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. 2022 Mar 14;12:800787. doi: 10.3389/fonc.2022.800787

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Copyright © 2022 Wei, Gong, He, Liu, Liu, Yang, Zhou, Liang, Zhan, Xia, Duan, Lin, Han, Li, Qin, Pickhardt and Deng

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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Flowchart of the study. (A) Liver segmentation is performed on axial T2-weighted and contrast-enhanced T1-weighted imaging. Pre-contrast, pre-contrast phase; HAP, hepatic arterial phase; PVP, portal venous phase; EP, equilibrium phase; T2WI, T2 weighted imaging. (B) Four types of features are extracted from within the defined liver areas on the MR images, including quantify intensity, shape, texture and wavelet texture of the entire liver. (C) The LASSO method was applied to select suitable features and the selected features were used to calculate the Rad-score for the radiomic nomogram. (D) The radiomic signature incorporated the prognostic clinical risk factors in a final radiomic nomogram for individual evaluation.