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| Differential Diagnosis of Papillary Thyroid Carcinoma by Superb Microvascular Imaging Combined with Shear Wave Elastography |
| LI Jing |
| First-author's address: Tai’an Maternity and Child Health Hospital, Shandong Province, Tai’an 271000, China |
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Abstract Objective: To evaluate the diagnostic value of combining quantitative parameters of shear wave elastography (SWE) and superb microvascular imaging (SMI) in differentiating papillary thyroid carcinoma (PTC). Method: A total of 88 patients with thyroid nodules who underwent thyroidectomy in the Surgery Department of Tai’an Maternity and Child Health Hospital from January 2020 to October 2022 were selected for this study. All patients received SMI and SWE examination before surgery. The patients were divided into PTC group (n=26) and benign group (n=62) according to the pathological results after surgery. Based on the mean value (Emean), minimum value (Emin), maximum value (Emax), dispersion (SD) of SWE elastic index and blood flow distribution pattern of SMI, the sensitivity, specificity and accuracy of SWE, SMI and combined diagnosis of PTC were analyzed. Result: Emean, Emin, Emax and SD in PTC group were significantly higher than those in benign group (P<0.05). ROC curve analysis showed that SD had the highest AUC in diagnosing PTC, and 53.80% sensitivity, 100% specificity and 86.36% accuracy could be obtained at the cut-off value of 3.52 kPa. SMI detection showed that the blood flow distribution pattern of nodules in benign group was mainly classified as type Ⅱ and type Ⅳ, while nodules in PTC group were mainly classified as type Ⅲ. The sensitivity was 65.38%, specificity was 91.94% and accuracy was 84.09% of SMI in diagnosing PTC alone. The sensitivity was 88.46%, specificity was 93.55% and accuracy was 92.05% of SMI combined with SWE. Conclusion: The combination of SWE quantitative parameters and SMI technology can improve the sensitivity, specificity and accuracy of the diagnosis of PTC, and has good clinical application value.
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Received: 22 February 2023
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