Abstract
BACKGROUND AND PURPOSE: This study aims to comprehensively assess microstructural abnormalities in both gray matter (GM) and white matter (WM) in patients with moyamoya disease (MMD) using neurite orientation dispersion and density imaging (NODDI). The analysis integrates GM-based and tract-based spatial statistics (GBSS and TBSS, respectively). METHODS: Diffusion-weighted imaging was performed on 26 healthy controls and 15 patients with MMD. NODDI metrics-including the neurite density index (NDI), orientation dispersion index (ODI), and isotropic volume fraction (ISOVF)-as well as diffusion tensor imaging (DTI) parameters-fractional anisotropy and mean diffusivity (MD)-were estimated and compared using GBSS and TBSS approaches. RESULTS: The analysis revealed significant microstructural alterations in both GM and WM among patients with MMD. In GM, reduced ODI was observed in multiple regions, including areas associated with the default mode network, executive control network, visual cortex, auditory cortex, sensorimotor cortex, and insula. In WM, decreased NDI and increased ISOVF were identified, predominantly in the corpus callosum, corona radiata, and bilateral frontal and parietal lobes. Although both DTI and NODDI metrics showed similar spatial distribution patterns of WM changes, the alterations detected by NODDI were more widespread. This suggests that NODDI may provide superior sensitivity for identifying microstructural changes associated with MMD. CONCLUSION: The integration of NODDI with GBSS and TBSS enhances the detection of cerebral microstructural alterations in MMD. These findings highlight the potential of NODDI-based metrics as valuable imaging biomarkers for improving diagnostic accuracy in MMD.