基于TI-RADS分类和CDFI的列线图鉴别诊断甲状腺结节良恶性的临床价值  

Clinical value of nomogram model based on TI-RADS category and CDFI in differentiating benign and malignant thyroid nodules

作　　者：彭欣雯 沈玥 PENG Xinwen;SHEN Yue(Department of Ultrasound,Changhai Hospital,the First Affiliated Hospital of Naval Medical University,Shanghai 200433,China)

机构地区：[1]海军军医大学第一附属医院长海医院超声科,上海200433

出　　处：《临床超声医学杂志》2025年第3期243-247,共5页Journal of Clinical Ultrasound in Medicine

摘　　要：目的基于TI-RADS分类和CDFI构建鉴别诊断甲状腺结节良恶性的列线图模型,探讨其临床应用价值。方法选取我院经病理确诊的甲状腺良性结节患者90例(良性组)和恶性结节患者70例(恶性组),应用二维超声观察结节位置、形态、结构、纵横比、边界、晕环厚度、内部回声、后方回声及钙化情况,并进行TI-RADS分类;CDFI观察结节血流情况并进行分级,比较两组上述检查结果的差异。采用Logistic回归分析筛选鉴别诊断甲状腺结节良恶性的独立影响因素,并基于上述因素构建列线图模型。绘制受试者工作特征(ROC)曲线分析列线图模型鉴别甲状腺结节良恶性的诊断效能;校准曲线分析列线图模型的校准度。结果两组TI-RADS分类>3类、晕环厚度≥2 mm、血流分级≥Ⅱ级占比比较差异均有统计学意义(均P<0.05);两组后方回声衰减比较差异无统计学意义。Logistic回归分析显示晕环厚度、血流分级及TI-RADS分类均为鉴别诊断甲状腺结节良恶性的独立危险因素(均P<0.05),基于上述因素构建列线图模型。ROC曲线分析显示,列线图模型鉴别诊断甲状腺结节良恶性的曲线下面积为0.891,灵敏度为91.73%,特异度为84.33%;校准曲线分析显示,列线图模型的校准度较好。结论基于TI-RADS分类和CDFI构建的列线图模型在鉴别诊断甲状腺结节良恶性中具有较高的临床应用价值。Objective To establish nomogram model based on TI-RADS category and CDFI in differentiating benign and malignant thyroid nodules,and to explore its clinical application value.Methods A total of 90 patients with benign thyroid nodules(benign group)and 70 patients with malignant thyroid nodules(malignant group)confirmed by pathology in our hospital were enrolled.Two-dimensional ultrasound was used to observe nodule location,shape,structure,aspect ratio,boundary,halo thickness,internal echogenicity,posterior echo attenuation,and calcification,and nodules were classified according to TI-RADS category.CDFI was used to observe the blood flow and classify it into grades.The differences in these parameters between the two groups were compared.Logistic regression analysis was performed to identify independent influencing factors for differentiating benign and malignant thyroid nodules,and a nomogram model was constructed based on these factors.Receiver operating characteristic(ROC)curve was drawn to evaluate the diagnostic performance of the nomogram model,and calibration curve was drawn to assess the calibration of the model.Results There were significant differences in the proportion of TI-RADS category>3,halo thickness≥2 mm,and blood flow grade≥Ⅱbetween the two groups(all P<0.05).No significant difference was found in posterior echo attenuation between the two groups.Logistic regression analysis showed that halo thickness,blood flow grade,and TI-RADS category were independent risk factors for differentiating benign and malignant thyroid nodules(all P<0.05).The nomogram model was constructed based on these factors.ROC curve analysis showed that the area under the curve of the nomogram model for differentiating benign and malignant thyroid nodules was 0.891,with a sensitivity of 91.73%and a specificity of 84.33%.Calibration curve analysis showed good calibration of the nomogram model.Conclusion The nomogram model based on TI-RADS category and CDFI has high clinical value in differentiating benign and malignant thyr

关 键 词：超声检查 甲状腺结节 良恶性 列线图模型 鉴别诊断 

分 类 号：R445.1[医药卫生—影像医学与核医学] R736.1[医药卫生—诊断学]