FIGURE 1:

Example of radiomics study workflow. In all, 163 breast cancer patients with DCE-MRI scans were included in this study. The ROIs were identified on (a) the first postcontrast image; (b) the corresponding intratumoral and peritumoral ROIs: the yellow region is the original intratumoral ROI covering the enhancing tumor drawn by the radiologist, while the red region indicates the peritumoral ROI after dilation; radiomic features were extracted from (c) washin map, (d) washout map, and (e) SER map. The dataset was then randomly separated into a training set (~67%) and a validation set (~33%). The prediction model was built in the training set after combining clinical and histopathological information and was further tested in the completely independent validation set. (Reprinted and adapted with permission from Liu et al. J Magn Reson Imaging 2019;49:131–140.)