摘要目的:建立基于弹性成像参数与超声图像特征的列线图模型，评估其在甲状腺乳头状癌（papillary thyroid carcinoma, PTC）中央区淋巴结转移（central lymph node metastasis, CLNM）中的预测价值。方法:回顾性分析2019年1月至2021年12月浙江大学附属金华医院超声医学科接受检查的甲状腺手术患者，其中168例PTC患者为研究组，另选取同期接受甲状腺手术检查的150例为验证组，根据研究组术后病理检查结果分为两组，CLNM组64例（38.10%），非CLNM组104例（61.90%）。临床资料包括性别、年龄、超声弹性成像参数（弹性比值、蓝色面积比值）、超声检查指标（结节直径、结节数目、内部回声、边界、边缘、纵横比、微钙化、被膜侵犯）。采用二元Logistic回归分析探究PTC患者发生CLNM的影响因素，并建立基于弹性成像参数与超声图像特征的列线图模型。绘制列线图模型预测PTC患者发生CLNM的受试者工作特征曲线（receiver operating characteristic curve, ROC）。结果:CLNM组和非CLNM组结节直径、边缘、微钙化、被膜侵犯、蓝色面积比值、弹性比值差异有统计学意义（ P<0.05），其中CLNM组结节直径多≥10 mm、边缘不光整、纵横比<1，往往存在微钙化及被膜侵犯。Logistic回归分析，结节直径、被膜侵犯、蓝色面积比值及弹性比值均是发生CLNM的危险因素（ P<0.05）。联合检测曲线下面积（area under the curve，AUC）为0.857（0.777～0.937），敏感度、特异度分别为78.1%、86.5%，其中AUC、敏感度明显高于各指标的单独检测（ P<0.05）。研究组中，超声参数预测模型预测CLNM的敏感度、特异度分别为81.25%（52/64）、84.62%（88/104）；验证组中，超声参数预测模型预测CLNM的敏感度、特异度分别为79.17%（38/48）、85.29%（87/102）。 结论:弹性成像参数（蓝色面积比值、弹性比值）与超声图像特征（结节直径、被膜侵犯）均为PTC患者发生CLNM的影响因素，基于以上4种指标联合预测具有良好的应用价值。

abstractsObjective:To establish a nomogram model based on elastic imaging parameters and ultrasound image features, and evaluate its predictive value in central lymph node metastasis (CLNM) in papillary thyroid carcinoma (PTC) .Methods:The clinical data of 168 patients (the research group) with papillary thyroid carcinoma who underwent thyroid surgery in our hospital from Jan. 2019 to Dec. 2021 were retrospectively collected, including gender, age, ultrasound elastography parameters (elasticity ratio, blue area ratio), and ultrasound examination indicators (nodule diameter, nodule number, internal echo, border, edge, aspect ratio, microcalcification, capsule invasion). Another 150 patients who underwent thyroid surgery in our hospital during the same period were selected as the validation group.According to the results of postoperative pathological examination, the the research group were divided into two groups: 64 cases (38.10%) of CLNM and 104 cases (61.90%) of non-CLNM. Binary logistic regression analysis was used to explore the influencing factors of CLNM in PTC patients, and a nomogram model based on elastic imaging parameters and ultrasound image features was established. The nomogram model was drawn to predict the receiver operating characteristic (ROC) curve of CLNM in PTC patients.Results:There were statistically significant differences in nodule diameter, edge, microcalcification, capsule invasion, blue area ratio, and elasticity ratio ( P<0.05). Most of the nodules in the CLNM group were ≥10 mm in diameter, with uneven margins, an aspect ratio of <1, microcalcifications and capsular invasion. Logistic regression analysis showed that nodule diameter, capsule invasion, blue area ratio and elastic ratio were risk factors for CLNM ( P<0.05). The AUC of the combined detection was 0.857 (0.777-0.937), and the sensitivity and specificity were 78.1% and 86.5%, respectively, and the AUC and sensitivity were significantly higher than the individual detection of each index ( P<0.05). In the research group, the sensitivity and specificity of the ultrasound parameter prediction model in predicting CLNM were 81.25% (52/64) and 84.62% (88/104), respectively. In the validation group, the sensitivity and specificity of the ultrasound parameter prediction model in predicting CLNM were 79.17% (38/48) and 85.29% (87/102), respectively. Conclusion:Elastography parameters (blue area ratio, elasticity ratio) and ultrasound image features (nodule diameter, capsular invasion) are the influencing factors of CLNM in PTC patients, and the combined prediction based on the above four indicators has good application value.