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

Factors Influencing Time to Return to Learn Among NCAA Student-Athletes Enrolled in the Concussion Assessment, Research, and Education (CARE) Study

PURPOSE

The aim was to describe the demographic and post-injury factors that influence time to return to learn (RTL) among student-athletes enrolled in the Concussion Assessment, Research and Education (CARE) Consortium.

METHODS

A total of 47,860 student-athletes enrolled in the National Collegiate Athletic Association-Department of Defense (NCAA-DoD) CARE Consortium study from 2014 to 2020, with 1485 sport-related concussions (SRCs) analyzed in the present dataset. Demographic and post-injury characteristics were calculated using descriptive statistics, followed by Kaplan-Meier estimates to examine median time to return to normal academic performance (i.e., RTL) by sex (male, female), baseline psychiatric conditions (depression, anxiety) and/or learning disorder, NCAA division (I, II, III), SRC history (0, 1, 2, 3+), NCAA sport category (contact, limited contact, non-contact sport), and median difference in baseline/post-injury symptom severity scores (< 21, ≥ 21). Further, a multivariable zero-inflated negative binomial (ZINB) regression model was used to examine their association with RTL.

RESULTS

Overall, time to RTL (mean = 4.96 ± 8.24 days, median = 3.0 [interquartile range = 0.0, 6.0] days) was found to be influenced by several factors resulting in earlier trajectories. Notably, nearly 25% of the sample demonstrated immediate RTL (i.e., 0 days). Among student-athletes who did not immediately RTL, males demonstrated a decreased rate in RTL (rate = 0.79; 95% CI 0.66-0.96) compared to females. Further, student-athletes with a ≥ 21 change in symptom severity score (post-injury baseline) demonstrated a higher rate of RTL (rate = 1.47; 95% CI 1.21-1.79) compared to student-athletes with a symptom severity change score < 21. Lastly, male student-athletes demonstrated two times higher odds (odds ratio = 1.95; 95% CI 1.02-3.73) of immediate RTL compared to female student-athletes. No other covariates were associated with time to RTL.

CONCLUSION

Collectively, the present findings suggest a rapid return to the classroom following concussion. Specifically, males demonstrated higher odds of time to RTL, whereas those with greater differences in symptom severity resulted in a higher rate of time to RTL among those who did not immediately RTL. Ultimately, these findings support prior work emphasizing an individualized approach to SRC management.

The Incidence and Propensity of Head Acceleration Events in a Season of Men's and Women's English Elite-Level Club Rugby Union Matches

OBJECTIVES

To describe and compare the incidence and propensity of head acceleration events (HAEs) using instrumented mouthguards (iMG) by playing position in a season of English elite-level men's and women's rugby union matches.

METHODS

iMG data were collected for 255 men and 133 women from 1,865 and 807 player-matches, respectively, and synchronised to video-coded match footage. Head peak resultant linear acceleration (PLA) and peak resultant angular acceleration (PAA) were extracted from each HAE. Mean incidence and propensity values were calculated across different recording thresholds for forwards and backs in addition to positional groups (front row, second row, back row, half backs, centres, back three) with 95% confidence intervals (CI) estimated. Significance was determined based on 95% CI not overlapping across recording thresholds.

RESULTS

For both men and women, HAE incidence was twice as high for forwards than backs across the majority of recording thresholds. HAE incidence and propensity were significantly lower in the women's game compared to the men's game. Back-row and front-row players had the highest incidence across all HAE thresholds for men's forwards, while women's forward positional groups and men's and women's back positional groups were similar. Tackles and carries exhibited a greater propensity to result in HAE for forward positional groups and the back three in the men's game, and back row in the women's game.

CONCLUSION

These data offer valuable benchmark and comparative data for future research, HAE mitigation strategies, and management of HAE exposure in elite rugby players. Positional-specific differences in HAE incidence and propensity should be considered in future mitigation strategies.

When to Pull the Trigger: Conceptual Considerations for Approximating Head Acceleration Events Using Instrumented Mouthguards

Head acceleration events (HAEs) are acceleration responses of the head following external short-duration collisions. The potential risk of brain injury from a single high-magnitude HAE or repeated occurrences makes them a significant concern in sport. Instrumented mouthguards (iMGs) can approximate HAEs. The distinction between sensor acceleration events, the iMG datum for approximating HAEs and HAEs themselves, which have been defined as the in vivo event, is made to highlight limitations of approximating HAEs using iMGs. This article explores the technical limitations of iMGs that constrain the approximation of HAEs and discusses important conceptual considerations for stakeholders interpreting iMG data. The approximation of HAEs by sensor acceleration events is constrained by false positives and false negatives. False positives occur when a sensor acceleration event is recorded despite no (in vivo) HAE occurring, while false negatives occur when a sensor acceleration event is not recorded after an (in vivo) HAE has occurred. Various mechanisms contribute to false positives and false negatives. Video verification and post-processing algorithms offer effective means for eradicating most false positives, but mitigation for false negatives is less comprehensive. Consequently, current iMG research is likely to underestimate HAE exposures, especially at lower magnitudes. Future research should aim to mitigate false negatives, while current iMG datasets should be interpreted with consideration for false negatives when inferring athlete HAE exposure.

Distinct Serum Glial Fibrillary Acidic Protein and Neurofilament Light Time-Courses After Rapid Head Rotations

Traumatic brain injury (TBI) causes significant neurophysiological deficits and is typically associated with rapid head accelerations common in sports-related incidents and automobile accidents. There are over 1.5 million TBIs in the United States each year, with children aged 0-4 being particularly vulnerable. TBI diagnosis is currently achieved through interpretation of clinical signs and symptoms and neuroimaging; however, there is increasing interest in minimally invasive fluid biomarkers to detect TBI objectively across all ages. Pre-clinical porcine models offer controlled conditions to evaluate TBI with known biomechanical conditions and without comorbidities. The objective of the current study was to establish pediatric porcine healthy reference ranges (RRs) of common human serum TBI biomarkers and to report their acute time-course after nonimpact rotational head injury. A retrospective analysis was completed to quantify biomarker concentrations in porcine serum samples collected from 4-week-old female (n = 215) and uncastrated male (n = 6) Yorkshire piglets. Subjects were assigned to one of three experimental groups (sham, sagittal-single, sagittal-multiple) or to a baseline only group. A rapid nonimpact rotational head injury model was used to produce mild-to-moderate TBI in piglets following a single rotation and moderate-to-severe TBI following multiple rotations. The Quanterix Simoa Human Neurology 4-Plex A assay was used to quantify glial fibrillary acidic protein (GFAP), neurofilament light (Nf-L), tau, and ubiquitin carboxyl-terminal hydrolase L1 (UCH-L1). The 95% healthy RRs for females were calculated and validated for GFAP (6.3-69.4 pg/mL), Nf-L (9.5-67.2 pg/mL), and UCH-L1 (3.8-533.7 pg/mL). Rising early, GFAP increased significantly above the healthy RRs for sagittal-single (to 164 and 243 pg/mL) and increased significantly higher in sagittal-multiple (to 494 and 413 pg/mL) groups at 30 min and 1 h postinjury, respectively, returning to healthy RRs by 1-week postinjury. Rising later, Nf-L increased significantly above the healthy RRs by 1 day in sagittal-single (to 69 pg/mL) and sagittal-multiple groups (to 140 pg/mL) and rising further at 1 week (single = 231 pg/mL, multiple = 481 pg/mL). Sagittal-single and sagittal-multiple UCH-L1 serum samples did not differ from shams or the healthy RRs. Sex differences were observed but inconsistent. Serum GFAP and Nf-L levels had distinct time-courses following head rotations in piglets, and both corresponded to load exposure. We conclude that serum GFAP and Nf-L offer promise for early TBI diagnosis and intervention decisions for TBI and other neurological trauma.

Do Sport-Related Concussions Later in the Season Take Longer to Recover From?

OBJECTIVE

In a cohort of high-school football athletes with sport-related concussion (SRC), we sought to investigate the role of seasonality, defined as time of injury during a season, on recovery.

DESIGN

Retrospective cohort study.

SETTING

Regional sport concussion center.

PARTICIPANTS

High-school football athletes ages 14 to 19 -years old who sustained an SRC from 11, 2017 to 04, 2022.

INTERVENTION

Athletes were divided into 3 groups based on seasonality: early, middle, and late season.

MAIN OUTCOME MEASURES

The primary outcomes were initial Post-Concussion Symptom Scale score and recovery, as defined by time to return-to-learn (RTL), symptom resolution, and return-to-play (RTP). Descriptive statistics, analysis-of-variance, t tests, and multivariable regressions were performed.

RESULTS

Of our cohort of 273 high-school football players who sustained an SRC, 97 (35.5%) sustained an SRC during early season, 107 (39.2%) during middle season, and 69 (25.3%) during late season. Compared with late-season concussions, early-season concussions took less days to symptom resolution (early = 11.5 ± 12.9 vs late = 25.5 ± 27.0, P = 0.03), but no differences were found in days to RTL (early = 5.3 ± 4.8 vs late = 7.2 ± 15.8, P = 0.51) and RTP (early = 13.5 ± 11.8 vs late = 23.0 ± 22.8, P = 0.08). Seasonality was not a significant predictor for any recovery metric in multivariable regressions.

CONCLUSION

Sport-related concussions occurring in the early third of the season took significantly less time to symptom resolution than those occurring in the later third of the season; however, this was not statistically significant in multivariable analyses. No association was observed between seasonality and time to RTL and RTP. A trend of worse recovery with concussions later in the season may be present.

Head Acceleration Events in Male Community Rugby Players: An Observational Cohort Study across Four Playing Grades, from Under-13 to Senior Men

OBJECTIVES

The aim of this study was to examine the cumulative head acceleration event (HAE) exposure in male rugby players from the Under-13 (U13) to senior club level over 4 weeks of matches and training during the 2021 community rugby season.

METHODS

This prospective, observational cohort study involved 328 male rugby players. Players were representative of four playing grades: U13 (N = 60, age 12.5 ± 0.6 years), U15 (N = 100, age 14.8 ± 0.9 years), U19 (N = 78, age 16.9 ± 0.7 years) and Premier senior men (N = 97, age 22.5 ± 3.1 years). HAE exposure was tracked across 48 matches and 113 training sessions. HAEs were recorded using boil-and-bite instrumented mouthguards (iMGs). The study assessed the incidence and prevalence of HAEs by ages, playing positions, and session types (match or training).

RESULTS

For all age grades, weekly match HAE incidence was highest at lower magnitudes (10-29 g). Proportionally, younger players experienced higher weekly incidence rates during training. The U19 players had 1.36 times the risk of high-magnitude (> 30 g) events during matches, while the U13 players had the lowest risk compared with all other grades. Tackles and rucks accounted for the largest HAE burden during matches, with forwards having 1.67 times the risk of > 30 g HAEs in rucks compared with backs.

CONCLUSIONS

This study provides novel data on head accelerations during rugby matches and training. The findings have important implications for identifying populations at greatest risk of high cumulative and acute head acceleration. Findings may guide training load management and teaching of skill execution in high-risk activities, particularly for younger players who may be exposed to proportionally more contact during training and for older players during matches.

On-field instrumented mouthguard coupling

Instrumented mouthguard (iMG) sensors have been developed to measure sports head acceleration events (HAE) in brain injury research. Laboratory validation studies show that effective coupling of iMGs with the human skull is crucial for accurate head kinematics measurements. However, iMG-skull coupling has not been investigated in on-field sports settings. The objective of this study was to assess on-field iMG coupling using infrared proximity sensing and to investigate coupling effects on kinematics signal characteristics. Forty-two university-level men's ice hockey (n = 21) and women's rugby (n = 21) athletes participated in the study, wearing iMGs during 6-7 month in-season periods. Proximity data classified video-verified HAE recordings into four main iMG coupling categories: coupled (on-teeth), decoupling (on-teeth to off-teeth), recoupling (off-teeth to on-teeth) and decoupled (off-teeth). Poorly-coupled HAEs showed significantly higher peak angular acceleration amplitudes and greater signal power in medium-high frequency bands compared with well-coupled HAEs, indicating potential iMG movements independent of the skull. Further, even video-verified true positives included poorly-coupled HAEs, and iMG coupling patterns varied between the men's hockey and women's rugby teams. Our findings show the potential of using proximity sensing in iMGs to identify poorly-coupled HAEs. Utilizing this data screening process in conjunction with video review may mitigate a key source of sensor noise and enhance the overall quality of on-field sports HAE datasets.

Head Impacts in the Top 1% by Peak Linear Acceleration and/or Work Cause Immediate Concussion Signs and 'Check Engine' Responses in Military Service Members and Civilian Athletes

PURPOSE

Historically, head impact monitoring sensors have suffered from single impact measurement errors, leading to their data described by clinical experts as 'clinically irrelevant.' The purpose of this study was to use an accurate impact monitoring mouthguard system and (1) define head impact distributions for military service members and civilians and (2) determine if there was a dose-response relationship between accurately measured head impact magnitudes versus observations of concussion signs.

METHODS

A laboratory-calibrated commercial impact monitoring mouthguard system, along with video and hardware to confirm the sensor was on the teeth during impacts, was used to acquire 54,602 head acceleration events (HAE) in 973 military and civilian subjects over 3,449 subject days.

RESULTS

There were 17,551 head impacts (32% of HAE) measured with peak linear acceleration (PLA) > 10 g and 37,051 low-g events (68% of HAE) in the range of activities of daily living < 10 g PLA. The median of all HAE and of all head impacts was 8 g/15 g PLA and 1 J/4 J Work, respectively. The top 1% of head impacts were above 47 g and 32 J, respectively. There were fifty-six (56) head impacts where at least one clinical indicator of a concussion sign was observed. All the clinical indicator impacts were in the top 1% by magnitude of PLA, Work, or both. The median magnitude of these 'check engine' impacts was 58 g and 48 J. This median magnitude was substantially larger than the median of all HAE as well as the median of all head impacts.

CONCLUSION

This study shows a correlation between single head impacts in the top 1% by peak linear acceleration and/or Work and clinical indicators of concussion signs in civilians and military service members.

Interaction of Surface Type, Temperature, and Week of Season on Concussion Risk in the National Football League: A Bayesian Analysis

BACKGROUND

Artificial turf fields and environmental conditions may influence sports concussion risk, but existing research is limited by uncontrolled confounding factors, limited sample size, and the assumption that risk factors are independent of one another. The purpose of this study was to examine how playing surface, time of season, and game temperature relate to diagnosed concussion risk in the National Football League (NFL).

METHODS

This retrospective cohort study examined data from the 2012 to the 2019 NFL regular season. We fit Bayesian negative binomial regression models to relate how playing surface, game temperature, and week of the season independently related to diagnosed concussion risk and any interactions among these factors.

RESULTS

We identified 1096 diagnosed concussions in 1830 games. There was a >99% probability that concussion risk was reduced on grass surface (median incidence rate ratio [IRR] = 0.78 [95% credible interval: 0.68, 0.89]), >99% probability that concussion risk was lower at higher temperatures (IRR = 0.85 [0.76,0.95] for each 7.9 °C), and >91% probability that concussion risk increased with each week of the season (IRR = 1.02 [1.00,1.04]). There was an >84% probability for a surface × temperature interaction (IRR = 1.01 [0.96, 1.28]) and >75% probability for a surface × week interaction (IRR = 1.02 [0.99, 1.05]).

CONCLUSIONS

Diagnosed concussion risk is increased on artificial turf compared with natural grass, and this is exacerbated in cold weather and, independently, later in the season. The complex interplay between these factors necessitates accounting for multiple factors and their interactions when investigating sports injury risk factors and devising mitigation methods.

Integrating biomechanics with stakeholder perspectives to inform safety in grassroots dirt track racing

Grassroots dirt track racing is a foundational part of motorsports with a high risk of severe injury. This study aimed to gather perspectives and experiences of motorsports drivers surrounding safety and head acceleration events experienced during grassroots dirt track racing to inform strategies to improve driver safety. Thirteen drivers (n=9 who primarily race on dirt tracks; n=4 who primarily race on pavement tracks) with prior dirt track racing experience participated in separate, group-specific focus groups and/or one-on-one interviews where video, simulations of head motion, and head acceleration data were shared. Peak kinematics of laps and crash contact scenarios were recorded, and head perturbations (i.e., deviations in head motion relative to its moving-average trajectory) were quantified for each lap and presented through guided discussion. Responses were summarized using Rapid Assessment Process. Audio recordings and field notes were collected from focus groups and interviews and analyzed across 25 domains. Drivers described dirt track racing as short, fast bursts of racing. Benefits of dirt track racing for driver development were described, including learning car control. Drivers acknowledged risks of racing and expressed confidence in safety equipment but identified areas for improvement. Drivers observed lateral bouncing of the head in video and simulations but recognized that such motions were not noticed while racing. Track conditions and track type were identified as factors influencing head perturbations. Mean PLA (5.5 g) and PRV (3.07 rad/s) of perturbations experienced during racing laps and perturbation frequencies of 5 and 7 perturbations per second were reported. Generally, drivers accurately estimated the head acceleration magnitudes but were surprised by the frequency and maximum magnitude of perturbations. Maximum perturbation magnitudes (26.8 g and 19.0 rad/s) were attributed to hitting a "rut" in the dirt. Drivers described sudden stops, vertical loads due to landing from a large height, and impacts to the vehicle frame as crash events they physically feel the most. Summary statistics for crashes (medians = 7.30 g, 6.94 rad/s) were reported. Typical impact magnitudes measured in other sports (e.g., football) were provided for context. Upon reviewing the biomechanics, drivers were surprised that crash accelerations were relatively low compared to other contact/collision sports. Pavement drivers noted limited safety features in dirt track racing compared to pavement, including rigidity of vehicle frames, seat structure, seatbelt integration, and lack of oversight from sanctioning bodies. Most drivers felt seat inserts and head and neck restraints are important for injury prevention; however, usage of seat inserts and preferred head and neck restraint system differed among drivers. Drivers described their perspectives and experiences related to safety and identified strategies to improve safety in grassroots dirt track racing. Drivers expressed support for future safety research.

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.

Acute evaluation of sport-related concussion and implications for the Sport Concussion Assessment Tool (SCAT6) for adults, adolescents and children: a systematic review

OBJECTIVES

To systematically review the scientific literature regarding the acute assessment of sport-related concussion (SRC) and provide recommendations for improving the Sport Concussion Assessment Tool (SCAT6).

DATA SOURCES

Systematic searches of seven databases from 2001 to 2022 using key words and controlled vocabulary relevant to concussion, sports, SCAT, and acute evaluation.

ELIGIBILITY CRITERIA

(1) Original research articles, cohort studies, case-control studies, and case series with a sample of >10; (2) ≥80% SRC; and (3) studies using a screening tool/technology to assess SRC acutely (<7 days), and/or studies containing psychometric/normative data for common tools used to assess SRC.

DATA EXTRACTION

Separate reviews were conducted involving six subdomains: Cognition, Balance/Postural Stability, Oculomotor/Cervical/Vestibular, Emerging Technologies, and Neurological Examination/Autonomic Dysfunction. Paediatric/Child studies were included in each subdomain. Risk of Bias and study quality were rated by coauthors using a modified SIGN (Scottish Intercollegiate Guidelines Network) tool.

RESULTS

Out of 12 192 articles screened, 612 were included (189 normative data and 423 SRC assessment studies). Of these, 183 focused on cognition, 126 balance/postural stability, 76 oculomotor/cervical/vestibular, 142 emerging technologies, 13 neurological examination/autonomic dysfunction, and 23 paediatric/child SCAT. The SCAT discriminates between concussed and non-concussed athletes within 72 hours of injury with diminishing utility up to 7 days post injury. Ceiling effects were apparent on the 5-word list learning and concentration subtests. More challenging tests, including the 10-word list, were recommended. Test-retest data revealed limitations in temporal stability. Studies primarily originated in North America with scant data on children.

CONCLUSION

Support exists for using the SCAT within the acute phase of injury. Maximal utility occurs within the first 72 hours and then diminishes up to 7 days after injury. The SCAT has limited utility as a return to play tool beyond 7 days. Empirical data are limited in pre-adolescents, women, sport type, geographical and culturally diverse populations and para athletes.

PROSPERO REGISTRATION NUMBER

CRD42020154787.

Youth Tackle Football Head-Impact Estimation by Players and Parents: Is the Perception the Reality?

CONTEXT

With growing concerns surrounding exposure to head impacts in youth tackle football, players and parents must understand the exposure level when assenting and consenting to participate.

OBJECTIVE

To determine whether youth football players and parents could estimate on-field head-impact frequency, severity, and location.

DESIGN

Prospective cohort study.

SETTING

Football field.

PATIENTS OR OTHER PARTICIPANTS

We administered a 10-question head-impact estimation tool to parents (n = 23; mean age = 36.5 years [95% CI = 31.7, 37.3 years]) and players (n = 16 boys; mean age = 11.1 years [95% CI = 10.3, 11.8 years]).

MAIN OUTCOME MEASURE(S)

Player on-field head-impact exposure was captured using the Triax SIM-G system. We determined the accuracy between player and parent estimates relative to on-field head-impact exposures using κ and weighted κ values.

RESULTS

Youth tackle football players and parents did not accurately estimate on-field head-impact frequency (κ range = -0.09 to 0.40), severity (κ range = -0.05 to 0.34), or location (κ range = -0.30 to 0.13). Players and parents overestimated head-impact frequency in practices but underestimated the frequency in games. Both groups overestimated head-impact severity, particularly in games. Most players and parents underestimated the number of head impacts to the top of the head, particularly during practices.

CONCLUSIONS

Underestimations of head-impact frequency in games and to the top of the head suggest that informed consent processes aimed at educating players and parents should be improved. Overestimations of head-impact frequency in practices and severity may explain declining rates of youth tackle football participation.

Differences in head impact biomechanics between playing positions in Canadian high school football players

The objective of this study was to compare head impact magnitudes and time between impacts among positions in Canadian high-school football. Thirty nine players from two high-school football teams were recruited and assigned a position profile: Profile 1 (quarterback, receiver, defensive back, kicker), Profile 2 (linebacker, running back), and Profile 3 (linemen). Players wore instrumented mouthguards to measure peak magnitudes of linear and angular acceleration and velocity for each head impact throughout the season. A principal component analysis reduced the dimensionality of biomechanical variables, resulting in one principal component (PC1) score assigned to every impact. Time between impacts was calculated by subtracting the timestamps of subsequent head impacts within a session. Significant differences in PC1 scores and time between impacts occurred between playing position profiles (ps<0.001). Post-hoc comparisons determined that PC1 was greatest in Profile 2, followed by Profiles 1 and 3. Time between impacts was lowest in Profile 3, followed by Profiles 2 and 1. This study delivers a new method of reducing the multidimensionality of head impact magnitudes and suggests different Canadian high-school football playing positions experience different head impact magnitudes and frequencies, which is important for monitoring concussion and repetitive head impact exposure.

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.

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.

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.

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 .

Automated soccer head impact exposure tracking using video and deep learning

Head impacts are highly prevalent in sports and there is a pressing need to investigate the potential link between head impact exposure and brain injury risk. Wearable impact sensors and manual video analysis have been utilized to collect impact exposure data. However, wearable sensors suffer from high deployment cost and limited accuracy, while manual video analysis is a long and resource-intensive task. Here we develop and apply DeepImpact, a computer vision algorithm to automatically detect soccer headers using soccer game videos. Our data-driven pipeline uses two deep learning networks including an object detection algorithm and temporal shift module to extract visual and temporal features of video segments and classify the segments as header or nonheader events. The networks were trained and validated using a large-scale professional-level soccer video dataset, with labeled ground truth header events. The algorithm achieved 95.3% sensitivity and 96.0% precision in cross-validation, and 92.9% sensitivity and 21.1% precision in an independent test that included videos of five professional soccer games. Video segments identified as headers in the test data set correspond to 3.5 min of total film time, which can be reviewed through additional manual video verification to eliminate false positives. DeepImpact streamlines the process of manual video analysis and can help to collect large-scale soccer head impact exposure datasets for brain injury research. The fully video-based solution is a low-cost alternative for head impact exposure monitoring and may also be expanded to other sports in future work.

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.

Head Impact Exposure in Youth and Collegiate American Football

The relationship between head impact and subsequent brain injury for American football players is not well-defined, especially for youth. The objective of this study is to quantify and assess Head Impact Exposure (HIE) metrics among youth and collegiate football players. This multi-season study enrolled 639 unique athletes (354 collegiate; 285 youth, ages 9-14), recording 476,209 head impacts (367,337 collegiate; 108,872 youth) over 971 sessions (480 collegiate; 491 youth). Youth players experienced 43 and 65% fewer impacts per competition and practice, respectively, and lower impact magnitudes compared to collegiate players (95th percentile peak linear acceleration (PLA, g) competition: 45.6 vs 61.9; 95th percentile PLA practice: 42.6 vs 58.8; 95th percentile peak rotational acceleration (PRA, rad·s^-2) competition: 2262 vs 4422; 95th percentile PRA practice: 2081 vs 4052; 95th percentile HITsp competition: 25.4 vs 32.8; 95th percentile HITsp practice: 23.9 vs 30.2). Impacts during competition were more frequent and of greater magnitude than during practice at both levels. Quantified comparisons of head impact frequency and magnitude between youth and collegiate athletes reveal HIE differences as a function of age, and expanded insight better informs the development of age-appropriate guidelines for helmet design, prevention measures, standardized testing, brain injury diagnosis, and recovery management.

Overview of Traumatic Brain Injury in American Football Athletes

OBJECTIVE

The aim of this review is to provide a summary of the epidemiology, clinical presentation, pathophysiology, and treatment of traumatic brain injury in collision athletes, particularly those participating in American football.

DATA SOURCES

A literature search was conducted using the PubMed/MEDLINE and Google Scholar databases for publications between 1990 and 2019. The following search phrases were used: "concussion," "professional athletes," "collision athletes," "mild traumatic brain injury," "severe traumatic brain injury," "management of concussion," "management of severe traumatic brain injury," and "chronic traumatic encephalopathy." Publications that did not present epidemiology, clinical presentation, pathophysiology, radiological evaluation, or management were omitted. Classic articles as per senior author recommendations were retrieved through reference review.

RESULTS

The results of the literature review yielded 147 references: 21 articles discussing epidemiology, 16 discussing clinical presentation, 34 discussing etiology and pathophysiology, 10 discussing radiological evaluation, 34 articles for on-field management, and 32 articles for medical and surgical management.

CONCLUSION

Traumatic brain injuries are frequent in professional collision athletes, and more severe injuries can have devastating and lasting consequences. Although sport-related concussions are well studied in professional American football, there is limited literature on the epidemiology and management of severe traumatic brain injuries. This article reviews the epidemiology, as well as the current practices in sideline evaluation, acute management, and surgical treatment of concussions and severe traumatic brain injury in professional collision athletes. Return-to-play decisions should be based on individual patient symptoms and recovery.

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.

Characterizing Head Impact Exposure in Men and Women During Boxing and Mixed Martial Arts

Background:

The accumulation of subconcussive impacts has been implicated in permanent neurological impairment. A gap in understanding the relationship between head impacts and neurological function is the lack of precise characterization and quantification of forces that individuals experience during sports training and competition.

Purpose:

To characterize impact exposure during training and competition among male and female athletes participating in boxing and mixed martial arts (MMA) via an instrumented custom-fit Impact Monitoring Mouthguard (IMM).

Study Design:

Cross-sectional study; Level of evidence, 3.

Methods:

Twenty-three athletes (n = 4 women) were provided a custom-fit IMM. The IMM monitored impacts during sparring and competition. All training and competition sessions were videotaped. Video and IMM data were synchronized for post hoc data verification of true positives and substantiation of impact location. IMM data were collected from boxing and MMA athletes at a collaborating site. For each true-positive impact, peak linear acceleration and peak angular acceleration were calculated. Wilcoxon rank sum tests were used to evaluate potential differences in sport, activity type, and sex with respect to each outcome. Differences in impact location were assessed via Kruskal-Wallis tests.

Results:

IMM data were collected from 53 amateur training sessions and 6 competitions (session range, 5-20 minutes). A total of 896 head impacts (men, n = 786; women, n = 110) were identified using IMM data and video verification: 827 in practice and 69 during competition. MMA and boxers experienced a comparable number of impacts per practice session or competition. In general, MMA impacts produced significantly higher peak angular acceleration than did boxing impacts (P < .001) and were more varied in impact location on the head during competitions. In terms of sex, men experienced a greater number of impacts than women per practice session. However, there was no significant difference between men and women in terms of impact magnitude.

Conclusion:

Characteristic profiles of head impact exposure differed between boxing and MMA athletes; however, the impact magnitudes were not significantly different for male and female athletes.

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.

Development of a Machine-Learning-Based Classifier for the Identification of Head and Body Impacts in Elite Level Australian Rules Football Players

Background: Exposure to thousands of head and body impacts during a career in contact and collision sports may contribute to current or later life issues related to brain health. Wearable technology enables the measurement of impact exposure. The validation of impact detection is required for accurate exposure monitoring. In this study, we present a method of automatic identification (classification) of head and body impacts using an instrumented mouthguard, video-verified impacts, and machine-learning algorithms.

Methods: Time series data were collected via the Nexus A9 mouthguard from 60 elite level men (mean age = 26.33; SD = 3.79) and four women (mean age = 25.50; SD = 5.91) from the Australian Rules Football players from eight clubs, participating in 119 games during the 2020 season. Ground truth data labeling on the captures used in this machine learning study was performed through the analysis of game footage by two expert video reviewers using SportCode and Catapult Vision. The visual labeling process occurred independently of the mouthguard time series data. True positive captures (captures where the reviewer directly observed contact between the mouthguard wearer and another player, the ball, or the ground) were defined as hits. Spectral and convolutional kernel based features were extracted from time series data. Performances of untuned classification algorithms from scikit-learn in addition to XGBoost were assessed to select the best performing baseline method for tuning.

Results: Based on performance, XGBoost was selected as the classifier algorithm for tuning. A total of 13,712 video verified captures were collected and used to train and validate the classifier. True positive detection ranged from 94.67% in the Test set to 100% in the hold out set. True negatives ranged from 95.65 to 96.83% in the test and rest sets, respectively.

Discussion and conclusion: This study suggests the potential for high performing impact classification models to be used for Australian Rules Football and highlights the importance of frequencies <150 Hz for the identification of these impacts.

Head Impact Sensor Triggering Bias Introduced by Linear Acceleration Thresholding

Contact sports players frequently sustain head impacts, most of which are mild impacts exhibiting 10-30 g peak head center-of-gravity (CG) linear acceleration. Wearable head impact sensors are commonly used to measure exposure and typically detect impacts using a linear acceleration threshold. However, linear acceleration across the head can substantially vary during 6-degree-of-freedom motion, leading to triggering biases that depend on sensor location and impact condition. We conducted an analytical investigation with impact characteristics extracted from on-field American football and soccer data. We assumed typical mouthguard sensor locations and evaluated whether simulated multi-directional impacts would trigger recording based on per-axis or resultant acceleration thresholding. Across 1387 impact directions, a 10g peak CG linear acceleration impact would trigger at only 24.7% and 31.8% of directions based on a 10 g per-axis and resultant acceleration threshold, respectively. Anterior impact locations had lower trigger rates and even a 30 g impact would not trigger recording in some directions. Such triggering biases also varied by sensor location and linear-rotational head kinematics coupling. Our results show that linear acceleration-based impact triggering could lead to considerable bias in head impact exposure measurements. We propose a set of recommendations to consider for sensor manufacturers and researchers to mitigate this potential exposure measurement bias.

Selected issues in sport-related concussion (SRC|mild traumatic brain injury) for the team physician: a consensus statement

Selected Issues in Sport-Related Concussion (SRC|Mild Traumatic Brain Injury) for the Team Physician: A Consensus Statement is title 22 in a series of annual consensus documents written for the practicing team physician. This document provides an overview of selected medical issues important to team physicians who are responsible for athletes with sports-related concussion (SRC). This statement was developed by the Team Physician Consensus Conference (TPCC), an annual project-based alliance of six major professional associations. The goal of this TPCC statement is to assist the team physician in providing optimal medical care for the athlete with SRC.

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.

Potential Mechanisms of Acute Standing Balance Deficits After Concussions and Subconcussive Head Impacts: A Review

Standing balance deficits are prevalent after concussions and have also been reported after subconcussive head impacts. However, the mechanisms underlying such deficits are not fully understood. The objective of this review is to consolidate evidence linking head impact biomechanics to standing balance deficits. Mechanical energy transferred to the head during impacts may deform neural and sensory components involved in the control of standing balance. From our review of acute balance-related changes, concussions frequently resulted in increased magnitude but reduced complexity of postural sway, while subconcussive studies showed inconsistent outcomes. Although vestibular and visual symptoms are common, potential injury to these sensors and their neural pathways are often neglected in biomechanics analyses. While current evidence implies a link between tissue deformations in deep brain regions including the brainstem and common post-concussion balance-related deficits, this link has not been adequately investigated. Key limitations in current studies include inadequate balance sampling duration, varying test time points, and lack of head impact biomechanics measurements. Future investigations should also employ targeted quantitative methods to probe the sensorimotor and neural components underlying balance control. A deeper understanding of the specific injury mechanisms will inform diagnosis and management of balance deficits after concussions and subconcussive head impact exposure.

Selected Issues in Sport-Related Concussion (SRC | Mild Traumatic Brain Injury) for the Team Physician: A Consensus Statement

ABSTRACT

Selected Issues in Sport-Related Concussion (SRC | Mild Traumatic Brain Injury) for the Team Physician: A Consensus Statement is title 22 in a series of annual consensus articles written for the practicing team physician. This document provides an overview of select medical issues important to team physicians who are responsible for athletes with sports-related concussion (SRC). This statement was developed by the Team Physician Consensus Conference (TPCC), an annual project-based alliance of six major professional associations. The goal of this TPCC statement is to assist the team physician in providing optimal medical care for the athlete with SRC.

Differences in Head Impact Exposures Between Youth Tackle and Flag Football Games and Practices: Potential Implications for Prevention Strategies

BACKGROUND

Interventions designed to reduce the risk for head impacts and concussion in youth football have increased over the past decade; however, understanding of the role of regular game play on head impact exposure among youth tackle and flag football athletes is currently limited.

PURPOSE

To explore head impact exposure among youth tackle and flag football athletes (age range, 6-14 years) during both practices and games.

STUDY DESIGN

Cohort study; Level of evidence, 2.

METHODS

Using the Vector MouthGuard sensor, the authors collected head impact data from 524 tackle and flag youth football athletes over the course of a football season. Quantities of interest were estimated from regression models using Bayesian methods.

RESULTS

For impacts ≥10g, a tackle football athlete had an estimated 17.55 (95% CI, 10.78-28.96) times more head impacts per practice compared with a flag football athlete (6.85 [95% CI, 6.05-7.76] and 0.39 [95% CI, 0.24-0.62] head impacts, respectively). Additionally, a tackle football athlete had an estimated 19.48 (95% CI, 12.74-29.98) times more head impacts per game compared with a flag football athlete (13.59 [95% CI, 11.97-15.41] and 0.70 [95% CI, 0.46-1.05] head impacts, respectively). Among tackle football athletes, the estimated average impact rate was 6.51 (95% CI, 5.75-7.37) head impacts during a practice and 12.97 (95% CI, 11.36-14.73) impacts during a game, resulting in 2.00 (95% CI, 1.74-2.29) times more ≥10g head impacts in games versus practices. Tackle football athletes had 2.06 (95% CI, 1.80-2.34) times more high-magnitude head impacts (≥40g) during a game than during a practice. On average, flag football athletes experienced an estimated 0.37 (95% CI, 0.20-0.60) head impacts during a practice and 0.77 (95% CI, 0.53-1.06) impacts during a game, resulting in 2.06 (95% CI, 1.29-3.58) times more ≥10g head impacts in games versus practices. Because of model instability caused by a large number of zero impacts for flag football athletes, a comparison of high-magnitude head impacts is not reported for practices or games.

CONCLUSION

This study provides a characterization of the head impact exposure of practices and games among a large population of youth tackle and flag football athletes aged 6 to 14 years. These findings suggest that a greater focus on game-based interventions, such as fair play interventions and strict officiating, may be beneficial to reduce head impact exposures for youth football athletes.

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.

Opportunities for Prevention of Concussion and Repetitive Head Impact Exposure in College Football Players: A Concussion Assessment, Research, and Education (CARE) Consortium Study

Importance

Concussion ranks among the most common injuries in football. Beyond the risks of concussion are growing concerns that repetitive head impact exposure (HIE) may increase risk for long-term neurologic health problems in football players.

Objective

To investigate the pattern of concussion incidence and HIE across the football season in collegiate football players.

Design, Setting, and Participants

In this observational cohort study conducted from 2015 to 2019 across 6 Division I National Collegiate Athletic Association (NCAA) football programs participating in the Concussion Assessment, Research, and Education (CARE) Consortium, a total of 658 collegiate football players were instrumented with the Head Impact Telemetry (HIT) System (46.5% of 1416 eligible football players enrolled in the CARE Advanced Research Core). Players were prioritized for instrumentation with the HIT System based on their level of participation (ie, starters prioritized over reserves).

Exposure

Participation in collegiate football games and practices from 2015 to 2019.

Main Outcomes and Measures

Incidence of diagnosed concussion and HIE from the HIT System.

Results

Across 5 seasons, 528 684 head impacts recorded from 658 players (all male, mean age [SD], 19.02 [1.25] years) instrumented with the HIT System during football practices or games met quality standards for analysis. Players sustained a median of 415 (interquartile range [IQR], 190-727) recorded head impacts (ie, impacts) per season. Sixty-eight players sustained a diagnosed concussion. In total, 48.5% of concussions (n = 33) occurred during preseason training, despite preseason representing only 20.8% of the football season (0.059 preseason vs 0.016 regular-season concussions per team per day; mean difference, 0.042; 95% CI, 0.020-0.060; P = .001). Total HIE in the preseason occurred at twice the proportion of the regular season (324.9 vs 162.4 impacts per team per day; mean difference, 162.6; 95% CI, 110.9-214.3; P < .001). Every season, HIE per athlete was highest in August (preseason) (median, 146.0 impacts; IQR, 63.0-247.8) and lowest in November (median, 80.0 impacts; IQR, 35.0-148.0). Over 5 seasons, 72% of concussions (n = 49) (game proportion, 0.28; 95% CI, 0.18-0.40; P < .001) and 66.9% of HIE (262.4 practices vs 137.2 games impacts per player; mean difference, 125.3; 95% CI, 110.0-140.6; P < .001) occurred in practice. Even within the regular season, total HIE in practices (median, 175.0 impacts per player per season; IQR, 76.0-340.5) was 84.2% higher than in games (median, 95.0 impacts per player per season; IQR, 32.0-206.0).

Conclusions and Relevance

Concussion incidence and HIE among college football players are disproportionately higher in the preseason than regular season, and most concussions and HIE occur during football practices, not games. These data point to a powerful opportunity for policy, education, and other prevention strategies to make the greatest overall reduction in concussion incidence and HIE in college football, particularly during preseason training and football practices throughout the season, without major modification to game play. Strategies to prevent concussion and HIE have important implications to protecting the safety and health of football players at all competitive levels.

Heading-Related Slowing by Twenty-Four Hours in Youth Athletes

Research suggests cumulative effects of repetitive head impacts (RHIs) on brain structure, especially with younger age of first exposure. Further, recent evidence suggests no immediate cognitive changes with increased RHIs but impairments across a sports season. The aim was to examine more closely the short-term time course of behavioral effects of exposure to RHI. Across 2 years, 18 female adolescent soccer players were tested on ProPoint (sensorimotor) and AntiPoint (cognitive) tasks with reaction time (RT) being the main outcome measure. The athletes were tested before and after workout with ball heading (immediate effect), as well as 24 h after workout (24 h effect) throughout two consecutive seasons. The number of headers performed 24 h before workout, during workout, and season average per workout were recorded. The athletes showed a decrease in ProPoint and AntiPoint RTs immediately after a workout, with no change or decrease in RTs with increasing RHIs. However, increasing RHIs during workout increased RTs in both tasks when tested 24 h later. The athletes also showed an increase in AntiPoint RTs with increasing season average RHIs. Our findings show a complex time course of effects of RHIs on sensorimotor and cognitive performance in adolescent athletes, with exposure to RHIs associated with no change or immediate benefits and then deficits by 24 h. Pathophysiological changes associated with exercise and traumatic brain injury can account for the sensorimotor and cognitive performance changes occurring within 24 h after RHIs.

An Improved Method for Developing Injury Risk Curves Using the Brier Metric Score

Many injury metrics are routinely proposed from measured or derived quantities from biomechanical experiments using post mortem human subjects (PMHS). The existing literature did not provide guidance on deciding between parameters collected in an experiment that would be best to use for the development of human injury probability curves (HIPC). The objective of this study was to use the Brier Metric Score (BMS) to identify the most appropriate metric from an experiment that predicts injury outcomes. The Brier Metric Score assesses how well a metric predicts the outcome for a censored data point (a lower BMS is better). Survival analysis was then conducted with the selected metric and the best distribution was selected using Akaike information criterion (AIC). Confidence intervals (CIs) and the normalized confidence interval width (NCIS) were calculated for the injury probability curve. The testing and validation of the methods described were performed using biomechanics data in the open literature. The methods for the HIPC development procedure detailed herein have been rigorously tested and used in the generation of WIAMan HIPCs and Injury Assessment Reference Curves (IARCs) for the WIAMan ATD, but can also be used in other ATD or PMHS injury risk curve development.

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.

High Energy Side and Rear American Football Head Impacts Cause Obvious Performance Decrement on Video

The objective of this study was to compare head impact data acquired with an impact monitoring mouthguard (IMM) to the video-observed behavior of athletes' post-collision relative to their pre-collision behaviors. A total of n = 83 college and high school American football players wore the IMM and were video-recorded over 260 athlete-exposures. Ex-athletes and clinicians reviewed the video in a two-step process and categorized abnormal post-collision behaviors according to previously published Obvious Performance Decrement (OPD) definitions. Engineers qualitatively reviewed datasets to check head impact and non-head impact signal frequency and magnitude. The ex-athlete reviewers identified 2305 head impacts and 16 potential OPD impacts, 13 of which were separately categorized as Likely-OPD impacts by the clinical reviewers. All 13 Likely-OPD impacts were in the top 1% of impacts measured by the IMM (ranges 40-100 g, 3.3-7.0 m/s and 35-118 J) and 12 of the 13 impacts (92%) were to the side or rear of the head. These findings require confirmation in a larger data set before proposing any type of OPD impact magnitude or direction threshold exists. However, OPD cases in this study compare favorably with previously published impact monitoring studies in high school and college American football players that looked for OPD signs, impact magnitude and direction. Our OPD findings also compare well with NFL reconstruction studies for ranges of concussion and sub-concussive impact magnitudes in side/rear collisions, as well as prior theory, analytical models and empirical research that suggest a directional sensitivity to brain injury exists for single high-energy impacts.

Concussions in Dancers and Other Performing Artists

Dancers and other performing artists are subject to head impacts that result in concussion-like symptoms. In spite of this, performing arts do not have access to the continual, focused emphasis on the diagnosis, management, and prevention of concussions that is commonplace in sports. Performing arts present a unique environment in which concussions occur and must be managed. This article outlines what is known about performing arts concussions, describes mechanisms of head impacts sustained by participants in dance and the related artforms of theater, circus, and film and television stunts, and offers concussion management guidelines for these artistic fields.

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.

A Two-Phased Approach to Quantifying Head Impact Sensor Accuracy: In-Laboratory and On-Field Assessments

Measuring head impacts in sports can further our understanding of brain injury biomechanics and, hopefully, advance concussion diagnostics and prevention. Although there are many head impact sensors available, skepticism on their utility exists over concerns related to measurement error. Previous studies report mixed reliability in head impact sensor measurements, but there is no uniform approach to assessing accuracy, making comparisons between sensors and studies difficult. The objective of this paper is to introduce a two-phased approach to evaluating head impact sensor accuracy. The first phase consists of in-lab impact testing on a dummy headform at varying impact severities under loading conditions representative of each sensor's intended use. We quantify in-lab accuracy by calculating the concordance correlation coefficient (CCC) between a sensor's kinematic measurements and headform reference measurements. For sensors that performed reasonably well in the lab (CCC ≥ 0.80), we completed a second phase of evaluation on-field. Through video validation of impacts measured by sensors on athletes, we classified each sensor measurement as either true-positive and false-positive impact events and computed positive predictive value (PPV) to summarize real-world accuracy. Eight sensors were tested in phase one, but only four sensors were assessed in phase two. Sensor accuracy varied greatly. CCC from phase one ranged from 0.13 to 0.97, with an average value of 0.72. Overall, the four devices that were implemented on-field had PPV that ranged from 16.3 to 91.2%, with an average value of 60.8%. Performance in-lab was not always indicative of the device's performance on-field. The methods proposed in this paper aim to establish a comprehensive approach to the evaluation of sensors so that users can better interpret data collected from athletes.