Correlation of Concussion Symptom Profile with Head Impact Biomechanics: A Case for Individual-Specific Injury Tolerance

Characterizing Head Acceleration Events in Law Enforcement Cadets During Subject Control Technique Training

Law enforcement cadets (LECs) complete weeks of subject control technique training. Similar sport-related combat training has been shown to expose participants to head acceleration events (HAEs) that have potential to result in short- and long-term impairments. The purpose of this study was to describe the number and magnitude of HAEs in LECs throughout their training. 37 LECs (7 females; age = 30.6 ± 8.8 years; BMI = 30.0 ± 6.0) were recruited from a law enforcement organization. Participants wore instrumented mouthguards, which recorded all HAEs exceeding a resultant 5 g threshold for training sessions with the potential for HAEs. Participants completed three defensive tactics (DT) training sessions, a DT skill assessment (DTA), and three boxing sessions. Outcome measures included the number of HAEs, peak linear acceleration (PLA), and peak rotational velocity (PRV). There were 2758 true-positive HAEs recorded across the duration of the study. Boxing sessions accounted for 63.7% of all true-positive HAEs, while DT accounted for 31.4% and DTA accounted for 4.9%. Boxing sessions resulted in a higher number of HAEs per session (F2,28 = 48.588, p < 0.001, ηp2 = 0.776), and higher median PLA (F2,28 = 8.609, p = 0.001, ηp2 = 0.381) and median PRV (F2,28 = 11.297, p < 0.001, ηp2 = 0.447) than DT and DTA. The LECs experience a high number of HAEs, particularly during boxing sessions. Although this training is necessary for job duties, HAE monitoring may lead to modifications in training structure to improve participant safety and enhance recovery.

A Method for Evaluating Brain Deformation Under Sagittal Blunt Impacts Using a Half-Skull Human-Scale Surrogate

Trauma to the brain is a biomechanical problem where the initiating event is a dynamic loading (blunt, inertial, blast) to the head. To understand the relationship between the mechanical parameters of the injury and the spatial and temporal deformation patterns in the brain, there is a need to develop a reusable and adaptable experimental traumatic brain injury (TBI) model that can measure brain motion under varying parameters. In this effort, we aim to directly measure brain deformation (strain and strain rates) in different brain regions in a human head model using a drop tower.

METHODS

Physical head models consisting of a half, sagittal plane skull, brain, and neck were constructed and subjected to crown and frontal impacts at two impact speeds. All tests were recorded with a high-speed camera at 1000 frames per second. Motion of visual markers within brain surrogates were used to track deformations and calculate spatial strain histories in 6 brain regions of interest. Principal strains, strain rates and strain impulses were calculated and reported.

RESULTS

Higher impact velocities corresponded to higher strain values across all impact scenarios. Crown impacts were characterized by high, long duration strains distributed across the parietal, frontal and hippocampal regions whereas frontal impacts were characterized by sharply rising and falling strains primarily found in the parietal, frontal, hippocampal and occipital regions. High strain rates were associated with short durations and impulses indicating fast but short-lived strains. 2.23 m/s (5 mph) crown impacts resulted in 53% of the brain with shear strains higher than 0.15 verses 32% for frontal impacts.

CONCLUSIONS

The results reveal large differences in the spatial and temporal strain responses between crown and forehead impacts. Overall, the results suggest that for the same speed, crown impact leads to higher magnitude strain patterns than a frontal impact. The data provided by this model provides unique insight into the spatial and temporal deformation patterns that have not been provided by alternate surrogate models. The model can be used to investigate how anatomical, material and loading features and parameters can affect deformation patterns in specific regions of interest in the brain.

Comparing Impact and Concussion Risk in Leatherhead and Modern Football and Hockey Helmets

BACKGROUND

Improvements in the modern helmet have demonstrated beneficial effects in reducing concussion risk in football players. However, previous studies yield conflicting results regarding the protective quality of leatherhead football helmets. There is limited research comparing the modern football helmet and the modern hockey helmet, with one previous study demonstrating the football helmet as providing a lower risk of concussion.

OBJECTIVE

To compare the head acceleration produced in a leatherhead football helmet vs a modern football helmet vs a modified modern football helmet with softer padding vs a modern hockey helmet in helmet-to-helmet strikes.

METHODS

Accelerometers were placed on the frontal, apex, and parietal regions of a Century Body Opponent Bag manikin. Each type of helmet was placed on the manikin and struck by a swinging modern football helmet. The G-force acceleration was determined in three-dimensional axes of 100 total helmet-to-helmet impacts.

RESULTS

The leatherhead football helmet was the least protective in reducing G-forces. The modified modern football helmet did not provide a significant difference compared with the modern football helmet. Significantly greater G-forces were produced in a collision between 2 modern football helmets in comparison with 2 modern hockey helmets.

CONCLUSION

The leatherhead football helmet was the least protective, and the hockey helmet was the most protective, with the football helmet being intermediate. This study provides additional insight into the inconclusive evidence regarding the safety of leatherhead football helmets and into the design of football and hockey helmets in the future.

Motor vehicle crash concussion mechanism displays a greater total number of symptoms and greater affective symptom severity but no neurocognitive differences compared with sport-related concussion mechanism

Previous research among adolescents has shown differences in symptoms and neurocognitive performance between sport-related (SRC) and motor vehicle crash (MVC) concussion mechanisms. Limited research has focused on young adults. The purpose of our study was to compare symptoms, balance, and neurocognitive performance between SRC and MVC mechanisms in young adults. Forty-three (58.1% female, age = 25.5 ± 3.2 years, days since concussion = 12.8 ± 12.7) and 26 (76.9% female, age = 24.1 ± 5.6 years, days since concussion = 12.6 ± 8.3) individuals with an SRC and MVC mechanism, respectively, participated. Primary outcome measures included the total number, severity, cluster (disorientation, migraine, lethargy, and affective) of post-concussion symptoms endorsed, Balance Error Scoring System (BESS), and CNS Vital Signs scores. Clusters are subgroups of symptoms used for targeted rehabilitation. We used independent t-tests and Mann-Whitney U tests to compare symptoms, BESS, and neurocognitive performance. Cliff's Delta effect size was interpreted as negligible (<0.15), small (0.15-0.33), medium (0.34-0.47), and large (≥0.48). There were no group differences for any demographic factors or preexisting conditions (p-range = 0.112-0.991). Participants with an MVC mechanism reported a greater number of total post-concussion symptoms (p = 0.025, Cliff's Delta = 0.32) and a more severe affective symptom cluster (p = 0.010, Cliff's Delta = 0.37). There were no group differences for BESS or neurocognitive performance after correcting for multiple comparisons. The MVC mechanism resulted in a greater total symptom burden relative to the SRC mechanism. Medical practitioners and individuals experiencing a concussion should know that concussions are heterogeneous within and across various mechanisms.

A Review of Head Injury Metrics Used in Automotive Safety and Sports Protective Equipment

Despite advances in the understanding of human tolerances to brain injury, injury metrics used in automotive safety and protective equipment standards have changed little since they were first implemented nearly a half-century ago. Although numerous metrics have been proposed as improvements over the ones currently used, evaluating the predictive capability of these metrics is challenging. The purpose of this review is to summarize existing head injury metrics that have been proposed for both severe head injuries, such as skull fractures and traumatic brain injuries (TBI), and mild traumatic brain injuries (mTBI) including concussions. Metrics have been developed based on head kinematics or intracranial parameters such as brain tissue stress and strain. Kinematic metrics are either based on translational motion, rotational motion, or a combination of the two. Tissue-based metrics are based on finite element model simulations or in vitro experiments. This review concludes with a discussion of the limitations of current metrics and how improvements can be made in the future.

Use of Brain Biomechanical Models for Monitoring Impact Exposure in Contact Sports

Head acceleration measurement sensors are now widely deployed in the field to monitor head kinematic exposure in contact sports. The wealth of impact kinematics data provides valuable, yet challenging, opportunities to study the biomechanical basis of mild traumatic brain injury (mTBI) and subconcussive kinematic exposure. Head impact kinematics are translated into brain mechanical responses through physics-based computational simulations using validated brain models to study the mechanisms of injury. First, this article reviews representative legacy and contemporary brain biomechanical models primarily used for blunt impact simulation. Then, it summarizes perspectives regarding the development and validation of these models, and discusses how simulation results can be interpreted to facilitate injury risk assessment and head acceleration exposure monitoring in the context of contact sports. Recommendations and consensus statements are presented on the use of validated brain models in conjunction with kinematic sensor data to understand the biomechanics of mTBI and subconcussion. Mainly, there is general consensus that validated brain models have strong potential to improve injury prediction and interpretation of subconcussive kinematic exposure over global head kinematics alone. Nevertheless, a major roadblock to this capability is the lack of sufficient data encompassing different sports, sex, age and other factors. The authors recommend further integration of sensor data and simulations with modern data science techniques to generate large datasets of exposures and predicted brain responses along with associated clinical findings. These efforts are anticipated to help better understand the biomechanical basis of mTBI and improve the effectiveness in monitoring kinematic exposure in contact sports for risk and injury mitigation purposes.

Consensus Head Acceleration Measurement Practices (CHAMP): Study Design and Statistical Analysis

Head impact measurement devices enable opportunities to collect impact data directly from humans to study topics like concussion biomechanics, head impact exposure and its effects, and concussion risk reduction techniques in sports when paired with other relevant data. With recent advances in head impact measurement devices and cost-effective price points, more and more investigators are using them to study brain health questions. However, as the field's literature grows, the variance in study quality is apparent. This brief paper aims to provide a high-level set of key considerations for the design and analysis of head impact measurement studies that can help avoid flaws introduced by sampling biases, false data, missing data, and confounding factors. We discuss key points through four overarching themes: study design, operational management, data quality, and data analysis.

Concussion Prone Scenarios: A Multi-Dimensional Exploration in Impact Directions, Brain Morphology, and Network Architectures Using Computational Models

While individual susceptibility to traumatic brain injury (TBI) has been speculated, past work does not provide an analysis considering how physical features of an individual's brain (e.g., brain size, shape), impact direction, and brain network features can holistically contribute to the risk of suffering a TBI from an impact. This work investigated each of these features simultaneously using computational modeling and analyses of simulated functional connectivity. Unlike the past studies that assess the severity of TBI based on the quantification of brain tissue damage (e.g., principal strain), we approached the brain as a complex network in which neuronal oscillations orchestrate to produce normal brain function (estimated by functional connectivity) and, to this end, both the anatomical damage location and its topological characteristics within the brain network contribute to the severity of brain function disruption and injury. To represent the variations in the population, we analyzed a publicly available database of brain imaging data and selected five distinct network architectures, seven different brain sizes, and three uniaxial head rotational conditions to study the consequences of 74 virtual impact scenarios. Results show impact direction produces the most significant change in connections across brain areas (structural connectome) and the functional coupling of activity across these brain areas (functional connectivity). Axial rotations were more injurious than those with sagittal and coronal rotations when the head kinematics were the same for each condition. When the impact direction was held constant, brain network architecture showed a significantly different vulnerability across axial and sagittal, but not coronal rotations. As expected, brain size significantly affected the expected change in structural and functional connectivity after impact. Together, these results provided groupings of predicted vulnerability to impact-a subgroup of male brain architectures exposed to axial impacts were most vulnerable, while a subgroup of female brain architectures was the most tolerant to the sagittal impacts studied. These findings lay essential groundwork for subject-specific analyses of concussion and provide invaluable guidance for designing personalized protection equipment.

Time Delta Head Impact Frequency: An Analysis on Head Impact Exposure in the Lead Up to a Concussion: Findings from the NCAA-DOD Care Consortium

Sport-related concussions can result from a single high magnitude impact that generates concussive symptoms, repeated subconcussive head impacts aggregating to generate concussive symptoms, or a combined effect from the two mechanisms. The array of symptoms produced by these mechanisms may be clinically interpreted as a sport-related concussion. It was hypothesized that head impact exposure resulting in concussion is influenced by severity, total number, and frequency of subconcussive head impacts. The influence of total number and magnitude of impacts was previously explored, but frequency was investigated to a lesser degree. In this analysis, head impact frequency was investigated over a new metric called ‘time delta’, the time difference from the first recorded head impact of the day until the concussive impact. Four exposure metrics were analyzed over the time delta to determine whether frequency of head impact exposure was greater for athletes on their concussion date relative to other dates of contact participation. Those metrics included head impact frequency, head impact accrual rate, risk weighted exposure (RWE), and RWE accrual rate. Athletes experienced an elevated median number of impacts, RWE, and RWE accrual rate over the time delta on their concussion date compared to non-injury sessions. This finding suggests elevated frequency of head impact exposure on the concussion date compared to other dates that may precipitate the onset of concussion.

Consensus Head Acceleration Measurement Practices (CHAMP): Origins, Methods, Transparency and Disclosure

The use of head kinematic measurement devices has recently proliferated owing to technology advances that make such measurement more feasible. In parallel, demand to understand the biomechanics of head impacts and injury in sports and the military has increased as the burden of such loading on the brain has received focused attention. As a result, the field has matured to the point of needing methodological guidelines to improve the rigor and consistency of research and reduce the risk of scientific bias. To this end, a diverse group of scientists undertook a comprehensive effort to define current best practices in head kinematic measurement, culminating in a series of manuscripts outlining consensus methodologies and companion summary statements. Summary statements were discussed, revised, and voted upon at the Consensus Head Acceleration Measurement Practices (CHAMP) Conference in March 2022. This manuscript summarizes the motivation and methods of the consensus process and introduces recommended reporting checklists to be used to increase transparency and rigor of future experimental design and publication of work in this field. The checklists provide an accessible means for researchers to apply the best practices summarized in the companion manuscripts when reporting studies utilizing head kinematic measurement in sport and military settings.

American Football Helmet Effectiveness Against a Strain-Based Concussion Mechanism

Brain strain is increasingly being used in helmet design and safety performance evaluation as it is generally considered as the primary mechanism of concussion. In this study, we investigate whether different helmet designs can meaningfully alter brain strains using two commonly used metrics, peak maximum principal strain (MPS) of the whole brain and cumulative strain damage measure (CSDM). A convolutional neural network (CNN) that instantly produces detailed brain strains is first tested for accuracy for helmeted head impacts. Based on N = 144 impacts in 12 impact conditions from three random and representative helmet models, we conclude that the CNN is sufficiently accurate for helmet testing applications, for elementwise MPS (success rate of 98.6%), whole-brain peak MPS and CSDM (coefficient of determination of 0.977 and 0.980, with root mean squared error of 0.015 and 0.029, respectively). We then apply the technique to 23 football helmet models (N = 1104 impacts) to reproduce elementwise MPS. Assuming a concussion would occur when peak MPS or CSDM exceeds a threshold, we sweep their thresholds across the value ranges to evaluate the number of predicted hypothetical concussions that different helmets sustain across the impact conditions. Relative to the 12 impact conditions tested, we find that the "best" and "worst" helmets differ by an average of 22.5% in terms of predicted concussions, ranging from 0 to 42% (the latter achieved at the threshold value of 0.28 for peak MPS and 0.4 for CSDM, respectively). Such a large variation among helmets in strain-based concussion predictions demonstrate that helmet designs can still be optimized in a clinically meaningful way. The robustness and accuracy of the CNN tool also suggest its potential for routine use for helmet design and safety performance evaluation in the future. The CNN is freely available online at https://github.com/Jilab-biomechanics/CNN-brain-strains .

Association between Preseason/Regular Season Head Impact Exposure and Concussion Incidence in NCAA Football

PURPOSE

Contact sport athletes are exposed to a unique environment where they sustain repeated head impacts throughout the season and can sustain hundreds of head impacts over a few months. Accordingly, recent studies outlined the role that head impact exposure (HIE) has in concussion biomechanics and in the development of cognitive and brain-based changes. Those studies focused on time-bound effects by quantifying exposure leading up to the concussion, or cognitive changes after a season in which athletes had high HIE. However, HIE may have a more prolonged effect. This study identified associations between HIE and concussion incidence during different periods of the college football fall season.

METHODS

This study included 1120 athlete seasons from six National Collegiate Athletic Association Division I football programs across 5 yr. Athletes were instrumented with the Head Impact Telemetry System to record daily HIE. The analysis quantified associations of preseason/regular season/total season concussion incidence with HIE during those periods.

RESULTS

Strong associations were identified between HIE and concussion incidence during different periods of the season. Preseason HIE was associated with preseason and total season concussion incidence, and total season HIE was associated with total season concussion incidence.

CONCLUSIONS

These findings demonstrate a prolonged effect of HIE on concussion risk, wherein elevated preseason HIE was associated with higher concussion risk both during the preseason and throughout the entire fall season. This investigation is the first to provide evidence supporting the hypothesis of a relationship between elevated HIE during the college football preseason and a sustained decreased tolerance for concussion throughout that season.

A Preclinical Rodent Model for Repetitive Subconcussive Head Impact Exposure in Contact Sport Athletes

Repetitive subconcussive head impact exposure has been associated with clinical and MRI changes in some non-concussed contact sport athletes over the course of a season. However, analysis of human tolerance for repeated head impacts is complicated by concussion and head impact exposure history, genetics, and other personal factors. Therefore, the objective of the current study was to develop a rodent model for repetitive subconcussive head impact exposure that can be used to understand injury mechanisms and tolerance in the human. This study incorporated the Medical College of Wisconsin Rotational Injury Model to expose rats to multiple low-level head accelerations per day over a 4-week period. The peak magnitude of head accelerations were scaled from our prior human studies of contact sport athletes and the number of exposures per day were based on the median (moderate exposure) and 95th percentile (high exposure) number of exposures per day across the human sample. Following the exposure protocol, rats were assessed for cognitive deficits, emotional changes, blood serum levels of axonal injury biomarkers, and histopathological evidence of injury. High exposure rats demonstrated cognitive deficits and evidence of anxiety-like behaviors relative to shams. Moderate exposure rats did not demonstrate either of those behaviors. Similarly, high exposure rats had histopathological evidence of gliosis [i.e., elevated Iba1 intensity and glial fibrillary acidic protein (GFAP) volume relative to shams] in the basolateral amygdala and other areas. Blood serum levels of neurofilament light (NFL) demonstrated a dose response relationship with increasing numbers of low-level head acceleration exposures with a higher week-to-week rate of NFL increase for the high exposure group compared to the moderate exposure group. These findings demonstrate a cumulative effect of repeated low-level head accelerations and provide a model that can be used in future studies to better understand mechanisms and tolerance for brain injury resulting from repeated low-level head accelerations, with scalable biomechanics between the rat and human.

Concussion biomechanics, head acceleration exposure and brain injury criteria in sport: a review

There are mounting concerns surrounding the risk of neurodegenerative diseases and complications associated with concussion incidence and repetitive head acceleration events (HAE) in sport. The aim of this review is to provide an overview of concussion biomechanics, head acceleration exposure and brain injury criteria in sport. Rotational head motion appears to be the primary contributor to brain injury risk due to the unique mechanical properties of the brain and its location within the body. There is a growing evidence base of different biomechanical brain injury mechanisms, including those involving repetitive HAE. Historically, many studies on concussion biomechanics, head acceleration exposure and brain injury criteria in sport have been limited by validity of the biomechanical approaches undertaken. Biomechanical approaches such as instrumented mouthguards and subject-specific finite element (FE) brain models provide a unique opportunity to develop greater brain injury criteria and aid in on-field athlete removal. Implementing these approaches on a large-scale can gain insight into potential risk factors within sports and certain athletes/cohorts who sustain a greater number and/or severity of HAE throughout their playing career. These findings could play a key role in the development of concussion prevention strategies and techniques that mitigate the severity of HAE in sport.

In-Season Concussion Symptom Reporting in Male and Female Collegiate Rugby Athletes

Symptom inventories are generally only collected after a suspected concussion, but regular in-season monitoring may allude to clinical symptoms associated with repetitive subconcussive impacts and potential undiagnosed concussions. Despite sex-specific differences in symptom presentation and outcome of concussion, no return-to-play protocol takes sex into account. The objective of this study was to monitor a cohort of contact-sport athletes and compare the frequency and severity of in-season concussion-like symptom reporting between sexes. Graded symptom checklists from 144 female and 104 male athlete-seasons were administered weekly to quantify the effect of subconcussive impacts on frequency and severity of in-season symptom reporting. In-season, mean symptom severity score (SSS) (p = 0.026, mean difference of 1.8), mean number of symptoms (p = 0.044, mean difference of 0.9), max SSS (p < 0.001, mean difference of 19.2), and max number of symptoms (p < 0.001, mean difference of 6.8) were higher in the females. The females' survey results showed differences between elevated and concussed SSS (p < 0.005, mean difference of 28.1) and number of symptoms reported (p = 0.001, mean difference of 6.6). The males did not have a difference in SSS (p = 0.97, mean difference of 1.12) nor in number of symptoms (p = 0.35, mean difference of 1.96) from elevated to concussed athletes. Rugby players report concussion-like symptoms in the absence of a diagnosed concussion in-season. Female athletes reported elevated symptom frequencies with greater severities than the males, but both sexes reported considerable levels throughout the season.

Head Impact Research Using Inertial Sensors in Sport: A Systematic Review of Methods, Demographics, and Factors Contributing to Exposure

BACKGROUND

The number and magnitude of head impacts have been assessed in-vivo using inertial sensors to characterise the exposure in various sports and to help understand their potential relationship to concussion.

OBJECTIVES

We aimed to provide a comprehensive review of the field of in-vivo sensor acceleration event research in sports via the summary of data collection and processing methods, population demographics and factors contributing to an athlete's exposure to sensor acceleration events.

METHODS

The systematic search resulted in 185 cohort or cross-sectional studies that recorded sensor acceleration events in-vivo during sport participation.

RESULTS

Approximately 5800 participants were studied in 20 sports using 18 devices that included instrumented helmets, headbands, skin patches, mouthguards and earplugs. Female and youth participants were under-represented and ambiguous results were reported for these populations. The number and magnitude of sensor acceleration events were affected by a variety of contributing factors, suggesting sport-specific analyses are needed. For collision sports, being male, being older, and playing in a game (as opposed to a practice), all contributed to being exposed to more sensor acceleration events.

DISCUSSION

Several issues were identified across the various sensor technologies, and efforts should focus on harmonising research methods and improving the accuracy of kinematic measurements and impact classification. While the research is more mature for high-school and collegiate male American football players, it is still in its early stages in many other sports and for female and youth populations. The information reported in the summarised work has improved our understanding of the exposure to sport-related head impacts and has enabled the development of prevention strategies, such as rule changes.

CONCLUSIONS

Head impact research can help improve our understanding of the acute and chronic effects of head impacts on neurological impairments and brain injury. The field is still growing in many sports, but technological improvements and standardisation of processes are needed.

Instantaneous Whole-Brain Strain Estimation in Dynamic Head Impact

Head injury models are notoriously time consuming and resource demanding in simulations, which prevents routine application. Here, we extend a convolutional neural network (CNN) to instantly estimate element-wise distribution of peak maximum principal strain (MPS) of the entire brain (>36 k speedup accomplished on a low-end computing platform). To achieve this, head impact rotational velocity and acceleration temporal profiles are combined into two-dimensional images to serve as CNN input for training and prediction of MPS. Compared with the directly simulated counterparts, the CNN-estimated responses (magnitude and distribution) are sufficiently accurate for 92.1% of the cases via 10-fold cross-validation using impacts drawn from the real world (n = 5661; range of peak rotational velocity in augmented data extended to 2-40 rad/sec). The success rate further improves to 97.1% for "in-range" impacts (n = 4298). When using the same CNN architecture to train (n = 3064) and test on an independent, reconstructed National Football League (NFL) impact dataset (n = 53; 20 concussions and 33 non-injuries), 51 out of 53, or 96.2% of the cases, are sufficiently accurate. The estimated responses also achieve virtually identical concussion prediction performances relative to the directly simulated counterparts, and they often outperform peak MPS of the whole brain (e.g., accuracy of 0.83 vs. 0.77 via leave-one-out cross-validation). These findings support the use of CNN for accurate and efficient estimation of spatially detailed brain strains across the vast majority of head impacts in contact sports. Our technique may hold the potential to transform traumatic brain injury (TBI) research and the design and testing standards of head protective gears by facilitating the transition from acceleration-based approximation to strain-based design and analysis. This would have broad implications in the TBI biomechanics field to accelerate new scientific discoveries. The pre-trained CNN is freely available online at https://github.com/Jilab-biomechanics/CNN-brain-strains.

A new open-access platform for measuring and sharing mTBI data

Despite numerous research efforts, the precise mechanisms of concussion have yet to be fully uncovered. Clinical studies on high-risk populations, such as contact sports athletes, have become more common and give insight on the link between impact severity and brain injury risk through the use of wearable sensors and neurological testing. However, as the number of institutions operating these studies grows, there is a growing need for a platform to share these data to facilitate our understanding of concussion mechanisms and aid in the development of suitable diagnostic tools. To that end, this paper puts forth two contributions: (1) a centralized, open-access platform for storing and sharing head impact data, in collaboration with the Federal Interagency Traumatic Brain Injury Research informatics system (FITBIR), and (2) a deep learning impact detection algorithm (MiGNet) to differentiate between true head impacts and false positives for the previously biomechanically validated instrumented mouthguard sensor (MiG2.0), all of which easily interfaces with FITBIR. We report 96% accuracy using MiGNet, based on a neural network model, improving on previous work based on Support Vector Machines achieving 91% accuracy, on an out of sample dataset of high school and collegiate football head impacts. The integrated MiG2.0 and FITBIR system serve as a collaborative research tool to be disseminated across multiple institutions towards creating a standardized dataset for furthering the knowledge of concussion biomechanics.

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.

Using Oculomotor Features to Predict Changes in Optic Nerve Sheath Diameter and ImPACT Scores From Contact-Sport Athletes

There is mounting evidence linking the cumulative effects of repetitive head impacts to neuro-degenerative conditions. Robust clinical assessment tools to identify mild traumatic brain injuries are needed to assist with timely diagnosis for return-to-field decisions and appropriately guide rehabilitation. The focus of the present study is to investigate the potential for oculomotor features to complement existing diagnostic tools, such as measurements of Optic Nerve Sheath Diameter (ONSD) and Immediate Post-concussion Assessment and Cognitive Testing (ImPACT). Thirty-one high school American football and soccer athletes were tracked through the course of a sports season. Given the high risk of repetitive head impacts associated with both soccer and football, our hypotheses were that (1) ONSD and ImPACT scores would worsen through the season and (2) oculomotor features would effectively capture both neurophysiological changes reflected by ONSD and neuro-functional status assessed via ImPACT. Oculomotor features were used as input to Linear Mixed-Effects Regression models to predict ONSD and ImPACT scores as outcomes. Prediction accuracy was evaluated to identify explicit relationships between eye movements, ONSD, and ImPACT scores. Significant Pearson correlations were observed between predicted and actual outcomes for ONSD (Raw = 0.70; Normalized = 0.45) and for ImPACT (Raw = 0.86; Normalized = 0.71), demonstrating the capability of oculomotor features to capture neurological changes detected by both ONSD and ImPACT. The most predictive features were found to relate to motor control and visual-motor processing. In future work, oculomotor models, linking neural structures to oculomotor function, can be built to gain extended mechanistic insights into neurophysiological changes observed through seasons of participation in contact sports.

A Review of On-Field Investigations into the Biomechanics of Concussion in Football and Translation to Head Injury Mitigation Strategies

This review paper summarizes the scientific advancements in the field of concussion biomechanics in American football throughout the past five decades. The focus is on-field biomechanical data collection, and the translation of that data to injury metrics and helmet evaluation. On-field data has been collected with video analysis for laboratory reconstructions or wearable head impact sensors. Concussion biomechanics have been studied across all levels of play, from youth to professional, which has allowed for comparison of head impact exposure and injury tolerance between different age groups. In general, head impact exposure and injury tolerance increase with increasing age. Average values for concussive head impact kinematics are lower for youth players in both linear and rotational acceleration. Head impact data from concussive and non-concussive events have been used to develop injury metrics and risk functions for use in protective equipment evaluation. These risk functions have been used to evaluate helmet performance for each level of play, showing substantial differences in the ability of different helmet models to reduce concussion risk. New advances in head impact sensor technology allow for biomechanical measurements in helmeted and non-helmeted sports for a more complete understanding of concussion tolerance in different demographics. These sensors along with advances in finite element modeling will lead to a better understanding of the mechanisms of injury and human tolerance to head impact.

Do Head Injury Biomechanics Predict Concussion Clinical Recovery in College American Football Players?

Identifying the associations between head impact biomechanics and clinical recovery may inform better head impact monitoring procedures and identify athletes who may benefit from early treatments aimed to enhance recovery. The purpose of this study was to test whether head injury biomechanics are associated with clinical recovery of symptom severity, balance, and mental status, as well as symptom resolution time (SRT) and return-to-participation (RTP) time. We studied 45 college American football players (n = 51 concussions) who sustained an incident concussion while participating in a multi-site study. Player race/ethnicity, prior concussion, medical history, position, body mass index, event type, and impact location were covariates in our multivariable analyses. Multivariable negative binomial regression models analyzed associations between our study outcomes and (1) injury-causing linear and rotational head impact severity, (2) season repetitive head impact exposure (RHIE), and (3) injury day RHIE. Median SRT was 6.1 days (IQR 5.8 days, n = 45) and median RTP time was 12.3 days (IQR 7.8 days, n = 36) across our study sample. RTP time was 86% (Ratio 1.86, 95% CI [1.05, 3.28]) longer in athletes with a concussion history. Offensive players had SRTs 49% shorter than defensive players (Ratio 0.51, 95% CI [0.29, 0.92]). Per-unit increases in season RHIE were associated with 22% longer SRT (Ratio 1.22, 95% CI [1.09, 1.36]) but 28% shorter RTP time (Ratio 0.72, 95% CI [0.56, 0.93]). No other head injury biomechanics predicted injury recovery.

Concussion Risk Between Individual Football Players: Survival Analysis of Recurrent Events and Non-events

Concussion tolerance and head impact exposure are highly variable among football players. Recent findings highlight that head impact data analyses need to be performed at the subject level. In this paper, we describe a method of characterizing concussion risk between individuals using a new survival analysis technique developed with real-world head impact data in mind. Our approach addresses the limitations and challenges seen in previous risk analyses of football head impact data. Specifically, this demonstrative analysis appropriately models risk for a combination of left-censored recurrent events (concussions) and right-censored recurrent non-events (head impacts without concussion). Furthermore, the analysis accounts for uneven impact sampling between players. In brief, we propose using the Consistent Threshold method to develop subject-specific risk curves and then determine average risk point estimates between subjects at injurious magnitude values. We describe an approach for selecting an optimal cumulative distribution function to model risk between subjects by minimizing injury prediction error. We illustrate that small differences in distribution fit can result in large predictive errors. Given the vast amounts of on-field data researchers are collecting across sports, this approach can be applied to develop population-specific risk curves that can ultimately inform interventions that reduce concussion incidence.

Effect of concussion on salary and employment: a population-based event time study using a quasi-experimental design

OBJECTIVE

Concussions are the most frequent traumatic brain injuries. Yet, the socioeconomic impact of concussions remains unclear. Socioeconomic effects of concussions on working-age adults were studied on a population scale.

DESIGN

This population-based, event time study uses administrative data as well as hospital and emergency room records for the population of Denmark.

SETTING

We study all Danish patients, aged 20-59 years, who were treated at a public hospital or at an emergency room between 2003 and 2017 after suffering a concussion without other intracranial or extracranial injuries (n=55 424 unique individuals). None of the patients had a prior diagnosis of intracranial or extracranial injuries within the past 10 years leading up to the incident.

PRIMARY AND SECONDARY OUTCOME MEASURES

As primary endpoint, we investigate the mean effect of concussion on annual salaried income within a 5-year period after trauma. In an exploratory analysis, we study whether the potential impact of concussion on annual salaried income is driven by patient age, education or economic cycle.

RESULTS

Concussion was associated with an average change in annual salary income of -€1223 (95% CI: -€1540 to -905, p<0.001) corresponding to a salary change of -4.2% (95% CI: -5.2% to -3.1 %). People between 30 and 39 years and those without high school degrees suffered the largest salary decreases. Affected individuals leaving the workforce drove the main part of the decrease. Absolute annual effect sizes were countercyclical to the unemployment rate.

CONCLUSIONS

Concussions have a large and long-lasting impact on salary and employment of working-age adults on a nationwide scale.

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.

Concussion Symptom Characteristics and Resolution in 20 United States High School Sports, 2013/14-2017/18 Academic Years

BACKGROUND

High school (HS) sport-related concussions (SRCs) remain a public health concern in the United States.

OBJECTIVE

To describe patterns in symptom prevalence, symptom resolution time (SRT), and return-to-play time (RTP) for SRCs sustained in 20 HS sports during the 2013/14-2017/18 academic years.

METHODS

A convenience sample of athletic trainers reported concussion information to the HS RIOTM surveillance system. Symptom prevalence, average number of symptoms, and SRT and RTP distributions were examined and compared by event type (practice, competition), injury mechanism (person contact, nonperson contact), sex, and contact level (collision, high contact, and low contact) with chi-square tests and Wilcoxon rank-sum tests.

RESULTS

Among all SRCs (n = 9542), headache (94.5%), dizziness (73.8%), and difficulty concentrating (56.0%) were commonly reported symptoms. On average, 4.7 ± 2.4 symptoms were reported per SRC. Overall, 51.3% had symptoms resolve in <7 d, yet only 7.9% had RTP < 7 d. Differential prevalence of amnesia was seen between practice and competition-related SRCs (8.8% vs 13.0%; P < .001); nonperson-contact and person-contact SRCs (9.3% vs 12.7%; P < .001); and female and male SRCs in low-contact sports (5.8% vs 17.5%; P < .001). Differential prevalence of loss of consciousness was seen between practice and game-related SRCs (1.3% vs 3.2%; P < .001); and female and male SRCs in high contact sports (1.2% vs 4.0%; P < .001). Differential longer SRT (>21 d) was seen between new and recurrent SRCs (9.4% vs 15.9%; P < .001).

CONCLUSION

Headache was the most commonly reported symptom. Notable group differences in the prevalence of amnesia, loss of consciousness, and SRT may be associated with more severe SRCs, warranting further attention.

Quantifying Youth Football Helmet Performance: Assessing Linear and Rotational Head Acceleration

Youth football helmet testing standards have served to largely eliminate catastrophic head injury from the sport. These standards, though, do not presently consider concussion and do not offer consumers the capacity to differentiate the impact performance of youth football helmets. This study adapted the previously developed Summation of Tests for the Analysis of Risk (STAR) equation for youth football helmet assessment. This adaptation made use of a youth-specific testing surrogate, on-field data collected from youth football players, and a concussion risk function developed for youth athletes. Each helmet is subjected to 48 laboratory impacts across 12 impact conditions. Peak linear head acceleration and peak rotational head acceleration values from each laboratory impact are aggregated into a single STAR value that combines player exposure and risk of concussion. This single value can provide consumers with valuable information regarding the relative performance of youth football helmets.

An Investigation of Factors Associated With Head Impact Exposure in Professional Male and Female Australian Football Players

BACKGROUND

Exposure to head acceleration events (HAEs) has been associated with player sex, player position, and player experience in North American football, ice hockey, and lacrosse. Little is known of these factors in professional Australian football. Video analysis allows HAE verification and characterization of important determinants of injury.

PURPOSE

To characterize verified HAEs in the nonhelmeted contact sport of professional Australian football and investigate the association of sex, player position, and player experience with HAE frequency and magnitude.

STUDY DESIGN

Descriptive epidemiology study.

METHODS

Professional Australian football players wore a nonhelmeted accelerometer for 1 match, with data collected across 14 matches. HAEs with peak linear accelerations (PLAs) ≥30g were verified with match video. Verified HAEs were summarized by frequency and median PLA and compared between the sexes, player position, and player experience. Characterization of match-related situations of verified HAEs was conducted, and the head impact rate per skill execution was calculated.

RESULTS

92 male and 118 female players were recruited during the 2017 season. Male players sustained more HAEs (median, 1; IQR, 0-2) than female players (median, 0; IQR, 0-1; P = .007) during a match. The maximum PLAs incurred during a match were significantly higher in male players (median, 61.8g; IQR, 40.5-87.1) compared with female players (median, 44.5g; IQR, 33.6-74.8; P = .032). Neither player position nor experience was associated with HAE frequency. Of all verified HAEs, 52% (n = 110) occurred when neither team had possession of the football, and 46% (n = 98) were caused by contact from another player attempting to gain possession of the football. A subset of HAEs (n = 12; 5.7%) resulted in players seeking medical aid and/or being removed from the match (median PLA, 58.8g; IQR, 34.0-89.0), with 2 (male) players diagnosed with concussion after direct head impacts and associated PLAs of 62g and 75g, respectively. In the setting of catching (marking) the football, female players exhibited twice the head impact rate (16 per 100 marking contests) than male players (8 per 100 marking contests).

CONCLUSION

Playing situations in which players have limited control of the football are a common cause of impacts. Male players sustained a greater exposure to HAEs compared with female players. Female players, however, sustained higher exposure to HAEs than male players during certain skill executions, possibly reflecting differences in skill development. These findings can therefore inform match and skill development in the emerging professional women's competition of Australian football.

Predicting Concussion Outcome by Integrating Finite Element Modeling and Network Analysis

Concussion is a significant public health problem affecting 1.6-2.4 million Americans annually. An alternative to reducing the burden of concussion is to reduce its incidence with improved protective equipment and injury mitigation systems. Finite element (FE) models of the brain response to blunt trauma are often used to estimate injury potential and can lead to improved helmet designs. However, these models have yet to incorporate how the patterns of brain connectivity disruption after impact affects the relay of information in the injured brain. Furthermore, FE brain models typically do not consider the differences in individual brain structural connectivities and their purported role in concussion risk. Here, we use graph theory techniques to integrate brain deformations predicted from FE modeling with measurements of network efficiency to identify brain regions whose connectivity characteristics may influence concussion risk. We computed maximum principal strain in 129 brain regions using head kinematics measured from 53 professional football impact reconstructions that included concussive and non-concussive cases. In parallel, using diffusion spectrum imaging data from 30 healthy subjects, we simulated structural lesioning of each of the same 129 brain regions. We simulated lesioning by removing each region one at a time along with all its connections. In turn, we computed the resultant change in global efficiency to identify regions important for network communication. We found that brain regions that deformed the most during an impact did not overlap with regions most important for network communication (Pearson's correlation, ρ = 0.07; p = 0.45). Despite this dissimilarity, we found that predicting concussion incidence was equally accurate when considering either areas of high strain or of high importance to global efficiency. Interestingly, accuracy for concussion prediction varied considerably across the 30 healthy connectomes. These results suggest that individual network structure is an important confounding variable in concussion prediction and that further investigation of its role may improve concussion prediction and lead to the development of more effective protective equipment.

Concussion incidence and time-loss in Australian football: A systematic review

OBJECTIVES

Australian football is associated with a risk of concussion. However, despite the extensive and varied nature of literature devoted to this issue, concussion incidence has not been systematically evaluated. To address this, we aimed to conduct a meta-analysis of concussion incidence in Australian football.

DESIGN

Systematic review. Prospero registration number: CRD42017064290.

METHODS

A systematic search of 14 databases using the terms 'concussion', and 'Australian football' (and variations) was used to obtain records that reported concussion incidence per 1000 players hours across age, sex, and level-of-play. Data were grouped based on how time-loss was applied to the concussion definition.

RESULTS

Forty-two studies met inclusion criteria. Incidence rates based on a possible time-loss definition per 1000 player hours, ranged from 2.24 to 17.63 at the elite level, and 0.35 to 14.77 at the community/amateur level. Return-to-play details were reported by six studies and only two studies measured head-impacts in real-time. Several limitations were identified with this literature. First, insufficient return-to-play details precluded a meta-analysis of incidence rates. Second, no longitudinal studies across levels-of-play were found. Third, concussion incidence data for junior and female players were notably scarce.

CONCLUSIONS

There was limited scope to determine concussion burden (i.e., incidence and severity) and only preliminary data for player exposure to head-impacts. To address these limitations, injury surveillance should capture sufficient information to permit comparisons within and across levels-of-play. This will also help determine the influence of interventions aimed at reducing the frequency and severity of concussive-injuries.

A network-based response feature matrix as a brain injury metric

Conventional brain injury metrics are scalars that treat the whole head/brain as a single unit but do not characterize the distribution of brain responses. Here, we establish a network-based "response feature matrix" to characterize the magnitude and distribution of impact-induced brain strains. The network nodes and edges encode injury risks to the gray matter regions and their white matter interconnections, respectively. The utility of the metric is illustrated in injury prediction using three independent, real-world datasets: two reconstructed impact datasets from the National Football League (NFL) and Virginia Tech, respectively, and measured concussive and non-injury impacts from Stanford University. Injury predictions with leave-one-out cross-validation are conducted using the two reconstructed datasets separately, and then by combining all datasets into one. Using support vector machine, the network-based injury predictor consistently outperforms four baseline scalar metrics including peak maximum principal strain of the whole brain (MPS), peak linear/rotational acceleration, and peak rotational velocity across all five selected performance measures (e.g., maximized accuracy of 0.887 vs. 0.774 and 0.849 for MPS and rotational acceleration with corresponding positive predictive values of 0.938, 0.772, and 0.800, respectively, using the reconstructed NFL dataset). With sufficient training data, real-world injury prediction is similar to leave-one-out in-sample evaluation, suggesting the potential advantage of the network-based injury metric over conventional scalar metrics. The network-based response feature matrix significantly extends scalar metrics by sampling the brain strains more completely, which may serve as a useful framework potentially allowing for other applications such as characterizing injury patterns or facilitating targeted multi-scale modeling in the future.

Development of a Concussion Risk Function for a Youth Population Using Head Linear and Rotational Acceleration

Physical differences between youth and adults, which include incomplete myelination, limited neck muscle development, and a higher head-body ratio in the youth population, likely contribute towards the increased susceptibility of youth to concussion. Previous research efforts have considered the biomechanics of concussion for adult populations, but these known age-related differences highlight the necessity of quantifying the risk of concussion for a youth population. This study adapted the previously developed Generalized Acceleration Model for Brian Injury Threshold (GAMBIT) that combines linear and rotational head acceleration to model the risk of concussion for a youth population with the Generalized Acceleration Model for Concussion in Youth (GAM-CY). Survival analysis was used in conjunction with head impact data collected during participation in youth football to model risk between individuals who sustained medically-diagnosed concussions (n = 15). Receiver operator characteristic curves were generated for peak linear acceleration, peak rotational acceleration, and GAM-CY, all of which were observed to be better injury predictors than random guessing. GAM-CY was associated with an area under the curve of 0.89 (95% confidence interval: 0.82–0.95) when all head impacts experienced by the concussed players were considered. Concussion tolerance was observed to be lower for youth athletes, with average peak linear head acceleration of 62.4 ± 29.7 g compared to 102.5 ± 32.7 g for adults and average peak rotational head acceleration of 2609 ± 1591 rad/s² compared to 4412 ± 2326 rad/s². These data provide further evidence of age-related differences in concussion tolerance and may be used for the development of youth-specific protective designs.

Estimated Age of First Exposure to Contact Sports Is Not Associated with Greater Symptoms or Worse Cognitive Functioning in Male U.S. Service Academy Athletes

This study examined the association between estimated age of first exposure (eAFE) to contact sport participation and neurocognitive performance and symptom ratings in U.S. service academy National Collegiate Athletic Association (NCAA) athletes. Male cadets (N = 891), who participate in lacrosse (n = 211), wrestling (n = 170), ice hockey (n = 81), soccer (n = 119), rugby (n = 10), or non-contact sports (n = 298), completed the Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) test before the season. Generalized linear modeling was used to predict each neurocognitive domain score and total symptom severity score. Predictor variables were entered in the following order: group (contact vs. non-contact); eAFE (eAFE <12 years vs. eAFE ≥12 years); group-by-eAFE; and covariates for learning accommodation status, concussion history, and age. The group-by-eAFE interaction was not significant for any of the ImPACT composite scores (Verbal Memory, Wald χ² = 0.073, p = 0.788; Visual Memory, Wald χ² = 2.71, p = 0.100; Visual Motor Speed, Wald χ² = 0.078, p = 0.780; Reaction Time, Wald χ² = 0.003, p = 0.955; Symptom Severity, Wald χ² = 2.87, p = 0.090). Learning accommodation history was associated with lower scores on Visual Motor Speed (χ² = 6.19, p = 0.013, B = -2.97). Older age was associated with faster reaction time (χ² = 4.40, p = 0.036, B = -0.006) and lesser symptom severity (χ² = 5.55, p = 0.019, B = -0.068). No other parameters were significant. We observed no association between eAFE, contact sport participation, neurocognitive functioning, or subjectively experienced symptoms in this cohort. Earlier eAFE to contact sport participation is not related to worse neurocognitive performance or greater subjectively experienced symptoms in male U.S. service academy NCAA athletes.

Repetitive Head Impact Exposure in College Football Following an NCAA Rule Change to Eliminate Two-A-Day Preseason Practices: A Study from the NCAA-DoD CARE Consortium

Repetitive head impact exposure sustained by athletes of contact sports has been hypothesized to be a mechanism for concussion and a possible explanation for the high degree of variability in sport-related concussion biomechanics. In an attempt to limit repetitive head impact exposure during the football preseason, the NCAA eliminated two-a-day practices in 2017, while maintaining the total number of team practice sessions. The objective of this study was to quantify head impact exposure during the preseason and regular season in Division I college football athletes to determine whether the 2017 NCAA ruling decreased head impact exposure. 342 unique athletes from five NCAA Division I Football Bowl Subdivision (FBS) programs were consented and enrolled. Head impacts were recorded using the Head Impact Telemetry (HIT) System during the entire fall preseasons and regular seasons in 2016 and 2017. Despite the elimination of two-a-day practices, the number of preseason contact days increased in 2017, with an increase in average hourly impact exposure (i.e., contact intensity), resulting in a significant increase in total head impact burden (+ 26%) for the 2017 preseason. This finding would indicate that the 2017 NCAA ruling was not effective at reducing the head impact burden during the football preseason. Additionally, athletes sustained a significantly higher number of recorded head impacts per week (+ 40%) during the preseason than the regular season, implicating the preseason as a time of elevated repetitive head impact burden. With increased recognition of a possible association between repetitive head impact exposure and concussion, increased preseason exposure may predispose certain athletes to a higher risk of concussion during the preseason and regular season. Accordingly, efforts at reducing concussion incidence in contact sports should include a reduction in overall head impact exposure.

Accounting for Variance in Concussion Tolerance Between Individuals: Comparing Head Accelerations Between Concussed and Physically Matched Control Subjects

Researchers have been collecting head impact data from instrumented football players to characterize the biomechanics of concussion for the past 15 years, yet the link between biomechanical input and clinical outcome is still not well understood. We have previously shown that even though concussive biomechanics might be unremarkable in large datasets of head impacts, the impacts causing injury are of high magnitude for the concussed individuals relative to their impact history. This finding suggests a need to account for differences in tolerance at the individual level. In this study, we identified control subjects for our concussed subjects who demonstrated traits we believed were correlated to factors thought to affect injury tolerance, including height, mass, age, race, and concussion history. A total of 502 college football players were instrumented with helmet-mounted accelerometer arrays and provided complete baseline assessment data, 44 of which sustained a total of 49 concussion. Biomechanical measures quantifying impact frequency and acceleration magnitude were compared between groups. On average, we found that concussed subjects experienced 93.8 more head impacts (p = 0.0031), 10.2 more high magnitude impacts (p = 0.0157), and 1.9 × greater risk-weighted exposure (p = 0.0175) than their physically matched controls. This finding provides further evidence that head impact data need to be considered at the individual level and that cohort wide assessments may be of little value in the context of concussion.

The Effectiveness of Protective Headgear in Attenuating Ball-to-Forehead Impacts in Water Polo

Recent reports have demonstrated that there is a serious risk of head impact and injury in water polo. The use of protective headgear in contact sports is a commonly accepted strategy for reducing the risk of head injury, but there are few available protective headgears for use in water polo. Many of those that are available are banned by the sport's governing bodies due to a lack of published data supporting the effectiveness of those headgears in reducing head impact kinematics. To address this gap in knowledge, we launched a water polo ball at the forehead of an anthropomorphic testing device fitted with either a standard water polo headgear or one of two protective headgears. We selected a range of launch speeds representative of those observed across various athlete ages. Mixed-model ANOVAs revealed that, relative to standard headgear, protective headgears reduced peak linear acceleration (by 10.8-21.6%; p < 0.001), and peak rotational acceleration (by 24.5-48.5%; p < 0.001) induced by the simulated ball-to-forehead impacts. We discuss the possibility of using protective headgears in water polo to attenuate head impact kinematics.

Does baseline concussion testing aid in identifying future concussion risk?

The purpose was to determine differences in pre-season baseline performance between student-athletes who suffered a future sport-related concussion (fSRC) and those who did not. Collegiate student-athletes (82 fSRC, 82 matched control, age = 18.4 ± 0.8years, height = 172.7 ± 10.3 cm, mass = 80.1 ± 20.9 kg) completed baseline Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT), Balance Error Scoring System (BESS), and Standardized Assessment of Concussion (SAC). Results of the independent t-tests suggested there were no differences between the fSRC and the control groups for ImPACT composite scores (95% confidence intervals, Visual Memory: fSRC 70.4-75.9, Control 73.4-78.5, p = 0.134; Verbal Memory: fSRC 83.8-87.7, Control 85.7-89.9, p = 0.155; Reaction Time: fSRC 0.562-0.591, Control 0.580-0.614, p = 0.071; Visual Motor Speed: fSRC 38.5-41.1, Control 38.2-40.9, p = 0.757), BESS total errors (fSRC 11.3-13.7, Control 11.8-14.4, p = 0.483), or SAC (fSRC 26.6-27.4, Control 26.9-27.6, p = 0.394). Receiver operating characteristic (ROC) areas-under-the-curve were 0.417-0.515. Our findings suggest that baseline concussion assessments cannot be used to predict individuals who may sustain a fSRC.

Pathophysiology of Concussion

Although concussion has been a subject of interest for centuries, this condition remains poorly understood. The mechanistic underpinnings and accepted definition of concussion remain elusive. To make sense of these issues, this article presents a brief history of concussion studies, detailing the evolution of motivations and experimental conclusions over time. Interest in concussion as a subject of scientific inquiry has increased with growing concern about the long-term consequences of mild traumatic brain injury (TBI). Although concussion is often associated with mild TBI, these conditions-the former a neurological syndrome, the latter a neurological event-are distinct, both mechanistically and pathobiologically. Modern research primarily focuses on the study of the biomechanics, pathophysiology, potential biomarkers and neuroimaging to distinguish concussion from mild TBI. In addition, mild TBI and concussion outcomes are influenced by age, sex, and genetic differences in people. With converging experimental objectives and methodologies, future concussion research has the potential to improve clinical assessment, treatment, and preventative measures.

Concussion Pathophysiology and Injury Biomechanics

PURPOSE OF REVIEW

The concussion public health burden has increased alongside our knowledge of the pathophysiology of mild traumatic brain injury (mTBI). The purpose of this review is to summarize our current understanding of mTBI pathophysiology and biomechanics and how these underlying principles correlate with clinical manifestations of mTBI.

RECENT FINDINGS

Changes in post-mTBI glutamate and GABA concentrations seem to be region-specific and time-dependent. Genetic variability may predict recovery and symptom severity while gender differences appear to be associated with the neuroinflammatory response and neuroplasticity. Ongoing biomechanical research has shown a growing body of evidence in support of an "individual-specific threshold" for mTBI that varies based on individual intrinsic factors. The literature demonstrates a well-characterized timeframe for mTBI pathophysiologic changes in animal models while work in this area continues to grow in humans. Current human research shows that these underlying post-mTBI effects are multifactorial and may correlate with symptomatology and recovery. While wearable sensor technology has advanced biomechanical impact research, a definitive concussion threshold remains elusive.

Cortical Spreading Depression Denotes Concussion Injury

Cortical spreading depression (CSD) has been described after moderate-to-severe traumatic brain injury (TBI). It is uncertain, however, whether CSD occurs after mild, concussive TBI and whether it relates to brain pathology and functional outcome. Male C57BL6/J mice (n = 62) were subjected to closed head TBI with a 25 g weight (n = 11), 50 g weight (n = 45), or sham injury (n = 6). Laser Doppler flowmetry and optical intrinsic signal imaging were used to determine cerebral blood flow dynamics after concussive CSD. Functional deficits were assessed at baseline, 2 h, 24 h, and 48 h. TUNEL and Prussian blue staining were used to determine cell death and presence of cerebral microbleeds at 48 h. No CSD was observed in mice subjected to a 25 g weight drop whereas 58.9% of mice subjected to a 50 g weight drop developed a CSD. Mice with concussive CSD displayed significantly greater numbers of apoptotic cell profiles in the ipsilesional hemisphere compared with mice without a CSD that underwent the same 50 g weight drop paradigm (p < 0.05, each). All investigated animals had at least one cerebral microbleed (range 1 to 24). Compared with mice without a CSD, mice with a CSD had significantly more microbleeds in the traumatized hemisphere (p < 0.05, each) and showed impaired functional recovery (p < 0.05). Incidence of CSD after mild TBI depended on impact severity and was associated with histological and behavioral outcomes. These observations indicate that concussive CSD may serve as viable marker for concussion severity and provide novel avenues for outcome prediction and therapeutic decision making.

Comparison of Head Impact Exposure Between Concussed Football Athletes and Matched Controls: Evidence for a Possible Second Mechanism of Sport-Related Concussion

Studies of football athletes have implicated repetitive head impact exposure in the onset of cognitive and brain structural changes, even in the absence of diagnosed concussion. Those studies imply accumulating damage from successive head impacts reduces tolerance and increases risk for concussion. Support for this premise is that biomechanics of head impacts resulting in concussion are often not remarkable when compared to impacts sustained by athletes without diagnosed concussion. Accordingly, this analysis quantified repetitive head impact exposure in a cohort of 50 concussed NCAA Division I FBS college football athletes compared to controls that were matched for team and position group. The analysis quantified the number of head impacts and risk weighted exposure both on the day of injury and for the season to the date of injury. 43% of concussed athletes had the most severe head impact exposure on the day of injury compared to their matched control group and 46% of concussed athletes had the most severe head impact exposure for the season to the date of injury compared to their matched control group. When accounting for date of injury or season to date of injury, 72% of all concussed athletes had the most or second most severe head impact exposure compared to their matched control group. These trends associating cumulative head impact exposure with concussion onset were stronger for athletes that participated in a greater number of contact activities. For example, 77% of athletes that participated in ten or more days of contact activities had greater head impact exposure than their matched control group. This unique analysis provided further evidence for the role of repetitive head impact exposure as a predisposing factor for the onset of concussion. The clinical implication of these findings supports contemporary trends of limiting head impact exposure for college football athletes during practice activities in an effort to also reduce risk of concussive injury.