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Change in structural brain network abnormalities after traumatic brain injury determines post-injury recovery

2022-05-29 · James J Gugger, Nishant Sinha, Yiming Huang, Alexa Walter, Cillian Lynch, Justin Morrison, Nathan Smyk, Danielle Sandsmark, Ramon Diaz-Arrastia, Kathryn A Davis

The trajectory of an individual's recovery after traumatic brain injury (TBI) is heterogeneous, with complete recovery in some cases but persistent disability in others. We hypothesized that changes in structural brain network abnormalities guide the trajectory of an individual's recovery post-injury. Our objective was to characterize the variability in recovery post-TBI by identifying a putative neuroimaging biomarker of traumatic axonal injury (TAI) in individuals with mild TBI. We analyzed 70 T1-weighted and diffusion MRIs longitudinally collected from 35 individuals during the subacute and chronic post-injury periods. Each individual underwent longitudinal blood work to characterize blood protein biomarkers of axonal and glial injury and assessment of post-injury recovery in the subacute and chronic periods. By comparing the MRI data of individual cases with 35 controls, we estimated the longitudinal change in structural brain network abnormalities. We validated this proxy measure of TAI with independent measures of acute intracranial injury estimated from head CT and blood protein biomarkers. Post-injury structural network abnormality was significantly higher than controls in both subacute and chronic periods, associated with an acute CT lesion and subacute blood levels of glial fibrillary acid protein (r=0.5, p=0.008) and neurofilament light (r=0.41, p=0.02). Longitudinal change in abnormality associated with change in functional outcome status (r=-0.51, p=0.003) and post-concussive symptoms (BSI: r=0.46, p=0.03; RPQ:r = 0.46, p=0.02). Brain regions that most closely mapped onto symptom change over time corresponded to structural network hubs or areas susceptible to neurotrauma. Structural network abnormalities might be a biomarker of TAI. Assessing changes in brain network abnormality might enable better patient stratification for monitoring recovery after neurotrauma.

📄 PDF Abstract BibTeX arXiv:2205.14663

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