Predicting Progression-Free Survival Using MRI-Based Radiomics for Patients With Nonmetastatic Nasopharyngeal Carcinoma
Hesong Shen, Yu Wang, Daihong Liu, Rongfei Lv, Yuanying Huang, Chao Peng, Shixi Jiang, Ying Wang, Yongpeng He, Xiaosong Lan, Hong Huang, Jianqing Sun, Jiuquan Zhang
Abstract
Objectives To explore the predictive value of MRI-based radiomics model for progression-free survival (PFS) in non-metastatic nasopharyngeal carcinoma (NPC). Methods 327 non-metastatic NPC patients (training cohort (n=230) and validation cohort (n=97)) were enrolled. The clinical and MRI data were collected. The least absolute shrinkage selection operator (LASSO) and recursive feature elimination (RFE) were used to select radiomics features. Five models (Model 1: clinical data, Model 2: overall stage, Model 3: radiomics, Model 4: radiomics + overall stage, Model 5: radiomics + overall stage +EBV DNA) were constructed. The prognostic performances of these models were evaluated by Harrell’s concordance index (C-index). The Kaplan-Meier method was applied for the survival analysis. Results The model 5 incorporating radiomics,overall stage and EBV DNA yielded the highest C-indices for predicting PFS in comparision with model 1, model 2, model 3 and model 4(training cohorts: 0.805 vs 0.766 vs 0.749 vs 0.641 vs 0.563, validation cohorts: 0.874 vs 0.839 vs 836 vs 0.689 vs 0.456). The survival curve showed that the high-risk group yielded a lower PFS than the low-risk group. Conclusions The model incorporating radiomics, overall stage and EBV DNA showed better performance for predicting PFS in non-metastatic NPC patients.