Shultz et al. investigated the effects of a mild lateral fluid-percussion injury (0.50–0.99 atm) on rat behavior and neuropathological changes in an attempt to better understand subconcussive brain injury. 75 In their study, male Long-Evans rats received either a single mild lateral fluidpercussion injury or a sham injury, followed by either a short (24 hours) or a long (4 weeks) recovery period. No significant group differences were found in behavioral and axonal injury measures; however, the rats given one subconcussive mild fluid-percussion injury displayed a significant increase in microglial activation and reactive astrogliosis at 4 days postinjury. 75 The authors inferred that this result was consistent with an acute neuroinflammatory response. Chronic neuroinflammation is a mechanism with the potential to contribute to the cumulative and neurodegenerative effects of repeated subconcussive injuries, and these findings are consistent with those in humans experiencing a subconcussive impact. 9 , 75

In a fluid-percussion brain injury model in rats, Lifshitz and Lisembee found at 28 days that thalamic ventral basal neurons exhibit atrophic changes without neuronal death. 41 Persistence in a chronic atrophic state after ipsilateral hippocampal injury was noted to deprive the deafferentated basal cholinergic neurons of trophic support, a finding consistent with detailed autopsy studies on athletes with CTE. 59–63 In one vertical-impact model of mTBI in rodents, the authors found that there was minimal change in the animals' behavioral response following injury; however, at euthanization, the animals showed dark, swollen neuronal soma. 39 Creed et al. showed that compared with sham-injured mice, the mice with concussive brain injuries had abnormal spatial acquisition and working memory as measured by the Morris water maze over the first 3 days (p < 0.001) but not later than the 4th day postinjury. 16 At 1 and 3 days postinjury, intraaxonal accumulation of amyloid precursor protein in the corpus callosum and cingulum was associated with neurofilament dephosphorylation, abnormal transport of FluoroGold and synaptophysin, and deficits in axonal conductance, which continued until 14 days postinjury when axonal degeneration was apparent. Although there may be recovery from acute cognitive deficits, this model showed that even subconcussive brain trauma leads to axonal degeneration and abnormal axonal function. 16

Some researchers have demonstrated evidence of deleterious effects following a single subconcussive experimental head injury. By modifying the Marmarou weight-drop model of concussion, we have been able to diminish impact forces to effect no obvious reaction or behavior change, and thus simulating less than a concussive injury. 2 , 51–53 Using staining for amyloid precursor protein, we have shown that these subconcussive impacts reliably produce tearing of axons and the formation of axonal retraction bulbs in the brainstem-level descending motor pathways. In reducing the fall height of a 450-g mass from 2 to 1 m, we found no alteration of consciousness or responsiveness but significant numbers of amyloid precursor protein–positive axons compared with the number in controls (JD Mills, JE Bailes, unpublished data, 2010).

Kanayama et al. demonstrated that repetitive mTBI causes changes in cortical and hippocampal cytoskeletal proteins, whereas a single injury does not. 36 Laurer et al. showed that a second injury induces both local and regional changes in the cerebral cortex. 40 Given their results, these authors suggested that the brain has an increased vulnerability to a second traumatic insult for at least 24 hours following an initial episode of mild brain trauma. Another study used microtubule-associated protein–2 staining techniques to demonstrate that local and remote injuries are significantly greater if they occur in a shorter time window following an initial injury in mice, which exhibited minimal behavioral response following head impact. 42 Some of these studies also documented evidence of CNS injury despite no overt behavioral deficits, which is consistent with subconcussive injury.

Little attention was paid to repetitive mild head injury before the year 2000, with just a few repetitive injury studies being published. 36 , 56 , 87 Since then, there has been increased interest in laboratory research focused on repetitive mTBI. 1 , 8 , 14 , 17 , 23 , 25 , 37 , 40 , 42 , 69 , 74 , 82 , 88 Most of these studies were performed in rodents, with a few performed in pig models of TBI. In one study, DeFord et al. showed that as compared with a single episode of mTBI, repeat injury was associated with impairments in complex spatial learning and cognitive impairment 23 —this despite no overt cell death in the cortex or hippocampus or blood-brain barrier compromise.

In essence, axonal membranes are injured and axonal transport is interrupted in a progressive process. This concept is supported by recent autopsy findings in professional contact-sport athletes who demonstrate multifocal areas of damaged neurons and their processes, remarkable for tau protein antibody staining, representing a temporal and spatial pattern of repetitive injury. 6 , 27 , 49 , 57 , 59–63 In addition, a recently proposed theory suggests that chronic inflammation may occur, based in large part upon the activation of microglia, leading to a cascade of deleterious effects. 9

There may be immediate and delayed cellular events, which can include ionic shifts, disturbances in calcium channels, ATP pump failure, and mitochondrial perturbations resulting in neurological dysfunction and the potential for cell death through apoptotic pathways. 54 In mTBI, cellular metabolism is disturbed, ultrastructural damage can occur, and both biochemical and vascular autoregulation abnormalities may be involved.

Traumatic brain injury is traditionally thought to involve both primary and secondary injury phases. The primary injury is represented by the moment of impact, resulting from the translation of kinetic energy and force vectors in a linear acceleration-deceleration mechanism, through a rotational mechanism, or a combination of both. 22 Secondary injury is the indirect result of the trauma and its subsequent pathophysiological processes and includes both immediate and delayed cellular events. 22 In addition to primary and secondary injury, the concept of a tertiary phase of TBI may now be thought of as ongoing abnormalities in glucose utilization and cellular metabolism as well as membrane fluidity, synaptic function, and structural integrity. 3 , 35 , 43–45 , 66 , 67 , 71 , 78 This phase of TBI may become chronic and compounded if the individual is subjected to repetitive minor head impacts.

Clinical Evidence of Subconcussion

Biophysics Data In most cases of head injury there are components of both linear and angular forces at work. It is important to remember the variables in play that determine the kinetic energy imparted by these forces (kinetic energy = ½mv2). Modern-day athletes are bigger, stronger, and faster. Interestingly, neck-strengthening exercises and increasing the mass of the head-neck segment have been suggested as means of possibly reducing the incidence of concussion or subconcussion; however, no definitive evidence has proven that neck strengthening plays a role in concussion prevention. Increased neck strength (not just mass) may diffuse the forces imparted in a head impact or may limit the cranial excursion and brain movement inside the skull (slosh).77 Neck strength may be particularly important at the junior and youth athletic levels and in female athletes.4,5,15,81 In general, modern players have amassed a greater total size (mass), thus increasing the kinetic energy imparted in blows to the head. Moreover, during the past several decades, the velocities of impacts have increased and are probably the single greatest factor in the apparent rise in concussion incidence. In actuality, it is the change in velocity, through acceleration and deceleration, that relates to the energy transmitted to the player's body and brain.22 Concussion and subconcussion can occur in any sport; however, American football has a high incidence of concussion, largely because of the style of play, high rate of impacts, and extent of participation.34 The mandatory use of helmets in American football has allowed for the systematic analysis of injury biomechanics and real-time measurements of forces, velocities, accelerations, and frequencies of head impacts by using implanted telemetry devices. In addition, studies organized by the NFL have included detailed computerized video analysis of actual game film in 182 concussive and subconcussive hits that occurred between 1996 and 2001.64 These impacts were then modeled or reenacted in a laboratory setting using crash test dummies. These studies showed that the highest strain forces were imparted to the deep midbrain level near the head's center of gravity, occurring 10 msec following impact. The researchers postulated that the forces imparted to the mesencephalon, corpus callosum, and fornix may be responsible for concussion symptoms, such as LOC, amnesia, and cognitive dysfunction.64 However, in those instances without LOC, which are the majority, there appeared to be significant forces transmitted to deep midbrain and brainstem structures, which implies a mechanism in which subconcussive injury may also occur. Broglio et al. examined 95 high school football players across four seasons by using a helmet telemetry system to record the total number of head impacts and the associated acceleration forces.11 Results showed that the number of impacts during a 14-week season varied with an athlete's playing position and starting status. The average player sustained 652 impacts (range 5–2235 impacts) during a season. Linemen had the greatest number of impacts per season (868); followed by tight ends, running backs, and linebackers (619); quarterbacks (467); and receivers, cornerbacks, and safeties (372). The seasonal linear acceleration burden averaged 16,746.1g, whereas the rotational acceleration burden was 1,090,697.7 rad/sec.2 These findings indicate that high school football players sustain a high number of head impacts each season, with associated cumulative impact burdens that are equally impressive.11 Talavage et al., who used similar technology, found comparable numbers and rates of hit accumulations.79 Studies have varied in their estimation of the threshold for diagnosed or recognized concussion, both between individual athletes and within the same athlete. One investigation monitored all football-related head impacts in 78 high school athletes (mean age 16.7 years) in the period from 2005 to 2008 to better understand the biomechanical characteristics of concussive impacts.12 Fifty-four thousand two hundred forty-seven impacts were recorded, and 13 concussive episodes were captured for analysis. Classification and regression tree analysis of impacts indicated that rotational acceleration (5582.3 rad/sec2), linear acceleration (96.1g), and impact location (front, top, and back) yielded the highest predictive value of concussion.12 In general, it is believed that the greatest risk is with a linear acceleration greater than 95g, rotational acceleration greater than 5500 rad/sec,2 and impacts occurring on the top, front, or back of the helmet.11,28 The NFL studies showed that while many impacts may exceed 98g, this is the threshold for 75% human tolerance for symptomatic concussion.64 Eckner et al. explored the characteristics of 20 concussion-invoking impacts in 19 high school football players, analyzing the total number of head impacts, severity profile values, cumulative linear and rotational acceleration values during the same game or practice session, and 30-minute and 1-week periods preceding these impacts.24 They found that concussions occurred over a wide range of impact magnitudes and that the cumulative impact burden prior to a concussion was not different from that before nonconcussive impacts of greater magnitudes in the same athletes. Therefore, they concluded that an athlete's concussion threshold may be a dynamic feature over time and that there is a lack of cumulative effects of nonconcussive impacts on the concussion threshold. Alternatively, another interpretation of such a study is that the type of impacts occurring in players who sustain a concussion can be no different from those occurring in asymptomatic players, further pointing to the role and potential importance of subconcussive impacts. Crisco et al. have investigated impact characteristics in collegiate football players.18–20 They found that player position and impact location were the most significant factors accounting for differences in head impacts. Running backs and quarterbacks sustained the greatest-magnitude head impacts, whereas linemen and linebackers received the greatest overall number of head impacts. The total number of head impacts was a median of 420 and a maximum of 2492. Prior studies have shown variance in the total number of head impacts in collegiate players from 950 head impacts per season31,32 to 1353 per season.72 Schnebel et al. used accelerometers embedded in the crown of helmets in both high school and collegiate football players.72 The authors found the expected number of high-speed, open-field collisions in skill position athletes, with forces in the range of 90–120g and a duration of about 15 msec. They, like other researchers, documented a threshold in the range of 60–90g (mean 75g) for concussion and asserted that collegiate players tend to have higher-impact accelerations than high school players in similar playing positions. Moreover, the highest-intensity impacts in high school players occurred frequently and at levels greater than 100g. However, the most intriguing and unexpected finding in this study was that linemen incur impacts of 20–30g on nearly every play. Given the football tradition of linemen starting every play in the 3-point stance and lunging forward to immediately encounter their opposing player, head contact occurs on a constant and ubiquitous basis. Schnebel and colleagues also noted that linemen experienced high impacts of up to 120g forces in 1 out of every 120 plays.72 If one were to extrapolate these data to the average number of plays per game, linemen sustain direct head impacts of an average force of 25g 45–55 times per game. Further, depending on the style of practice sessions, similar head impact exposure may be seen on a daily basis during both seasonal and spring training periods. However, as Guskiewicz and Mihalik31 and others64,72 have found, the magnitude of impacts to an opponent's football helmet does not necessarily correlate with the probability of sustaining a concussion or its severity. Youth football players, generally 7–14 years of age, constitute approximately 70% of all football players and of 3.5 million participants. Authors of a recent study monitored 7 youth football participants, ages 7 and 8 years, during a football season and noted an average of 107 impacts per player for the season.21 Linear accelerations ranged from 10 to 100g, and rotational accelerations ranged from 52 to 7694 rad/sec.2 The majority of the impacts were to the sides (36%) and front (31%) of the helmets, and 61% occurred during practices. Of these hits, 38 were greater than 40g and 6 were greater than 80g, all occurring at practice sessions. This study was the first to document that very-high-velocity impacts are possible at the youth level of football play. Thus, while youth football players may have fewer helmet impacts and lower-force hits than their older counterparts, high-magnitude impacts may occur nonetheless, and their long-term implications in an exposure paradigm are uncertain.

Neuropsychological Evaluation In a recent study, Gysland et al. sought to investigate the relationship between subconcussive impacts and concussion history on clinical measures of neurological function.33 Before and after a single season 46 collegiate football players completed 5 clinical measures of neurological function commonly used in the evaluation of concussion. These tests included the Automated Neuropsychological Assessment Metrics, Sensory Organization Test, Standardized Assessment of Concussion, Balance Error Scoring System, and Graded Symptom Checklist, and impact data were recorded using the Head Impact Telemetry system. Although each player averaged 1177.3 ± 772.9 head impacts over the course of a season, Gysland and colleagues found that they did not demonstrate any clinically meaningful changes from preseason to postseason on the measures of neurological function utilized.33 Similar findings were reported in another study of college football players, according to both Sideline Assessment of Concussion and Immediate Post-Concussion Assessment and Cognitive Testing scores.50 Although there may be a dose response with regard to impacts that must be considered over the course of a player's career, the measures of neurological function used may not have been sensitive enough to detect subclinical neurological dysfunction in athletes sustaining many repetitive subconcussive impacts. However, additional research now suggests that these nonconcussive impacts may not be benign. Killam et al. found that nonconcussed collegiate athletes in contact sports actually scored lower than controls in two memory domains and had lower total scores on the Repeatable Battery for the Assessment of Neuropsychological Status.38 Their study was limited by its small sample size as well as its design. The independent groups were established on the basis of self-reported data, which may yield less validity than a more rigorous prospective study design. The retrospective survey design also did not allow for pretesting of cognitive performance, and thus there was no individualized internal standardization. This finding might suggest that the findings could be attributed to selection bias; however, the controls (with which the nonconcussed collegiate athletes were compared) also did not undergo prestudy testing, and there did not appear to be any differences in demographic characteristics including mean grade point average. The authors' data suggest that participation in contact sports may produce subclinical cognitive impairments in the absence of a diagnosable concussion, presumably resulting from the cumulative effects produced by multiple mild head injuries. This and other studies12,72 demonstrate that peak acceleration may not be a sufficient measure to predict cognitive deficit and that greater impact forces do not necessarily correlate with a greater likelihood of neurological impairment. Instead, the cumulative number of helmet impacts may become the major criterion of subconcussive burden. The observable neurological signs and symptoms are probably the result of interrupting the communication between complex neural networks, and thus representing a diffuse rather than a focal brain injury. McAllister et al. studied 214 collegiate Division I football and ice hockey players, analyzing their accelerometer data and neuropsychological outcomes, as compared with those in a control group of athletes in noncontact sports. The authors found that the athletes in contact sports had a worse performance on tests for new learning and that poorer scores on postseason cognitive testing correlated with greater head impact exposure. This worse performance was evident despite the fact that none of the contact-sport athletes had a documented sports concussion during the period of study.46 In contrast, Miller et al., who used Standardized Assessment of Concussion and computerized neuropsychological testing in Division III football players, found no difference among preseason baseline, midseason, and postseason assessments in the players who did not sustain a concussion.50 Thus, there may be specific neuropsychological metrics that are better suited or more sensitive in detecting the effects of repetitive subconcussion forces. Perhaps the symptoms or sequelae of repetitive subconcussion require a greater amount of time to develop than a single season.

Neuroradiological Findings The role of neuroimaging in concussion had been a progressive one. While most standard MRI sequences have been designed to evaluate for structural damage at the macroscopic level, recently developed advanced sequences have the potential to increase the sensitivity of MRI to detect both structural and functional abnormalities associated with concussion. This potential exists in the acute setting and, subsequently, in the subacute and chronic phases of recovery. The use of these new techniques is especially relevant in cases in which conventional CT and MRI sequences cannot detect macroscopic structural abnormalities.68 To test the hypothesis that subconcussive blows cause an accumulation of neurophysiological changes, it is necessary to measure changes in neurological function over time. Talavage and colleagues performed MRI, fMRI, and neurocognitive assessments in a group of high school football players at 3 distinct times: 1) prior to the start of contact practices, 2) during the season, and 3) 2–5 months after the season concluded.79 In addition to these assessments, the Head Impact Telemetry system was used to record head collisions during all contact practices and games. In the absence of outwardly observable symptoms of concussion, the athletes demonstrated quantifiable neurophysiological changes on both fMRI studies and Immediate Post-Concussion Assessment and Cognitive Testing. Those players with functionally observed impairment (FOI+) exhibited changes in fMRI activation while performing a working memory task, and these changes were at least as great as those in players in whom a diagnosis of concussion (that is, a clinically observed impairment [COI+]) had been made by the team physician (Fig. 110,79). Of particular interest, the FOI+ group of players was primarily composed of linemen, individuals who experience obligatory helmet-to-helmet contact on nearly every play from the line of scrimmage; the number of blows to the head was the only measure by which this groups' telemetry values differed from those in players with diagnosed concussion or who exhibited no neurophysiological alteration (Table 110). This finding of neuropsychological disturbance in the absence of classic symptoms of concussion is consistent with prior observations in 7 former NFL offensive linemen and a wide receiver, as reported by Omalu and colleagues and described below.60,61,63 F ig . 1. Magnetic resonance and fMR images obtained in high school football players for baseline purposes prior to the season (preseason), with repeated assessments made during (in-season) and after (postseason) the season. For each group, activation is shown in axial (upper rows), sagittal (center rows), and coronal (lower rows) images intersecting near the left inferior parietal lobule. A: Group COI−/FOI−. Approximately half of the asymptomatic athletes exhibited minimal changes on their in-season fMRI results. B: Group COI−/FOI+. The other half of the asymptomatic athletes exhibited substantial changes on their fMR images. C: Group COI+/FOI+. This finding was on par with changes observed in concussed athletes, although the affected regions differ considerably. Depicted fMRI maps illustrate preferential activation observed in a contrast of a 2-back single letter task (orange-yellow activation) against a 1-back single letter task (blue-cyan activation), both of which were conducted in a single fMRI run. Changes in direction (or presence/absence) of the contrast are considered meaningful. In-Season #1 = first assessment during the competition season; In-Season #2 = second assessment during the competition season. TABLE 1: Summary statistics for peak translational acceleration and number of helmet impacts over the course of the season in a population of high school football players* Parameter Group (mean ± SD; range) COI−/FOI− COI−/FOI+ COI+/FOI+ peak translational acceleration (g) 27.5 ± 16.6; 10.0–194.1 27.7 ± 17.5; 10.0–255.6 28.5 ± 20.1; 10.0–279.0 no. of helmet impacts over the season 656 ± 378; 226–1463 1090 ± 570; 396–1855 546 ± 464; 218–1551 A follow-up study by Breedlove et al. demonstrated that the fMRI changes in many regions of the brain statistically correlated with the number and (spatial) distribution of hits received after beginning contact practices.10 Critically, regression models constructed to relate the hits experienced to the observed fMRI changes were found to explain an even greater proportion of the variance for the concussed group (COI+) than the asymptomatic group (COI−). The COI− group exhibited substantial hit-correlated involvement of the visual processing systems in the upper parietal and occipital lobes. In contrast, the COI+ group demonstrated significant relationships between the number and locations of hits and the regions involved in verbal working memory. This last observation strongly suggests that the clinical diagnosis of neurological system deficits may depend on which systems have been compromised and that the entire (recent) history of blows to the head plays a causal role in overall neurological changes. A new study utilizing diffusion tensor imaging highlights the emerging clinical evidence for subconcussive brain injury.7 Bazarian et al. investigated the ability to detect subject-specific changes in brain white matter before and after sports-related concussion. Their prospective cohort study was performed in 9 high school athletes engaged in hockey or football and 6 controls. All 15 subjects underwent diffusion tensor imaging both pre- and postseason within a 3-month interval. Concussion was diagnosed in only 1 athlete (scanned within 72 hours of injury), and 8 suffered between 26 and 399 subconcussive head blows.7 Fractional anisotropy and mean diffusivity were measured, and the percentage of white matter voxels with significant (p < 0.05) preseason to postseason changes in these values was highest for the concussed athlete, intermediate for those with subconcussive head blows, and lowest for controls.7 While analysis detected significantly changed white matter in a single concussed athlete as expected, the most striking findings were in the athletes who did not sustain a concussion. Asymptomatic athletes with multiple subconcussive head blows had abnormalities in a percentage of their white matter that was more than 3 times higher than that in controls. The significance of these white matter changes and their relationship to head impact forces are unknown and will require further studies.