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Altered network topology in pediatric traumatic brain injury
Author(s): Emily L. Dennis; Faisal Rashid; Talin Babikian; Richard Mink; Christopher Babbitt; Jeffrey Johnson; Christopher C. Giza; Robert F. Asarnow; Paul M. Thompson
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Paper Abstract

Outcome after a traumatic brain injury (TBI) is quite variable, and this variability is not solely accounted for by severity or demographics. Identifying sub-groups of patients who recover faster or more fully will help researchers and clinicians understand sources of this variability, and hopefully lead to new therapies for patients with a more prolonged recovery profile. We have previously identified two subgroups within the pediatric TBI patient population with different recovery profiles based on an ERP-derived (event-related potential) measure of interhemispheric transfer time (IHTT). Here we examine structural network topology across both patient groups and healthy controls, focusing on the ‘rich-club’ - the core of the network, marked by high degree nodes. These analyses were done at two points post-injury - 2-5 months (post-acute), and 13-19 months (chronic). In the post-acute time-point, we found that the TBI-slow group, those showing longitudinal degeneration, showed hyperconnectivity within the rich-club nodes relative to the healthy controls, at the expense of local connectivity. There were minimal differences between the healthy controls and the TBI-normal group (those patients who show signs of recovery). At the chronic phase, these disruptions were no longer significant, but closer analysis showed that this was likely due to the loss of power from a smaller sample size at the chronic time-point, rather than a sign of recovery. We have previously shown disruptions to white matter (WM) integrity that persist and progress over time in the TBI-slow group, and here we again find differences in the TBI-slow group that fail to resolve over the first year post-injury.

Paper Details

Date Published: 17 November 2017
PDF: 7 pages
Proc. SPIE 10572, 13th International Conference on Medical Information Processing and Analysis, 105720P (17 November 2017); doi: 10.1117/12.2285245
Show Author Affiliations
Emily L. Dennis, Keck School of Medicine, Univ. of Southern California (United States)
Faisal Rashid, Keck School of Medicine, Univ. of Southern California (United States)
Talin Babikian, Semel Institute for Neuroscience and Human Behavior, Univ. of California, Los Angeles (United States)
Steve Tisch BrainSPORT Program, Univ. of California, Los Angeles (United States)
LAC+USC Medical Ctr. (United States)
Richard Mink, Harbor-UCLA Medical Ctr. (United States)
Los Angeles BioMedical Research Institute (United States)
Christopher Babbitt, Miller Children's Hospital (United States)
Jeffrey Johnson, LAC+USC Medical Ctr. (United States)
Christopher C. Giza, UCLA Brain Injury Research Ctr., Mattel Children's Hospital (United States)
Robert F. Asarnow, Semel Institute for Neuroscience and Human Behavior, Univ. of California, Los Angeles (United States)
Univ. of California, Los Angeles (United States)
Paul M. Thompson, Keck School of Medicine, Univ. of Southern California (United States)
Semel Institute for Neuroscience and Human Behavior, Univ. of California, Los Angeles (United States)
Univ. of Southern California (United States)


Published in SPIE Proceedings Vol. 10572:
13th International Conference on Medical Information Processing and Analysis
Eduardo Romero; Natasha Lepore; Jorge Brieva; Juan David García, Editor(s)

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