MRI-Based Radiomics of Rectal Cancer: Assessment of the Local Recurrence at the Site of Anastomosis

Abstract

To investigate the significance of magnetic resonance imaging (MRI)-based radiomics model in differentiating local recurrence of rectal cancer from nonrecurrence lesions at the site of anastomosis. A total of 80 patients with clinically suspected lesions of anastomosis underwent 3.0T pelvic MRI consisting of T2-weighted imaging (T2WI), diffusion-weighted imaging (DWI), and contrast-enhanced T1-weighted volume interpolated body examination (VIBE) imaging. Radiomics features were extracted from volumes of interest (VOIs), delineated manually on multiple MRI sequences. Subsequently, principal component analysis reduced the dimensionality of features for T2WI, DWI, VIBE, and combined multisequences, respectively. On this basis, the extreme gradient boosting (XGBoost) classifier was trained to build ModelT2WI, ModelDWI, ModelVIBE, and Modelcombination. Receiver operating characteristic curves were generated to determine the diagnostic performance of various models. Principal component analysis selected eight, four, seven, and six principal components to construct the radiomics model for T2WI, DWI, VIBE, and combined multisequences, respectively. Modelcombination had an area under the receiver operating characteristic curve of 0.864, with sensitivity and specificity of 81.82% and 75.86% in the validation set, demonstrating a more optimal performance compared to other models (p< 0.05). The decision curve analysis confirmed the clinical usefulness of the model. This study demonstrated that MRI-based radiomics is a sophisticated and noninvasive tool for accurately distinguishing LR from nonrecurrence lesions at the site of anastomosis. Combining multiple sequences significantly improves its performance.