There is no question that the vulnerabilities of the developing brain and the potential for recovery are unique, or that pediatric mild traumatic brain injury (pmTBI) represents a major public health concern with ?400,000 new cases annually. Although the neurobehavioral symptoms of pmTBI are well-documented in the first days to weeks post-injury, few well-designed studies have examined the long-term consequences of injury. Even less is known about the neuropathology underlying the expression of post-concussive symptoms (PCS) and the impact on clinical outcomes. Thus, clinicians currently do not understand how children typically recover in the first year of injury from either a clinical or neurophysiologic perspective. The current application addresses this critical knowledge gap by collecting longitudinal (1 week, 4 months and 1 year post-injury) neuroimaging and clinical data on a large cohort of pmTBI patients (N = 150) and healthy controls (N = 125). Our preliminary data suggests diffuse white matter injuries, hemodynamic abnormalities in deep gray matter, and signs of cortical atrophy at 4 months post-injury in a relatively small sample. Consistent with animal models, these data indicate that multiple imaging measures at multiple time-points are needed to understand the dynamic effects of pmTBI on neurophysiology and underlying contributory factors (e.g., cerebral blood flow, cerebral vascular reactivity). The current study will extend these findings to the early chronic and chronic injury stages, determine how these diffuse injuries relate to clinical outcomes, and determine the individual ?recovery time-courses? of selected biomarkers. Ratings of PCS are collected from both child and parent in conjunction with computerized cognitive testing, quality of life measures, and assessments of pre-morbid functioning. A multi-shell high angular resolution diffusion imaging sequence provides unique information on potential underlying mechanisms of action (water fractions). Functional activity is measured during a spatial attention task and through connectivity analyses. Additional quantitative measurements of resting cerebral blood flow and cerebral vascular reactivity will disambiguate hemodynamic from neuronal dysfunction. These independent measures will also provide critical information on how the vasculature in deep gray matter structures is affected by trauma, providing mechanisms of target engagement for future therapeutic trials. Growth curve modeling provides preliminary analyses of different recovery trajectories (fully versus partially recovered) for both clinical and imaging data. The public health significance of the current application is multifold. First, late childhood and adolescence constitutes a critical time for brain development, and persistent neurobehavioral symptoms following pmTBI can interfere with subsequent academic achievements and interpersonal relationships for years post-injury. Second, developing objective biomarkers that track injury progression will aid in diagnosis of injury severity and provide an empirical foundation for determining when it is truly safe for children to return to learn/physical activity. Finally, understanding the mechanisms of injury represents a critical first step for developing novel therapies that target neuropathology (i.e. target engagement) rather than symptom mitigation, the current approach for all pmTBI therapies.

Public Health Relevance

Approximately 400,000 youth experience a mild traumatic brain injury (pmTBI) each year. It is currently known that the neurobehavioral symptoms (i.e., cognitive, emotional, and somatic) of pmTBI are more pronounced in the first few weeks of injury, but it is not known how long these symptoms should typically last. Standard neuroimaging techniques are not very sensitive to the diffuse injuries that occur following pmTBI. Therefore, we do not understand why these symptoms occur or why certain children recover whereas others do not. Children who remain symptomatic are faced with impairment in academic, interpersonal and social functioning, ultimately resulting in a reduced quality of life. A growing literature also suggests that repetitive traumatic events may result in long-term neuropsychiatric disturbances. Thus, developing biomarkers that are capable of tracking neurological change from the semi-acute to more chronic injury phases is a major public health objective. The current application will utilize state-of-the-art neuroimaging techniques to quantify how diffuse injuries (e.g., gray matter, white matter and vascular) change during the dynamic course of pmTBI, and how they relate to neurobehavioral symptoms. This information is of vital significance for clinical decisions about injury severity and return to normal physical activity, as well as for ultimately developing treatments that target injury mechanisms rather than symptomatology.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
5R01NS098494-02
Application #
9298723
Study Section
Acute Neural Injury and Epilepsy Study Section (ANIE)
Program Officer
Lavaute, Timothy M
Project Start
2016-07-01
Project End
2021-03-31
Budget Start
2017-04-01
Budget End
2018-03-31
Support Year
2
Fiscal Year
2017
Total Cost
$598,046
Indirect Cost
$238,845
Name
The Mind Research Network
Department
Type
Research Institutes
DUNS #
098640696
City
Albuquerque
State
NM
Country
United States
Zip Code
87106
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Mayer, Andrew R; Kaushal, Mayank; Dodd, Andrew B et al. (2018) Advanced biomarkers of pediatric mild traumatic brain injury: Progress and perils. Neurosci Biobehav Rev 94:149-165
Vergara, Victor M; Mayer, Andrew R; Kiehl, Kent A et al. (2018) Dynamic functional network connectivity discriminates mild traumatic brain injury through machine learning. Neuroimage Clin 19:30-37
Quinn, Davin K; Mayer, Andrew R; Master, Christina L et al. (2018) Prolonged Postconcussive Symptoms. Am J Psychiatry 175:103-111
Dodd, Andrew B; Ling, Josef M; Bedrick, Edward J et al. (2018) Spatial distribution bias in subject-specific abnormalities analyses. Brain Imaging Behav 12:1828-1834
Mayer, Andrew R; Dodd, Andrew B; Ling, Josef M et al. (2018) An evaluation of Z-transform algorithms for identifying subject-specific abnormalities in neuroimaging data. Brain Imaging Behav 12:437-448
Mayer, Andrew R; Ling, Josef M; Dodd, Andrew B et al. (2017) A prospective microstructure imaging study in mixed-martial artists using geometric measures and diffusion tensor imaging: methods and findings. Brain Imaging Behav 11:698-711
Hanlon, Faith M; McGrew, Christopher A; Mayer, Andrew R (2017) Does a Unique Neuropsychiatric Profile Currently Exist for Chronic Traumatic Encephalopathy? Curr Sports Med Rep 16:30-35
Mayer, Andrew R; Wilcox, Claire E; Dodd, Andrew B et al. (2016) The efficacy of attention bias modification therapy in cocaine use disorders. Am J Drug Alcohol Abuse 42:459-68