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Article Open Access

Optimized algorithm in solid thyroid nodule elastography

  • Authors:
    • Hao Wu
    • Qin Chen
    • Yingxian Liu
    • Jidong Chen
    • Wanyue Deng
  • View Affiliations / Copyright

    Affiliations: Ultrasound Department, Sichuan Academy of Medical Sciences and Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, Sichuan 610072, P.R. China, Ultrasound Department, Emergency General Hospital, Beijing 100028, P.R. China
    Copyright: © Wu et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
  • Article Number: 248
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    Published online on: September 16, 2020
       https://doi.org/10.3892/ol.2020.12111
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Abstract

The present study aimed to evaluate the reproducibility and accuracy of the optimized algorithm of shear‑wave elastography (SWE) in diagnosing solid thyroid nodules. Two hundred and sixty‑three solid thyroid nodules in 248 patients who underwent conventional ultrasound and SWE, respectively, by two operators were scheduled for fine‑needle aspiration or surgery. Elasticity indices of the mean, minimum and maximum of nodules (EI) and thyroid parenchyma (EInorm) were measured respectively in the same frame of elastographic images for three times by both operators. The intraobserver and interobserver reproducibility of the optimized algorithm were assessed by intraclass correlation coefficients (ICC). Diagnostic performance of the optimized algorithm was compared with that of conventional SWE measurements by receiver‑operating characteristic (ROC) curves. Among a total of 243 nodules included, 121 were benign nodules and 122 were papillary thyroid carcinoma (PTC). Intraobserver reliability for EId and EIr was nearly perfect (ICC>0.80). Interobserver agreement for MEANd, MAXd, MEANr and MAXr was nearly perfect (ICC>0.80). MAXd had the largest areas under the ROC curve which was 0.82. Compared with conventional SWE, the optimized algorithm of SWE shows better reproducibility and performance in diagnosing solid thyroid nodules.
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Copy and paste a formatted citation
Spandidos Publications style
Wu H, Chen Q, Liu Y, Chen J and Deng W: Optimized algorithm in solid thyroid nodule elastography. Oncol Lett 20: 248, 2020.
APA
Wu, H., Chen, Q., Liu, Y., Chen, J., & Deng, W. (2020). Optimized algorithm in solid thyroid nodule elastography. Oncology Letters, 20, 248. https://doi.org/10.3892/ol.2020.12111
MLA
Wu, H., Chen, Q., Liu, Y., Chen, J., Deng, W."Optimized algorithm in solid thyroid nodule elastography". Oncology Letters 20.5 (2020): 248.
Chicago
Wu, H., Chen, Q., Liu, Y., Chen, J., Deng, W."Optimized algorithm in solid thyroid nodule elastography". Oncology Letters 20, no. 5 (2020): 248. https://doi.org/10.3892/ol.2020.12111
Copy and paste a formatted citation
x
Spandidos Publications style
Wu H, Chen Q, Liu Y, Chen J and Deng W: Optimized algorithm in solid thyroid nodule elastography. Oncol Lett 20: 248, 2020.
APA
Wu, H., Chen, Q., Liu, Y., Chen, J., & Deng, W. (2020). Optimized algorithm in solid thyroid nodule elastography. Oncology Letters, 20, 248. https://doi.org/10.3892/ol.2020.12111
MLA
Wu, H., Chen, Q., Liu, Y., Chen, J., Deng, W."Optimized algorithm in solid thyroid nodule elastography". Oncology Letters 20.5 (2020): 248.
Chicago
Wu, H., Chen, Q., Liu, Y., Chen, J., Deng, W."Optimized algorithm in solid thyroid nodule elastography". Oncology Letters 20, no. 5 (2020): 248. https://doi.org/10.3892/ol.2020.12111
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