Can Habitat-Based MRI Radiomics Distinguish Between T2 and T3 Stages in Rectal Cancer?

This study aims to investigate the use of multiparametric MRI (mp-MRI) habitat imaging techniques and radiomics to accurately predict the T2-T3 stages of rectal cancer.

A retrospective analysis was conducted on data from 507 rectal cancer patients across three medical centers. Data from Center 1 were randomly assigned in a 7:3 ratio to the training (n=264) and internal validation cohort (n=113). Data from Centers 2 and 3 served as external validation (n=130). Preoperative clinical data were analyzed, and independent predictors were identified using multivariable regression to develop a clinical model. MRI habitat imaging and radiomics were employed to derive radiomics feature scores, which were then used to construct habitat models.

Among 10 clinical factors, invasion depth and MR-report T stage were identified as independent predictive factors for the clinical model. Tumors were divided into three subregions using k-means clustering, and radiomics features were extracted from each subregion. After feature selection, 40, 37, and 39 highly correlated features were retained for habitat models 1, 2, and 3, respectively. The habitat combined (habitat C) model, which integrated all three individual habitat models, was developed. The AUC values for the clinical model in predicting T2-T3 stages ranged from 0.745 to 0.834, while the AUC values for the habitat models ranged from 0.817 to 0.981, with the habitat C model demonstrating the best predictive performance.

The mp-MRI habitat model developed in this study offers precise prediction of T2-T3 staging in rectal cancer.