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Validation of Diagnostic Performance and Interobserver Agreement of DTD-TIRADS for Diffuse Thyroid Disease on Ultrasound: A Single-Center Study. AJR Am J Roentgenol 2021; 216:1329-1334. [PMID: 33655773 DOI: 10.2214/ajr.20.23231] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
OBJECTIVE. This retrospective study aimed to investigate the capability of the already-proposed thyroid imaging reporting and data system for detecting diffuse thyroid disease (DTD-TIRADS) on ultrasound (US) by assessing interobserver agreement and diagnostic performance. MATERIALS AND METHODS. A total of 180 patients who underwent thyroid US before thyroid surgery were included. Three radiologists blinded to the pathologic and serologic data independently categorized the US features according to a four-category DTD-TIRADS classification system. On the basis of the pathologic results of thyroid parenchyma, diagnostic performance values were calculated using ROC curve analyses. Interobserver agreements of each US feature and DTD-TIRADS category among the three radiologists were also assessed. RESULTS. Of the 180 patients, 143 (79.4%) had normal thyroid parenchyma and 37 (20.6%) had diffuse thyroid disease (DTD). The areas under the ROC curve for DTD were not significantly different among the three radiologists: 0.876 (95% CI, 0.819-0.920) for radiologist 1, 0.883 (95% CI, 0.827-0.926) for radiologist 2, and 0.861 (95% CI, 0.801-0.908) for radiologist 3 (p > .05). The cutoff for the diagnosis of DTD was category III DTD-TIRADS. The sensitivity, specificity, and accuracy of DTD-TIRADS for detecting DTD were 86.5%, 81.1%, and 82.2% for radiologist 1; 86.5%, 83.2%, and 83.9% for radiologist 2; and 83.8%, 82.5%, and 82.8% for radiologist 3, respectively. Interobserver agreement of DTD-TIRADS categorization was almost perfect (κ = 0.81). CONCLUSION. DTD-TIRADS has high diagnostic performance and almost-perfect interobserver agreement. Thus, DTD-TIRADS can be considered to be an effective classification system for diagnosing DTD.
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Baek HJ, Kim DW, Ryu KH, Shin GW, Park JY, Lee YJ, Choo HJ, Park HK, Ha TK, Kim DH, Jung SJ, Park JS, Moon SH, Ahn KJ. Thyroid Imaging Reporting and Data System for Detecting Diffuse Thyroid Disease on Ultrasonography: A Single-Center Study. Front Endocrinol (Lausanne) 2019; 10:776. [PMID: 31781043 PMCID: PMC6857518 DOI: 10.3389/fendo.2019.00776] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/26/2019] [Accepted: 10/24/2019] [Indexed: 11/17/2022] Open
Abstract
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.
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Affiliation(s)
- Hye Jin Baek
- Department of Radiology, Gyeongsang National University Changwon Hospital, Gyeongsang National University School of Medicine, Changwon, South Korea
| | - Dong Wook Kim
- Department of Radiology, Busan Paik Hospital, Inje University College of Medicine, Busan, South Korea
- *Correspondence: Dong Wook Kim
| | - Kyeong Hwa Ryu
- Department of Radiology, Gyeongsang National University Changwon Hospital, Gyeongsang National University School of Medicine, Changwon, South Korea
| | - Gi Won Shin
- Department of Radiology, Busan Paik Hospital, Inje University College of Medicine, Busan, South Korea
| | - Jin Young Park
- Department of Radiology, Busan Paik Hospital, Inje University College of Medicine, Busan, South Korea
| | - Yoo Jin Lee
- Department of Radiology, Busan Paik Hospital, Inje University College of Medicine, Busan, South Korea
| | - Hye Jung Choo
- Department of Radiology, Busan Paik Hospital, Inje University College of Medicine, Busan, South Korea
| | - Ha Kyoung Park
- Department of General Surgery, Busan Paik Hospital, Inje University College of Medicine, Busan, South Korea
| | - Tae Kwun Ha
- Department of General Surgery, Busan Paik Hospital, Inje University College of Medicine, Busan, South Korea
| | - Do Hun Kim
- Department of Otorhinolaryngology-Head and Neck Surgery, Busan Paik Hospital, Inje University College of Medicine, Busan, South Korea
| | - Soo Jin Jung
- Department of Pathology, Busan Paik Hospital, Inje University College of Medicine, Busan, South Korea
| | - Ji Sun Park
- Department of Nuclear Medicine, Busan Paik Hospital, Inje University College of Medicine, Busan, South Korea
| | - Sung Ho Moon
- Department of Anesthesiology and Pain Medicine, Busan Paik Hospital, Inje University College of Medicine, Busan, South Korea
| | - Ki Jung Ahn
- Department of Radiation Oncology, Busan Paik Hospital, Inje University College of Medicine, Busan, South Korea
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