Abstract #1784

Development of an unbiased population-specific brain atlas for adolescent collision-sport athletes

Yukai Zou^1,2, Wenbin Zhu³, Ho-Ching (Shawn) Yang¹, Nicole L Vike⁴, Diana O Svaldi¹, Trey E Shenk⁵, Victoria N Poole^1,4, Gregory G Tamer, Jr.¹, Larry J Leverenz⁶, Ulrike Dydak⁷, Eric A Nauman^1,4,8, Thomas M Talavage^1,5, and Joseph V Rispoli^1,5

¹Weldon School of Biomedical Engineering, Purdue University, West Lafayette, IN, United States, ²College of Veterinary Medicine, Purdue University, West Lafayette, IN, United States, ³Department of Statistics, Purdue University, West Lafayette, IN, United States, ⁴Department of Basic Medical Sciences, Purdue University, West Lafayette, IN, United States, ⁵School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, United States, ⁶Department of Health and Kinesiology, Purdue University, West Lafayette, IN, United States, ⁷School of Health Sciences, Purdue University, West Lafayette, IN, United States, ⁸School of Mechanical Engineering, Purdue University, West Lafayette, IN, United States

Over years of practices and competitions, adolescent collision-sport (American football, soccer) athletes undergo repetitive subconcussive head impacts, and therefore may exhibit a neuroanatomical trajectory different from healthy adolescents in general. Targeting this vulnerable population, we constructed a specific brain atlas that includes templates (T1 and DTI) and semantic labels (cortical and white matter parcellations), and we demonstrated that the unbiased population-specific brain atlas can minimize bias introduced in spatial normalization, improve sensitivity of voxel-wise statistical analysis, and therefore better clarify the mechanisms that lead to traumatic brain injury in adolescent athletes.

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