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.

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.

Do American Youth Football Players Intentionally Use Their Heads for High-Magnitude Impacts?

BACKGROUND: Concern for head injuries is widespread and has been reported by the media to be the number one cause of decreased participation in football among the American youth population. Identifying player mechanisms associated with intentional, or purposeful, head impacts should provide critical data for rule modifications, educational programs, and equipment design. PURPOSE: To investigate the frequency of intentional and unintentional head impacts and to examine the player mechanisms associated with intentional high-magnitude head impacts by comparing the impact mechanism distributions among session type, player position, and ball possession. STUDY DESIGN: Cross-sectional study; Level of evidence, 3. METHODS: Head impact sensors and video footage of 68 players were used to analyze and classify 1319 high-magnitude impacts recorded over 1 season of youth football. RESULTS: In total, 80% of the high-magnitude head impacts were classified as being caused by intentional use of the head. Head-to-head impact was the primary impact mechanism (n = 868; 82.7%) within the 1050 intentional high-magnitude impacts, with classifiable mechanisms, followed by head-to-body (n = 139; 13.2%), head-to-ground (n = 34; 3.2%), and head-to-equipment (n = 9; 0.9%). Head-to-head impacts also accounted for a greater proportion of impacts during practices (n = 625; 88.9%) than games, for linemen (n = 585; 90.3%) than perimeters and backs, and for ball carriers (n = 72; 79.1%) than tacklers. CONCLUSION: Overall, the majority of high-magnitude head impacts were intentional and resulted from head-to-head contact. The proportion of head-to-head contact was significantly higher for practices than games, linemen than backs and perimeter players, and ball carriers than tacklers.

Head Impact Exposure in Practices Correlates With Exposure in Games for Youth Football Players.

This study aimed to compare head impact exposures between practices and games in football players ages 9 to 14 years, who account for approximately 70% of all football players in the United States. Over a period of 2 seasons, 136 players were enrolled from 3 youth programs, and 49,847 head impacts were recorded from 345 practices and 137 games. During the study, individual players sustained a median of 211 impacts per season, with a maximum of 1226 impacts. Players sustained 50th (95th) percentile peak linear acceleration of 18.3 (46.9) g, peak rotational acceleration of 1305.4 (3316.6) rad·s-2, and Head Impact Technology Severity Profile of 13.7 (24.3), respectively. Overall, players with a higher frequency of head impacts at practices recorded a higher frequency of head impacts at games (P < .001, r2 = .52), and players who sustained a greater average magnitude of head impacts during practice also recorded a greater average magnitude of head impacts during games (P < .001). The youth football head impact data quantified in this study provide valuable insight into the player exposure profile, which should serve as a key baseline in efforts to reduce injury.

Estimated Brain Tissue Response Following Impacts Associated With and Without Diagnosed Concussion.

Kinematic measurements of head impacts are sensitive to sports concussion, but not highly specific. One potential reason is these measures reflect input conditions only and may have varying degrees of correlation to regional brain tissue deformation. In this study, previously reported head impact data recorded in the field from high school and collegiate football players were analyzed using two finite element head models (FEHM). Forty-five impacts associated with immediately diagnosed concussion were simulated along with 532 control impacts without identified concussion obtained from the same players. For each simulation, intracranial response measures (max principal strain, strain rate, von Mises stress, and pressure) were obtained for the whole brain and within four regions of interest (ROI; cerebrum, cerebellum, brain stem, corpus callosum). All response measures were sensitive to diagnosed concussion; however, large inter-athlete variability was observed and sensitivity strength depended on measure, ROI, and FEHM. Interestingly, peak linear acceleration was more sensitive to diagnosed concussion than all intracranial response measures except pressure. These findings suggest FEHM may provide unique and potentially important information on brain injury mechanisms, but estimations of concussion risk based on individual intracranial response measures evaluated in this study did not improve upon those derived from input kinematics alone.

Biomechanics of head impacts associated with diagnosed concussion in female collegiate ice hockey players.

Epidemiological evidence suggests that female athletes may be at a greater risk of concussion than their male counterparts. The purpose of this study was to examine the biomechanics of head impacts associated with diagnosed concussions in a cohort of female collegiate ice hockey players. Instrumented helmets were worn by 58 female ice hockey players from 2 NCAA programs over a three year period. Kinematic measures of single impacts associated with diagnosed concussion and head impact exposure on days with and without diagnosed concussion were evaluated. Nine concussions were diagnosed. Head impact exposure was greater in frequency and magnitude on days of diagnosed concussions than on days without diagnosed concussion for individual athletes. Peak linear accelerations of head impacts associated with diagnosed concussion in this study are substantially lower than those previously reported in male athletes, while peak rotational accelerations are comparable. Further research is warranted to determine the extent to which female athletes' biomechanical tolerance to concussion injuries differs from males.

Group-wise evaluation and comparison of white matter fiber strain and maximum principal strain in sports-related concussion.

Sports-related concussion is a major public health problem in the United States and yet its biomechanical mechanisms remain unclear. In vitro studies demonstrate axonal elongation as a potential injury mechanism; however, current response-based injury predictors (e.g., maximum principal strain, ε(ep)) typically do not incorporate axonal orientations. We investigated the significance of white matter (WM) fiber orientation in strain estimation and compared fiber strain (ε(n)) with ε(ep) for 11 athletes with a clinical diagnosis of concussion. Geometrically accurate subject-specific head models with high mesh quality were created based on the Dartmouth Head Injury Model (DHIM), which was successfully validated (performance categorized as "good" to "excellent"). For WM regions estimated to be exposed to high strains using a range of injury thresholds (0.09-0.28), substantial differences existed between ε(n) and ε(ep) in both distribution (Dice coefficient of 0.13-0.33) and extent (∼ 5-10-fold differences), especially at higher threshold levels and higher rotational acceleration magnitudes. For example, an average of 3.2% vs. 29.8% of WM was predicted above an optimal threshold of 0.18 established from an in vivo animal study using ε(n) and ε(ep), respectively, with an average Dice coefficient of 0.14. The distribution of WM regions with high ε(n) was consistent with typical heterogeneous patterns of WM disruptions in diffuse axonal injury, and the group-wise extent at the optimal threshold matched well with the percentage of WM voxels experiencing significant longitudinal changes of fractional anisotropy and mean diffusivity (3.2% and 3.44%, respectively) found from a separate independent study. These results suggest the significance of incorporating WM microstructural anisotropy in future brain injury studies.

Head-impact mechanisms in men's and women's collegiate ice hockey.

CONTEXT: Concussion injury rates in men's and women's ice hockey are reported to be among the highest of all collegiate sports. Quantification of the frequency of head impacts and the magnitude of head acceleration as a function of the different impact mechanisms (eg, head contact with the ice) that occur in ice hockey could provide a better understanding of this high injury rate. OBJECTIVE: To quantify and compare the per-game frequency and magnitude of head impacts associated with various impact mechanisms in men's and women's collegiate ice hockey players. DESIGN: Cohort study. SETTING: Collegiate ice hockey rink. PATIENTS OR OTHER PARTICIPANTS: Twenty-three men and 31 women from 2 National Collegiate Athletic Association Division I ice hockey teams. MAIN OUTCOME MEASURE(S): We analyzed magnitude and frequency (per game) of head impacts per player among impact mechanisms and between sexes using generalized mixed linear models and generalized estimating equations to account for repeated measures within players. INTERVENTION(S): Participants wore helmets instrumented with accelerometers to allow us to collect biomechanical measures of head impacts sustained during play. Video footage from 53 games was synchronized with the biomechanical data. Head impacts were classified into 8 categories: contact with another player; the ice, boards or glass, stick, puck, or goal; indirect contact; and contact from celebrating. RESULTS: For men and women, contact with another player was the most frequent impact mechanism, and contact with the ice generated the greatest-magnitude head accelerations. The men had higher per-game frequencies of head impacts from contact with another player and contact with the boards than did the women (P < .001), and these impacts were greater in peak rotational acceleration (P = .027). CONCLUSIONS: Identifying the impact mechanisms in collegiate ice hockey that result in frequent and high-magnitude head impacts will provide us with data that may improve our understanding of the high rate of concussion in the sport and inform injury-prevention strategies.

Can helmet design reduce the risk of concussion in football?

Of all sports, football accounts for the highest incidence of concussion in the US due to the large number of athletes participating and the nature of the sport. While there is general agreement that concussion incidence can be reduced through rule changes and teaching proper tackling technique, there remains debate as to whether helmet design may also reduce the incidence of concussion. A retrospective analysis was performed of head impact data collected from 1833 collegiate football players who were instrumented with helmet-mounted accelerometer arrays for games and practices. Data were collected between 2005 and 2010 from 8 collegiate football teams: Virginia Tech, University of North Carolina, University of Oklahoma, Dartmouth College, Brown University, University of Minnesota, Indiana University, and University of Illinois. Concussion rates were compared between players wearing Riddell VSR4 and Riddell Revolution helmets while controlling for the head impact exposure of each player. A total of 1,281,444 head impacts were recorded, from which 64 concussions were diagnosed. The relative risk of sustaining a concussion in a Revolution helmet compared with a VSR4 helmet was 46.1% (95% CI 28.1%-75.8%). When controlling for each player's exposure to head impact, a significant difference was found between concussion rates for players in VSR4 and Revolution helmets (χ(2) = 4.68, p = 0.0305). This study illustrates that differences in the ability to reduce concussion risk exist between helmet models in football. Although helmet design may never prevent all concussions from occurring in football, evidence illustrates that it can reduce the incidence of this injury.

Parametric comparisons of intracranial mechanical responses from three validated finite element models of the human head.

A number of human head finite element (FE) models have been developed from different research groups over the years to study the mechanisms of traumatic brain injury. These models can vary substantially in model features and parameters, making it important to evaluate whether simulation results from one model are readily comparable with another, and whether response-based injury thresholds established from a specific model can be generalized when a different model is employed. The purpose of this study is to parametrically compare regional brain mechanical responses from three validated head FE models to test the hypothesis that regional brain responses are dependent on the specific head model employed as well as the region of interest (ROI). The Dartmouth Scaled and Normalized Model (DSNM), the Simulated Injury Monitor (SIMon), and the Wayne State University Head Injury Model (WSUHIM) were selected for comparisons. For model input, 144 unique kinematic conditions were created to represent the range of head impacts sustained by male collegiate hockey players during play. These impacts encompass the 50th, 95th, and 99th percentile peak linear and rotational accelerations at 16 impact locations around the head. Five mechanical variables (strain, strain rate, strain × strain rate, stress, and pressure) in seven ROIs reported from the FE models were compared using Generalized Estimating Equation statistical models. Highly significant differences existed among FE models for nearly all output variables and ROIs. The WSUHIM produced substantially higher peak values for almost all output variables regardless of the ROI compared to the DSNM and SIMon models (p < 0.05). DSNM also produced significantly different stress and pressure compared with SIMon for all ROIs (p < 0.05), but such differences were not consistent across ROIs for other variables. Regardless of FE model, most output variables were highly correlated with linear and rotational peak accelerations. The significant disparities in regional brain responses across head models regardless of the output variables strongly suggest that model-predicted brain responses from one study should not be extended to other studies in which a different model is utilized. Consequently, response-based injury tolerance thresholds from a specific model should not be generalized to other studies either in which a different model is used. However, the similar relationships between regional responses and the linear/rotational peak accelerations suggest that each FE model can be used independently to assess regional brain responses to impact simulations in order to perform statistical correlations with medical images and/or well-selected experiments with documented injury findings.

Head impact exposure in male and female collegiate ice hockey players.

The purpose of this study was to quantify head impact exposure (frequency, location and magnitude of head impacts) for individual male and female collegiate ice hockey players and to investigate differences in exposure by sex, player position, session type, and team. Ninety-nine (41 male, 58 female) players were enrolled and 37,411 impacts were recorded over three seasons. Frequency of impacts varied significantly by sex (males: 287 per season, females: 170, p<0.001) and helmet impact location (p<0.001), but not by player position (p=0.088). Head impact frequency also varied by session type; both male and female players sustained more impacts in games than in practices (p<0.001), however the magnitude of impacts did not differ between session types. There was no difference in 95th percentile peak linear acceleration between sexes (males: 41.6 g, females: 40.8 g), but 95th percentile peak rotational acceleration and HITsp (a composite severity measure) were greater for males than females (4424, 3409 rad/s(2), and 25.6, 22.3, respectively). Impacts to the back of the helmet resulted in the greatest 95th percentile peak linear accelerations for males (45.2 g) and females (50.4 g), while impacts to the side and back of the head were associated with the greatest 95th percentile peak rotational accelerations (males: 4719, 4256 rad/sec(2), females: 3567, 3784 rad/sec(2) respectively). It has been proposed that reducing an individual's head impact exposure is a practical approach for reducing the risk of brain injuries. Strategies to decrease an individual athlete's exposure need to be sport and gender specific, with considerations for team and session type.

Effect of head impacts on diffusivity measures in a cohort of collegiate contact sport athletes.

OBJECTIVE: To determine whether exposure to repetitive head impacts over a single season affects white matter diffusion measures in collegiate contact sport athletes. METHODS: A prospective cohort study at a Division I NCAA athletic program of 80 nonconcussed varsity football and ice hockey players who wore instrumented helmets that recorded the acceleration-time history of the head following impact, and 79 non-contact sport athletes. Assessment occurred preseason and shortly after the season with diffusion tensor imaging and neurocognitive measures. RESULTS: There was a significant (p = 0.011) athlete-group difference for mean diffusivity (MD) in the corpus callosum. Postseason fractional anisotropy (FA) differed (p = 0.001) in the amygdala (0.238 vs 0.233). Measures of head impact exposure correlated with white matter diffusivity measures in several brain regions, including the corpus callosum, amygdala, cerebellar white matter, hippocampus, and thalamus. The magnitude of change in corpus callosum MD postseason was associated with poorer performance on a measure of verbal learning and memory. CONCLUSION: This study suggests a relationship between head impact exposure, white matter diffusion measures, and cognition over the course of a single season, even in the absence of diagnosed concussion, in a cohort of college athletes. Further work is needed to assess whether such effects are short term or persistent.

Head impact exposure sustained by football players on days of diagnosed concussion.

PURPOSE: This study compares the frequency and severity of head impacts sustained by football players on days with and without diagnosed concussion and to identify the sensitivity and specificity of single-impact severity measures to diagnosed injury. METHODS: One thousand two hundred eight players from eight collegiate football teams and six high school football teams wore instrumented helmets to measure head impacts during all team sessions, of which 95 players were diagnosed with concussion. Eight players sustained two injuries and one sustained three, providing 105 injury cases. Measures of head kinematics (peak linear and rotational acceleration, Gadd severity index, head injury criteria (HIC15), and change in head velocity (Δv)) and the number of head impacts sustained by individual players were compared between days with and without diagnosed concussion. Receiver operating characteristic curves were generated to evaluate the sensitivity and specificity of each kinematic measure to diagnosed concussion using only those impacts that directly preceded diagnosis. RESULTS: Players sustained a higher frequency of impacts and impacts with more severe kinematic properties on days of diagnosed concussion than on days without diagnosed concussion. Forty-five injury cases were immediately diagnosed after head impact. For these cases, peak linear acceleration and HIC15 were most sensitive to immediately diagnosed concussion (area under the curve = 0.983). Peak rotational acceleration was less sensitive to diagnosed injury than all other kinematic measures (P = 0.01), which are derived from linear acceleration (peak linear, HIC15, Gadd severity index, and Δv). CONCLUSIONS: Players sustained more impacts and impacts of higher severity on days of diagnosed concussion than on days without diagnosed concussion. In addition, of historical measures of impact severity, those associated with peak linear acceleration are the best predictors of immediately diagnosed concussion.

Timing of concussion diagnosis is related to head impact exposure prior to injury.

PURPOSE: Concussions are commonly undiagnosed in an athletic environment because the postinjury signs and symptoms may be mild, masked by the subject, or unrecognized. This study compares measures of head impact frequency, location, and kinematic response before cases of immediate and delayed concussion diagnosis. METHODS: Football players from eight collegiate and six high school teams wore instrumented helmets during play (n = 1208), of which 95 were diagnosed with concussion (105 total cases). Acceleration data recorded by the instrumented helmets were reduced to five kinematic metrics: peak linear and rotational acceleration, Gadd severity index, head injury criterion, and change in head velocity (Δv). In addition, each impact was assigned to one of four general location regions (front, back, side, and top), and the number of impacts sustained before injury was calculated over two periods (1 and 7 days). RESULTS: All head kinematic measures associated with injury, except peak rotational acceleration (P = 0.284), were significantly higher for cases of immediate diagnosis than delayed diagnosis (P < 0.05). Players with delayed diagnosis sustained a significantly higher number of head impacts on the day of injury (32.9 ± 24.9, P < 0.001) and within 7 d of injury (69.7 ± 43.3, P = 0.006) than players with immediate diagnosis (16.5 ± 15.1 and 50.2 ± 43.6). Impacts associated with concussion occurred most frequently to the front of the head (46%) followed by the top (25%), side (16%), and back (13%) with the number of impacts by location independent of temporal diagnosis (χ(3) = 4.72, P = 0.19). CONCLUSIONS: Concussions diagnosed immediately after an impact event are associated with the highest kinematic measures, whereas those characterized by delayed diagnosis are preceded by a higher number of impacts.

Spectrum of acute clinical characteristics of diagnosed concussions in college athletes wearing instrumented helmets: clinical article.

OBJECT: Concussive head injuries have received much attention in the medical and public arenas, as concerns have been raised about the potential short- and long-term consequences of injuries sustained in sports and other activities. While many student athletes have required evaluation after concussion, the exact definition of concussion has varied among disciplines and over time. The authors used data gathered as part of a multiinstitutional longitudinal study of the biomechanics of head impacts in helmeted collegiate athletes to characterize what signs, symptoms, and clinical histories were used to designate players as having sustained concussions. METHODS: Players on 3 college football teams and 4 ice hockey teams (male and female) wore helmets instrumented with Head Impact Telemetry (HIT) technology during practices and games over 2-4 seasons of play. Preseason clinical screening batteries assessed baseline cognition and reported symptoms. If a concussion was diagnosed by the team medical staff, basic descriptive information was collected at presentation, and concussed players were reevaluated serially. The specific symptoms or findings associated with the diagnosis of acute concussion, relation to specific impact events, timing of symptom onset and diagnosis, and recorded biomechanical parameters were analyzed. RESULTS: Data were collected from 450 athletes with 486,594 recorded head impacts. Forty-eight separate concussions were diagnosed in 44 individual players. Mental clouding, headache, and dizziness were the most common presenting symptoms. Thirty-one diagnosed cases were associated with an identified impact event; in 17 cases no specific impact event was identified. Onset of symptoms was immediate in 24 players, delayed in 11, and unspecified in 13. In 8 cases the diagnosis was made immediately after a head impact, but in most cases the diagnosis was delayed (median 17 hours). One diagnosed concussion involved a 30-second loss of consciousness; all other players retained alertness. Most diagnoses were based on self-reported symptoms. The mean peak angular and rotational acceleration values for those cases associated with a specific identified impact were 86.1 ± 42.6g (range 16.5-177.9 g) and 3620 ± 2166 rad/sec( 2 ) (range 183-7589 rad/sec( 2 )), respectively. CONCLUSIONS: Approximately two-thirds of diagnosed concussions were associated with a specific contact event. Half of all players diagnosed with concussions had delayed or unclear timing of onset of symptoms. Most had no externally observed findings. Diagnosis was usually based on a range of self-reported symptoms after a variable delay. Accelerations clustered in the higher percentiles for all impact events, but encompassed a wide range. These data highlight the heterogeneity of criteria for concussion diagnosis, and in this sports context, its heavy reliance on self-reported symptoms. More specific and standardized definitions of clinical and objective correlates of a "concussion spectrum" may be needed in future research efforts, as well as in the clinical diagnostic arena.

Magnitude of head impact exposures in individual collegiate football players.

The purpose of this study was to quantify the severity of head impacts sustained by individual collegiate football players and to investigate differences between impacts sustained during practice and game sessions, as well as by player position and impact location. Head impacts (N = 184,358) were analyzed for 254 collegiate players at three collegiate institutions. In practice, the 50th and 95th percentile values for individual players were 20.0 g and 49.5 g for peak linear acceleration, 1187 rad/s2 and 3147 rad/s2 for peak rotational acceleration, and 13.4 and 29.9 for HITsp, respectively. Only the 95th percentile HITsp increased significantly in games compared with practices (8.4%, p = .0002). Player position and impact location were the largest factors associated with differences in head impacts. Running backs consistently sustained the greatest impact magnitudes. Peak linear accelerations were greatest for impacts to the top of the helmet, whereas rotational accelerations were greatest for impacts to the front and back. The findings of this study provide essential data for future investigations that aim to establish the correlations between head impact exposure, acute brain injury, and long-term cognitive deficits.