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Contrast-enhanced ultrasound–based nomogram for predicting malignant involvements among sonographically indeterminate/suspicious cervical lymph nodes in patients with differentiated thyroid carcinoma

列线图 医学 放射科 接收机工作特性 淋巴结 超声波 置信区间 甲状腺癌 超声造影 甲状腺球蛋白 单变量分析 转移 甲状腺 多元分析 癌症 肿瘤科 内科学
作者
Qianqian Guo,Chao Sun,Qing Chang,Yong Wang,Yu Chen,Qian Wang,Zhengjiang Li,Lijuan Niu
出处
期刊:Ultrasound in Medicine and Biology [Elsevier BV]
卷期号:48 (8): 1579-1589 被引量:9
标识
DOI:10.1016/j.ultrasmedbio.2022.04.004
摘要

This prospective study was aimed at assessing the value of nomograms based on conventional and contrast-enhanced ultrasound (CEUS) features in the pre-operative diagnosis of sonographically indeterminate/suspicious lymph node metastasis (LNM) in patients with differentiated thyroid carcinoma (DTC). A total of 72 cervical LNs from 47 patients with DTC from January to June 2018 were included in the primary data set, and 30 LNs from 15 patients with DTC from July to August 2018 were included in the external validation data set. The LNs of the included patients were preoperatively evaluated by conventional ultrasound (US) and CEUS. Each included LN was labeled by puncture localization with carbon nanoparticle suspension injection (Canalin) under US guidance and dissected separately to ensure the one-to-one correspondence between ultrasonic features and pathology status. Univariate logistic regression analysis was used to identify risk factors for LNM. A nomogram was used to construct a prediction model for cervical metastatic LNs. Round shape, absence of hilar structure, peripheral or mixed blood flow and centripetal or mass enhancement were risk factors for lymph node metastases. The area under the receiver operating characteristic curve of the nomogram model based on conventional US and CEUS features was 0.93 (95% confidence interval: 0.872-0.985), which was superior to that of the nomogram based on conventional US features(0.85, 95% confidence interval: 0.707-0.989). CEUS features can provide incremental benefit in the diagnosis of LNM among DTC cohorts. Nomograms based on conventional US and CEUS features can predict LN status with high accuracy.

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