Radiomics Nomogram Based on Multiple-Sequence Magnetic Resonance Imaging Predicts Long-Term Survival in Patients Diagnosed With Nasopharyngeal Carcinoma - Liu, Kai; Qiu, Qingtao; Qin, Yonghui; Chen, Ting; Zhang, Diangang; Huang, Li; Yin, Yong; Wang, Ruozheng (Frontiers in Oncology, 2022)
Purpose: Although the tumor-node-metastasis staging system is widely used for survival analysis of nasopharyngeal carcinoma (NPC), tumor heterogeneity limits its utility. In this study, we aimed to develop and validate a radiomics model, based on multiple sequences magnetic resonance imaging (MRI), to estimate the probability of overall survival in patients diagnosed with NPC. Methods: Multiple sequences MRIs, including T1 weighted, T1 contrast, and, T2 weighted imaging were collected from patients diagnosed with NPC. Radiomics features were extracted from the contoured gross tumor volume of three sequences from each patient using the least absolute shrinkage and selection operator with the Cox regression model. The optimal Rad score was determined using 12 of the 851 radiomics features derived from the multiple sequences MRI and its discrimination power compared in the training and validation cohorts. For better prediction performance, an optimal nomogram (radiomics nomogram-MS) that incorporated the optimal Rad score and clinical risk factors was developed, and a calibration curve and decision curve used to further evaluate the optimized discrimination power. Results: A total of 504 patients diagnosed with NPC were included in this study. The optimal Rad score was significantly correlated with overall survival in both the training (C-index: 0.731, 95 % confidence interval [CI]: 0.709-0.753) and validation cohorts (C-index: 0.807, 95 % CI: 0.782-0.832). Compared to the nomogram developed with only single sequence MRI, the radiomics nomogram-MS had a higher discrimination power in both the training (C-index: 0.827, 95 % CI: 0.809-0.845) and validation cohorts (C-index: 0.836, 95 % CI: 0.815-0.857). Analysis of the calibration and decision curves confirmed the effectiveness and utility of the optimal radiomics nomogram-MS. Conclusions: The radiomics nomogram model that incorporates multiple sequences MRI and clinical factors may be a useful tool for early assessment of the long-term prognosis of patients diagnosed with NPC.