列线图
医学
无线电技术
放射科
磁共振成像
神经组阅片室
逻辑回归
阶段(地层学)
内科学
肿瘤科
神经学
生物
精神科
古生物学
作者
Juan Chen,Shanhong Lu,Yun Mao,Lei Tan,Guo Li,Yan Gao,Pingqing Tan,Donghai Huang,Xin Zhang,Yuanzheng Qiu,Yong Liu
标识
DOI:10.1007/s00330-021-08292-z
摘要
To explore whether radiomics features extracted from pre-treatment magnetic resonance imaging (MRI) can predict the overall survival (OS) in patients with hypopharyngeal squamous cell carcinoma. A total of 190 patients with hypopharyngeal squamous cell carcinoma were eligibly enrolled from two institutions. Radiomics features were extracted from contrast-enhanced axial T1-weighted (CE-T1WI) sequence. The least absolute shrinkage selection operator (LASSO) algorithm was applied to establish a radiomics score correlated with OS. Multivariate logistic regression analysis was applied to determine the independent risk factors, which was combined with radiomics score to build the final radiomics nomogram. A radiomics score with 6 CE-T1WI features for OS prediction was constructed and validated; its integration with specific clinicopathologic factors (N stage) showed a better prediction performance in the training, internal validation, and external validation cohorts (C-index 0.78, 0.75, and 0.75). Calibration curves determined a good agreement between the predicted and actual overall survival. The radiomics-clinical nomogram and radiomics score might be non-invasive and reliable methods for the risk stratification in patients with hypopharyngeal squamous cell carcinoma. • An MRI-based radiomics model was constructed to evaluate of OS in patients with hypopharyngeal squamous cell carcinoma.
• A radiomics-clinical nomogram that combined radiomics features and clinical characteristics was established.
• Multi-cohort study validated the predictive performance of the radiomics-clinical nomogram to stratify patients with high risk in clinical practice.
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