White matter microstructural and network abnormalities in periventricular leukomalacia and their association with motor severity
摘要
To explore the value of diffusion tensor imaging (DTI)-based metrics (analysis along the perivascular space [ALPS] index and global fractional anisotropy [FA]), in evaluating motor impairment severity in children with periventricular leukomalacia (PVL), and to analyze white matter microstructural and network abnormalities correlated with disease severity.
MethodsProspective study included 68 PVL patients (grouped by Gross Motor Function Classification System [GMFCS]: mild [I], moderate [II–III], severe [IV–V]) and 32 age/sex-matched controls. DTI was acquired via 3.0T MRI. The DTI-ALPS index and global FA were calculated, and connectometry analysis and brain network metric assessment were performed. Statistical analyses included analysis of covariance (ANCOVA), Spearman/Pearson correlations, and receiver operating characteristic (ROC) curve analysis.
ResultsDTI-ALPS/global FA differed across controls and GMFCS subgroups (all P < 0.001), negatively correlating with GMFCS (DTI-ALPS: r=-0.695; global FA: r=-0.578). ROC analysis demonstrated that the DTI-ALPS index had good discriminative ability for mild vs. moderate cases (AUC = 0.838) and moderate vs. severe cases (AUC = 0.781), with higher efficiency than global FA (AUC = 0.729 and 0.733, respectively). Connectometry analysis revealed progressive expansion of white matter tract abnormalities with increasing severity, involving motor-related, commissural, and associative pathways. Brain network metrics showed significant disruptions in moderate and severe patients compared to controls.
ConclusionThe DTI-ALPS index and global FA are objective biomarkers for assessing motor impairment severity in PVL children, with the DTI-ALPS index showing superior discriminative performance. Progressive white matter microstructural damage and network disruptions are closely associated with worsening motor function, providing insights into PVL pathophysiology and clinical management.