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. 2016 Apr;26(4):562-72.
doi: 10.1089/thy.2015.0460. Epub 2016 Feb 9.

Thyroid Imaging Reporting and Data System Risk Stratification of Thyroid Nodules: Categorization Based on Solidity and Echogenicity

Affiliations

Thyroid Imaging Reporting and Data System Risk Stratification of Thyroid Nodules: Categorization Based on Solidity and Echogenicity

Dong Gyu Na et al. Thyroid. 2016 Apr.

Abstract

Background: Although ultrasonography (US) has an essential role in assessing the malignancy risk of thyroid nodules, a malignancy risk-stratification system has not been established. The purpose of this study was to develop a clinically feasible US risk-stratification system--the Thyroid Imaging Reporting and Data System (TIRADS)--primarily based on the solidity and echogenicity of thyroid nodules.

Methods: From January 2010 to May 2011, a total of consecutive 2000 thyroid nodules (≥ 1 cm) with final diagnoses were enrolled from the database of low and high cancer volume institutions (1000 nodules from each institution). For the development of TIRADS, the type and predictive value of US predictors in the groups categorized by solidity and echogenicity were analyzed, and the US predictors were integrated and categorized according to the malignancy risk.

Results: The suspicious US features of microcalcification, taller than wide shape, and spiculated/microlobulated margin were independently predictive of malignancy in the solid or hypoechoic nodule group (p < 0.001, respectively). Meanwhile, only microcalcification was independently predictive of malignancy in the partially cystic nodule group (p = 0.006), and microcalcification and spiculated/microlobulated margin were independently predictive of malignancy in the iso- and hyperechoic nodule group (p = 0.002 and p = 0.015, respectively). Although the presence of any suspicious US features had a high malignancy risk in the group of solid hypoechoic nodules, it had an intermediate malignancy risk in the group of partially cystic or iso- and hyperechoic nodules. The malignancy risk of thyroid nodules was stratified into five TIRADS categories by integrating the type and predictive values of US predictors based on solidity and echogenicity.

Conclusion: The malignancy risk of thyroid nodules can be stratified by TIRADS according to US patterns by combining solidity, echogenicity, and suspicious US features. The proposed risk-stratification system based on solidity and echogenicity will be useful for risk stratification and management decision of thyroid nodules.

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