Research Article
18 Jan 2022: Zhu C, Zhong L, Lin M, Tian C, Wang C (2022) The value of TI-RADS combined with superb micro-vascular imagine in distinguishing benign and malignant thyroid nodules: A meta-analysis. PLOS ONE 17(1): e0261521. https://doi.org/10.1371/journal.pone.0261521 View research article
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Abstract
Background
As a novel ultrasonic technique, superb microvascular imaging (SMI) can quickly, simply and noninvasively observe the microvascular distribution in a tumor and evaluate the microvascular perfusion. Previous studies have shown that SMI can detect the blood flow signals of neovascularization in tumors and increase the sensitivity for detecting thyroid cancer. However, the results of these studies have been contradictory, and the sample sizes were too small. Therefore, the present meta-analysis will aim at evaluating the value of a thyroid imaging report and data system (TI-RADS) combined with SMI in distinguishing between benign and malignant thyroid nodules.
Methods
We will search PubMed, Web of Science, Cochrane Library, Google Scholar, and Chinese biomedical databases from their inceptions to the June 31, 2020. Two authors will independently carry out searching literature records; scanning titles, abstracts, and full texts; collecting data; and assessing risk of bias. Review Manager 5.2 and Stata14.0 software will be used for data analysis.
Citation: Wang C, Lin M, Zhong L, Tian C (2021) The value of TI-RADS combined with superb microvascular imaging in distinguishing thyroid nodules: A protocol for systematic review and meta-analysis. PLoS ONE 16(1): e0245035. https://doi.org/10.1371/journal.pone.0245035
Editor: Oded Cohen, Kaplan Medical Center, ISRAEL
Received: August 8, 2020; Accepted: November 28, 2020; Published: January 7, 2021
Copyright: © 2021 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data from this study will be made available upon study completion.
Funding: This study is supported by Liaoning Natural Science Foundation Project (20170540256). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Thyroid cancer is a very common malignant disease that accounts for approximately 1% of all cancer patients [1]. A solid thyroid nodule is a risk factor for thyroid cancer, so it is very important to differentiate thyroid nodules effectively and in a timely manner [2]. Ultrasonography has the advantage of high sensitivity in the diagnosis of a thyroid nodule, and it is the first choice for the clinical diagnosis and differentiation of thyroid cancer [3]. In 2017, the American College of Radiology (ACR) proposed the latest version of thyroid imaging report and data system (TI-RADS) classification, ACR TI-RADS, based on large-scale, evidence-based clinical validation, which greatly promotes the differentiation of benign and malignant thyroid nodules [4]. However, due to the complexity and overlapping of the sonograms of thyroid nodules, it is still difficult to accurately identify some nodules with atypical ultrasound characteristics [5]. There are some differences in blood flow pattern and vascular morphology between benign and malignant thyroid nodules, which is helpful in distinguishing between benign and malignant thyroid nodules [6]. Color Doppler flow imaging (CDFI) is often used to show the blood flow inside the tumor, but CDFI is not good for some low-velocity microvessels and is not useful in distinguishing thyroid nodules [7,8]. As a novel ultrasonic technique, SMI can quickly, simply and noninvasively observe the microvascular distribution in the tumor and evaluate the microvascular perfusion [9]. Previous studies have shown that SMI can detect the blood flow signals of neovascularization in tumors and increase the sensitivity for detecting thyroid cancer [10–13]. However, the results of these studies have been contradictory, and the sample sizes were too small. Therefore, the present meta-analysis aimed at evaluating the value of TI-RADS combined with SMI in distinguishing between benign and malignant thyroid nodules.
Materials and methods
This study will be conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, and the protocol was registered in the INPLASY (INPLASY202070113).
Eligibility criteria
Search methods
PubMed, Web of Science, Cochrane Library, Google Scholar and Chinese biomedical databases will be searched from their inceptions to the June 31, 2020. The search strategy for PubMed is shown in Table 1. Other online databases will be used with the same strategy.
Data extraction and quality assessment
Two authors will independently selecte the trials according to the inclusion criteria and imported them into Endnote X9. Then, the duplicated or ineligible studies will be removed. Afterwards, the titles, abstracts, and full texts of all the literature will be screened to identify eligible studies. All essential data will be extracted using the data collection sheet previously created by 2 independent authors. Discrepancies in data collection between the 2 authors will be settled through discussion with the help of another author. The following data will be extracted from each included study: the first author's surname, publication year, language of publication, study design, sample size, number of lesions, source of the subjects, "gold standard," and diagnostic accuracy. The true positives (TPs), true negatives (TNs), false positives (FPs), and false negatives (FNs) in the fourfold (2 x 2) tables will also be collected. Methodological quality will be assessed by two researchers independently based on the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) tool [14]. The QUADAS criteria includes 14 assessment items. Each of these items was scored as "yes" (2), "no" (0), or "unclear" (1). The QUADAS score ranged from 0 to 28, and a score ≥ 22 indicated good quality.
Statistical analysis
STATA version 14.0 (Stata Corp, College Station, TX, USA), Meta-Disc version 1.4 (Universidad Complutense, Madrid, Spain), and MedCalc version 15.2.2 (MedCalc Software, Ostend, Belgium) software will be used for meta-analysis. We will calculate the pooled summary statistics for sensitivity (Sen) and specificity (Spe) with their 95% confidence intervals (CIs). The summary receiver operating characteristic (SROC) curve and corresponding area under the curve (AUC) were obtained. We will compare the two AUCs of TI-RADS alone and TI-RADS combined with SMI. Cochran’s Q-statistic and I2 test will be used to evaluate potential heterogeneity between studies. If the Q-test showes a P < 0.05 or I2 test exhibited > 50%, indicating significant heterogeneity, the random-effects model will be employed, or if heterogeneity is not significant, the fixed-effects model will be used. We will conduct Begg's funnel plots and Egger's linear regression tests to investigate publication bias. Sensitivity analysis will be performed to evaluate the influence of a single study on the overall estimate.
Discussion
Thyroid nodules are a common clinical disease, and their accurate differentiation has important guiding significance for clinical decision-making. High resolution ultrasound plays an important role in the differential diagnosis of thyroid nodules [13]. Although ultrasound features of malignant thyroid nodules, such as low echo, unclear margin, microcalcifications and aspect ratio > 1, increase the risk of evaluation of malignant nodules, no single ultrasound feature can independently diagnose malignant thyroid nodules [15]. Present studies have revealed that SMI was able to identify low-velocity blood flow without being affected by motion artifacts, and as an adjunct to grayscale ultrasound, SMI showed a significantly improved diagnostic performance in differentiating between benign and malignant thyroid nodules [16]. The present meta-analysis aims at evaluating the value of thyroid imaging report and data system (TI-RADS) combined with SMI in distinguishing between benign and malignant thyroid nodules and to provide evidence on the evidence-based medical support for clinical practice.
Supporting information
S1 Checklist. PRISMA-P (Preferred Reporting Items for Systematic review and Meta-Analysis Protocols) 2015 checklist: Recommended items to address in a systematic review protocol*.
https://doi.org/10.1371/journal.pone.0245035.s001
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