Juan Chen1,2,3, Shanhong Lu1,2,3, Yitao Mao4, Lei Tan5, Guo Li1,2,3, Yan Gao1,2,3, Pingqing Tan6, Donghai Huang1,2,3,7, Xin Zhang1,2,3,7, Yuanzheng Qiu8,9,10,11, Yong Liu12,13,14,15. 1. Department of Otolaryngology-Head and Neck Surgery, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, 410008, Hunan, China. 2. Otolaryngology Major Disease Research Key Laboratory of Hunan Province, Changsha, 410008, Hunan, China. 3. Clinical Research Center for Pharyngolaryngeal Diseases and Voice Disorders in Hunan Province, Changsha, 410008, Hunan, China. 4. Department of Radiology, Xiangya Hospital, Central South University, Changsha, 410008, Hunan, China. 5. College of Computer and Information Engineering, Hunan University of Technology and Business, Changsha, 410205, Hunan, China. 6. Department of Head and Neck Surgery, The Affiliated Tumor Hospital of Xiangya Medical School, Hunan Cancer Hospital, Central South University, Changsha, 410013, Hunan, China. 7. National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Xiangya Road, Changsha, 410008, Hunan, China. 8. Department of Otolaryngology-Head and Neck Surgery, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, 410008, Hunan, China. xyqyz@csu.edu.cn. 9. Otolaryngology Major Disease Research Key Laboratory of Hunan Province, Changsha, 410008, Hunan, China. xyqyz@csu.edu.cn. 10. Clinical Research Center for Pharyngolaryngeal Diseases and Voice Disorders in Hunan Province, Changsha, 410008, Hunan, China. xyqyz@csu.edu.cn. 11. National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Xiangya Road, Changsha, 410008, Hunan, China. xyqyz@csu.edu.cn. 12. Department of Otolaryngology-Head and Neck Surgery, Xiangya Hospital, Central South University, 87 Xiangya Road, Changsha, 410008, Hunan, China. liuyongent@csu.edu.cn. 13. Otolaryngology Major Disease Research Key Laboratory of Hunan Province, Changsha, 410008, Hunan, China. liuyongent@csu.edu.cn. 14. Clinical Research Center for Pharyngolaryngeal Diseases and Voice Disorders in Hunan Province, Changsha, 410008, Hunan, China. liuyongent@csu.edu.cn. 15. National Clinical Research Center for Geriatric Disorders (Xiangya Hospital), Xiangya Road, Changsha, 410008, Hunan, China. liuyongent@csu.edu.cn.
Abstract
OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. KEY POINTS: • 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.
OBJECTIVE: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: 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. KEY POINTS: • 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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