Comparative Study of C-TIRADS, ACR-TIRADS, and EU-TIRADS for Diagnosis and Management of Thyroid Nodules

The Diagnostic Value of Artificial Intelligence in C-TIRADS 4-5 Nodules, Real-Time Dynamic Ultrasound and Contrast-Enhanced Ultrasound to Enhance the Difference Between Papillary Thyroid Carcinoma and Nodular Goiter

BACKGROUND

Differentiating papillary thyroid carcinoma (PTC) from nodular goiter (NG) in thyroid nodules is challenging. Advanced tools such as contrast-enhanced ultrasound (CEUS) and artificial intelligence (AI)-assisted diagnostics may improve diagnostic accuracy for Chinese Thyroid Imaging Reporting and Data System (C-TIRADS) 4-5 nodules.

OBJECTIVE

To evaluate the diagnostic performance of conventional ultrasound (CUS), CEUS, and AI dynamic ultrasound in distinguishing PTC from NG in C-TIRADS 4-5 nodules.

METHODS

This retrospective, single-center study included 180 PTC and 158 NG patients. Diagnostic performance was assessed using the area under the receiver operating characteristic curve (AUC), with statistical comparisons conducted via bootstrapping methods (1000 iterations) implemented in Python 3.12.6.

RESULTS

The individual models demonstrated strong diagnostic performance, with AUCs of 0.85 (C-TIRADS), 0.86 (CEUS), and 0.86 (dynamic AI). Combining models enhanced sensitivity but reduced specificity. The majority voting system, incorporating all three models, achieved the highest diagnostic performance (AUC 0.93, sensitivity 97%, specificity 89%, accuracy 93%). No significant differences were observed between AUCs due to the strong discriminatory ability of each method.

CONCLUSION

All models, including C-TIRADS, CEUS, and dynamic AI, performed well in differentiating PTC from NG. Combining these methods, particularly with majority voting, improved diagnostic performance without compromising specificity.

A real-world comparison of the diagnostic performances of six different TI-RADS guidelines, including ACR-/Kwak-/K-/EU-/ATA-/C-TIRADS

PURPOSE

To compare the diagnostic performance of six different currently available guidelines including the American College of Radiology Thyroid Imaging and Reporting Data System (ACR-TIRADS), Kwak-TIRADS, Korean TIRADS (K-TIRADS), European TIRADS (EU-TIRADS), American Thyroid Association (ATA) and Chinese TIRADS (C-TIRADS), in differentiating malignant from benign thyroid nodules (TN).

MATERIALS AND METHODS

In this single-center study, between January-2007 and September-2023, ultrasound (US) images of TNs that were pathologically proven either by surgery or by fine needle aspiration biopsy (FNAB), were retrospectively evaluated and categorized according to six different currently available guidelines. Area under curve (AUC), sensitivity, specificity, positive and negative predictive values (PPV and NPV, respectively) and miss rates for malignancy (MRM) were calculated for each guideline.

RESULTS

A total of 829 TNs (n = 234 malignant and n = 595 benign) were included. AUC, sensitivity, specificity, PPV, NPV and accuracy for ACR-TIRADS were 0.786, 99.8 %, 27.1 %, 31.92 %, 99.73 % and 54.6 %, respectively; for Kwak-TIRADS 0.839, 97.8 %, 42.1 %, 36.29 %, 98.11 % and 63.1 %, respectively; for K-TIRADS 0.797, 97.6 %, 41.6 %, 36.01 %, 84.85 % and 62.8, respectively, for EU-TIRADS 0.766, 97.8 %, 35.6 %, 33.89 %, 97.92 % and 59.1 %, respectively, for ATA 0.788, 97.5 %, 49.8 %, 32.86 %, 88.16 % and 64.2 %, respectively and for C-TIRADS 0.842, 0 %, 92.8 %, 54.3 %, 39.53 %, 90.42 %, and 68.8 % respectively. MRM regarding ACR-/Kwak-/K-/EU-/ATA-/C-TIRADS were 2.2 %, 0.5 %, 2.9 %, 2.5 %, 3.3 % and 0.1 %, respectively.

CONCLUSION

Six different currently available TIRADS guidelines can provide effective differentiation of malignant TNs from benign ones with similar diagnostic performances. However; C-TIRADS offered the highest AUC and the lowest MRM than the other guidelines, in this series.

Additional Value of Pertechnetate Scintigraphy to American College of Radiology Thyroid Imaging Reporting and Data Systems and European Thyroid Imaging Reporting and Data Systems for Thyroid Nodule Classification in Euthyroid Patients

Background: Thyroid nodules are common yet remain a diagnostic challenge. While ultrasound and Thyroid Imaging Reporting and Data Systems (TIRADS) are accepted as standard, the use of thyroid scintigraphy in euthyroid patients is debated. The European Association of Nuclear Medicine advocates it, whereas the American Thyroid Association and European Thyroid Association do not. However, it has not been evaluated whether scintigraphy adds value to TIRADS in a multimodal approach. Our study addresses this gap by assessing the impact of integrated pertechnetate scintigraphy on TIRADS accuracy. Methods: The diagnostic performance of ACR-TIRADS, EU-TIRADS, pertechnetate scintigraphy, and multimodal models were retrospectively analyzed for 322 nodules (231 benign, 91 malignant) in 208 euthyroid patients with histopathology as a reference. Generalized estimating equations were used for statistical analysis. Results: On scintigraphy, 210 nodules were hypofunctional, 99 isofunctional, and 13 hyperfunctional. The AUC for thyroid scintigraphy, ACR-TIRADS, and EU-TIRADS were 0.6 (95% CI: 0.55-0.66), 0.83 (95% CI: 0.78-0.88), and 0.78 (95% CI: 0.72-0.83). Integrating scintigraphy with ACR-TIRADS and EU-TIRADS slightly increased diagnostic accuracy (AUC 0.86 vs. 0.83, p = 0.039 and AUC 0.80 vs. 0.78, p = 0.008) and adjusted the malignancy probability for intermediate risk TIRADS categories, with iso- or hyperfunctioning nodules in ACR-TIRADS-TR4 or EU-TIRADS-4 showing comparable malignancy probabilities as hypofunctioning nodules in TR3 or EU-TIRADS-3, respectively. Conclusions: Integrating thyroid scintigraphy with ACR- or EU-TIRADS moderately improves diagnostic performance, potentially benefiting management, especially in complex cases like multinodular goiter or indeterminate FNA. Further research is warranted to validate these findings and explore their clinical implications.

Radiomics Combined with ACR TI-RADS for Thyroid Nodules: Diagnostic Performance, Unnecessary Biopsy Rate, and Nomogram Construction

RATIONALE AND OBJECTIVES

To develop a radiomics model with enhanced diagnostic performance, reduced unnecessary fine needle aspiration biopsy (FNA) rate, and improved clinical net benefit for thyroid nodules.

METHODS

We conducted a retrospective study of 217 thyroid nodules. Lesions were divided into training (n = 152) and verification (n = 65) cohorts. Three radiomics scores were derived from B-mode ultrasound (B-US) and strain elastography (SE) images, alone and in combination. A radiomics nomogram was constructed by combining high-frequency ultrasonic features and the best-performing radiomics score. The area under the receiver operating characteristic curve (AUC), unnecessary FNA rate, and decision curve analysis (DCA) results for the nomogram were compared to those obtained with the American College of Radiology Thyroid Imaging, Reporting and Data System (ACR TI-RADS) score and the combined TI-RADS+SE+ contrast-enhanced ultrasound (CEUS) advanced clinical score.

RESULTS

The three radiomics scores (B-US, SE, B-US+SE) achieved training AUCs of 0.753 (0.668-0.825), 0.761 (0.674-0.838), and 0.795 (0.715-0.871), and validation AUCs of 0.732 (0.579-0.867), 0.753 (0.609-0.892), and 0.752 (0.592-0.899) respectively. The AUC of the nomogram for the entire patient cohort was 0.909 (0.864-0.954), which was higher than that of the ACR TI-RADS score (P < 0.001) and equivalent to the TI-RADS+SE+CEUS score (P = 0.753). Similarly, the unnecessary FNA rate of the radiomics nomogram was significantly lower than that of the ACR TI-RADS score (P = 0.007) and equivalent to the TI-RADS+SE+CEUS score (P = 0.457). DCA also showed that the radiomics nomogram brought more net clinical benefit than the ACR TI-RADS score but was similar to that of the TI-RADS+SE+CEUS score.

CONCLUSION

The radiomics nomogram developed in this study can be used as an objective, accurate, cost-effective, and noninvasive method for the characterization of thyroid nodules.

Predictive Value of the Nomogram Model Based on Multimodal Ultrasound Features for Benign and Malignant Thyroid Nodules of C-TIRADS Category 4

To explore the predictive value of the nomogram model based on multimodal ultrasound features for benign and malignant thyroid nodules of C-TIRADS category 4. A retrospective analysis was conducted on the general conditions and ultrasound features of patients who underwent thyroid ultrasound examination and fine needle aspiration biopsy (FNA) or thyroidectomy at the Affiliated Hospital of Zunyi Medical University from April 2020 to April 2023. Predictive signs for benign and malignant nodules of thyroid C-TIRADS category 4 were screened through LASSO regression and multivariate logistic regression analysis to construct a nomogram prediction model. The predictive efficiency and accuracy of the model were assessed through ROC curves and calibration curves. Seven independent risk factors in the predictive model for benign and malignant thyroid nodules of C-TIRADS category 4 were growth pattern, morphology, microcalcifications, SR, arterial phase enhancement intensity, initial perfusion time, and PE [%]. Based on these features, the area under the curve (AUC) of the constructed prediction model was 0.971 (p ＜ .001, 95% CI: 0.952-0.989), with a prediction accuracy of 93.1%. Internal validation showed that the nomogram calibration curve was consistent with reality, and the decision curve analysis indicated that the model has high clinical application value. The nomogram prediction model constructed based on the multimodal ultrasound features of thyroid nodules of C-TIRADS category 4 has high clinical application value.

Construction and validation of a diagnostic model for high-risk papillary thyroid microcarcinoma

Objective

The purpose of this study was to construct a diagnostic model by exploring the potential predictors of high-risk Papillary Thyroid Microcarcinoma (PTMC) and verifying its reliability.

Methods

A retrospective analysis of PTMC patients who underwent surgical treatment from 2004 to 2015 in the SEER database (training set) and the clinical pathological ultrasound information of PTMC patients at the Sichuan Provincial People's Hospital from 2020 to 2022 (external validation set) was conducted. In the training set, univariate and multivariate logistic regression analyses were used to screen independent predictive factors for high-risk PTMC patients in pathology. A nomogram diagnostic model was further constructed. Additionally, ROC curves and calibration curves were drawn to evaluate the efficiency of the model. In the external validation set, the diagnostic model was indirectly evaluated based on preoperative ultrasound imaging features to explore the feasibility and reliability of diagnosing high-risk PTMC through preoperative ultrasound imaging features.

Results

A total of 1628 patients were included in the training set, and 530 patients were included in the test set. The independent risk factors for pathological high-risk PTMC were sex, age, tumor maximum diameter, tumor invasive, and cervical lymph nodes (P<0.05). The C-index of the nomogram constructed based on these five factors was 0.947, with an optimal sensitivity of 96.7% and a specificity of 86.0%. The calibration curve showed that the model had high consistency. The area under the curve (AUC) value of the ROC curve for high-risk PTMC predicted by the risk score based on ultrasound features was 0.824 [95% CI (0.789, 0.860)], which was highly consistent with the risk score based on pathological features (κ= 0.758, P<0.05).

Conclusion

Indirect evaluation of a high-risk PTMC diagnostic model based on preoperative ultrasound imaging features had high predictive efficiency and potential value for clinical application.

A Comparative Study of Two Radiomics-Based Blood Flow Modes with Thyroid Imaging Reporting and Data System in Predicting Malignancy of Thyroid Nodules and Reducing Unnecessary Fine-Needle Aspiration Rate

RATIONALE AND OBJECTIVES

We aimed to compare superb microvascular imaging (SMI)-based radiomics methods, and contrast-enhanced ultrasound (CEUS)-based radiomics methods to the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) for classifying thyroid nodules (TNs) and reducing unnecessary fine-needle aspiration biopsy (FNAB) rate.

MATERIALS AND METHODS

This retrospective study enrolled a dataset of 472 pathologically confirmed TNs. Radiomics characteristics were extracted from B-mode ultrasound (BMUS), SMI, and CEUS images, respectively. After eliminating redundant features, four radiomics scores (Rad-scores) were constructed. Using multivariable logistic regression analysis, four radiomics prediction models incorporating Rad-score and corresponding US features were constructed and validated in terms of discrimination, calibration, decision curve analysis, and unnecessary FNAB rate.

RESULTS

The diagnostic performance of the BMUS + SMI radiomics method was better than ACR TI-RADS (area under the curve [AUC]: 0.875 vs. 0.689 for the training cohort, 0.879 vs. 0.728 for the validation cohort) (P < 0.05), and comparable with BMUS + CEUS radiomics method (AUC: 0.875 vs. 0.878 for the training cohort, 0.879 vs. 0.865 for the validation cohort) (P > 0.05). Decision curve analysis showed that the BMUS+SMI radiomics method could achieve higher net benefits than the BMUS radiomics method and ACR TI-RADS when the threshold probability was between 0.13 and 0.88 in the entire cohort. When applying the BMUS+SMI radiomics method, the unnecessary FNAB rate reduced from 43.4% to 13.9% in the training cohort and from 45.6% to 18.0% in the validation cohorts in comparison to ACR TI-RADS.

CONCLUSION

The dual-modal SMI-based radiomics method is convenient and economical and can be an alternative to the dual-modal CEUS-based radiomics method in helping radiologists select the optimal clinical strategy for TN management.

Alteration Trend and Overlap Analysis of Positive Features in Different-Sized Benign and Malignant Thyroid Nodules: Based on Chinese Thyroid Imaging Reporting and Data System

Purpose

This study aimed to investigate the alteration trends and overlaps of positive features in benign and malignant thyroid nodules of different sizes based on the Chinese Thyroid Imaging Reporting and Data System (C-TIRADS).

Patients and Methods

1337 patients with 1558 thyroid nodules were retrospectively recruited from November 2021 to December 2023. These nodules were divided into three groups according to maximum diameter: A (≤10 mm), B (10-20 mm), and C (≥20 mm). C-TIRADS positive features were compared between benign and malignant thyroid nodules of different sizes. In addition, the trends of positive features with changes in nodule size among malignant thyroid nodules were analyzed.

Results

The incidence of positive features in malignant thyroid nodules was higher than that in benign. As benign nodules grow, the incidence of all positive features showed a linear decreasing trend (Z values were 72.103, 101.081, 17.344, 33.909, and 129.304, P values < 0.001). With the size of malignant thyroid nodules increased, vertical orientation, solid, marked hypoechogenicity, and ill-defined/irregular margins/extrathyroidal extension showed a linear decreasing trend (Z = 148.854, 135.378, 8.590, and 69.239, respectively; P values < 0.05), while suspicious microcalcifications showed a linear increasing trend (Z = 34.699, P<0.001). In terms of overlapping characteristics, group A had a significantly higher overlapping rate than the other two groups, and the overlapping rate of solid indicators remained the highest among all three groups (P < 0.05).

Conclusion

Differences in positive features were observed between thyroid nodules of different sizes. Except for suspicious microcalcifications, the incidence of other four positive features decreased with increasing nodule size. In addition, a negative correlation was observed between the overlap rate and nodule size. These results may provide a basis for sonographers to upgrade or downgrade thyroid nodules based on their own experience.