Anomalous diffusion in cerebral glioma assessed using a fractional motion model. Issue 5 (5th January 2017)

• Record Type: Journal Article
• Authors: Xu, Boyan; Su, Lu; Wang, Zhenxiong; Fan, Yang; Gong, Gaolang; Zhu, Wenzhen; Gao, Peiyi; Gao, Jia‐Hong
• Is Part Of: Magnetic resonance in medicine. Volume 78:Issue 5(2017)
• Page Start: 1944
• Page End: 1949
• Publication Date: 2017-01-05
• Subjects: anomalous diffusion -- high b‐value diffusion imaging -- cerebral glioma; Nuclear magnetic resonance -- Periodicals; Electron paramagnetic resonance -- Periodicals; 616.07548
• DOI: 10.1002/mrm.26581
• Languages: English
• ISSNs: 0740-3194

Abstract

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.