医学
介入放射学
食管鳞状细胞癌
无线电技术
神经组阅片室
磁共振成像
肿瘤科
内科学
超声波
放射科
癌
神经学
精神科
作者
Funing Chu,Yun Liu,Qiuping Liu,Weijia Li,Zhengyan Jia,Chenglong Wang,Zhaoqi Wang,Shuang Lü,Ping Li,Yuanli Zhang,Yu-Bo Liao,Miao Xu,Xiaoqiang Yao,Zhen Wang,Cuicui Liu,Hongkai Zhang,Shaoyu Wang,Yan Xu,Ihab R. Kamel,Haibo Sun,Guang Yang,Yudong Zhang,Jinrong Qu
标识
DOI:10.1007/s00330-022-08776-6
摘要
To develop and validate an optimal model based on the 1-mm-isotropic-3D contrast-enhanced StarVIBE MRI sequence combined with clinical risk factors for predicting survival in patients with esophageal squamous cell carcinoma (ESCC).Patients with ESCC at our institution from 2015 to 2017 participated in this retrospective study based on prospectively acquired data, and were randomly assigned to training and validation groups at a ratio of 7:3. Random survival forest (RSF) and variable hunting methods were used to screen for radiomics features and LASSO-Cox regression analysis was used to build three models, including clinical only, radiomics only and combined clinical and radiomics models, which were evaluated by concordance index (CI) and calibration curve. Nomograms and decision curve analysis (DCA) were used to display intuitive prediction information.Seven radiomics features were selected from 434 patients, combined with clinical features that were statistically significant to construct the predictive models of disease-free survival (DFS) and overall survival (OS). The combined model showed the highest performance in both training and validation groups for predicting DFS ([CI], 0.714, 0.729) and OS ([CI], 0.730, 0.712). DCA showed that the net benefit of the combined model and of the clinical model is significantly greater than that of the radiomics model alone at different threshold probabilities.We demonstrated that a combined predictive model based on MR Rad-S and clinical risk factors had better predictive efficacy than the radiomics models alone for patients with ESCC.• Magnetic resonance-based radiomics features combined with clinical risk factors can predict survival in patients with ESCC. • The radiomics nomogram can be used clinically to predict patient recurrence, DFS, and OS. • Magnetic resonance imaging is highly reproducible in visualizing lesions and contouring the whole tumor.
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