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Abstract In the last decade, computational models of the brain have become the gold standard tool for investigating traumatic brain injury (TBI) mechanisms and developing novel protective equipment and other safety countermeasures. However, most studies utilizing finite element (FE) models of the brain have been conducted using models developed to represent the average neuroanatomy of a target demographic, such as the 50th percentile male. Although this is an efficient strategy, it neglects normal anatomical variations present within the population and their contributions on the brain's deformation response. As a result, the contributions of structural characteristics of the brain, such as brain volume, on brain deformation are not well understood. The objective of this study was to develop a set of statistical regression models relating measures of the size and shape of the brain to the resulting brain deformation. This was performed using a database of 125 subject-specific models, simulated under six independent head kinematic boundary conditions, spanning a range of impact modes (frontal, oblique, side), severity (non-injurious and injurious), and environments (volunteer, automotive, and American football). Two statistical regression techniques were utilized. First, simple linear regression (SLR) models were trained to relate intracranial volume (ICV) and the 95th percentile of maximum principal strain (MPS-95) for each of the impact cases. Second, a partial least squares regression model was constructed to predict MPS-95 based on the affine transformation parameters from each subject, representing the size and shape of their brain, considering the six impact conditions collectively. Both techniques indicated a strong linear relationship between ICV and MPS-95, with MPS-95 varying by approximately 5% between the smallest and largest brains. This difference represented up to 40% of the mean strain across all subjects. This study represents a comprehensive assessment of the relationships between brain anatomy and deformation, which is crucial for the development of personalized protective equipment, identifying individuals at higher risk of injury, and using computational models to aid clinical diagnostics of TBI.

As concerns about head impact in American football have grown, similar concerns have started to extend to other sports thought to experience less head impact, such as soccer and lacrosse. However, the amount of head impact experienced in soccer and lacrosse is relatively unknown, particularly compared with the substantial amount of data from football. This pilot study quantifies and compares head impact from four different types of sports teams: college football, high school football, college soccer, and college lacrosse. During the 2013 and 2014 seasons, 61 players wore mastoid patch accelerometers to quantify head impact during official athletic events (i.e., practices and games). In both practices and games, college football players experienced the most or second-most impacts per athletic event, highest average peak resultant linear and rotational acceleration per impact, and highest cumulative linear and rotational acceleration per athletic event. For average peak resultant linear and rotational acceleration per individual impact, college football was followed by high school football, then college lacrosse, and then college soccer, with similar trends in both practices and games. In the four teams under study, college football players experienced a categorically higher burden of head impact. However, for cumulative impact burden, the high school football cohort was not significantly different from the college soccer cohort. The results suggest that head impact in sport substantially varies by both the type of sport (football vs. soccer vs. lacrosse) and level of play (college vs. high school)., Competing Interests: Author Disclosure Statement Max Wintermark is a member of the advisory board of the GE NFL project. All other authors have no conflicts of interest to report.