Anisotropy of Anomalous Diffusion Improves the Accuracy of Differentiating and Grading Alzheimer's Disease Using Novel Fractional Motion Model - Du, Lei; Zhao, Zifang; Xu, Boyan; Gao, Wenwen; Liu, Xiuxiu; Chen, Yue; Wang, Yige; Liu, Jian; Liu, Bing; Sun, Shilong; Ma, Guolin; Gao, Jiahong (Frontiers in Aging Neuroscience, 2020)
Background and Purpose: Recent evidence shows that the fractional motion (FM) model may be a more appropriate model for describing the complex diffusion process of water in brain tissue, and has shown to be beneficial in clinical applications of Alzheimer’s disease (AD). However, the FM model averaged the anomalous diffusion parameter values, which omitted the impacts of anisotropy. This study aimed to investigate the potential feasibility of anisotropy of anomalous diffusion using the FM model for distinguishing and grading AD patients. Methods: Twenty-four patients with AD and 11 matched healthy controls were recruited, diffusion MRI was obtained from all participants, and analyzed using the FM model. Generalized fractional anisotropy (gFA), an anisotropy metric, was introduced and the gFA values of FM-related parameters, Noah exponent (α) and the Hurst exponent (H), were calculated and compared between healthy group and AD group, and between mild AD group and moderate AD group. The receiver-operating characteristic (ROC) analysis and the multivariate logistic regression analysis were used to assess the diagnostic performances of the anisotropy values and the directionally averaged values. Results: The gFA(α) and gFA(H) values of moderate AD group were higher than mild AD group in left hippocampus. The gFA(α) value of moderate AD group was significantly higher than healthy control group both in left and right hippocampus. The gFA (ADC) values of moderate AD group were significantly lower than mild AD group and healthy control group in the right hippocampus. Compared with the gFA(α), gFA(H), α, and H, the ROC analysis showed larger areas under curves for combination of α + gFA(α) and the combination of H + gFA(H) in differentiating mild AD and moderate AD groups, and larger area under curves for combination of α + gFA(α) in differentiating healthy controls and AD groups. Conclusion: The anisotropy of anomalous diffusion could significantly differentiate and grade patients with AD, and the diagnostic performance was improved when the anisotropy metric was combined with commonly used directionally averaged value. The utility of anisotropic anomalous diﬀusion may provide novel insights to profoundly understand the neuropathology of AD.