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Contrast-enhanced ultrasound for the differential diagnosis of thyroid nodules: An updated meta-analysis with comprehensive heterogeneity analysis.

ABSTRACT: The diagnostic accuracy of contrast-enhanced ultrasound (CEUS) for distinguishing malignant thyroid nodules from benign thyroid nodules remains controversial. This meta-analysis was performed to evaluate the overall diagnostic value of CEUS for the characterization of thyroid nodules. Relevant studies were identified by searching PubMed, Embase and the Cochrane Library until August 1th 2019 to assess the overall diagnostic accuracy of CEUS. 37 eligible studies were included in the present meta-analysis. The pooled sensitivity, specificity, positive likelihood rate, negative likelihood rate and diagnostic odds ratio of CEUS were 0.87, 0.83, 5.38, 0.17 and 38.94, respectively, with the AUC of 0.9263. Subgroup analysis showed the heterogeneity was greatly reduced in small nodules group (? 1 cm) (I2 = 0.0%), while heterogeneity was still observed in the group of variable sizes group (I2 = 69.5%). However, meta-regression analysis revealed that only diagnostic criterion was the major source of heterogeneity (p = 0.0259). The risk of publication bias was negligible (p = 0.35). CEUS exhibited high accuracy for the identification of thyroid nodules and might provide additional perfusion information for the current US imaging reporting systems.

SUBMITTER: Zhang J

PROVIDER: S-EPMC7170259 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Contrast-enhanced ultrasound for the differential diagnosis of thyroid nodules: An updated meta-analysis with comprehensive heterogeneity analysis.

Zhang Juanjuan J Zhang Xiuting X Meng Yanna Y Chen Yinghong Y

PloS one 20200420 4

The diagnostic accuracy of contrast-enhanced ultrasound (CEUS) for distinguishing malignant thyroid nodules from benign thyroid nodules remains controversial. This meta-analysis was performed to evaluate the overall diagnostic value of CEUS for the characterization of thyroid nodules. Relevant studies were identified by searching PubMed, Embase and the Cochrane Library until August 1th 2019 to assess the overall diagnostic accuracy of CEUS. 37 eligible studies were included in the present meta-a ...[more]

PMID: 32310968

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Project description:ObjectiveThis study aims to investigate the value of contrast-enhanced ultrasound (CEUS) in the differential diagnosis and risk stratification of ACR TI-RADS category 4 and 5 thyroid nodules with non-hypovascular.MethodsFrom January 2016 to December 2019 in our hospital, 217 ACR TI-RADS category 4 and 5 nodules with non-hypovascular in 210 consecutive patients were included for a derivation cohort. With surgery and/or fine-needle aspiration (FNA) as a reference, conventional ultrasound (US) features and CEUS features were analyzed. Multivariate logistic regression analysis was used to screen the independent risk factors and establish a risk predictive model. Between January 2020 and March 2021, a second cohort of 100 consecutive patients with 101 nodules were included for an external validation cohort. The model was converted into a simplified risk score and was validated in the validation cohort. The area under the receiver operating characteristic curves (AUC) were used to assess the models' diagnostic performance.ResultsMicro-calcification, irregular margin, earlier wash-out, centripetal enhancement, and absence of ring enhancement were independent risk factors and strongly discriminated malignancy in the derivation cohort (AUC = 0.921, 95% CI 0.876-0.953) and the validation cohort (0.900, 0.824-0.951). There was no significant difference (P = 0.3282) between the conventional US and CEUS in differentiating malignant non-hypovascular thyroid nodules, but a combination of them (the predictive model) had better performance than the single method (all P <0.05), with a sensitivity of 87.0%, specificity of 86.2%, and accuracy of 86.6% in the derivation cohort. The risk score based on the independent risk factors divided non-hypovascular thyroid nodules into low-suspicious (0-3 points; malignancy risk <50%) and high-suspicious (4-7 points; malignancy risk ≥ 50%), the latter with nodule ≥10mm was recommended for FNA. The risk score showed a good ability of risk stratification in the validation cohort. Comparing ACR TI-RADS in screening suitable non-hypovascular nodules for FNA, the risk score could avoid 30.8% benign nodules for FNA.ConclusionsCEUS is helpful in combination with conventional US in differentiating ACR TI-RADS category 4 and 5 nodules with non-hypovascular. The risk score in this study has the potential to improve the diagnosis and risk stratification of non-hypovascular thyroid nodules.

Project description:Objective:The incidence of superficial organ diseases has increased rapidly in recent years. New methods such as computer-aided diagnosis (CAD) are widely used to improve diagnostic efficiency. Convolutional neural networks (CNNs) are one of the most popular methods, and further improvements of CNNs should be considered. This paper aims to develop a multiorgan CAD system based on CNNs for classifying both thyroid and breast nodules and investigate the impact of this system on the diagnostic efficiency of different preprocessing approaches. Methods:The training and validation sets comprised randomly selected thyroid and breast nodule images. The data were subgrouped into 4 models according to the different preprocessing methods (depending on segmentation and the classification method). A prospective data set was selected to verify the clinical value of the CNN model by comparison with ultrasound guidelines. Diagnostic efficiency was assessed based on receiver operating characteristic (ROC) curves. Results:Among the 4 models, the CNN model using segmented images for classification achieved the best result. For the validation set, the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy, and area under the curve (AUC) of our CNN model were 84.9%, 69.0%, 62.5%, 88.2%, 75.0%, and 0.769, respectively. There was no statistically significant difference between the CNN model and the ultrasound guidelines. The combination of the two methods achieved superior diagnostic efficiency compared with their use individually. Conclusions:The study demonstrates the probability, feasibility, and clinical value of CAD in the ultrasound diagnosis of multiple organs. The use of segmented images and classification by the nature of the disease are the main factors responsible for the improvement of the CNN model. Moreover, the combination of the CNN model and ultrasound guidelines results in better diagnostic performance, which will contribute to the improved diagnostic efficiency of CAD systems.

Project description:BACKGROUND:Currently the cytological examination of fine needle aspiration (FNA) biopsies is the standard technique for the pre-operative differential diagnosis of thyroid nodules. However, the results may be non-informative in ~20% of cases due to an inadequate sampling and the lack of highly specific, measurable cytological criteria, therefore ancillary biomarkers that could aid in these cases are clearly needed. The aim of our study was to evaluate the mRNA expression levels of 8 candidate marker genes as the diagnostic biomarkers for the discrimination of benign and malignant thyroid nodules and to find a combination of biomarkers with the highest diagnostic value. MATERIALS AND METHODS:mRNA expression levels of eight candidate marker genes - BIRC5, CCND1, CDH1, CITED1, DPP4, LGALS3, MET and TFF3 was measured by real-time RT-PCR in paired nodular and surrounding normal thyroid tissue specimens of 105 consecutive patients undergoing thyroid surgery and compared between different types of thyroid lesions. RESULTS:Significant differences in the mRNA expression levels between the normal and malignant thyroid tissues and between benign and malignant nodules were found for BIRC5, CCND1, CITED1, DPP4, LGALS3, MET and TFF3, but not CDH1. On a single gene basis, relative quantity (RQ) of LGALS3 had the highest diagnostic value for the discrimination of malignant and benign thyroid nodules (AUC = 0.832, P < 0.0001 and 90.9% sensitivity and 65.6% specificity at the optimal cut-off on ROC curve). The only two-marker set that outperformed LGALS3 was RQ sum of LGALS3 and BIRC5 (AUC = 0.841, P < 0.0001). An application of multivariate logistic regression analysis resulted in the generation of a multiplex biomarker model based on LGALS3, BIRC5, TFF3, CCND1, MET and CITED1 that had considerably higher specificity than a single marker or two marker gene-based models (AUC = 0.895, P < 0.0001, 70.5% sensitivity and 93.4% specificity). CONCLUSIONS:This study confirmed that mRNA expression levels of 7 out of 8 candidate genes analysed have a diagnostic value for the distinction of benign and malignant thyroid nodules. The multiplex biomarker model based on 6 genes outperformed a single marker or two marker-based models and warrants feasibility studies on FNA biopsies and the validation in a larger cohort of patients.

Dataset Information

Contrast-enhanced ultrasound for the differential diagnosis of thyroid nodules: An updated meta-analysis with comprehensive heterogeneity analysis.

Publications

Contrast-enhanced ultrasound for the differential diagnosis of thyroid nodules: An updated meta-analysis with comprehensive heterogeneity analysis.

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