Enhanced CT radiomics combined with deep learning algorithm for predicting cervical lymph node metastasis of papillary thyroid carcinoma
10.13929/j.issn.1672-8475.2025.03.010
- VernacularTitle:增强CT影像组学结合深度学习算法预测甲状腺乳头状癌颈部淋巴结转移
- Author:
Yuanyuan YE
1
;
Kewu HE
1
;
Qifeng LIU
1
;
Wenmin HONG
1
Author Information
1. 安徽医科大学第三附属医院(合肥市第一人民医院)影像中心,安徽 合肥 230000
- Publication Type:Journal Article
- Keywords:
thyroid neoplasms;
lymphatic metastasis;
tomography,X-ray computed;
radiomics;
deep learning
- From:
Chinese Journal of Interventional Imaging and Therapy
2025;22(3):196-200
- CountryChina
- Language:Chinese
-
Abstract:
Objective To observe the value of enhanced CT radiomics combined with deep learning(DL)algorithm for predicting cervical lymph node metastasis(CLNM)of papillary thyroid carcinoma(PTC).Methods Totally 100 patients with single PTC were retrospectively enrolled and divided into training set(n=70)and test set(n=30)at the ratio of 7∶3.The optimal radiomics features and DL features of lesions were extracted and screened based on arterial phase cervical CT,and the radiomics score(Radscore)and DL score(Deepscore)were calculated to construct radiomics model and DL model,respectively.Clinical data,routine CT findings,Radscore and Deepscore were enrolled in multivariate logistic regression analysis to screen the independent predictors of PTC CLNM,and a combined model was then constructed.The receiver operating characteristic curve was plotted,and the area under the curve(AUC)was calculated to evaluate the efficacy of each model for predicting PTC CLNM.Results Thirteen optimal radiomics features and 12 DL features were selected.Radscore(OR=1.698,P=0.002)and Deepscore(OR=1.872,P=0.021)were both independent predictors of PTC CLNM.The AUC of radiomics mode,l DL model and combined model for predicting PTC CLNM was 0.775,0.876 and 0.880 in training set,which in test set was 0.739,0.776 and 0.789,respectively.In training set,the prediction efficacy of combined model was better than that of radiomics model(Z=2.551,P=0.011).Conclusion Combined with DL algorithm could effectively increase the efficacy of enhanced CT radiomics for predict PTC CLNM.
