Anomalous diffusion in cerebral glioma assessed using a fractional motion model

Magn Reson Med. 2017 Nov;78(5):1944-1949. doi: 10.1002/mrm.26581. Epub 2017 Jan 5.

Abstract

Purpose: 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.

Methods: 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.

Results: 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.

Conclusion: 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.

Keywords: anomalous diffusion; cerebral glioma; high b-value diffusion imaging.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Brain / diagnostic imaging
  • Brain Neoplasms / diagnostic imaging*
  • Diffusion Magnetic Resonance Imaging / methods*
  • Female
  • Glioma / diagnostic imaging*
  • Humans
  • Image Processing, Computer-Assisted / methods*
  • Male
  • Middle Aged
  • Movement
  • ROC Curve