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Author: Susan S. Margulies
Biomechanics can provide insight into the mechanisms of concussion, including the interrelationships among the forces experienced during impact, head and neck movements, tissue stiffness of the materials that compose the head/neck complex, deformation of structures at the macroscopic and microscopic level, and biological responses to the various forces imposed on the head.
Biological responses in traumatic brain injuries (TBIs) may be immediate or delayed, be structural (torn vessels and axons) or functional (changes in blood flow or neurological status), and differ with maturation. Biomechanical investigations typically include a variety of approaches:
Sources of Concussion Data for Research
Biomechanics investigators can use human data obtained prospectively (via sensors; Camarillo et al. 2013; Crisco et al. 2010; Daniel et al. 2012; Rowson et al. 2009, 2012) or retrospectively (via crash reconstructions) to help understand what scenarios cause TBIs. Concussions are diagnosed based on symptoms, and most assessments are influenced by the patients’ awareness of or willingness to report their symptoms. But this less reliable form of data gathering skews the dataset and undermines the process of identifying objective biomechanical thresholds associated with concussion using instrumented volunteers. Biomechanical data are occasionally captured by sensors in helmets, patches, and mouthguards but they often report limited information about the rotational head movements associated with concussion.
To obtain kinematic information in more controlled settings, anthropomorphic surrogates (crash test dummies) and laboratory-based studies are used to reenact film and witness accounts of sports-related events in order to estimate the forces of impact and head movements (kinematics). But surrogates cannot be used to predict or measure brain injuries or tissue distortions. Instead, results obtained using surrogates must be correlated with animal studies, autopsy reports, and patient records to infer biological responses to kinematic loading conditions, or with computational models to infer tissue deformations resulting from a head rotation or impact.
Computational models are used to estimate the tissue distortions and stresses that may result from a rapid head motion or head impact, using lifelike tissue stiffness values for children and adults (Cheng et al. 2008). Like surrogates, computational models cannot predict concussion; predicted tissue distortions in response to lifelike loading conditions must be correlated with animal or human data.
Animal models can provide a controlled laboratory setting to investigate the relationships between the risk of concussion and rapid head rotation magnitude and direction, as well as the contributions of age, sex, and previous concussions to biomechanical thresholds for concussion. Animal model–derived biomechanical thresholds are typically for more severe brain injuries than concussion, but animal models do provide insight into how head impacts and sudden head movements produce brain deformations and how such deformations result in a spectrum of brain injuries, from mild to severe TBI.
Human Studies of Concussion Biomechanics
Quantifying the relationship between biomechanical input and clinical outcome is critical to the advancement of concussion prevention principles, including the assessment of injury risk, the design of protective equipment such as helmets, and the development of training and policies intended to limit exposure to head impacts and injury risk.
Measuring Injury Risk and Impact
The most common approach to quantifying the link between biomechanical input and concussion is through injury risk curves (figure 1), which describe injury probability given a specific mechanical input—for example, concussion risk given a particular head acceleration. Pellman, Rowson, Duma, and colleagues (Pellman et al. 2003; Rowson and Duma 2011) have used football head impact data to describe the relationship between linear acceleration and concussion risk (Rowson and Duma 2013) and between rotational acceleration and concussion risk (Rowson et al. 2012).
Head impact sensors have been widely used to understand the link between the biomechanics of head impact and clinical outcomes of concussion in humans (Brainard et al. 2012; Crisco et al. 2010; Mihalik et al. 2007; Rowson et al. 2009; Wilcox et al. 2015). These sensors—attached to a helmet, headband, skullcap, or mouthguard, or directly attached to the athlete’s head (Bartsch et al. 2014; Hernandez et al. 2015; King et al. 2015)—consist of accelerometers, and in some cases gyroscopes, to estimate the magnitude of linear and rotational acceleration experienced by the athlete during head impact.
Recent studies, however, have quantified errors in risk curves associated with significant sensor inaccuracy (Allison et al. 2014, 2015; Funk et al. 2012; Jadischke et al. 2013), underreporting of concussion (estimated at 53 percent; McCrea et al. 2004), and incorrect clinical diagnosis (Elliott et al. 2015). Decreasing sources of error will be important for improving the accuracy of injury risk estimates.
Challenges in Diagnosis and Assessment
Improvements in concussion reporting and diagnosis are essential to define injury risk curves for concussion. Concussion diagnosis remains largely an inexact clinical determination, using subjective assessments and symptom self-reports (IOM 2014; Master et al. 2014) of neurocognitive effects (van Kampen et al. 2006), vestibular balance (Corwin et al. 2015; Guskiewicz 2011), oculomotor/visual systems (Master et al. 2015), and sleep (Towns et al. 2015).
Current clinical assessments—the Sport Concussion Assessment Tool 3 (SCAT3) (Guskiewicz et al. 2013), Vestibulo-Oculomotor Screen (Mucha et al. 2014), King-Devick Test (Galetta et al. 2013), computerized neurocognitive testing such as the Immediate Post Concussion Assessment and Cognitive Testing (ImPACT) (van Kampen et al. 2006), and self-report of symptoms like the Post-Concussion Symptom Scale (Chen et al. 2007)—have components that are subjective and dependent on the effort of the injured individual or influenced by repeated testing effects (Resch et al. 2013). Moreover, because concussion may be diagnosed by a variety of individuals—parents, coaches, trainers, primary care, emergency medicine, or urgent care clinicians (Leong et al. 2014; Taylor et al. 2015)—it is important to develop robust, accessible, and validated metrics for use.
Future research should target the validation of objective, graded, effort-independent neurologic system assessments (such as vestibular balance, eye tracking, visual function, and sleep) for concussion to enable timely and accurate diagnosis across a wide age spectrum. These quantitative involuntary metrics can also be used to guide clinical diagnosis and management of concussion and inform evidence-based decisions about athletes’ return to sport.
Animal Studies of Concussion Biomechanics
Because human data and computational models have limitations, researchers use experimental substitutes such as animals, tissues, and isolated cells to create controllable settings with similar predisposing conditions and reproducible mechanical loads.
Extensive Utility of Animal Studies
Animal models are useful for measuring physiological responses, neuropathology, and neurofunctional changes at prescribed time-points after injury. As a surrogate for humans, the animal models most commonly used to study brain injury are mice and rats, but ovine, porcine, and nonhuman primate models have also been used (Browne et al. 2011; Durham et al. 2000; Finnie et al. 2012; Gennarelli et al. 1981, 1982; Viano et al. 2012). Because reports indicate that rodents have limited similarity to human genomic and proteomic responses, injury timecourses, and grey and white brain matter distribution (Duhaime 2006; Seok et al. 2013), there may be challenges in applying what is learned about injury in the rodent brain to humans (Wall and Shani 2008). Animal models are nonetheless a valuable tool for understanding how head impacts and sudden head movements translate to short- and long-term biological responses, and how environment and agents can exacerbate or mitigate these responses.
Pigs are a popular large animal model used for assessing motor, cognitive, and behavioral responses after traumatic brain injury, stroke, and cardiac arrest (Gieling et al. 2011; Jiwa et al. 2010; Lind et al. 2007; Sullivan et al. 2013a,b; Wang et al. 2012). A sensitive and specific battery of behavioral, motor, memory, learning, and cognitive assessments developed for piglets have revealed the timecourse after traumatic brain injury and the importance of the direction of head rotation for head injury responses (Friess et al. 2007, 2009; Naim et al. 2010; Sullivan et al. 2013a,b). And recently developed objective assessments in the piglet show the feasibility of translating nonverbal assessments used in human studies, including balance, activity/rest, and serum biomarkers, to piglets (Costine et al. 2012; Diaz-Arrastia et al. 2013; Egea-Guerrero et al. 2012; Kilbaugh et al. 2015; Kochanek et al. 2013; Okonkwo et al. 2013).
Effects of Velocity Change and Rotation
Researchers have determined that, with or without a helmet, when the head contacts a stationary or moving object there is a rapid change in velocity and a possible deformation of the skull. Skull deformation may produce a local contusion or hemorrhage if the deformations of the tissues exceed their injury thresholds. When the properties of the contact surfaces are softer or allow sliding or deformation, the rate of velocity change is lower. Similarly, if there is no head contact but only body contact, the deceleration of the moving head is usually lower than when the head is contacted directly.
After the initial rapid change in velocity caused by impact to the head or body, the motion of the head is influenced by the location of the initial point of contact and the interaction between the head, neck, and body. There are three possible types of responses to head contact. First, if the contact is directed through the center of mass of the brain (centroid), there may be linear motion and no rotation of the head. Animal studies have shown that these purely linear motions produce little brain motion or distortion and no concussion (Hardy et al. 2001; Ommaya and Gennarelli 1974; Ommaya and Hirsch 1971; Ommaya et al. 1966).
However, most often the contact force is not directed through the centroid of the brain, and in the second type of response to contact the head may rotate without a linear motion (e.g., shaking the head “no”). The rotational motion produces a distortion of the brain’s neural and vascular structures in the skull because the brain is softer than and loosely coupled to the skull.
Third, and more commonly, a head impact produces both linear acceleration and rotation of the head. Internal structures of the head, such as the falx cerebri and tentorium, influence how the brain moves in the skull and may cause local brain regions to have very high deformations only in certain directions of head rotation. For example, sagittal and coronal rotations may produce more severe injuries in primates at lower accelerations and velocities (Gennarelli et al. 1982).
Moreover, animal and human studies have shown a general trend that higher rotational velocities and accelerations—rather than linear accelerations—can cause larger diffuse brain deformations and worse diffuse brain injuries (Gennarelli et al. 2003; Kimpara and Iwamoto 2012; Ommaya and Hirsch 1971), and that head injuries depend on the direction of head motion as well as on the magnitude of rotational kinematics (Eucker et al. 2011; Gennarelli et al. 1981; Ommaya and Gennarelli 1974; Sullivan et al. 2013a, 2015). Animal studies have indicated that it is important to limit the duration of exposure to acceleration, as concussions occur when that duration is increased (Ommaya 1966; Ommaya et al. 1966).
Research in New Tools and Technologies to Increase Understanding
Ongoing studies are identifying the causal relationship between head rotational acceleration magnitude and direction and head injury outcomes, and the influence of age, sex, and previous exposures to head injury. But further research is needed to understand the biomechanics of concussion and define thresholds for rotational accelerations associated with concussion across the age spectrum.
Emerging research in objective, involuntary neurofunctional metrics and biomarkers can bridge the gap between human and animal research, and provide important insight into the biomechanics of concussion, to provide a rational foundation for injury prevention, safety equipment design, rules of play, treatments and interventions.
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