Meta-Analysis of Contrast Enhanced Ultrasound in Judging Benign and Malignant Thyroid Tumors. (18th November 2021)

• Record Type: Journal Article
• Authors: Wan, Qing; Cao, Peng; Liu, Jing
• Other Names: Khalaf Osamah Ibrahim Academic Editor.
• Is Part Of: Computational and mathematical methods in medicine. Volume 2021(2021)
• Publication Date: 2021-11-18
• Subjects: Medicine -- Computer simulation -- Periodicals; Medicine -- Mathematical models -- Periodicals; 610.11
• DOI: 10.1155/2021/2577113
• Languages: English
• ISSNs: 1748-670X

Abstract

Abstract : 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.