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- Title
MRI-based radiomics analysis for preoperative evaluation of lymph node metastasis in hypopharyngeal squamous cell carcinoma.
- Authors
Shanhong Lu; Hang Ling; Juan Chen; Lei Tan; Yan Gao; Huayu Li; Pingqing Tan; Donghai Huang; Xin Zhang; Yong Liu; Yitao Mao; Yuanzheng Qiu
- Abstract
Objective: To investigate the role of pre-treatment magnetic resonance imaging (MRI) radiomics for the preoperative prediction of lymph node (LN) metastasis in patients with hypopharyngeal squamous cell carcinoma (HPSCC). Methods: A total of 155 patients with HPSCC were eligibly enrolled from single institution. Radiomics features were extracted from contrast-enhanced axial T-1 weighted (CE-T1WI) sequence. Themost relevant features of LNmetastasiswere selected by the least absolute shrinkage and selection operator (LASSO) method. Univariate andmultivariate logistic regression analysis was adopted to determine the independent clinical risk factors. Three models were constructed to predict the LN metastasis status: one using radiomics only, one using clinical factors only, and the other one combined radiomics and clinical factors. Receiver operating characteristic (ROC) curves and calibration curve were used to evaluate the discrimination and the accuracy of the models, respectively. The performances were tested by an internal validation cohort (n=47). The clinical utility of the models was assessed by decision curve analysis. Results: The nomogramconsisted of radiomics scores and theMRI-reported LN status showed satisfactory discrimination in the training and validation cohorts with AUCs of 0.906 (95% CI, 0.840 to 0.972) and 0.853 (95% CI, 0.739 to 0.966), respectively. The nomogram, i.e., the combined model, outperformed the radiomics and MRI-reported LN status in both discrimination and clinical usefulness. Conclusions: The MRI-based radiomics nomogram holds promise for individual and non-invasive prediction of LN metastasis in patients with HPSCC.
- Subjects
LYMPHATIC metastasis; RADIOMICS; SQUAMOUS cell carcinoma; FEATURE extraction; MAGNETIC resonance imaging
- Publication
Frontiers in Oncology, 2022, Vol 12, p1
- ISSN
2234-943X
- Publication type
Article
- DOI
10.3389/fonc.2022.936040