Dataset Information

Diagnostic Performance of ACR and Kwak TI-RADS for Benign and Malignant Thyroid Nodules: An Update Systematic Review and Meta-Analysis.

ABSTRACT: (1) Background: To determine the optimal cut-off values of two risk stratification systems to discriminate malignant thyroid nodules and to compare the diagnostic performance; (2) Methods: True and false positive and negative data were collected, and methodological quality was assessed for forty-six studies involving 39,085 patients; (3) Results: The highest area under the receiver operating characteristic (ROC) curve (AUC) of ACR and Kwak TI-RADS were 0.875 and 0.884. Based on the optimal sensitivity and specificity, the highest accuracy values of ROC curves or diagnostic odds ratios (DOR) were taken as the cut-off values for TR4 (moderate suspicious) and 4B. The sensitivity, specificity, DOR, and AUC by ACR (TR4) and Kwak TI-RADS (4B) for malignancy risk stratification of thyroid nodules were 94.3% and 96.4%; 52.2% and 53.7%; 17.5185 and 31.8051; 0.786 and 0.884, respectively. There were no significant differences in diagnostic accuracy in any of the direction comparisons of the two systems; (4) Conclusions: ACR and Kwak TI-RADS had good diagnostic performances (AUCs > 85%). Although we determined the best cut-off values in individual risk stratification systems based on statistical assessment, clinicians can adjust the optimal cut-off value according to the clinical purpose of the ultrasonography because raising or lowering cut-points leads to reciprocal changes in sensitivity and specificity.

SUBMITTER: Kang YJ

PROVIDER: S-EPMC9740871 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature

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Diagnostic Performance of ACR and Kwak TI-RADS for Benign and Malignant Thyroid Nodules: An Update Systematic Review and Meta-Analysis.

Kang Yun Jin YJ Stybayeya Gulnaz G Lee Ju Eun JE Hwang Se Hwan SH

Cancers 20221202 23

(1) Background: To determine the optimal cut-off values of two risk stratification systems to discriminate malignant thyroid nodules and to compare the diagnostic performance; (2) Methods: True and false positive and negative data were collected, and methodological quality was assessed for forty-six studies involving 39,085 patients; (3) Results: The highest area under the receiver operating characteristic (ROC) curve (AUC) of ACR and Kwak TI-RADS were 0.875 and 0.884. Based on the optimal sensi ...[more]

PMID: 36497443

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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:BackgroundA subset of patients undergoing thyroid surgery for presumed benign thyroid disease presented with papillary thyroid microcarcinoma (PTMC). A non-invasive and precise method for early recognition of PTMC are urgently needed. The aim of this study was to construct and validate a nomogram that combines intratumoral and peritumoral radiomics features as well as clinical features for predicting PTMC in the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) 3 nodules using ultrasonography.MethodsA retrospective review was conducted on a cohort of 221 patients who presented with ACR TI-RADS 3 nodules. These patients were subsequently pathologically diagnosed with either PTMC or benign thyroid nodules. These patients were randomly divided into a training and test cohort with an 8:2 ratio for developing the clinical model, intratumor-region model, peritumor-region model and the combined-region model respectively. The radiomics features were extracted from ultrasound (US) images of each patient. We employed K-nearest neighbor (KNN) model as the base model for building the radiomics signature and clinical signature. Finally, a radiomics-clinical nomogram that combined intratumoral and peritumoral radiomics features as well as clinical features was developed. The prediction performance of each model was assessed by the area under the curve (AUC), sensitivity, specificity and calibration curve.ResultsA total of 23 radiomics features were selected to develop radiomics models. The combined-region radiomics model showed favorable prediction efficiency in both the training dataset (AUC: 0.955) and the test dataset (AUC: 0.923). A radiomics-clinical nomogram was constructed and achieved excellent calibration and discrimination, which yielded an AUC value of 0.950, a sensitivity of 0.950 and a specificity of 0.920.ConclusionsThis study proposed the nomogram that contributes to the accurate and intuitive identification of PTMC in ACR TI-RADS 3 nodules.

Project description:BackgroundThe contrasted-enhanced ultrasound thyroid imaging reporting and data system (CEUS TI-RADS) is the first international risk stratification system for thyroid nodules based on conventional ultrasound (US) and CEUS. This study aimed to evaluate the diagnostic efficacy of CEUS TI-RADS for benign and malignant thyroid nodules and to assess the related interobserver agreement.MethodsThe study recruited 433 patients who underwent thyroid US and CEUS between January 2019 and June 2023 at the Affiliated Hospital of Guangdong Medical University. A retrospective analysis of 467 thyroid nodules confirmed by fine-needle aspiration (FNA) and/or surgery was performed. Further, a CEUS TI-RADS classification was assigned to each thyroid nodule based on the CEUS TI-RADS scoring criteria for the US and CEUS features of the nodule. The nodules were grouped based on their sizes as follows: size ≤1 cm, group A; size >1 and ≤4 cm, group B; and size >4 cm, group C. Multivariate logistic regression was used to analyze independent risk factors for malignant thyroid nodules. Pathological assessment was the reference standard for establishing the sensitivity (SEN), specificity (SPE), accuracy (ACC), positive predictive value (PPV), and negative predictive value (NPV) of CEUS TI-RADS in diagnosing malignant thyroid nodules. The area under the curve (AUC) in the receiver operating characteristic (ROC) curve analysis was used to compare the diagnostic efficacy of the scoring system in predicting malignancy in three groups of nodules. The intragroup correlation coefficient (ICC) was adopted to assess the interobserver agreement of the CEUS TI-RADS score.ResultsOut of the 467 thyroid nodules, 262 were malignant and 205 were benign. Logistic regression analysis revealed that the independent risk factors for malignant thyroid nodules included punctate echogenic foci (P<0.001), taller-than-wide shape (P=0.015), extrathyroidal invasion (P=0.020), irregular margins/lobulation (P=0.036), hypoechoicity on US (P=0.038), and hypoenhancement on CEUS (P<0.001). The AUC for the CEUS TI-RADS in diagnosing malignant thyroid nodules was 0.898 for all nodules, 0.795 for group A, 0.949 for group B, and 0.801 for group C, with the optimal cutoff values of the CEUS TI-RADS being 5 points, 6 points, 5 points, and 5 points, respectively. Among these groups of nodules, group B had the highest AUC, with the SEN, SPE, ACC, PPV, and NPV for diagnosing malignant nodules being 95.9%, 88.1%, 92.8%, 92.6%, and 93.2%, respectively. The ICC of the CEUS TI-RADS classification between senior and junior physicians was 0.862 (P<0.001).ConclusionsIn summary, CEUS TI-RADS demonstrated significant efficacy in distinguishing thyroid nodules. Nonetheless, there were variations in its capacity to detect malignant nodules across diverse sizes, and it demonstrate optimal performance in 1- to 4-cm nodules. These findings may serve as important insights for clinical diagnoses.

Dataset Information

Diagnostic Performance of ACR and Kwak TI-RADS for Benign and Malignant Thyroid Nodules: An Update Systematic Review and Meta-Analysis.

Publications

Diagnostic Performance of ACR and Kwak TI-RADS for Benign and Malignant Thyroid Nodules: An Update Systematic Review and Meta-Analysis.

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