Altered network topology in pediatric traumatic brain injury

Emily L. Dennis; Faisal Rashid; Talin Babikian; Richard Mink; Christopher Babbitt; Jeffrey Johnson; Christopher C. Giza; Robert F. Asarnow; Paul M. Thompson

doi:10.1117/12.2285245

17 November 2017 Altered network topology in pediatric traumatic brain injury

Emily L. Dennis, Faisal Rashid, Talin Babikian, Richard Mink, Christopher Babbitt, Jeffrey Johnson, Christopher C. Giza, Robert F. Asarnow, Paul M. Thompson

Author Affiliations +

Proceedings Volume 10572, 13th International Conference on Medical Information Processing and Analysis; 105720P (2017) https://doi.org/10.1117/12.2285245
Event: 13th International Symposium on Medical Information Processing and Analysis, 2017, San Andres Island, Colombia

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.

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Emily L. Dennis, Faisal Rashid, Talin Babikian, Richard Mink, Christopher Babbitt, Jeffrey Johnson, Christopher C. Giza, Robert F. Asarnow, and Paul M. Thompson "Altered network topology in pediatric traumatic brain injury", Proc. SPIE 10572, 13th International Conference on Medical Information Processing and Analysis, 105720P (17 November 2017); https://doi.org/10.1117/12.2285245

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