Neuroradiology · 2026
White matter microstructural and network abnormalities in periventricular leukomalacia and their association with motor severity.
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Liu Zhenghua, Yao Ruowei, Wang Ya
Аннотация
PURPOSE: 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.
METHODS: Prospective 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.
RESULTS: DTI-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.
CONCLUSION: The 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.
METHODS: Prospective 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.
RESULTS: DTI-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.
CONCLUSION: The 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.