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

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.

journal_name

Medicine (Baltimore)

journal_title

Medicine

authors

Tan H,Li Z,Li N,Qian J,Fan F,Zhong H,Feng J,Xu H,Li Z

doi

10.1097/MD.0000000000018320

subject

Has Abstract

pub_date

2019-12-01 00:00:00

pages

e18320

issue

eissn

0025-7974

issn

1536-5964

pii

00005792-201912130-00060

journal_volume

pub_type

杂志文章,多中心研究

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