Longitudinal Tracking of Traumatic Brain Injury: Advanced Connectomics

创伤性脑损伤的纵向追踪：高级连接组学

基本信息

批准号：
9087791
负责人：
Emily Larsen Dennis
金额：
$ 8.78万
依托单位：
UNIVERSITY OF SOUTHERN CALIFORNIA
依托单位国家：
美国
项目类别：
财政年份：
2016
资助国家：
美国
起止时间：
2016-04-15 至 2018-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9087791
关键词：
Acute Adolescent Adult Affect Afghanistan Age Animals Anterior Area Atlases Biochemistry Biological Biological Markers Blast Cell Brain Brain Injuries Brain Mapping Brain imaging Cause of Death Child Childhood Childhood Injury Chronic Phase Clinical Collaborations Corpus Callosum Craniocerebral Trauma Data Data Analyses Data Set Demyelinations Development Developmental Process Diffusion Diffusion Magnetic Resonance Imaging Electroencephalography Emergency department visit Environment Event Fiber Foundations Goals Heterogeneity Hockey Image Incidence Individual Inflammation Injury Institutes Intake Iraq Knowledge Length Longitudinal Studies Magnetic Resonance Spectroscopy Manufactured football Maps Measures Mental disorders Mentors Meta-Analysis Methods Military Personnel Modality Moscow Neurobiology Outcome Participant Pathway interactions Patients Pattern Play Population Process Public Health Recovery Reporting Resolution Resources Risk Russia Sampling Scientist Seasons Services Site Source Sports Time Training Translating Traumatic Brain Injury United States Veterans Work aged base career clinical research site cognitive testing cohort college combat disability follow-up high risk high school imaging modality improved indexing inflammatory marker member myelination nervous system disorder neurochemistry neuron loss neuropsychological patient population prevent prognostic tool public health relevance relating to nervous system targeted treatment trend white matter white matter damage

项目摘要

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.

描述（通过应用程序证明）：我的项目应用了高级，多模式的连接方法，以研究脑损伤（TBI）如何在几个同伙中纵向大脑。兵役成员。）TBI的损害和预测f TBI，尤其是在IRY的大型Sarge Sarge Sarge Sasssssmessment间隔。通过TBI，它如何影响恢复过程通过我们的实验室，史诗般的（改善连接组的进化分区）；受伤后的19个月）具有大脑成像和认知评估。评估是UCLA的校队运动员，他们在17-23岁之间进行了NCAA认可的接触运动。随着检测变化的敏感性，将用于跨性别和纵向分析的神经化学光谱。检查跨核心趋势y。确定哪些生物标志物和结果是可复制的，并且可以将其转化为至关重要更大的患者人数。