Wei An, Tang Yu-Long, Tang Shi-Chu, Cui Xin-Wu, Zhang Chao-Xue
Department of Ultrasound, Hunan Provincial People's Hospital/The First Affiliated Hospital of Hunan Normal University, Changsha, Hunan, China.
Department of Ultrasound, The First Affiliated Hospital of Anhui Medical University, Hefei, Anhui, China.
Front Endocrinol (Lausanne). 2025 Mar 3;16:1442575. doi: 10.3389/fendo.2025.1442575. eCollection 2025.
This study aimed to explore the performance of a model based on Chinese Thyroid Imaging Reporting and Data Systems (C-TIRADS), clinical characteristics, and other ultrasound characteristics for the prediction of Bethesda III/IV thyroid nodules before fine needle aspiration (FNA).
A total of 855 thyroid nodules from 810 patients were included. All nodules underwent ultrasound examination before FNA. All nodules were categorized according to the C-TIRADS criteria and classified into two groups, Bethesda III/IV and non-III/IV thyroid nodules, using cytologic diagnosis as the gold standard. The clinical and ultrasonographic characteristics of the nodules in the two groups were compared, and independent predictors of Bethesda III/IV nodules were determined by univariate and multivariate logistic regression analyses, based on which a prediction model was constructed. The predictive efficacy of the model was compared with that of C-TIRADS alone by sensitivity, specificity, and area under the curve (AUC).
Our study found that the C-TIRADS category, homogeneous echotexture, blood flow signal present, and posterior echo unchanged were independent predictors for Bethesda III/IV thyroid nodules. Based on multiple logistic regression, a predictive model was established: Logit (p)= - 4.213 + 0.965 × homogeneous echotexture+ 1.050 × blood flow signal present + 0.473 × posterior echo unchanged+ 2.859 × C-TIRADS 3 + 2.804 × C-TIRADS 4A + 1.824 × C-TIRADS 4B + 0.919 × C-TIRADS 4C. The AUC of the model among all nodules was 0.746 (95%CI: 0.710-0.782), 0.779 (95%CI: 0.730-0.829) among nodules with a diameter (D) > 10mm, and 0.718 (95%CI: 0.667-0.769) among nodules with D ≤ 10mm, which were significantly higher than that of the C-TIRADS alone.
We developed a predictive model for Bethesda III/IV thyroid nodules that is better for nodules with D > 10mm FNA operators can choose the optimal puncture strategy based on the prediction results to improve the rate of definitive diagnosis of the first FNA of Bethesda III/IV nodules and thus reduce repeat FNA.
本研究旨在探索基于中国甲状腺影像报告和数据系统（C-TIRADS）、临床特征及其他超声特征的模型在细针穿刺活检（FNA）前预测甲状腺Bethesda III/IV类结节的性能。
纳入810例患者的855个甲状腺结节。所有结节在FNA前均接受超声检查。所有结节根据C-TIRADS标准进行分类，并以细胞诊断为金标准分为Bethesda III/IV类和非III/IV类甲状腺结节两组。比较两组结节的临床和超声特征，通过单因素和多因素逻辑回归分析确定Bethesda III/IV类结节的独立预测因素，并据此构建预测模型。通过敏感性、特异性和曲线下面积（AUC）比较该模型与单独使用C-TIRADS的预测效能。
本研究发现，C-TIRADS分类、内部回声均匀、存在血流信号及后方回声无改变是甲状腺Bethesda III/IV类结节的独立预测因素。基于多因素逻辑回归建立预测模型：Logit (p)= - 4.213 + 0.965×内部回声均匀 + 1.050×存在血流信号 + 0.473×后方回声无改变 + 2.859×C-TIRADS 3 + 2.804×C-TIRADS 4A + 1.824×C-TIRADS 4B + 0.919×C-TIRADS 4C。该模型在所有结节中的AUC为0.746（95%CI：0.710 - 0.782），直径（D）> 10mm结节中的AUC为0.779（95%CI：0.730 - 0.829），D≤10mm结节中的AUC为0.718（95%CI：0.667 - 0.769），均显著高于单独使用C-TIRADS。
我们建立了甲状腺Bethesda III/IV类结节的预测模型，对直径D > 10mm的结节效果更佳。FNA操作者可根据预测结果选择最佳穿刺策略，以提高Bethesda III/IV类结节首次FNA的确诊率，从而减少重复FNA。
