Sub-concussive Hit Characteristics Predict Deviant Brain Metabolism in Football Athletes

Magnetic resonance spectroscopy and helmet telemetry were used to monitor the neural metabolic response to repetitive head collisions in 25 high school American football athletes. Specific hit characteristics were determined highly predictive of metabolic alterations, suggesting that sub-concussive blows can produce biochemical changes and potentially lead to neurological problems

Computational modeling of brain tissue biomechanics at high strain rates

Traumatic brain injury (TBI) has become a significant public health concern. However, despite decades of biomechanics and pathology research, the exact mechanism of injury is poorly understood. Because the injury is inherently mechanical, an accurate description of brain tissue mechanics is essential to better understanding and preventing TBI. Historically, brain tissue has been modeled as a linear or nonlinear viscoelastic material. However, the extracellular fluid in brain tissue is believed to significantly impact the stress distributions and deformations at higher strain rates, such as would occur during an impact or blast injury. Nevertheless, few studies have examined brain tissue as a porous material, and none have employed a nonlinear porous description. In the present work, the theoretical basis for describing gray matter is discussed. As a side-development, it is shown that the two classical porous material theories–Biot\u27s poroelastic theory and continuum mixture theory–are in fact derived from the same thermodynamic constraints and are equivalent. Subsequently, the numerical methods available to simulate brain tissue mechanics are discussed in detail. Ultimately, the finite element method was selected, and a new quadratic, axisymmetric element is developed. The new element is validated against a one-dimensional wave propagation problem. The primary application of the new finite element code is to determine the material properties of gray matter based on highs strain rate compression experimental data. An inverse approach is presented, which resulted in a best fit with mean absolute percent error of approximately 58%. Despite the high error, the model successfully demonstrated that the use of a porous media model captures key features of high strain rate compression behavior in brain tissue and better unifies the quasistatic and high strain rate stress-strain response. The finite element model is also applied to explore two aspects of brain tissue mechanics. First, a series of simulations at various strain rates are evaluated in order to determine the range of strain rates in which the behavior of brain tissue diverges substantially from a polymeric solid. Subsequently, a model of wave propagation in a cylinder of brain tissue is described, and the pressure wave attenuation and frequency response of are evaluated. The successful development of a nonlinear, porous material finite element description of brain tissue represents an improvement in the available analytical tools for studying brain tissue mechanics. Further development and application of the methods presented here may help improve understanding of the brain\u27s response under impact loading and ultimately allow for the development of better preventative technologies

Head impact telemetry in football and correlations with neurophysiological impairment

A growing body of evidence indicates that concussions depend not only on a single offending head impact, but also on the series of subconcussive head impacts prior to concussion. Talavage et al. have shown that several subjects in their cohort of high school football players exhibit substantial changes in their neural health due to subconcussive blows without developing any outward symptoms. They probed neural health through the use of functional magnetic resonance imaging (fMRI). Breedlove et al. subsequently demonstrated that changes in fMRI correlate with the number and location of head impacts experienced throughout the football season. This work builds upon the analysis of Breedlove et al. Regression models based on an updated and expanded data set are presented. This analysis confirms that the number and location of subconcussive head impacts are factors in eliciting deleterious changes in neural health as measured by fMRI. Further analysis indicates that the peak linear acceleration of head impacts is also a factor in eliciting changes in fMRI. Collectively, these results indicate that the subconcussive injury mechanism is analogous to mechanical fatigue or soft tissue overuse injury. Furthermore, comparison of player head impacts based on position (i.e., linemen versus skill positions) indicates that player position may be a risk factor for subconcussive injury due to the large number of head impacts characteristic of linemen. These analyses help elucidate the connection between head impact biomechanics and subconcussive pathophysiology. Analyses indicate that improvements in football equipment and changes in coaching and rules would likely have a protective effect in the prevention of subconcussive and concussive injury in football

Functionally-detected cognitive impairment in high school football players without clinically-diagnosed concussion

Head trauma and concussion in football players have recently received considerable media attention. Postmortem evidence suggests that accrual of damage to the brain may occur with repeated blows to the head, even when the individual blows fail to produce clinical symptoms. There is an urgent need for improved detection and characterization of head trauma to reduce future injury risk and promote development of new therapies. In this study we examined neurological performance and health in the presence of head collision events in high school football players, using longitudinal measures of collision events (the HIT(™) System), neurocognitive testing (ImPACT(™)), and functional magnetic resonance imaging MRI (fMRI). Longitudinal assessment (including baseline) was conducted in 11 young men (ages 15-19 years) participating on the varsity and junior varsity football teams at a single high school. We expected and observed subjects in two previously described categories: (1) no clinically-diagnosed concussion and no changes in neurological behavior, and (2) clinically-diagnosed concussion with changes in neurological behavior. Additionally, we observed players in a previously undiscovered third category, who exhibited no clinically-observed symptoms associated with concussion, but who demonstrated measurable neurocognitive (primarily visual working memory) and neurophysiological (altered activation in the dorsolateral prefrontal cortex [DLPFC]) impairments. This new category was associated with significantly higher numbers of head collision events to the top-front of the head, directly above the DLPFC. The discovery of this new category suggests that more players are suffering neurological injury than are currently being detected using traditional concussion-assessment tools. These individuals are unlikely to undergo clinical evaluation, and thus may continue to participate in football-related activities, even when changes in brain physiology (and potential brain damage) are present, which will increase the risk of future neurological injury

Development of brain atlases for early-to-middle adolescent collision-sport athletes

Human brains develop across the life span and largely vary in morphology. Adolescent collision-sport athletes undergo repetitive head impacts over years of practices and competitions, and therefore may exhibit a neuroanatomical trajectory different from healthy adolescents in general. However, an unbiased brain atlas targeting these individuals does not exist. Although standardized brain atlases facilitate spatial normalization and voxel-wise analysis at the group level, when the underlying neuroanatomy does not represent the study population, greater biases and errors can be introduced during spatial normalization, confounding subsequent voxel-wise analysis and statistical findings. In this work, targeting early-to-middle adolescent (EMA, ages 13-19) collision-sport athletes, we developed population-specific brain atlases that include templates (T1-weighted and diffusion tensor magnetic resonance imaging) and semantic labels (cortical and white matter parcellations). Compared to standardized adult or age-appropriate templates, our templates better characterized the neuroanatomy of the EMA collision-sport athletes, reduced biases introduced during spatial normalization, and exhibited higher sensitivity in diffusion tensor imaging analysis. In summary, these results suggest the population-specific brain atlases are more appropriate towards reproducible and meaningful statistical results, which better clarify mechanisms of traumatic brain injury and monitor brain health for EMA collision-sport athletes.</p