机构：[a]Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, China[b]Center for MRI Research, Peking University, Beijing, China[c]Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China重点科室医技科室放射科放射科首都医科大学附属天坛医院[d]Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China其他科室放射科华中科技大学同济医学院附属同济医院[e]MR Research China, GE Healthcare, Beijing, China[f]State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China[g]McGovern Institute for Brain Research, Peking University, Beijing, China[h]Shenzhen Key Laboratory of Affective and Social Cognitive Science, Institute of Affective and Social Neuroscience, Shenzhen University, Shenzhen, China[i]Center for Emotion and Brain, Shenzhen Institute of Neuroscience, Shenzhen, China
Background: Anomalous diffusion model has been introduced and shown to be beneficial in clinical applications. However, only the directionally averaged values of anomalous diffusion parameters were investigated, and the anisotropy of anomalous diffusion remains unexplored. The aim of this study was to demonstrate the feasibility of using anisotropy of anomalous diffusion for differentiating low- and high-grade cerebral gliomas. Methods: Diffusion MRI images were acquired from brain tumor patients and analyzed using the fractional motion (FM) model. Twenty-two patients with histopathologically confirmed gliomas were selected. An anisotropy metric for the FM-related parameters, including the Noah exponent (alpha) and the Hurst exponent (H), was introduced and their values were statistically compared between the low- and high-grade gliomas. Additionally, multivariate logistic regression analysis was performed to assess the combination of the anisotropy metric and the directionally averaged value for each parameter. The diagnostic performances for grading gliomas were evaluated using a receiver operating characteristic (ROC) analysis. Results: The Hurst exponent H was more anisotropic in high-grade than in low-grade gliomas (P = 0.015), while no significant difference was observed for the anisotropy of alpha. The ROC analysis revealed that larger areas under the ROC curves were produced for the combination of alpha (1) and the combination of H (0.813) compared with the directionally averaged alpha (0.979) and H (0.594), indicating an improved performance for tumor differentiation. Conclusion: The anisotropy of anomalous diffusion can provide distinctive information and benefit the differentiation of low- and high-grade gliomas. The utility of anisotropic anomalous diffusion may have an improved effect for investigating pathological changes in tissues.
基金：
National Key Research and Development Program of China [2017YFC0108900]; National Natural Science Foundation of ChinaNational Natural Science Foundation of China [81430037, 81727808, 81790650, 81790651]; Beijing Municipal Science & Technology CommissionBeijing Municipal Science & Technology Commission [Z171100000117012, Z161100000216152]; Shenzhen Peacock Plan [KQTD2015033016104926]; Shenzhen Science and Technology Research Funding Program [JCYJ20170412164413575]; Guangdong Pearl River Talents Plan Innovative and Entrepreneurial Team [2016ZT065220]
第一作者机构：[a]Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, China[b]Center for MRI Research, Peking University, Beijing, China
通讯作者：
通讯机构：[a]Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, China[b]Center for MRI Research, Peking University, Beijing, China[g]McGovern Institute for Brain Research, Peking University, Beijing, China[h]Shenzhen Key Laboratory of Affective and Social Cognitive Science, Institute of Affective and Social Neuroscience, Shenzhen University, Shenzhen, China[i]Center for Emotion and Brain, Shenzhen Institute of Neuroscience, Shenzhen, China[*1]Center for MRI Research, Peking University, Beijing 100871, China.
推荐引用方式(GB/T 7714)：
Xu Boyan,Su Lu,Wang Zhenxiong,et al.Anisotropy of anomalous diffusion improves the accuracy of differentiating low- and high-grade cerebral gliomas[J].MAGNETIC RESONANCE IMAGING.2018,51:14-19.doi:10.1016/j.mri.2018.04.005.
APA：
Xu, Boyan,Su, Lu,Wang, Zhenxiong,Fan, Yang,Gong, Gaolang...&Gao, Jia-Hong.(2018).Anisotropy of anomalous diffusion improves the accuracy of differentiating low- and high-grade cerebral gliomas.MAGNETIC RESONANCE IMAGING,51,
MLA：
Xu, Boyan,et al."Anisotropy of anomalous diffusion improves the accuracy of differentiating low- and high-grade cerebral gliomas".MAGNETIC RESONANCE IMAGING 51.(2018):14-19
