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International Journal of Clinical and Experimental Medicine Research

ISSN Online: 2575-7970 Downloads: 324396 Total View: 3033514
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Article Open Access http://dx.doi.org/10.26855/ijcemr.2021.04.006

Two Diffusion Kurtosis Imaging Post-Processing Methods for Differentiating Glioma Grades, IDH Mutation Statuses, and Heterogeneity

Jie Bai1, Ankang Gao1, Yuan Hong2, Guohua Zhao1, Yong Zhang1, Dexing Kong2, Jingliang Cheng1,*

1Department of MRI, the First Affiliated Hospital of Zhengzhou University, Zhengzhou, China.

2School of Mathematical Sciences, Zhejiang University, Hangzhou, China.

*Corresponding author: Jingliang Cheng

Published: March 2,2021

Abstract

Background: To compare the application of two DKI post-processing methods that DKE software and DKI histogram analysis in glioma grading, IDH mutation typing, and evaluation of tumor heterogeneity. Methods: Patients who underwent surgery and were pathologically diagnosed with glioma after MR DKI scan. DKE software was used to calculate diffusion parameters, including fractional anisotropy, mean kurtosis (MK), radial kurtosis, and axial kurtosis. Histogram parameters were calculated, including minimum, maximum, mean, standard deviation, percentile values (25th, 50th, 75th, 95th), kurtosis, and skewness of Kapp and Dapp. The ROIs of the two post-processing methods were consistently and manually selected in continuous solid tumor regions. According to the result of Kolmogorov-Smirnov (K-S) test, Independent-samples T test or Mann-Whitney-Wilcoxon test was used to distinguish glioma grads. The parameters with the best percentile were identified by analysis of the area under the curve (AUC) of the receiver operating characteristic (ROC) analysis. Results: Seventy-three patients with glioma were observed, including 21 with low-grade gliomas (WHOII) and 52 with high-grade gliomas (WHO III, n = 13: WHO IV, n = 39), 38 of whom had IDH mutation status. There were significant differences between the high- and low-grade glioma groups regarding the maximum, mean, standard deviation, C75, and C95 of the Kapp values and the minimum, mean, C25, C50, C75, C95, and skewness of the Dapp values. The MK values were significantly different among the WHO II, III, and IV grades. MK, mean Kapp, and C75 and C95 of the Kapp could be used to predict IDH mutations in patients with glioma. Conclusions: Several quantitative DKI parameters obtained from the DKE software and histogram analysis could be used for glioma grading and predicting IDH mutations. However, DKI histogram analysis was useful for glioma heterogeneity.

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How to cite this paper

Two Diffusion Kurtosis Imaging Post-Processing Methods for Differentiating Glioma Grades, IDH Mutation Statuses, and Heterogeneity

How to cite this paper: Jie Bai, Ankang Gao, Yuan Hong, Guohua Zhao, Yong Zhang, Dexing Kong, Jingliang Cheng. (2021) Two Diffusion Kurtosis Imaging Post-Processing Methods for Differentiating Glioma Grades, IDH Mutation Statuses, and Heterogeneity. International Journal of Clinical and Experimental Medicine Research, 5(2), 127-134.

DOI: http://dx.doi.org/10.26855/ijcemr.2021.04.006

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