Anisotropy of Anomalous Diffusion Improves the Accuracy of Differentiating and Grading Alzheimer's Disease Using Novel Fractional Motion Model

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 av...

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Main Authors: Lei Du, Zifang Zhao, Boyan Xu, Wenwen Gao, Xiuxiu Liu, Yue Chen, Yige Wang, Jian Liu, Bing Liu, Shilong Sun, Guolin Ma, Jiahong Gao
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-11-01
Series:Frontiers in Aging Neuroscience
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fnagi.2020.602510/full
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record_format Article
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language English
format Article
sources DOAJ
author Lei Du
Lei Du
Zifang Zhao
Boyan Xu
Wenwen Gao
Xiuxiu Liu
Yue Chen
Yige Wang
Jian Liu
Bing Liu
Shilong Sun
Guolin Ma
Guolin Ma
Jiahong Gao
Jiahong Gao
Jiahong Gao
spellingShingle Lei Du
Lei Du
Zifang Zhao
Boyan Xu
Wenwen Gao
Xiuxiu Liu
Yue Chen
Yige Wang
Jian Liu
Bing Liu
Shilong Sun
Guolin Ma
Guolin Ma
Jiahong Gao
Jiahong Gao
Jiahong Gao
Anisotropy of Anomalous Diffusion Improves the Accuracy of Differentiating and Grading Alzheimer's Disease Using Novel Fractional Motion Model
Frontiers in Aging Neuroscience
diffusion magnetic resonance imaging
fractional motion model
anisotropy
Alzheimer's disease
hippocampus
author_facet Lei Du
Lei Du
Zifang Zhao
Boyan Xu
Wenwen Gao
Xiuxiu Liu
Yue Chen
Yige Wang
Jian Liu
Bing Liu
Shilong Sun
Guolin Ma
Guolin Ma
Jiahong Gao
Jiahong Gao
Jiahong Gao
author_sort Lei Du
title Anisotropy of Anomalous Diffusion Improves the Accuracy of Differentiating and Grading Alzheimer's Disease Using Novel Fractional Motion Model
title_short Anisotropy of Anomalous Diffusion Improves the Accuracy of Differentiating and Grading Alzheimer's Disease Using Novel Fractional Motion Model
title_full Anisotropy of Anomalous Diffusion Improves the Accuracy of Differentiating and Grading Alzheimer's Disease Using Novel Fractional Motion Model
title_fullStr Anisotropy of Anomalous Diffusion Improves the Accuracy of Differentiating and Grading Alzheimer's Disease Using Novel Fractional Motion Model
title_full_unstemmed Anisotropy of Anomalous Diffusion Improves the Accuracy of Differentiating and Grading Alzheimer's Disease Using Novel Fractional Motion Model
title_sort anisotropy of anomalous diffusion improves the accuracy of differentiating and grading alzheimer's disease using novel fractional motion model
publisher Frontiers Media S.A.
series Frontiers in Aging Neuroscience
issn 1663-4365
publishDate 2020-11-01
description 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 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(α) and gFA(H) values of the moderate AD group were higher than those of the mild AD group in left hippocampus. The gFA(α) 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(α), gFA(H), α, and H, the ROC analysis showed larger areas under the curves for combination of α + gFA(α) 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 α + gFA(α) 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.
topic diffusion magnetic resonance imaging
fractional motion model
anisotropy
Alzheimer's disease
hippocampus
url https://www.frontiersin.org/articles/10.3389/fnagi.2020.602510/full
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spelling doaj-9c9a8266ef544f90a0d50c8bacb21fb82020-11-25T04:10:30ZengFrontiers Media S.A.Frontiers in Aging Neuroscience1663-43652020-11-011210.3389/fnagi.2020.602510602510Anisotropy of Anomalous Diffusion Improves the Accuracy of Differentiating and Grading Alzheimer's Disease Using Novel Fractional Motion ModelLei Du0Lei Du1Zifang Zhao2Boyan Xu3Wenwen Gao4Xiuxiu Liu5Yue Chen6Yige Wang7Jian Liu8Bing Liu9Shilong Sun10Guolin Ma11Guolin Ma12Jiahong Gao13Jiahong Gao14Jiahong Gao15Department of Radiology, China-Japan Friendship Hospital, Beijing, ChinaGraduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaDepartment of Anesthesiology, Peking University First Hospital, Peking University, Beijing, ChinaBeijing Intelligent Brain Cloud Inc., Beijing, ChinaDepartment of Radiology, China-Japan Friendship Hospital, Beijing, ChinaDepartment of Radiology, China-Japan Friendship Hospital, Beijing, ChinaDepartment of Radiology, China-Japan Friendship Hospital, Beijing, ChinaDepartment of Radiology, China-Japan Friendship Hospital, Beijing, ChinaDepartment of Ultrasound Diagnosis, China-Japan Friendship Hospital, Beijing, ChinaDepartment of Radiology, China-Japan Friendship Hospital, Beijing, ChinaDepartment of Radiology, China-Japan Friendship Hospital, Beijing, ChinaDepartment of Radiology, China-Japan Friendship Hospital, Beijing, ChinaGraduate School of Peking Union Medical College, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, ChinaBeijing City Key Lab for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, ChinaCenter for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, ChinaMcGovern Institute for Brain Research, Peking University, Beijing, ChinaBackground 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 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(α) and gFA(H) values of the moderate AD group were higher than those of the mild AD group in left hippocampus. The gFA(α) 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(α), gFA(H), α, and H, the ROC analysis showed larger areas under the curves for combination of α + gFA(α) 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 α + gFA(α) 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.https://www.frontiersin.org/articles/10.3389/fnagi.2020.602510/fulldiffusion magnetic resonance imagingfractional motion modelanisotropyAlzheimer's diseasehippocampus