title: Anomalous diffusion in cerebral glioma assessed using a fractional motion model.
abstract: To demonstrate the capability of the fractional motion (FM) model for describing anomalous diffusion in cerebral gliomas and to assess the potential feasibility of FM for grading these tumors.
  
  
  
  Diffusion MRI images were acquired from brain tumor patients using a special Stejskal-Tanner diffusion sequence with variable diffusion gradient amplitudes and separation times. Patients with histopathologically confirmed gliomas, including astrocytic and oligoastrocytic tumors, were selected. The FM-related parameters, including the Noah exponent ( α), the Hurst exponent ( H), and the memory parameter ( μ=H-1/α), were calculated and compared between low- and high-grade gliomas using a two-sample t-test. The grading performance was evaluated using the receiver operating characteristic analysis.
  
  
  
  Twenty-two patients were included in the present study. The calculated α, H, and μ permitted the separation of tumor lesions from surrounding normal tissues in parameter maps and helped differentiate glioma grades. Moreover, α showed greater sensitivity and specificity in distinguishing low- and high-grade gliomas compared with the apparent diffusion coefficient.
  
  
  
  The FM model could improve the diagnostic accuracy in differentiating low- and high-grade gliomas. This improved diffusion model may facilitate future studies of neuro-pathological changes in clinical populations. Magn Reson Med 78:1944-1949, 2017. © 2017 International Society for Magnetic Resonance in Medicine.
authors.affiliation: Beijing City Key Lab for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, China.|Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.
authors.forename: Boyan
authors.initials: B
authors.lastname: Xu
authors.affiliation: Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
authors.forename: Lu
authors.initials: L
authors.lastname: Su
authors.affiliation: Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
authors.forename: Zhenxiong
authors.initials: Z
authors.lastname: Wang
authors.affiliation: MR Research China, GE Healthcare, Beijing, China.
authors.forename: Yang
authors.initials: Y
authors.lastname: Fan
authors.affiliation: State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China.
authors.forename: Gaolang
authors.initials: G
authors.lastname: Gong
authors.affiliation: Department of Radiology, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
authors.forename: Wenzhen
authors.initials: W
authors.lastname: Zhu
authors.affiliation: Department of Radiology, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
authors.forename: Peiyi
authors.initials: P
authors.lastname: Gao
authors.affiliation: Beijing City Key Lab for Medical Physics and Engineering, Institute of Heavy Ion Physics, School of Physics, Peking University, Beijing, China.|Center for MRI Research, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China.|McGovern Institute for Brain Research, Peking University, Beijing, China.
authors.forename: Jia-Hong
authors.initials: JH
authors.lastname: Gao
mesh_terms: D000328:Adult; D001921:Brain / Q000000981:diagnostic imaging; D001932:Brain Neoplasms / Q000000981:diagnostic imaging*; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D005260:Female; D005910:Glioma / Q000000981:diagnostic imaging*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009068:Movement; D012372:ROC Curve
keywords: anomalous diffusion; cerebral glioma; high b-value diffusion imaging