Brain and Behavior (Nov 2024)
Disrupted White Matter Topology Organization in Preschool Children with Tetralogy of Fallot
Abstract
Abstract Background: Cognitive impairment is the most common long‐term complication in children with congenital heart disease (CHD) and is closely related to the brain network. However, little is known about the impact of CHD on brain network organization. This study aims to investigate brain structural network properties that may underpin cognitive deficits observed in children with Tetralogy of Fallot (TOF). Methods: In this prospective study, 29 preschool‐aged children diagnosed with TOF and 19 without CHD (non‐CHD) were enrolled. Participants underwent diffusion tensor imaging (DTI) scans alongside cognitive assessment using the Chinese version of the Wechsler Preschool and Primary Scale of Intelligence—fourth edition (WPPSI‐IV). We constructed a brain structural network based on DTI and applied graph analysis methodology to investigate alterations in diverse network topological properties in TOF compared with non‐CHD. Additionally, we explored the correlation between brain network topology and cognitive performance in TOF. Results: Although both TOF and non‐CHD exhibited small‐world characteristics in their brain networks, children with TOF significantly demonstrated increased characteristic path length and decreased clustering coefficient, global efficiency, and local efficiency compared with non‐CHD (p < 0.05). Regionally, reduced nodal betweenness and degree were found in the left cingulate gyrus, and nodal efficiency was decreased in the right precentral gyrus and cingulate gyrus, left inferior frontal gyrus (triangular part), and insula (p < 0.05). Furthermore, a positive correlation was identified between local efficiency and cognitive performance (p < 0.05). Conclusion: This study elucidates a disrupted brain structural network characterized by impaired integration and segregation in preschool TOF, correlating with cognitive performance. These findings indicated that the brain structural network may be a promising imaging biomarker and potential target for neurobehavioral interventions aimed at improving brain development and preventing lasting impairments across the lifetime.
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