A CT-based radiomics nomogram for differentiation of squamous cell carcinoma and non-Hodgkin's lymphoma of the palatine tonsil

被引:4
作者
Dong, Cheng [1 ]
Zheng, Ying-Mei [2 ]
Li, Jian [3 ]
Wu, Zeng-Jie [1 ]
Yang, Zhi-Tao [1 ]
Li, Xiao-Li [1 ]
Xu, Wen-Jian [1 ]
Hao, Da-Peng [1 ]
机构
[1] Qingdao Univ, Dept Radiol, Affiliated Hosp, 16 Jiangsu Rd, Qingdao 266000, Peoples R China
[2] Qingdao Univ, Hlth Management Ctr, Affiliated Hosp, 16 Jiangsu Rd, Qingdao 266000, Peoples R China
[3] Univ Hong Kong, Dept Radiol, Shenzhen Hosp, 1 Haiyuan Rd, Shenzhen 518000, Peoples R China
关键词
Tonsillar neoplasms; Tomography; X-ray computed; Radiomics; APPARENT DIFFUSION-COEFFICIENTS; CONTRAST-ENHANCED MRI; MALIGNANT-LYMPHOMA; TEXTURE ANALYSIS; HEAD; NASOPHARYNX; DIAGNOSIS; NECK;
D O I
10.1007/s00330-021-08153-9
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
Objectives Accurate preoperative differentiation between squamous cell carcinoma (SCC) and non-Hodgkin's lymphoma (NHL) in the palatine tonsil is crucial because of their different treatment. This study aimed to construct and validate a contrast-enhanced CT (CECT)-based radiomics nomogram for preoperative differentiation of SCC and NHL in the palatine tonsil. Methods This study enrolled 135 patients with a pathological diagnosis of SCC or NHL from two clinical centers, who were divided into training (n = 94; SCC = 50, NHL = 44) and external validation sets (n = 41; SCC = 22, NHL = 19). A radiomics signature was constructed from radiomics features extracted from routine CECT images and a radiomics score (Rad-score) was calculated. A clinical model was established using demographic features and CT findings. The independent clinical factors and Rad-score were combined to construct a radiomics nomogram. Performance of the clinical model, radiomics signature, and nomogram was assessed using receiver operating characteristics analysis and decision curve analysis. Results Eleven features were finally selected to construct the radiomics signature. The radiomics nomogram incorporating gender, mean CECT value, and radiomics signature showed better predictive value for differentiating SCC from NHL than the clinical model for training (AUC, 0.919 vs. 0.801, p = 0.004) and validation (AUC, 0.876 vs. 0.703, p = 0.029) sets. Decision curve analysis demonstrated that the radiomics nomogram was more clinically useful than the clinical model. Conclusions A CECT-based radiomics nomogram was constructed incorporating gender, mean CECT value, and radiomics signature. This nomogram showed favorable predictive efficacy for differentiating SCC from NHL in the palatine tonsil, and might be useful for clinical decision-making.
引用
收藏
页码:243 / 253
页数:11
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