单位：[1]Department of Radiology, China-Japan Friendship Hospital, Beijing, China[2]Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China[3]Department of Anesthesiology, Peking University First Hospital, Peking University, Beijing, China[4]Beijing Intelligent Brain Cloud Inc., Beijing, China[5]Department of Ultrasound Diagnosis, China-Japan Friendship Hospital, Beijing, China[6]Beijing City Key Lab for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, China[7]Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China[8]McGovern Institute for Brain Research, Peking University, Beijing, China
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 (alpha) and the Hurst exponent (H), were calculated and compared between the healthy group and AD group and between the 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(alpha) and gFA(H) values of the moderate AD group were higher than those of the mild AD group in left hippocampus. The gFA(alpha) value of the moderate AD group was significantly higher than that of the healthy control group in both the left and right hippocampus. The gFA(ADC) values of the moderate AD group were significantly lower than those of the mild AD group and healthy control group in the right hippocampus. Compared with the gFA(alpha), gFA(H), alpha, and H, the ROC analysis showed larger areas under the curves for combination of alpha + gFA(alpha) and the combination of H + gFA(H) in differentiating the mild AD and moderate AD groups, and larger area under the curves for combination of alpha + gFA(alpha) in differentiating the 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 values. The utility of anisotropic anomalous diffusion may provide novel insights to profoundly understand the neuropathology of AD.
基金：
National Key Research and Development Program of China [2020YFC2003903, 2019YFC0120903, 2016YFC1307001]; National Natural Science Foundation of China (NSFC)National Natural Science Foundation of China (NSFC) [81971585, 81571641, 91959123]
第一作者单位：[1]Department of Radiology, China-Japan Friendship Hospital, Beijing, China[2]Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
共同第一作者：
通讯作者：
通讯机构：[1]Department of Radiology, China-Japan Friendship Hospital, Beijing, China[2]Graduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
推荐引用方式(GB/T 7714)：
Du Lei,Zhao Zifang,Xu Boyan,et al.Anisotropy of Anomalous Diffusion Improves the Accuracy of Differentiating and Grading Alzheimer's Disease Using Novel Fractional Motion Model[J].FRONTIERS in AGING NEUROSCIENCE.2020,12:doi:10.3389/fnagi.2020.602510.
APA：
Du, Lei,Zhao, Zifang,Xu, Boyan,Gao, Wenwen,Liu, Xiuxiu...&Gao, Jiahong.(2020).Anisotropy of Anomalous Diffusion Improves the Accuracy of Differentiating and Grading Alzheimer's Disease Using Novel Fractional Motion Model.FRONTIERS in AGING NEUROSCIENCE,12,
MLA：
Du, Lei,et al."Anisotropy of Anomalous Diffusion Improves the Accuracy of Differentiating and Grading Alzheimer's Disease Using Novel Fractional Motion Model".FRONTIERS in AGING NEUROSCIENCE 12.(2020)
