Clinical Study of the Prediction of Malignancy in Thyroid Nodules: Modified Score versus 2017 American College of Radiology's Thyroid Imaging Reporting and Data System Ultrasound Lexicon

Applying machine-learning models to differentiate benign and malignant thyroid nodules classified as C-TIRADS 4 based on 2D-ultrasound combined with five contrast-enhanced ultrasound key frames

Objectives

To apply machine learning to extract radiomics features from thyroid two-dimensional ultrasound (2D-US) combined with contrast-enhanced ultrasound (CEUS) images to classify and predict benign and malignant thyroid nodules, classified according to the Chinese version of the thyroid imaging reporting and data system (C-TIRADS) as category 4.

Materials and methods

This retrospective study included 313 pathologically diagnosed thyroid nodules (203 malignant and 110 benign). Two 2D-US images and five CEUS key frames ("2nd second after the arrival time" frame, "time to peak" frame, "2nd second after peak" frame, "first-flash" frame, and "second-flash" frame) were selected to manually label the region of interest using the "Labelme" tool. A total of 7 images of each nodule and their annotates were imported into the Darwin Research Platform for radiomics analysis. The datasets were randomly split into training and test cohorts in a 9:1 ratio. Six classifiers, namely, support vector machine, logistic regression, decision tree, random forest (RF), gradient boosting decision tree and extreme gradient boosting, were used to construct and test the models. Performance was evaluated using a receiver operating characteristic curve analysis. The area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), accuracy (ACC), and F1-score were calculated. One junior radiologist and one senior radiologist reviewed the 2D-US image and CEUS videos of each nodule and made a diagnosis. We then compared their AUC and ACC with those of our best model.

Results

The AUC of the diagnosis of US, CEUS and US combined CEUS by junior radiologist and senior radiologist were 0.755, 0.750, 0.784, 0.800, 0.873, 0.890, respectively. The RF classifier performed better than the other five, with an AUC of 1 for the training cohort and 0.94 (95% confidence interval 0.88-1) for the test cohort. The sensitivity, specificity, accuracy, PPV, NPV, and F1-score of the RF model in the test cohort were 0.82, 0.93, 0.90, 0.85, 0.92, and 0.84, respectively. The RF model with 2D-US combined with CEUS key frames achieved equivalent performance as the senior radiologist (AUC: 0.94 vs. 0.92, P = 0.798; ACC: 0.90 vs. 0.92) and outperformed the junior radiologist (AUC: 0.94 vs. 0.80, P = 0.039, ACC: 0.90 vs. 0.81) in the test cohort.

Conclusions

Our model, based on 2D-US and CEUS key frames radiomics features, had good diagnostic efficacy for thyroid nodules, which are classified as C-TIRADS 4. It shows promising potential in assisting less experienced junior radiologists.

Improved cancer risk stratification of isoechoic thyroid nodules to reduce unnecessary biopsies using quantitative ultrasound

Objective

Gray-scale ultrasound (US) is the standard-of-care for evaluating thyroid nodules (TNs). However, the performance is better for the identification of hypoechoic malignant TNs (such as classic papillary thyroid cancer) than isoechoic malignant TNs. Quantitative ultrasound (QUS) utilizes information from raw ultrasonic radiofrequency (RF) echo signal to assess properties of tissue microarchitecture. The purpose of this study is to determine if QUS can improve the cancer risk stratification of isoechoic TNs.

Methods

Patients scheduled for TN fine needle biopsy (FNB) were recruited from the Thyroid Health Clinic at Boston Medical Center. B-mode US and RF data (to generate QUS parameters) were collected in 274 TNs (163 isoechoic, 111 hypoechoic). A linear combination of QUS parameters (CQP) was trained and tested for isoechoic [CQP(i)] and hypoechoic [CQP(h)] TNs separately and compared with the performance of conventional B-mode US risk stratification systems.

Results

CQP(i) produced an ROC AUC value of 0.937+/- 0.043 compared to a value of 0.717 +/- 0.145 (p >0.05) for the American College of Radiology Thyroid Imaging, Reporting and Data System (ACR TI-RADS) and 0.589 +/- 0.173 (p >0.05) for the American Thyroid Association (ATA) risk stratification system. In this study, CQP(i) avoids unnecessary FNBs in 73% of TNs compared to 55.8% and 11.8% when using ACR TI-RADS and ATA classification system.

Conclusion

This data supports that a unique QUS-based classifier may be superior to conventional US stratification systems to evaluate isoechoic TNs for cancer and should be explored further in larger studies.

Diagnostic efficacy of a combination of the Chinese thyroid imaging reporting and data system and shear wave elastography in detecting category 4a and 4b thyroid nodules

Objectives

Differential diagnosis of benign and malignant thyroid imaging reporting and data system (TIRADS) category 4a and 4b nodules can be difficult using conventional ultrasonography (US). The objective of this study was to evaluate the diagnostic efficacy of a combination of the Chinese-TIRADS (C-TIRADS) and shear wave elastography (SWE) in detecting malignant nodules among category 4a and 4b thyroid nodules.

Methods

Among 409 thyroid nodules in 332 patients that we included in this study, 106 thyroid nodules were diagnosed as category 4a and 4b using C-TIRADS. We used SWE to measure the maximum Young's modulus (Emax) values of category 4a and 4b thyroid nodules. We calculated the diagnostic efficacy of only the C-TIRADS, only SWE, and a combination of C-TIRADS with SWE, and compared these, while taking the pathology results as the gold standard.

Results

The area under the ROC curve (AUC), sensitivity, and accuracy values of the combination of C-TIRADS and SWE (0.870, 83.3%, and 84.0%, respectively) were all higher when compared with the values of only the C-TIRADS (0.785, 68.5%, and 78.3%, respectively) or only SWE (0.775, 68.5%, and 77.4%, respectively) in the diagnosis of category 4a and 4b thyroid nodules.

Conclusion

In this study, we found that the combination of C-TIRADS and SWE significantly improved the diagnostic efficacy in detecting malignant nodules among category 4a and 4b thyroid nodules, and this could provide a reference for further use of this combination by clinicians for diagnosis and treatment.

Comparison of S-Detect and thyroid imaging reporting and data system classifications in the diagnosis of cytologically indeterminate thyroid nodules

PURPOSE

The aim of this study was to investigate the value of S-Detect for predicting the malignant risk of cytologically indeterminate thyroid nodules (CITNs).

METHODS

The preoperative prediction of 159 CITNs (Bethesda III, IV and V) were performed using S-Detect, Thyroid Imaging Reporting and Data System of American College of Radiology (ACR TI-RADS) and Chinese TI-RADS (C-TIRADS). First, Linear-by-Linear Association test and chi-square test were used to analyze the malignant risk of CITNs. McNemar's test and receiver operating characteristic curve were used to compare the diagnostic efficacy of S-Detect and the two TI-RADS classifications for CITNs. In addition, the McNemar's test was used to compare the diagnostic accuracy of the above three methods for different pathological types of nodules.

RESULTS

The maximum diameter of the benign nodules was significantly larger than that of malignant nodules [0.88(0.57-1.42) vs 0.57(0.46-0.81), P=0.002]. The risk of malignant CITNs in Bethesda system and the two TI-RADS classifications increased with grade (all P for trend<0.001). In all the enrolled CITNs, the diagnostic results of S-Detect were significantly different from those of ACR TI-RADS and C-TIRADS, respectively (P=0.021 and P=0.007). The sensitivity and accuracy of S-Detect [95.9%(90.1%-98.5%) and 88.1%(81.7%-92.5%)] were higher than those of ACR TI-RADS [87.6%(80.1%-92.7%) and 81.8%(74.7%-87.3%)] (P=0.006 and P=0.021) and C-TIRADS [84.3%(76.3%-90.0%) and 78.6%(71.3%-84.5%)] (P=0.001 and P=0.001). Moreover, the negative predictive value and the area under curve value of S-Detect [82.8% (63.5%-93.5%) and 0.795%(0.724%-0.855%)] was higher than that of C-TIRADS [54.8%(38.8%-69.8%) and 0.724%(0.648%-0.792%] (P=0.024 and P=0.035). However, the specificity and positive predictive value of S-Detect were similar to those of ACR TI-RADS (P=1.000 and P=0.154) and C-TIRADS (P=1.000 and P=0.072). There was no significant difference in all the evaluated indicators between ACR TI-RADS and C-TIRADS (all P>0.05). The diagnostic accuracy of S-Detect (97.4%) for papillary thyroid carcinoma (PTC) was higher than that of ACR TI-RADS (90.4%) and C-TIRADS (87.8%) (P=0.021 and P=0.003).

CONCLUSION

The diagnostic performance of S-Detect in differentiating CITNs was similar to ACR TI-RADS and superior to C-TIRADS, especially for PTC.

Multimodal ultrasound imaging: A method to improve the accuracy of diagnosing thyroid TI-RADS 4 nodules

Thyroid nodule is a common and frequently occurring disease in the neck in recent years, and ultrasound has become the preferred imaging diagnosis method for thyroid nodule due to its advantages of noninvasive, nonradiation, real-time, and repeatable. The thyroid imaging, reporting and data system (TI-RADS) classification standard scores suspicious nodules that are difficult to determine benign and malignant as grade 4, and further pathological puncture is recommended clinically, which may lead to a large number of unnecessary biopsies and operations. Including conventional ultrasound, ACR TI-RADS, shear wave elastography, super microvascular imaging, contrast enhanced ultrasound, "firefly," artificial intelligence, and multimodal ultrasound imaging used in combination. In order to identify the most clinically significant malignant tumors when reducing invasive operations. This article reviews the application and research progress of multimodal ultrasound imaging in the diagnosis of TI-RADS 4 thyroid nodules.

The diagnostic value of a nomogram based on multimodal ultrasonography for thyroid-nodule differentiation: A multicenter study

Objective

To establish and verify a nomogram based on multimodal ultrasonography (US) for the assessment of the malignancy risk of thyroid nodules and to explore its value in distinguishing benign from malignant thyroid nodules.

Methods

From September 2020 to December 2021, the data of 447 individuals with thyroid nodules were retrieved from the multicenter database of medical images of the National Health Commission’s Capacity Building and Continuing Education Center, which includes data from more than 20 hospitals. All patients underwent contrast-enhanced US (CEUS) and elastography before surgery or fine needle aspiration. The training set consisted of three hundred datasets from the multicenter database (excluding Zhejiang Cancer Hospital), and the external validation set consisted of 147 datasets from Zhejiang Cancer Hospital. As per the pathological results, the training set was separated into benign and malignant groups. The characteristics of the lesions in the two groups were analyzed and compared using conventional US, CEUS, and elastography score. Using multivariate logistic regression to screen independent predictive risk indicators, then a nomogram for risk assessment of malignant thyroid nodules was created. The diagnostic performance of the nomogram was assessed utilizing calibration curves and receiver operating characteristic (ROC) from the training and validation cohorts. The nomogram and The American College of Radiology Thyroid Imaging, Reporting and Data System were assessed clinically using decision curve analysis (DCA).

Results

Multivariate regression showed that irregular shape, elastography score (≥ 3), lack of ring enhancement, and unclear margin after enhancement were independent predictors of malignancy. During the training (area under the ROC [AUC]: 0.936; 95% confidence interval [CI]: 0.902–0.961) and validation (AUC: 0.902; 95% CI: 0.842–0.945) sets, the multimodal US nomogram with these four variables demonstrated good calibration and discrimination. The DCA results confirmed the good clinical applicability of the multimodal US nomogram for predicting thyroid cancer.

Conclusions

As a preoperative prediction tool, our multimodal US-based nomogram showed good ability to distinguish benign from malignant thyroid nodules.

Validating and Comparing C-TIRADS, K-TIRADS and ACR-TIRADS in Stratifying the Malignancy Risk of Thyroid Nodules

The thyroid imaging reporting and data system (TIRADS) was proposed by experts for optimal ultrasound evaluation of malignancy risk of thyroid focal lesions. There are several versions of TIRADS, some of them have been validated sufficiently, and the others have not been well assessed. In this study, a recently launched Chinese version of TIRADS (C-TIRADS) for malignancy risk stratification of thyroid nodules was validated, and the performance was compared to that of the Korean TIRADS (K-TIRADS) and American College of Radiology(ACR) TIRADS (ACR-TIRADS). Archives of 2177 patients who had undergone thyroid ultrasound examination, coarse needle tissue biopsy and/or surgery were reviewed, and 1978 patients with 1982 thyroid nodules were assessed according to the three TIRADSs. The histopathology was taken as the golden standard. The results showed the 1982 thyroid nodules were consisted of 1306 benign nodules and 676 malignant nodules. The malignancy risk accounted for 1.09%, 2.14%, 10.34%, 49.28%, 88.19% and 85.29% of the total nodules that were categorised as C-TIRADS 2, 3, 4A, 4B, 4C and 5, respectively; 0.00%, 1.64%, 2.87%,18.71% and 82.22% of the total nodules that were categorised as ACR-TIRADS 1, 2, 3, 4 and 5, respectively; 0.85%, 3.27%, 24.27% and 80.96% of the total nodules that were categorised as K-TIRADS 2, 3, 4 and 5, respectively. The correlation between the category of TIRADS and percentile of malignancy was 0.94 in the C-TIRADS, 1.00 in the ACR-TIRADS, and 1.00 in the K-TIRADS, respectively. The highest values of accuracy(AUC) of ROC curves of C-TIRADS 4B, K-TIRADS 5 and ACR-TIRADS 5 were taken as the cut-off values for risk stratification, respectively. The sensitivity, specificity, positive and negative predictive values and AUC by C-TIRADS 4B, K-TIRADS 5 and ACR-TIRADS 5 for malignancy risk stratification of thyroid nodules were 90.83%, 84.23%, 74.88% and 94.66% and 0.88, respectively; 83.58%, 89.82%, 80.95%, 91.36% and 0.87, respectively; and 85.50%, 90.35%, 82.10%, 92.33% and 0.88, respectively (P>0.05 for all). We concluded that the C-TIRADS has excellent performance in the malignancy risk stratification of thyroid nodules by the optimized cut-off value, which is comparable to that in K-TIRADS and ACR-TIRADS.

Comparison of ACR TI-RADS, Kwak TI-RADS, ATA guidelines and KTA/KSThR guidelines in combination with SWE in the diagnosis of thyroid nodules

OBJECTIVE

To compare the diagnostic efficacy of ACR TI-RADS, Kwak TI-RADS, ATA guidelines and KTA/KSThR guidelines in combination with shear wave elastography (SWE) for thyroid nodules.

METHODS

The retrospective study included 566 thyroid nodules with maximum diameter≥5 mm which confirmed by FNA cytology or/and surgical pathology. The sensitivity, specificity, accuracy, Youden index of diagnosis of thyroid nodules by ACR TI-RADS, Kwak TI-RADS, ATA guidelines, KTA/KSThR guidelines and SWE were calculated. The ROC curve was drawn to determine the cut-off values of the four ultrasound classification systems and SWE Emax. The diagnostic efficacy of the four ultrasound classification systems in combination with SWE were calculated and compared with those of pre-combination.

RESULTS

The ROC curves indicated that the cut-off value of ACR TI-RADS, Kwak TI-RADS, ATA guidelines, KTA/KSThR guidelines and Emax of SWE was TR5, 4c, high-suspicion, high-suspicion, and 41.7 kPa, respectively, and the area under the ROC curve (AUC) was 0.907(0.879-0.934), 0904(0.876-0.932), 0.894(0.863-0.924), 0.888(0.856-0.919), 0.886(0.859-0.913), respectively. After combination with SWE, the the sensitivities of the four ultrasound classification systems for the diagnosis of nodules were improved, and the differences were statistically significant (all P≤0.001); the specificities were decreased, but the differences were not statistically significant (all P > 0.05); the accuracies were improved, but only the difference of ACR TI-RADS was statistically significant (x2 = 4.45, P = 0.035); the differences in the AUCs were not significant (all P > 0.05).

CONCLUSIONS

The four ultrasound classification systems and SWE all had high performance in the diagnosis of thyroid nodules. The four classification systems in combination with SWE were all beneficial to the differential diagnosis of nodules, and ACR TI-RADS in combination with SWE was more effective, especially for TR3 and TR4 nodules.

Contrast-Enhanced Ultrasound in the Differential Diagnosis and Risk Stratification of ACR TI-RADS Category 4 and 5 Thyroid Nodules With Non-Hypovascular

Objective

This 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.

Methods

From 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.

Results

Micro-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.

Conclusions

CEUS 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.

SWE combined with ACR TI-RADS categories for malignancy risk stratification of thyroid nodules with indeterminate FNA cytology

OBJECTIVES

To compare the diagnostic efficacy of shear wave elastography (SWE) comnined with ACR TI-RADS categories for malignancy risk stratification of thyroid nodules with interminate FNA cytology.

METHODS

The clinical data, sonographic features, ACR TI-RADS grading and shear wave elastography images of 193 patients of surgical pathologically proven thyroid nodules with interminate FNA cytology were retrospectively analyzed. The diagnostic efficacy of ACR TI-RADS categories, the maximum Young's modulus (Emax) of SWE and the combination of the two were calculated respectively.

RESULTS

The ROC curves were drawn using surgical pathology results as the gold standard. The ROC curves indicated that the cut-off value of ACR TI-RADS and Emax of SWE was TR5 and 41.2 kPa respectively, and the area under the ROC curve (AUC) was 0.864 (95% CI: 0.879-0.934) and 0.858 (95% CI: 0.796-0.920) respectively. The diagnostic sensitivity, specificity and accuracy of ACR TI-RADS was 81.4% (127/156), 84.8% (31/37), and 81.9% (158/193), respectively. That of SWE Emax was 80.8% (126/156), 78.4% (29/37), and 80.3% (155/193), respectively. After SWE combined with ACR TI-RADS, the sensitivity, specificity and accuracy was 94.2% (147/156), 75.7% (28/37), and 90.7% (175/193), respectively.

CONCLUSIONS

ACR TI-RADS classification system and shear wave elastography had high diagnostic efficacy for thyroid nodules with interminate FNA cytology. The combination of the two could improve diagnostic sensitivity and accuracy, and could help to differentiate benign and malignant thyroid nodules with interminate FNA cytology.

A Preliminary Study of Quantitative Ultrasound for Cancer-Risk Assessment of Thyroid Nodules

BACKGROUND

Gray-scale, B-mode ultrasound (US) imaging is part of the standard clinical procedure for evaluating thyroid nodules (TNs). It is limited by its instrument- and operator-dependence and inter-observer variability. In addition, the accepted high-risk B-mode US TN features are more specific for detecting classic papillary thyroid cancer rather than the follicular variant of papillary thyroid cancer or follicular thyroid cancer. Quantitative ultrasound (QUS) is a technique that can non-invasively assess properties of tissue microarchitecture by exploiting information contained in raw ultrasonic radiofrequency (RF) echo signals that is discarded in conventional B-mode imaging. QUS provides quantitative parameter-value estimates that are a function of the properties of US scatterers and microarchitecture of the tissue. The purpose of this preliminary study was to assess the performance of QUS parameters in evaluating benign and malignant thyroid nodules.

METHODS

Patients from the Thyroid Health Center at the Boston Medical Center were recruited to participate. B-mode and RF data were acquired and analyzed in 225 TNs (24 malignant and 201 benign) from 208 patients. These data were acquired either before (167 nodules) or after (58 nodules) subjects underwent fine-needle biopsy (FNB). The performance of a combination of QUS parameters (CQP) was assessed and compared with the performance of B-mode risk-stratification systems.

RESULTS

CQP produced an ROC AUC value of 0.857 ± 0.033 compared to a value of 0.887 ± 0.033 (p=0.327) for the American College of Radiology Thyroid Imaging, Reporting and Data System (ACR TI-RADS) and 0.880 ± 0.041 (p=0.367) for the American Thyroid Association (ATA) risk-stratification system. Furthermore, using a CQP threshold of 0.263 would further reduce the number of unnecessary FNBs in 44% of TNs without missing any malignant TNs. When CQP used in combination with ACR TI-RADS, a potential additional reduction of 49 to 66% in unnecessary FNBs was demonstrated.

CONCLUSION

This preliminary study suggests that QUS may provide a method to classify TNs when used by itself or when combined with a conventional gray-scale US risk-stratification system and can potentially reduce the need to biopsy TNs.

Diagnostic value of 2017 ACR Thyroid Imaging Reporting and Data System (TI-RADS) combined with fine needle aspiration biopsy in thyroid nodules

OBJECTIVE

To evaluate diagnostic value of Thyroid Imaging Reporting and Data System published by American College of Radiology (ACR TI-RADS) in 2017, ultrasound-guided fine-needle aspiration (US-FNA), and the combination of both methods in differentiation between benign and malignant thyroid nodules.

METHODS

The data of US-FNA and ACR TI-RADS are collected from 159 patients underwent thyroid surgery in our hospital, which include a total of 178 thyroid nodules. A Bethesda System for Reporting Thyroid Cytopathology category of ≥IV and an ACR TI-RADS category ≥4 are regarded as diagnosis standards for malignancy in US-FNA and ACR TI-RADS, respectively. The pathological results after surgery are considered as the gold standard. The sensitivity, specificity, accuracy, positive predictive value and negative predictive value of the ACR TI-RADS, US-FNA and the combination of both methods for the differential diagnosis of thyroid nodules are calculated, respectively.

RESULTS

The sensitivity, specificity and accuracy of ACR TI-RADS are 85.4%, 37.5%and 72.5%, respectively. The sensitivity, specificity and accuracy of US-FNA are 70.0%, 100%and 78.1%, respectively. After combining these two methods, the sensitivity, specificity and accuracy increase to 99.23%, 37.50%and 82.58%, respectively. The sensitivity of ACR TI-RADS is higher than that of US-FAN, and the sensitivity of combining these two methods is also higher than that of using ACR TI-RADS and US-FNA alone.

CONCLUSION

The established ACR TI-RADS can help in selecting the target during nodule puncture, while the combination of ACR TI-RADS and US-FAN can further improve diagnostic ability for detecting malignant thyroid nodules.

Conventional ultrasound characteristics, TI-RADS category and shear wave speed measurement between follicular adenoma and follicular thyroid carcinoma

The purpose of the study was to explore the differences of conventional ultrasound characteristics, thyroid imaging reporting and data system (TI-RADS) category and shear wave speed (SWS) measurement between follicular adenoma (FA) and follicular thyroid carcinoma (FTC). Twenty-eight FTCs and 67 FAs proven by surgery were retrospectively included for analysis. Conventional ultrasound and point-shear wave elastography (p-SWE) were performed in all of the included patients. The ultrasound features, American Thyroid Association (ATA) TI-RADS category and American College of Radiology (ACR) TI-RADS category, SWS measurement were compared between the two groups. Receiver operating characteristic (ROC) curve was performed and area under ROC curve (AUC) was obtained for significant features. There were no statistical differences in mean age (46.9±15.7years vs. 48.6±13.6years, P = 0.639), gender (9 males, 32.1% vs. 18 males, 29.0%, P = 0.766) and mean diameter (28.3±16.2 mm vs. 33.8±11.9 mm, P = 0.077) between FTCs and FAs. Hypoechogenicity, lobulated or irregular margin, macrocalcification were more common in FTCs than FAs (all P < 0.05). Mean SWS of FTCs (2.29±0.64 m/s) was slightly higher than that of FAs (1.94±0.68 m/s) (P = 0.023). The AUCs were 0.655, 0.744, and 0.744 with the cut-off SWS≥1.89 m/s, ACR TI-RADS category 4 and intermediate suspicion of ATA TI-RADS category. The sensitivity and AUC were 82.1% and 0.812 with combined ultrasound features of hypoechogenicity, lobulated or irregular margin and macrocalcification. In Conclusion, SWS measurement and TI-RADS categories were useful for the identification of FTCs from FAs.

Diagnostic Performance of Four Ultrasound Risk Stratification Systems: A Systematic Review and Meta-Analysis

Background: Several ultrasound (US)-based risk stratification systems have been increasingly used for the optimal management of thyroid nodules. However, there are considerable discrepancies across these systems. This study aimed to summarize and compare the category-based diagnostic performance in the detection of thyroid cancer of different US-based risk stratification systems from four societies: the American College of Radiology-Thyroid Imaging Reporting and Data System (ACR-TIRADS), the American Thyroid Association (ATA), the Korean Thyroid Association/Korean Society of Thyroid Radiology (KTA/KSThR; K-TIRADS), and the European Thyroid Association (EU-TIRADS). Methods: MEDLINE/PubMed and EMBASE databases were searched to identify original articles investigating the category-based diagnostic performance according to at least one of the following guidelines: ACR-TIRADS, ATA, K-TIRADS, and EU-TIRADS. Pooled sensitivity and specificity were calculated using a bivariate random-effects model. A subgroup analysis on nodules of 1 cm or larger and a meta-regression analysis to identify factors associated with the diagnostic performance were performed. Results: A total of 29 articles including 33,748 thyroid nodules met the eligibility criteria and were included in the analysis. For ACR-TIRADS, the pooled sensitivity and specificity were, respectively, 66% and 91% for category 5 and 95% and 55% for category 4 or 5. For ATA, the pooled sensitivity and specificity were, respectively, 74% and 88% for category 5 and 91% and 64% for category 4 or 5. For K-TIRADS, the pooled sensitivity and specificity were, respectively, 55% and 95% for category 5 and 89% and 64% for category 4 or 5. For EU-TIRADS, the pooled sensitivity and specificity were, respectively, 82% and 90% for category 5 and 96% and 52% for category 4 or 5. Study location, proportion of female patients and malignant nodules, and study design were associated with study heterogeneity. Conclusions: The overall diagnostic performance of the four US-based risk stratification systems was comparable.

Accuracy of thyroid imaging reporting and data system category 4 or 5 for diagnosing malignancy: a systematic review and meta-analysis

OBJECTIVES

To determine the accuracies of the American College of Radiology (ACR)-thyroid imaging reporting and data systems (TIRADS), Korean (K)-TIRADS, and European (EU)-TIRADS for diagnosing malignancy in thyroid nodules.

METHODS

Original studies reporting the diagnostic accuracy of TIRADS for determining malignancy on ultrasound were identified in MEDLINE and EMBASE up to June 23, 2019. The meta-analytic summary sensitivity and specificity were obtained for TIRADS category 5 (TR-5) and category 4 or 5 (TR-4/5), using a bivariate random effects model. To explore study heterogeneity, meta-regression analyses were performed.

RESULTS

Of the 34 eligible articles (37,585 nodules), 25 used ACR-TIRADS, 12 used K-TIRADS, and seven used EU-TIRADS. For TR-5, the meta-analytic sensitivity was highest for EU-TIRADS (78% [95% confidence interval, 64-88%]), followed by ACR-TIRADS (70% [61-79%]) and K-TIRADS (64% [58-70%]), although the differences were not significant. K-TIRADS showed the highest meta-analytic specificity (93% [91-95%]), which was similar to ACR-TIRADS (89% [85-92%]) and EU-TIRADS (89% [77-95%]). For TR-4/5, all three TIRADS systems had sensitivities higher than 90%. K-TIRADS had the highest specificity (61% [50-72%]), followed by ACR-TIRADS (49% [43-56%]) and EU-TIRADS (48% [35-62%]), although the differences were not significant. Considerable threshold effects were noted with ACR- and K-TIRADS (p ≤ 0.01), with subject enrollment, country of origin, experience level of reviewer, number of patients, and clarity of blinding in review being the main causes of heterogeneity (p ≤ 0.05).

CONCLUSIONS

There was no significant difference among these three international TIRADS, but the trend toward higher sensitivity with EU-TIRADS and higher specificity with K-TIRADS.

KEY POINTS

• For TIRADS category 5, the meta-analytic sensitivity was highest for the EU-TIRADS, followed by the ACR-TIRADS and the K-TIRADS, although the differences were not significant. • For TIRADS category 5, K-TIRADS showed the highest meta-analytic specificity, which was similar to ACR-TIRADS and EU-TIRADS. • Considerable threshold effects were noted with ACR- and K-TIRADS, with subject enrollment, country of origin, experience level of reviewer, number of patients, and clarity of blinding in review being the main causes of heterogeneity.