scholarly journals Meta-Analysis of Contrast Enhanced Ultrasound in Judging Benign and Malignant Thyroid Tumors

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Qing Wan ◽  
Peng Cao ◽  
Jing Liu

In recent years, the incidence of thyroid cancer (TC) patients has gradually increased, and it ranks first among all endocrine tumors. TC has no obvious characteristics at the initial stage of onset. Thyroid tumors (TT) have formed when they are discovered, and they are easy to see when they are diagnosed. The disease is confused, so it is necessary to rely on imaging methods for tumor diagnosis. Contrast-enhanced ultrasound (CEUS), as the most commonly used imaging method in current clinical testing, is simple, safe, highly sensitive, can accurately display tumor conditions, and has high clinical value in the judgment of TC tumors. This article uses meta-analysis to select 63 published studies on CEUS to determine benign and malignant (BAM) TT to analyze and explore its clinical application value. This article understands the analysis of BAM TT and its diagnostic methods, clarifies the diagnostic efficiency of CEUS for TT, imaging methods, and imaging characteristics, and uses statistical analysis to analyze its heterogeneity. In this paper, the meta-analysis of CEUS in judging BAM TT is mainly based on references. The sensitivity, specificity, and difference of CEUS in diagnosing BAM TT are analyzed. Real-time elastography (RTE) is the comparison experiment object, and CEUS is used to compare the diagnostic efficiency, pathological results, and diagnostic efficiency of thyroid nodules in CEUS mode. The results of the study show that the nodule with higher diagnostic sensitivity is the echo feature, with a sensitivity of 97.73%, followed by the halo feature, with a sensitivity of 86.36%. In terms of diagnostic specificity, the boundary feature is the most specific. The specificity is 89.47%. In the judgment of BAM tumor nodules, the most obvious difference is the echo feature, which is as high as 14.09, followed by the acoustic halo feature, and the difference is 10.65.

2020 ◽  
Vol 93 (1112) ◽  
pp. 20200195
Author(s):  
Jiamin Pan ◽  
Wenjuan Tong ◽  
Jia Luo ◽  
Jinyu Liang ◽  
Fushun Pan ◽  
...  

Objective: To compare the efficacy of contrast-enhanced ultrasound enabled reclassification of Breast Imaging Reporting and Data System (CEUS-BI-RADS) with MRI in the diagnosis of breast lesions with calcification. Methods: A total of 52 breast lesions with calcification from 51 patients were detected by ultrasound as hyperechoic foci and categorized as BI-RADS 3–5. The 51 patients further underwent CEUS scan and MRI. The ultrasound-BI-RADS combined with CEUS 5-point score system redefined the classification of BI-RADS which was called CEUS-BI-RADS. The diagnostic efficacy of three methods was assessed by receiver operating characteristic (ROC) curve analysis. Histopathological assessment used as the gold-standard. Results: The sensitivities of Ultrasound-BI-RADS, MRI classification of BI-RADS (MRI-BI-RADS) and CEUS-BI-RADS were 85%, 90% and 95% without significant difference among the three modalities (p > 0.05). The diagnostic specificities of ultrasound-BI-RADS, MRI-BI-RADS and CEUS-BI-RADS were 78.1%, 78.1% and 96.8%, respectively (p < 0.05); and the accuracy were 80.7%, 82.6% and 96.1% for ultrasound-BI-RADS, MRI-BI-RADS and CEUS-BI-RADS, respectively (p < 0.05). The area under ROC (AUROC) in differentiation of breast lesions with calcification was 0.945 for CEUS-BI-RADS, 0.907 for MRI-BI-RADS and 0.853 for ultrasound-BI-RADS, with no significant difference among the three modalities (p > 0.05). Conclusion: The CEUS-BI-RADS has a better diagnostic efficiency than MRI-BI-RADS in the differentiation of the breast lesions with calcification. Advances in knowledge: •CEUS is a better method in differentiation of breast lesions with calcification. •CEUS-BI-RADS increases the efficiency of diagnosis compared to MRI.


2013 ◽  
Vol 33 (5) ◽  
pp. 739-755 ◽  
Author(s):  
Mireen Friedrich-Rust ◽  
Tom Klopffleisch ◽  
Julia Nierhoff ◽  
Eva Herrmann ◽  
Johannes Vermehren ◽  
...  

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