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

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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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Funding

This study was funded by National Natural Science Foundation of China (CN) (Grant No. 81201074) and Fundamental Research Funds for the Central Universities (Grant No. 13ykpy14).

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Author notes

  1. Jing Zhao and Yu-liang Wang have contributed equally to this work.

Authors and Affiliations

  1. Department of Radiology, The First Affiliated Hospital, Sun Yat-Sen University, 58th, The Second Zhongshan Road, Guangzhou, 510080, Guangdong, China

    Jing Zhao, Man-shi Hu, Zhu-hao Li, Jing-yan Wang, Yi-su Tian, Li Jiang, Zhi-yun Yang & Jian-ping Chu

  2. Department of Radiology, Shenzhen City Nanshan District People’s Hospital, Shenzhen, 518000, China

    Yu-liang Wang

  3. Department of Radiology, Shenzhen Traditional Chinese Medicine Hospital, Shenzhen, 518033, China

    Xin-bei Li

  4. Department of Radiology, The First Affiliated Hospital of Xiamen University, Xiamen, 361003, China

    Yu-kun Song

  5. Department of Pathology, The First Affiliated Hospital, Sun Yat-Sen University, 58, The Second Zhongshan Road, Guangzhou, 510080, Guangdong, China

    Da-wei Liu

  6. MR Collaboration NE Asia, Siemens Healthcare, 278, Zhou Zhu Road, Nanhui, Shanghai, 201318, China

    Xu Yan

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  1. Jing Zhao
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Correspondence to Jian-ping Chu.

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The authors declare that they have no conflict of interest.

Ethical approval

This study was approved by the Research Ethics Committee of the First Affiliated Hospital of Sun Yat-sen University according to the ethical guidelines for human research and is compliant with the Health Insurance Portability and Accountability Act (HIPAA).

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Written informed consent was obtained from adult patients or their legal guardians.

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Zhao, J., Wang, Yl., Li, Xb. et al. Comparative analysis of the diffusion kurtosis imaging and diffusion tensor imaging in grading gliomas, predicting tumour cell proliferation and IDH-1 gene mutation status. J Neurooncol 141, 195–203 (2019). https://doi.org/10.1007/s11060-018-03025-7

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