Computed tomography-based radiomics for predicting lymphovascular invasion in rectal cancer.

Abstract Purpose To develop and externally validate a computed tomography (CT)-based radiomics model for predicting lymphovascular invasion (LVI) before treatment in patients with rectal cancer (RC). Method This retrospective study enrolled 351 patients with RC from three hospitals between March 2018 and March 2021. These patients were assigned to one of the following three groups: training set (n = 239, from hospital 1), internal validation set (n = 60, from hospital 1), and external validation set (n = 52, from hospitals 2 and 3). Large amounts of radiomics features were extracted from the intratumoral and peritumoral regions in the portal venous phase contrast-enhanced CT images. The score of radiomics features (Rad-score) was calculated by performing logistic regression analysis following the L1-based method. A combined model (Rad-score + clinical factors) was developed in the training cohort and validated internally and externally. The models were compared using the area under the receiver operating characteristic curve (AUC). Results Of the 351 patients, 106 (30.2%) had an LVI + tumor. Rad-score (comprised of 22 features) was significantly higher in the LVI + group than in the LVI- group (0.60 ± 0.17 vs. 0.42 ± 0.19, P = 0.001). The combined model obtained good predictive performance in the training cohort (AUC = 0.813 [95% CI: 0.758–0.861]), with robust results in internal and external validations (AUC = 0.843 [95% CI: 0.726–0.924] and 0.807 [95% CI: 0.674–0.903]). Conclusions The proposed combined model demonstrated the potential to predict LVI preoperatively in patients with RC.