X-Ray Reconstruction of Moving Morphology (XROMM) comprises a set of 3D X-ray motion analysis techniques that merge motion data from in vivo X-ray videos with skeletal morphology data from bone scans into precise and accurate animations of 3D bones moving in 3D space. XROMM methods include: (1) manual alignment (registration) of bone models to video sequences, i.e., Scientific Rotoscoping; (2) computer vision-based autoregistration of bone models to biplanar X-ray videos; and (3) marker-based registration of bone models to biplanar X-ray videos. Here, we describe a novel set of X-ray hardware, software, and workflows for marker-based XROMM. Refurbished C-arm fluoroscopes retrofitted with high-speed video cameras offer a relatively inexpensive X-ray hardware solution for comparative biomechanics research. Precision for our biplanar C-arm hardware and analysis software, measured as the standard deviation of pairwise distances between 1 mm tantalum markers embedded in rigid objects, was found to be +/-0.046 mm under optimal conditions and +/-0.084 mm under actual in vivo recording conditions. Mean error in measurement of a known distance between two beads was within the 0.01 mm fabrication tolerance of the test object, and mean absolute error was 0.037 mm. Animating 3D bone models from sets of marker positions (XROMM animation) makes it possible to study skeletal kinematics in the context of detailed bone morphology. The biplanar fluoroscopy hardware and computational methods described here should make XROMM an accessible and useful addition to the available technologies for studying the form, function, and evolution of vertebrate animals.

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The findings of the present study are relevant to the clinical practice of examining motions of the cervical spine in three dimensions and to the understanding of spinal trauma and degenerative diseases.

Context: Measuring head impact exposure is a critical step toward understanding the mechanism and prevention of sportrelated mild traumatic brain (concussion) injury, as well as the possible effects of repeated subconcussive impacts.Objective: To quantify the frequency and location of head impacts that individual players received in 1 season among 3 collegiate teams, between practice and game sessions, and among player positions.Design: Cohort study. Setting: Collegiate football field. Patients or Other Participants: One hundred eighty-eight players from 3 National Collegiate Athletic Association football teams.Intervention(s): Participants wore football helmets instrumented with an accelerometer-based system during the 2007 fall season.Main Outcome Measure(s): The number of head impacts greater than 10g and location of the impacts on the player's helmet were recorded and analyzed for trends and interactions among teams (A, B, or C), session types, and player positions using Kaplan-Meier survival curves.Results: The total number of impacts players received was nonnormally distributed and varied by team, session type, and player position. The maximum number of head impacts for a single player on each team was 1022 (team A), 1412 (team B), and 1444 (team C). The median number of head impacts on each team was 4.8 (team A), 7.5 (team B), and 6.6 (team C) impacts per practice and 12.1 (team A), 14.6 (team B), and 16.3 (team C) impacts per game. Linemen and linebackers had the largest number of impacts per practice and per game. Offensive linemen had a higher percentage of impacts to the front than to the back of the helmet, whereas quarterbacks had a higher percentage to the back than to the front of the helmet.Conclusions: The frequency of head impacts and the location on the helmet where the impacts occur are functions of player position and session type. These data provide a basis for quantifying specific head impact exposure for studies related to understanding the biomechanics and clinical aspects of concussion injury, as well as the possible effects of repeated subconcussive impacts in football.