The goal of this study was to investigate the value of high resolution T2-weighted–based radiomics in prediction of treatment response to neoadjuvant chemoradiotherapy (nCRT) in patients with rectal mucinous adenocarcinoma (RMAC). The result demonstrated that the MRI based radiomics machine learning model could assess tumoral treatment response to nCRT in patients with RMAC.
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