Longitudinal Tracking of Traumatic Brain Injury: Advanced Connectomics

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 DESCRIPTION (provided by applicant): My project applies advanced, multi-modal connectomics methods to study how traumatic brain injury (TBI) affects the brain longitudinally, across several cohorts. I analyze three populations at heightened risk of TBI: children and adolescents, athletes, and military service members. TBI is associated with higher risk of developing neurological and psychiatric disorders, and in children and adolescents it can delay or disrupt ongoing brain development. There is considerable heterogeneity in post-injury outcome, which is poorly explained by existing prognostic tools. Biomarkers from advanced connectomics methods that we have developed, including multi-modal data harnessing functional, structural, and neurochemical information will improve our sensitivity for mapping white matter (WM) damage in TBI and predicting outcome. There are few longitudinal studies of TBI, especially with large samples and circumscribed assessment intervals post-injury. As there is a dynamic cascade of post-injury neurobiological events, a restricted post-injury window is critical. In my proposal, I follow 3 cohorts longitudinally to examine how brain connectivity is altered by TBI, how it recovers, and what factors impact the recovery process. With this goal, I have four aims: (1) identify disruptions in tract-based indices of white matter integrity associate with TBI using a new method developed by our lab, autoMATE (automated multi-atlas tract extraction); (2) identify network connectivity alterations associated with TBI using another method developed by our lab, EPIC (evolving partitions to improve connectomics); (3) combine data from DWI and magnetic resonance spectroscopy (MRS) to understand inflammation and WM disruption in TBI; (4) expand these analyses to include additional cohorts from collaborators across the world. My first cohort is a pediatric cohort (RAPBI), including children and adolescents aged 8-19 years. They are assessed in the post-acute (1-5 months post-injury) and chronic phases (13-19 months post-injury) with both brain imaging and cognitive assessments. The second cohort is active duty U.S. Service Members who sustained TBI while in Iraq or Afghanistan, between 18-60 years old. They are assessed at 4 time-points within 6 months of intake, with brain imaging and cognitive assessments. The third is UCLA varsity athletes who play an NCAA-recognized contact sport, between 17-23 years old. They are assessed at the beginning of the season, and after an injury receive 6 follow-up imaging and cognitive assessments. AutoMATE and EPIC are advanced methods, with increased sensitivity for detecting change, and will be used for both cross-sectional and longitudinal analyses. Integrating neurochemical spectra from MRS with the diffusion information from DWI will help us interpret results by revealing disruptions in underlying biochemistry. Through meta-analyses, I will examine cross-cohort trends, respecting the clinical and site heterogeneity. Determining what biomarkers and results are replicable and generalizable is critical to translating them to the greater patient population. My longitudinal multi-modal project will advance our understanding of recovery post-TBI.