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. 2021 Mar 31;11:582788. doi: 10.3389/fonc.2021.582788

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Copyright © 2021 Zhao, Wang, Wu, Zhang, Lin, Yao, Chen, Wang, Sheng, Liu, Song, Wang, An, Guo, Li, Wu and Liu

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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The workflow of radiomics analysis in our study. (A) Contrast-enhanced MR imaging was acquired. (B) Tumors were manually delineated around the entire tumor outline on all axial slices of arterial phase (AP), portal venous phase (PVP), and delayed phase (DP) images, and three-dimensional segmentations were formed. (C) Total 2367 radiomics features were extracted. (D) Four steps of feature dimensionality reduction were applied to all extracted features. (E) The radiomics model was constructed using logistic regression algorithm, and a nomogram that incorporates the radiomics score and clinical-radiological risk factors was established to provide a more understandable treatment response measurement for individualized evaluation, followed by receiver operating characteristic curve analysis, calibration curve, and decision curve analysis.