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Magnetic resonance imaging texture analyses in lower-grade gliomas with a commercially available software: correlation of apparent diffusion coefficient and T2 skewness with 1p/19q codeletion

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Abstract

Preoperative prediction of molecular information of lower-grade gliomas (LrGGs) helps to determine the overall treatment strategy as well as the initial surgical strategy. This study aimed to detect magnetic resonance imaging (MRI) texture parameters to predict the molecular signature of LrGGs using a commercially available software and routine MR images. Forty-three patients treated at Keio University Hospital who had World Health Organization grade II or III gliomas were included. All patients having preoperative T1- and T2-weighted, fluid-attenuated inversion recovery (FLAIR) and diffusion-weighted (DW) images were also included. Texture analyses of T2, FLAIR, and apparent diffusion coefficient (ADC) histograms were performed using a commercially available software. Texture parameters including kurtosis, skewness, and entropy were investigated to determine any correlation with the presence or absence of isocitrate dehydrogenase (IDH) mutations, 1p/19q codeletion, and O6-methylguanine-DNA methyltransferase (MGMT) promoter methylation. ADC skewness and T2 skewness were significantly associated with 1p/19q codeletion status. ADC skewness of ≥ 0.25 predicted 1p/19q codeletion with a sensitivity and specificity of 80% and 65.2%, respectively (AUC = 0.728). T2 skewness of ≥ − 0.11 predicted 1p/19q codeletion with a sensitivity and specificity of 80% and 91.3%, respectively, (AUC = 0.866). None of the texture parameters were associated with IDH mutation and MGMT promoter methylation. MRI texture analysis using a commercially available software demonstrated that T2 skewness could predict 1p/19q codeletion with high sensitivity and specificity, suggesting a clinical utility.

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Acknowledgments

We greatly thank Ms. Naoko Tsuzaki at the Department of Neurosurgery, Keio University School of Medicine, for the technical assistance of laboratory works. The authors also greatly thank Dr. Ryota Ishii and Dr. Ryo Takemura at Center for Clinical Research, Department of Preventive Medicine and Public Health, Keio University School of Medicine, for the statistical advice.

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  1. Department of Neurosurgery, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan

    Tokunori Kanazawa, Masahiro Toda, Kazunari Yoshida & Hikaru Sasaki

  2. Department of Diagnostic Radiology, Keio University School of Medicine, 35 Shinanomachi, Shinjuku-ku, Tokyo, 160-8582, Japan

    Yasuhiro Minami, Hidenori Takahashi, Hirokazu Fujiwara & Masahiro Jinzaki

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  1. Tokunori Kanazawa
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Correspondence to Hikaru Sasaki.

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This study was conducted as a part of the molecular-clinical translational research program approved by the Institutional Review Board at Keio University School of Medicine and named “Towards molecular classification and personalized treatment of brain tumors” (approval number 20050002). All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

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Kanazawa, T., Minami, Y., Takahashi, H. et al. Magnetic resonance imaging texture analyses in lower-grade gliomas with a commercially available software: correlation of apparent diffusion coefficient and T2 skewness with 1p/19q codeletion. Neurosurg Rev 43, 1211–1219 (2020). https://doi.org/10.1007/s10143-019-01157-6

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