child’s head model, named aHEAD 2yo (aHEAD: advanced Head models for safety Enhancement And medical Development), has been developed, which advances the state-of-the-art. The model is one of the first published in the literature, which entirely consists of hexahedral elements for three-dimensional (3D) structures of the head, such as the cerebellum, skull, and cerebrum with detailed geometry of gyri and sulci. It includes cerebrospinal fluid as Smoothed Particle Hydrodynamics (SPH) and a detailed model of pressurized bringing veins. Moreover, the presented review of the literature showed that material models for children are now one of the major limitations. There is also no unambiguous opinion as to the use of separate materials for gray and white matter. Thus, this work examines the impact of various material models for the brain on the biomechanical response of the brain tissues during the mechanical loading described by Hardy et al. The study compares the inhomogeneous models with the separation of gray and white matter against the homogeneous models, i.e., without the gray/white matter separation. The developed model along with its verification aims to establish a further benchmark in finite element head modelling for children and can potentially provide new insights into injury mechanisms.

The influence of impact surface on head kinematics and brain tissue response during impacts with equestrian helmets

Current equestrian standards employ a drop test to a rigid steel anvil. However, falls in equestrian sports often result in impacts with soft ground. The purpose of this study was to compare head kinematics and brain tissue response associated with surfaces impacted during equestrian accidents and corresponding helmet certification tests. A helmeted Hybrid III headform was dropped freely onto three different anvils (steel, turf and sand) at three impact locations. Peak linear acceleration, rotational acceleration and impact duration of the headform were measured. Resulting accelerations served as input into a three-dimensional finite element head model, which calculated Maximum principal strain (MPS) and von Mises stress (VMS) in the cerebrum. The results indicated that impacts to a steel anvil produced peak head kinematics and brain tissue responses that were two to three times greater than impacts against both turf and sand. Steel impacts were less than half the duration of turf and sand impacts. The observed response magnitudes obtained in this study suggest that equestrian helmet design should be improved, not only for impacts to rigid surfaces but also to compliant surfaces as response magnitudes for impacts to soft surfaces were still within the reported range for concussion in the literature.

Assessing women's lacrosse head impacts using finite element modelling

Recently studies have assessed the ability of helmets to reduce peak linear and rotational acceleration for women's lacrosse head impacts. However, such measures have had low correlation with injury. Maximum principal strain interprets loading curves which provide better injury prediction than peak linear and rotational acceleration, especially in compliant situations which create low magnitude accelerations but long impact durations. The purpose of this study was to assess head and helmet impacts in women's lacrosse using finite element modelling. Linear and rotational acceleration loading curves from women's lacrosse impacts to a helmeted and an unhelmeted Hybrid III headform were input into the University College Dublin Brain Trauma Model. The finite element model was used to calculate maximum principal strain in the cerebrum. The results demonstrated for unhelmeted impacts, falls and ball impacts produce higher maximum principal strain values than stick and shoulder collisions. The strain values for falls and ball impacts were found to be within the range of concussion and traumatic brain injury. The results also showed that men's lacrosse helmets reduced maximum principal strain for follow-through slashing, falls and ball impacts. These findings are novel and demonstrate that for high risk events, maximum principal strain can be reduced by implementing the use of helmets if the rules of the sport do not effectively manage such situations.

A biomechanical analysis of traumatic brain injury for slips and falls from height

Background

Falls are a common cause of morbidity and mortality in society, particularly among the aged and young. There has been research to describe the epidemiology of these types of events, but to date there has been few correlations of clinical brain injury outcomes and metrics used in biomechanical research; parameters often used to help develop protective devices and environments. The purpose of this research was to examine the kinematic characteristics of falls from standing and higher heights in an effort to understand how clinical brain injury is predicted by biomechanical injury metrics.

Methods

Computer simulations of nine traumatic brain injury events from falling were conducted to determine the biomechanical metrics associated with each injury case.

Results

Many of the impacts were to the occipital region of the head, as would be expected from backward falls or from slipping from ladders. These falls resulted in low rotational acceleration values and high linear accelerations, suggesting linear acceleration may be an important characteristic of this injury mechanism. In addition, even though each case resulted in severe head injury, the HIC15 (Head Injury Criterion) values did not consistently predict injury when the kinematic output was lower than 300 g. This result suggests that HIC15 may have limited value as a predictor for high energy short duration direct impacts to the head. The results supported a relationship between fall height and duration of loss of consciousness, with the higher fall heights producing longer times of unconsciousness.

Conclusion

Linear acceleration may be the metric that should be focused on to develop further strategies to protect against severe TBI for fall cases similar to those in this research. In addition, the HIC15 may not be suitable as a predictive metric for TBI and future development of protective devices for the prevention of head injury should take this into account.