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Updated: Jan 12, 2026
Diffusion Tensor Magnetic Resonance Imaging in the Analysis of Neurodegenerative Diseases
Published on: July 28, 2013
Neurite orientation dispersion and density imaging reveals microstructural damage in moyamoya disease: a study based
Jia-Yan Shi1, Shao-Peng Zhuang1, Zi-Wei Cai1
1Department of Radiology, Fujian Medical University Union Hospital, Fuzhou, 350001, China.
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.
Insights
Neurite orientation dispersion and density imaging (NODDI) reveals widespread microstructural changes in gray and white matter of moyamoya disease (MMD) patients. NODDI offers enhanced sensitivity for detecting these brain alterations, aiding MMD diagnosis.
Area of Science:
- Neuroimaging
- Radiology
- Neurology
Background:
- Moyamoya disease (MMD) is a rare cerebrovascular disorder characterized by progressive stenosis of the internal carotid arteries.
- Understanding the underlying microstructural brain abnormalities in MMD is crucial for diagnosis and management.
Purpose of the Study:
- To comprehensively assess gray matter (GM) and white matter (WM) microstructural abnormalities in MMD patients using neurite orientation dispersion and density imaging (NODDI).
- To integrate GM-based and tract-based spatial statistics (GBSS and TBSS) for enhanced detection of MMD-related changes.
- To evaluate the sensitivity of NODDI compared to diffusion tensor imaging (DTI) in identifying MMD microstructural alterations.
Main Methods:
- Diffusion-weighted imaging was acquired from 15 MMD patients and 26 healthy controls.
- NODDI metrics (neurite density index [NDI], orientation dispersion index [ODI], isotropic volume fraction [ISOVF]) and DTI parameters (fractional anisotropy, mean diffusivity) were calculated.
- GBSS and TBSS approaches were employed for statistical comparison of imaging metrics between groups.
Main Results:
- Significant microstructural alterations were observed in both GM and WM of MMD patients.
- Reduced ODI in GM was noted in regions associated with major brain networks and sensory cortices.
- WM analysis revealed decreased NDI and increased ISOVF, particularly in the corpus callosum and frontal/parietal lobes; NODDI detected more widespread changes than DTI.
Conclusions:
- The integration of NODDI with GBSS and TBSS effectively detects cerebral microstructural alterations in MMD.
- NODDI-based metrics demonstrate superior sensitivity and potential as valuable imaging biomarkers for improving MMD diagnostic accuracy.
