Cognitive Impairment and Altered Structural Connectivity After Mild Traumatic Brain Injury: A Longitudinal Study Based on Generalized Q-sampling Imaging


Neural regeneration research  ·  2026

Xinjia Xu; Mengjun Li; Chuxin Huang; Anqi Qiu; Sihong Huang; Jun Liu;


HIGHLIGHT
Subsequent graph theory and statistical analyses showed that generalized q-sampling imaging-based structural brain networks captured small-worldness in patients with mild traumatic brain injury compared with healthy controls.
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ABSTRACT
The pathophysiological mechanism of mild traumatic brain injury remains poorly understood. Generalized q-sampling imaging is applicable to a broad spectrum of diffusion imaging data, provides high-resolution depictions of the brain's structural connectivity, enables tracking neural fibers across brain regions, and shows promise for predicting neurological outcomes. Graph theory, a quantitative method for modeling complex networks, has been widely used to study changes in brain structure and function. This longitudinal observational study involved 34 patients with acute mild traumatic brain injury (12 men and 22 women) and 31 healthy controls (14 men and 17 women). Clinical and cognitive assessments, and magnetic resonance imaging scans were conducted within 72 hours and at 3 months post-injury. Subsequent graph theory and statistical analyses showed that generalized q-sampling imaging-based structural brain networks captured small-worldness in patients with mild traumatic brain injury compared with healthy controls. Patients with mild traumatic brain injury exhibited cognitive deficits, which showed improvement at the 3-month follow-up. The results also indicated changes in betweenness centrality, node efficiency, and node clustering coefficient of the left fusiform gyrus in patients with chronic mild traumatic brain injury, and an increase in connectivity strength between the bilateral anterior cingulate cortices. Preliminary explanations were made based on neural plasticity and compensatory mechanisms. The underlying mechanisms remain to be further explored in our subsequent research.

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year_of_publication2026
sourceNeural regeneration research

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