Football head injuries involve significant forces and can result in mild to severe traumatic brain injuries. While this has received increasing attention at the professional and collegiate levels, there is less data available for the millions of participants in high school leagues (14-18 years old) during this time of rapid brain development. The purpose of this study is to relate information about cumulative head impact exposure over a season of high school football with neurocognitive and neuroimaging data to determine the effects of sub-concussive impacts on the brain. All elements of this study focus on the objective to increase understanding of pediatric mild Traumatic Brain Injury (mTBI) and prospectively collect biomechanical, imaging, functional, and computational modeling data on a scale never before attempted in adolescents involved in contact sports. This project integrates neuroinformatics work and the computational modeling techniques developed by Drs. Whitlow, Maldjian and Stitzel at Wake Forest University Health Sciences.
Evidence is growing that sub-concussive head impacts in high school football may result in brain MRI changes and functional outcomes that are similar to those seen with mild traumatic brain injury. Such changes are alarming given that adolescence is a period of extensive brain maturation, including continued development of white matter tracts that subserve a variety of higher order cognitive functions. This study will relate information about head motion during a hit in high school football to neurocognitive and neuroimaging data to determine the effects of subconcussive impacts on the brain.
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| Davenport, Elizabeth M; Urban, Jillian E; Mokhtari, Fatemeh et al. (2016) Subconcussive impacts and imaging findings over a season of contact sports. Concussion 1:CNC19 |
| Davenport, Elizabeth M; Apkarian, Kalyna; Whitlow, Christopher T et al. (2016) Abnormalities in Diffusional Kurtosis Metrics Related to Head Impact Exposure in a Season of High School Varsity Football. J Neurotrauma 33:2133-2146 |
| Maldjian, Joseph A; Daunais, James B; Friedman, David P et al. (2014) Vervet MRI atlas and label map for fully automated morphometric analyses. Neuroinformatics 12:543-50 |
