Title:Application of Diffusion Tensor Imaging Based on Automatic Fiber Quantification
in Alzheimer's Disease
Volume: 19
Issue: 6
Author(s): Bo Yu, Zhongxiang Ding, Luoyu Wang, Qi Feng, Yifeng Fan, Xiufang Xu*Zhengluan Liao*
Affiliation:
- School of Medical Imaging, Hangzhou Medical College, Hangzhou, P.R. China
- Center for Rehabilitation Medicine, Department of Geriatric VIP No.3, Zhejiang Provincial People's Hospital, Affiliated
People 's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang 310024, China
Keywords:
Alzheimer's disease, automatic fiber quantification, white matter microarchitecture, superior longitudinal fasciculus, Diffusion tensor imaging, normal controls.
Abstract:
Background: Neuroimaging suggests that white matter microstructure is severely affected in
Alzheimer's disease (AD) progression. However, whether alterations in white matter microstructure are
confined to specific regions and whether they can be used as potential biomarkers to distinguish normal
control (NC) from AD are unknown.
Methods: In this cross-sectional study, 33 cases of AD and 25 cases of NC were recruited for automatic
fiber quantification (AFQ). A total of 20 fiber bundles were equally divided into 100 segments for
quantitative assessment of fractional anisotropy (FA), mean diffusivity (MD), volume and curvature. In
order to further evaluate the diagnostic value, the maximum redundancy minimum (mRMR) and LASSO
algorithms were used to select features, calculate the Radscore of each subject, establish logistic
regression models, and draw ROC curves, respectively, to assess the predictive power of four different
models.
Results: There was a significant increase in the MD values in AD patients compared with healthy subjects.
The differences were mainly located in the left cingulum hippocampus (HCC), left uncinate fasciculus
(UF) and superior longitudinal fasciculus (SLF). The point-wise level of 20 fiber bundles was
used as a classification feature, and the MD index exhibited the best performance to distinguish NC
from AD.
Conclusion: These findings contribute to the understanding of the pathogenesis of AD and suggest that
abnormal white matter based on DTI-based AFQ analysis is helpful to explore the pathogenesis of AD.
