微血流成像模式鉴别甲状腺结节良恶性的价值

目的 评价微血流成像(MFI)对甲状腺结节良恶性的鉴别诊断价值。方法 选取2020年5至12月在中国人民解放军总医院第一医学中心行常规超声、MFI和超声造影检查并获得明确组织学或细胞学病理结果的甲状腺结节患者50例,回顾性分析患者的临床资料和超声声像图,构建二分类Logistic回归模型,评价该模型预测甲状腺结节良恶性的能力。结果 Logistic回归分析显示成分和“S-W-C征”是预测恶性甲状腺结节的独立危险因素。Logistic回归模型对甲状腺结节良恶性预测的灵敏度、特异度、约登指数分别为73.33%、80.00%、0.53,受试者工作特征曲线下面积为0.799(95%CI=0.662~0.899)。结论 MFI模式有助于鉴别甲状腺结节良恶性,具有潜在应用价值。

Application of Micro-flow Imaging in the Differentiation of Benign and Malignant Thyroid Nodules

Objective To evaluate the performance of micro-flow imaging(MFI)in the differential diagnosis of benign and malignant thyroid nodules. Methods Totally 50 patients with thyroid nodules examined by conventional ultrasound,MFI,and contrast-enhanced ultrasound and confirmed by histological or cytological pathology in the First Medical Center of Chinese PLA General Hospital from May to December in 2020 were enrolled in the study.The clinical data and ultrasound images were retrospectively analyzed.A binary logistic regression model was established to evaluate the performance of the model in predicting benign and malignant thyroid nodules. Results Logistic regression showed that composition and “S-W-C” sign were independent risk factors for predicting malignant thyroid nodule.The sensitivity,specificity,and Youden index of the logistic regression model were 73.33%,80.00%,and 0.53,respectively,and the area under receiver operating characteristic curve was 0.799(95%CI=0.662-0.899). Conclusion MFI facilitates the differential diagnosis of benign and malignant thyroid nodules and has the potential to be applied in the future.