Long Longitudinal Tract Lesion Contributes to the Progression of Alzheimer's Disease - Luo, Caimei; Li, Mengchun; Qin, Ruomeng; Chen, Haifeng; Huang, Lili; Yang, Dan; Ye, Qing; Liu, Renyuan; Xu, Yun; Zhao, Hui; Bai, Feng (Frontiers in Neurology, 2020)
Background: The degenerative pattern of white matter (WM) microstructure during Alzheimer’s disease (AD) and its relationship with cognitive function have not yet been clarified. The present research aimed to explore the alterations of WM microstructure and its impact on amnestic mild cognitive (aMCI) and AD patients. Mechanical learning methods was used to explore the validity of WM microstructure lesions on classification in AD spectrum disease. Methods: Neuropsychological data and diffusion tensor imaging (DTI) images were collected from 28 AD subjects, 31 aMCI subjects, and 27 normal controls (NC). Tract-based spatial statistics (TBSS) were used to extract diffusion parameters in WM tracts. We performed ANOVA analysis to compare diffusion parameters and clinical features among the three groups. Partial correlation analysis was used to explore the relationship between diffusion metrics and cognitive functions controlling for age, gender, and years of education. Additionally, we performed the support vector machine (SVM) classification to determine the discriminative ability of DTI metrics in differentiation of aMCI and AD patients from controls. Results: As compared to controls or aMCI patients, AD patients displayed widespread WM lesions, including in the inferior longitudinal fasciculus, inferior fronto-occipital fasciculi, superior longitudinal fasciculus, etc... Significant correlations between FA/MD/RD metrics of long longitudinal tract and memory deficit were found in aMCI and AD groups respectively. Furthermore, through SVM classification, we found DTI indicators generated by FA and MD parameters can effectively distinguish AD patients from the control group with accuracy rate up to 89% and 85%, respectively. Conclusion: WM microstructure is extensively disrupted in AD patients, and long longitudinal tract integrity is closely related to memory, which would hold potential value for monitoring the progression of AD. The classification method based on SVM and WM damage features may be objectively helpful to the classification of AD diseases.