Thyroid imaging reporting and data system combined with Bethesda classification in qualitative thyroid nodule diagnosis

甲状腺影像报告和数据系统结合贝塞斯达分类法在甲状腺结节定性诊断中的应用

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Abstract

OBJECTIVE: We aimed to investigate the value of the combined use of high-resolution ultrasound thyroid imaging reporting and data system (TI-RADS) classification and thyroid fine needle aspiration cytology (Bethesda classification) for the qualitative diagnosis of benign and malignant thyroid nodules. METHODS: We enrolled 295 patients with 327 thyroid nodules who were scheduled to undergo thyroid nodule surgery. Before surgery, all the patients underwent ultrasound and scoring with the TI-RADS classification, along with thyroid fine needle biopsy cytology under ultrasound guidance (US-FNAC) and scoring with the Bethesda classification. After surgery, the TI-RADS and Bethesda classification scores, separately and in combination, were compared with the postoperative pathological results in terms of the differential diagnosis of thyroid nodules. RESULTS: TI-RADS classification score 4 exhibited the highest diagnostic value for thyroid cancer; the sensitivity, specificity, and accuracy were 92.7%, 70.7%, and 87.1%, respectively, whereas the Kappa and receiver-operating characteristics (ROC) values were 0.651 and 0.817, respectively. Moreover, Bethesda classification score 3 exhibited the highest diagnostic value for thyroid cancer; the sensitivity, specificity, and accuracy were 90.0%, 94.3%, and 91.1%, respectively, whereas the Kappa and ROC values were 0.78 and 0.914, respectively. With regard to the combined diagnostic method, a score of 7 exhibited the highest diagnostic value for thyroid cancer; the sensitivity, specificity, and accuracy were 97.3%, 92.0%, and 95.9%, respectively, whereas the Kappa and ROC values were 0.893 and 0.946, respectively. CONCLUSION: The combination of high-resolution ultrasonography TI-RADS classification and US-FNAC (Bethesda classification) can improve the accuracy of malignant thyroid nodules diagnosis.

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