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09.11.2018 | Clinical Study

Comparative analysis of the diffusion kurtosis imaging and diffusion tensor imaging in grading gliomas, predicting tumour cell proliferation and IDH-1 gene mutation status

Zeitschrift:
Journal of Neuro-Oncology
Autoren:
Jing Zhao, Yu-liang Wang, Xin-bei Li, Man-shi Hu, Zhu-hao Li, Yu-kun Song, Jing-yan Wang, Yi-su Tian, Da-wei Liu, Xu Yan, Li Jiang, Zhi-yun Yang, Jian-ping Chu
Wichtige Hinweise
Jing Zhao and Yu-liang Wang have contributed equally to this work.

Abstract

Introduction

Few studies have applied diffusion kurtosis imaging (DKI) and diffusion tensor imaging (DTI) for the comprehensive assessment of gliomas [tumour grade, isocitrate dehydrogenase-1 (IDH-1) mutation status and tumour proliferation rate (Ki-67)]. This study describes the efficacy of DKI and DTI to comprehensively evaluate gliomas, compares their results.

Methods

Fifty-two patients (18 females; median age, 47.5 years) with pathologically proved gliomas were prospectively included. All cases underwent DKI examination. DKI (mean kurtosis: MK, axial kurtosis: Ka, radial kurtosis: Kr) and DTI (mean diffusivity: MD, fractional anisotropy: FA) maps of each metric was derived. Three ROIs were manually drawn.

Results

MK, Ka, Kr and FA were significantly higher in HGGs than in LGGs, whereas MD was significantly lower in HGGs than in LGGs (P < 0.01). ROC analysis demonstrated that MK (specificity: 100% sensitivity: 79%) and Ka (specificity: 96% sensitivity: 82%) had the same and highest (AUC: 0.93) diagnostic value. Moreover, MK, Ka, and Kr were significantly higher in grade III than II gliomas (P ≦ 0.01). Further, DKI and DTI can significantly identify IDH-1 mutation status (P ≦ 0.03). Ka (sensitivity: 74%, specificity: 75%, AUC: 0.72) showed the highest diagnostic value. In addition, DKI metrics and MD showed significant correlations with Ki-67 (P ≦ 0.01) and Ka had the highest correlation coefficient (rs = 0.72).

Conclusions

Compared with DTI, DKI has great advantages for the comprehensive assessment of gliomas. Ka might serve as a promising imaging index in predicting glioma grading, tumour cell proliferation rate and IDH-1 gene mutation status.

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