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Updated: Nov 15, 2025

Author Spotlight: Integrating Ultrasound Imaging with Biochemical Markers for Thyroid Disease Diagnosis
Published on: February 9, 2024
Validation of Diagnostic Performance and Interobserver Agreement of DTD-TIRADS for Diffuse Thyroid Disease on
Hye Jin Baek1,2, Kyeong Hwa Ryu1, Hyo Jung An3
1Department of Radiology, Gyeongsang National University School of Medicine and Gyeongsang National University Changwon Hospital, Changwon, Republic of Korea.
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.

