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Updated: Jul 16, 2025

A Swin Transformer-Based Model for Thyroid Nodule Detection in Ultrasound Images
Published on: April 21, 2023
Diagnostic performance of ultrasound risk stratification systems on thyroid nodules cytologically classified as
Zhichao Xing1,2, Yuxuan Qiu3, Jingqiang Zhu1
1Center of Thyroid and Parathyroid Surgery, West China Hospital, Sichuan University, Chengdu, China.
Purpose:
Ultrasound (US) risk stratification systems (RSSs) are increasingly being utilized for the optimal management of thyroid nodules, including those with indeterminate cytology. The goal of this study was to evaluate the category-based diagnostic performance of US RSSs in identifying malignancy in indeterminate nodules.
Methods:
This systematic review and meta-analysis was registered on PROSPERO (CRD42021266195). PubMed, EMBASE, and Web of Science were searched through December 1, 2022. Original articles reporting data on the performance of US RSSs for indeterminate nodules were included. The numbers of nodules classified as true negative, true positive, false negative, and false positive were extracted.
Results:
Thirty-three studies evaluating 7,225 indeterminate thyroid nodules were included. The diagnostic accuracy was quantitatively synthesized using a Bayesian bivariate model based on the integrated nested Laplace approximation in R. For the intermediate- to high-risk category, the sensitivity levels of the American College of Radiology, the American Thyroid Association, the European Thyroid Association, the Korean Thyroid Association/Korean Society of Thyroid Radiology, and Kwak et al. were found to be 0.80, 0.72, 0.76, 0.96, and 0.97, respectively. The corresponding specificity measurements were 0.36, 0.50, 0.49, 0.28, and 0.17. Furthermore, for the high-risk category, the sensitivity values were 0.40, 0.46, 0.55, 0.47, and 0.10, while the specificity levels were 0.91, 0.90, 0.71, 0.91, and 0.99, respectively.
Conclusion:
The overall diagnostic performance of the US RSSs was moderate in the differentiation of indeterminate nodules.
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