4.3 Article

Evaluation of histopathological changes in the microstructure at the center and periphery of glioma tumors using diffusional kurtosis imaging

Journal

CLINICAL NEUROLOGY AND NEUROSURGERY
Volume 151, Issue -, Pages 120-127

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.clineuro.2016.10.018

Keywords

Glioma; Diffusional kurtosis imaging; Microstructural change; Histopathology

Funding

  1. National Natural Science Foundation of China [81372439]
  2. Natural Science Foundation of Shandong Province [ZR2015HQ017]

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Objective: To explore the relationship between alterations in gliomas revealed by diffusional kurtosis imaging (DKI) and the histopathological microstructural changes. Methods: Thirty-seven patients with cerebral gliomas underwent conventional MRI and DKI at 3.0T. Normalized fractional anisotropy (FA), mean diffusivity (MD) and mean kurtosis (MM) were compared in different regions of glioma tumors. Parameters with a high sensitivity and specificity regarding the discrimination of glioma grade were evaluated using receiver operating characteristic (ROC) curve analysis. Correlations between normalized FA, MD, and MK and histopathological findings (tumor cell density, total vascular area [TVA], and Ki-67 labeling index [LI]) were assessed using Pearson correlation analyses. Results: Normalized FA, MD, and MK differed significantly between low-grade gliomas (LGGs) and high-grade gliomas (HGGs) (P=0.02, P=0.001 and P < 0.001, respectively) at the center of the tumor. Normalized MM exhibited the highest sensitivity (80%) and specificity (100%) in distinguishing HGGs from LGGs. Relative to the tumor center, normalized MK was significantly increased in the tumor periphery (P< 0.001) in LGGs and significantly decreased (P= 0.002) in HGGs. The significant correlations were found between normalized MM and all histopathological findings (tumor cell density: r= 0.596, P= 0.006; TVA: r= 0.764, P< 0.001; and Ki-67 LI: r= 0.766, P< 0.001) among samples from the center of the tumor. Conclusion: DKI, especially concerning the MM parameter, demonstrated high sensitivity in the detection of microstructural changes in patients with brain gliomas. (C) 2016 Elsevier B.V. All rights reserved.

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