Contrast Enhancement Ultrasound Improves Diagnostic Accuracy for Thyroid Nodules: A Prospective Multi-Center Study

甲状腺结节 医学 接收机工作特性 超声造影 逻辑回归 放射科 超声波 恶性肿瘤 甲状腺 诊断准确性 对比度(视觉) 核医学 内科学 人工智能 计算机科学
作者
Jianming Li,Jianping Dou,Huarong Li,Xiao Fan,Jie Yu,Mingxing Xie,Ping Zhou,Lei Liang,Guangxi Zhou,Ying Che,Cun Liu,Zhibin Cong,Fangyi Liu,Zhiyu Han,Ping Liang
出处
期刊:Journal of the Endocrine Society [Endocrine Society]
卷期号:8 (1)
标识
DOI:10.1210/jendso/bvad145
摘要

Abstract Objective To evaluate potential improvements in the diagnosis of thyroid nodules when conventional ultrasound (US) is combined with contrast-enhanced US (CEUS). Methods We recruited 515 participants with 323 malignant and 192 benign nodules, who underwent both US and CEUS examinations at 8 different medical centers in China between October 2020 and October 2021. We assessed the malignancy of thyroid nodules in US using the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TIRADS). Diagnostic criteria for US and US + CEUS were developed by investigators based on evaluations of sonographic features. Using multivariate logistic regression and receiver operating characteristic (ROC) analysis, we compared diagnostic performance between the 2 methods based on criteria identified by investigators and via statistical models. Results On the basis of diagnostic criteria identified by investigators, we measured statistically significant differences in area under the curve (AUC) values between ACR TIRADS (0.83) and CEUS TIRADS (0.87; P < .001). On the basis of diagnostic regression models, we found statistically significant differences in AUC values between US (0.76) and US + CEUS (0.84; P = .001). Models based on US + CEUS outperformed those based on US alone (Akaike information criterion of 347.7 and significant improvement in integrated discrimination). These results were confirmed by similar analyses applied to a validation cohort. Conclusion The accuracy of conventional US for differentiating between benign and malignant thyroid nodules can be improved by combining this approach with CEUS.
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