Thyroid Imaging Reporting and Data System for Detecting Diffuse Thyroid Disease on Ultrasonography: A Single-Center Study

• Published in: Frontiers in endocrinology (Lausanne) Vol. 10; p. 776
• Main Authors: Baek, Hye Jin, Kim, Dong Wook, Ryu, Kyeong Hwa, Shin, Gi Won, Park, Jin Young, Lee, Yoo Jin, Choo, Hye Jung, Park, Ha Kyoung, Ha, Tae Kwun, Kim, Do Hun, Jung, Soo Jin, Park, Ji Sun, Moon, Sung Ho, Ahn, Ki Jung
• Format: Journal Article
• Language: English
• Published: Frontiers Media S.A 08.11.2019
• Subjects: autoimmune thyroiditis; diffuse thyroid disease; Endocrinology; thyroid; TIRADS; ultrasonography
• DOI: 10.3389/fendo.2019.00776
• ISSN: 1664-2392

Objective: This study aimed to compare the ultrasonography (US) features of diffuse thyroid disease (DTD) and normal thyroid parenchyma (NTP), and to propose a structured imaging reporting system for detecting DTD. Methods: This retrospective study assessed the findings for 270 consecutive patients who underwent thyroid US before thyroid surgery. The following US data were analyzed: DTD-specific features, parenchymal echotexture and echogenicity, anteroposterior diameter, glandular margin, and parenchymal vascularity. Univariate and multivariate analyses with generalized estimating equations were performed to investigate the relationship between US features and DTD. The fitted probability of DTD was analyzed by using a regression equation. Results: Of the 270 patients, there were NTP ( n = 193), Hashimoto thyroiditis ( n = 24), non-Hashimoto lymphocytic thyroiditis ( n = 51), Graves' disease ( n = 1), and diffuse hyperplasia ( n = 1). The following US features were significantly associated with DTD: decreased or increased parenchymal echogenicity, coarse parenchymal echotexture, increased anteroposterior diameter, lobulated glandular margin, and increased parenchymal vascularity. Of these, coarse parenchymal echotexture was the most significant independent predictor of DTD. The numbers of abnormal US features were positively correlated with the fitted probability and risk of DTD. The diagnostic indices were highest when the chosen cut-off criterion was category III with the largest Az value (0.867, 95% confidence interval: 0.820–0.905), yielding a sensitivity of 68.8%, specificity of 92.2%, positive predictive value of 77.9%, negative predictive value of 88.1%, and accuracy of 85.6% ( p < 0.001). Conclusions: Our sonographic reporting and data system may be useful for detecting DTD.