1. Predicting malignancy in thyroid nodules based on conventional ultrasound and elastography: the value of predictive models in a multi-center study
- Author
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Ying Zhang, Qiong-Yi Huang, Chang-Jun Wu, Qi Chen, Chun-Juan Xia, Bo-Ji Liu, Yun-Yun Liu, Yi-Feng Zhang, and Hui-Xiong Xu
- Subjects
Endocrinology ,Endocrinology, Diabetes and Metabolism - Abstract
Background: This study aimed to establish predictive models based on features of Conventional Ultrasound (CUS) and elastography in a multi-center study to determine appropriate preoperative diagnosis of malignancy in thyroid nodules with different risk stratification based on 2017 Thyroid Imaging Reporting and Data System by the American College of Radiology (ACR TI-RADS) guidelines.Methods: Five hundred forty-eight thyroid nodules from three centers pathologically confirmed by the cytology or histology were retrospectively enrolled in the study, which were examined by CUS and elastography before fine needle aspiration (FNA) and surgery. Characteristics of CUS of thyroid nodules were reviewed according to 2017 ACR TI-RADS. Binary logistic regression analysis was used to develop the prediction models based on the different risk stratification of CUS features and elastography which were statistically significant. Values of predictive models were evaluated regarding the discrimination and calibration.Results: Binary logistic regression showed that patients’ age, taller-than-wider, lobulated or irregular boundary, extra-thyroid extension, microcalcification and the elastic parameter of Virtual touch tissue imaging quantification (VTIQ) max were independent predictors for thyroid malignancy (p0.05).Conclusions: Predictive models combined CUS and elastography features would aid clinicians to make appropriate preoperative diagnosis of thyroid nodules among different risk stratification. The elastography parameter of VTIQ max has the priority in distinguishing thyroid malignancy with moderately suspicious (ACR TR4).
- Published
- 2022