Multi-parametric MRI-based Radiomics integrated with Clinical Features for Predicting the Ki-67 Labeling Index in Nasopharyngeal Carcinoma

To investigate the value of a nomogram based on multi-parametric MRI-based radiomics combined with clinical imaging features in predicting the Ki-67 LI in nasopharyngeal carcinoma. Least absolute shrinkage and selection operator (LASSO) regression was performed to select radiomics features. A nomogram was established using multivariable logistic regression. The receiver operating characteristic (ROC) curves, calibration, and decision curves were performed to evaluate the predictive performance of the different models. The nomograms constructed by integrating radiomics score (Rad-Score) with clinical imaging factors outperformed the clinical or the radiomics models alone.