期刊
EUROPEAN RADIOLOGY
卷 25, 期 7, 页码 2153-2162出版社
SPRINGER
DOI: 10.1007/s00330-015-3621-7
关键词
Thyroid module; Ultrasound; Classification; Diagnosis; Thyroid cancer
The purpose of this study was to stratify the malignancy risk of US features, with an emphasis on nodule echogenicity. A total of 1,058 nodules of 824 consecutive patients (236 malignant and 822 benign) were included in this study. Malignancy risk of each nodule was analyzed according to US features, with an emphasis on nodule echogenecity, and was stratified into 4-tier categories. In multivariate analysis, isoechogenicity, indistinct margin, non-solid internal content, and parallel orientation were predictive of benign nodules (P < 0.002), while hypoechogenicity, marked hypoechogenicity, spiculated/microlobulated margin, solid content, nonparallel orientation (taller than wide), microcalcification, and macrocalcification were predictive of malignancy (P a parts per thousand currency signaEuro parts per thousand 0.037). Although the presence of US features associated with malignancy was significantly predictive of malignancy in hypoechoic and markedly hypoechoic nodules (P a parts per thousand currency signaEuro parts per thousand 0.004), it was not associated with malignancy in isoechoic or hyperechoic nodules. Thyroid nodules could be stratified into four categories according to the malignancy risk: benign (risk 0 %), probably benign (risk a parts per thousand currency sign 5 %), indeterminate (risk > 5 and < 50 %), and suspicion of malignancy (risk > 50 %). The US-based four-tier categorization system will be useful for predicting the risk of malignancy and decisions regarding FNA for thyroid nodules. aEuro cent No US feature was predictive of malignancy in isoechoic nodules. aEuro cent Isoechoic nodules without calcification can be included in the probably benign category. aEuro cent We suggest a four-tier categorization stratified primarily by nodule echogenecity. aEuro cent The four-tier categorization of thyroid nodules will be useful for FNA decisions.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据