Anisotropy of anomalous diffusion improves the accuracy of differentiating low- and high-grade cerebral gliomas

Boyan Xu; Lu Su; Zhenxiong Wang; Yang Fan; Gaolang Gong; Wenzhen Zhu; Peiyi Gao; Jia-Hong Gao

doi:10.1016/j.mri.2018.04.005

Anisotropy of anomalous diffusion improves the accuracy of differentiating low- and high-grade cerebral gliomas

Magn Reson Imaging. 2018 Sep:51:14-19. doi: 10.1016/j.mri.2018.04.005. Epub 2018 Apr 17.

Authors

Boyan Xu¹, Lu Su², Zhenxiong Wang³, Yang Fan⁴, Gaolang Gong⁵, Wenzhen Zhu³, Peiyi Gao², Jia-Hong Gao⁶

Affiliations

¹ Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, China; Center for MRI Research, Peking University, Beijing, China.
² Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
³ Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
⁴ MR Research China, GE Healthcare, Beijing, China.
⁵ State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
⁶ Beijing City Key Lab for Medical Physics and Engineering, Institution of Heavy Ion Physics, School of Physics, Peking University, Beijing, China; Center for MRI Research, Peking University, Beijing, China; McGovern Institute for Brain Research, Peking University, Beijing, China; Shenzhen Key Laboratory of Affective and Social Cognitive Science, Institute of Affective and Social Neuroscience, Shenzhen University, Shenzhen, China; Center for Emotion and Brain, Shenzhen Institute of Neuroscience, Shenzhen, China. Electronic address: jgao@pku.edu.cn.

PMID: 29673894
DOI: 10.1016/j.mri.2018.04.005

Abstract

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 (α) 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 α. The ROC analysis revealed that larger areas under the ROC curves were produced for the combination of α (1) and the combination of H (0.813) compared with the directionally averaged α (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.

Keywords: Anisotropy; Anomalous diffusion; Cerebral glioma; High b-value diffusion imaging; Tumor grading.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Adult
Aged
Anisotropy
Brain Neoplasms / diagnostic imaging*
Brain Neoplasms / pathology*
Diffusion Magnetic Resonance Imaging / methods*
Female
Glioma / diagnostic imaging*
Glioma / pathology*
Humans
Male
Middle Aged
Multivariate Analysis
Neoplasm Grading