Predicting Mismatch-Repair Status in Rectal Cancer Using Multiparametric MRI-Based Radiomics Models: A Preliminary Study.

ABSTRACT: Detecting mismatch-repair (MMR) status is crucial for personalized treatment strategies and prognosis in rectal cancer (RC). A preoperative, noninvasive, and cost-efficient predictive tool for MMR is critically needed. Therefore, this study developed and validated machine learning radiomics models for predicting MMR status in patients directly on preoperative MRI scans. Pathologically confirmed RC cases administered surgical resection in two distinct hospitals were examined in this retrospective trial. Totally, 78 and 33 cases were included in the training and test sets, respectively. Then, 65 cases were enrolled as an external validation set. Radiomics features were obtained from preoperative rectal MR images comprising T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), contras

SUBMITTER: Jing G 

PROVIDER: S-EPMC9400426 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature