Diagnostic Performance Evaluation of Practice Guidelines, Elastography and Their Combined Results for Thyroid Nodules: A Multicenter Study

Using multimodal ultrasound including full-time-series contrast-enhanced ultrasound cines for identifying the nature of thyroid nodules

Background

Based on the conventional ultrasound images of thyroid nodules, contrast-enhanced ultrasound (CEUS) videos were analyzed to investigate whether CEUS improves the classification accuracy of benign and malignant thyroid nodules using machine learning (ML) radiomics and compared with radiologists.

Materials and methods

The B-mode ultrasound (B-US), real-time elastography (RTE), color doppler flow images (CDFI) and CEUS cines of patients from two centers were retrospectively gathered. Then, the region of interest (ROI) was delineated to extract the radiomics features. Seven ML algorithms combined with four kinds of radiomics data (B-US, B-US + CDFI + RTE, CEUS, and B-US + CDFI + RTE + CEUS) were applied to establish 28 models. The diagnostic performance of ML models was compared with interpretations from expert and nonexpert readers.

Results

A total of 181 thyroid nodules from 181 patients of 64 men (mean age, 42 years +/- 12) and 117 women (mean age, 46 years +/- 12) were included. Adaptive boosting (AdaBoost) achieved the highest area under the receiver operating characteristic curve (AUC) of 0.89 in the test set among 28 models when combined with B-US + CDFI + RTE + CEUS data and an AUC of 0.72 and 0.66 when combined with B-US and B-US + CDFI + RTE data. The AUC achieved by senior and junior radiologists was 0.78 versus (vs.) 0.69 (p > 0.05), 0.79 vs. 0.64 (p < 0.05), and 0.88 vs. 0.69 (p < 0.05) combined with B-US, B-US+CDFI+RTE and B-US+CDFI+RTE+CEUS, respectively.

Conclusion

With the addition of CEUS, the diagnostic performance was enhanced for all seven classifiers and senior radiologists based on conventional ultrasound images, while no enhancement was observed for junior radiologists. The diagnostic performance of ML models was similar to senior radiologists, but superior to those junior radiologists.

Incorporation of CEUS and SWE parameters into a multivariate logistic regression model for the differential diagnosis of benign and malignant TI-RADS 4 thyroid nodules

PURPOSE

To investigate the diagnostic value of contrast-enhanced ultrasound (CEUS) quantitative analysis parameters combined with shear wave elastography (SWE) quantitative parameters in the differentiation of benign and malignant ACR TI-RADS category 4 thyroid nodules and to provide a more effective reference for clinical work.

METHODS

We analyzed 187 category 4 nodules, including 132 nodules in the development cohort and 55 nodules in the validation cohort, divided the development cohort into benign and malignant groups, and analyzed the differences in all CEUS and SWE quantitative parameters between the two groups. We selected the highest AUC of the two parameters, performed binary logistic regression analysis with the ACR TI-RADS score and constructed a diagnostic model. ROC curves were applied to evaluate their diagnostic efficacy.

RESULTS

1) The diagnostic model had an AUC of 0.926, sensitivity of 87.5%, specificity of 86.8%, diagnostic threshold of 3, accuracy of 87.12%, positive predictive value of 86.15%, and negative predictive value of 88.06%. 2) The diagnostic model had an AUC of 0.890 in the validation cohort, sensitivity of 81.5%, specificity of 79.6%, and accuracy of 80.00%.

CONCLUSION

The combined multiparameter construction of the nodule diagnostic model can effectively improve the diagnostic efficacy of 4 types of thyroid nodules and provide a new reference index for clinical diagnostic work.

Application value of gray-scale ultrasound and shear wave elastography in differential diagnosis of thyroid nodules

BACKGROUND

The global prevalence of thyroid cancer has increased significantly in recent years. Ultrasonography is the preferred method for differentiating benign and malignant thyroid nodules preoperatively and is recommended by guidelines.

OBJECTIVE

To assess the application value of gray-scale ultrasound and shear wave elastography in distinguishing small thyroid nodules.

METHODS

A retrospective analysis of 228 thyroid nodules, all of which were confirmed by pathology after surgery or FNA from January 2019 to January 2020, was carried out. All nodules were divided into a ⩽ 5 mm group and a > 5 mm group according to their maximum size. We compared the differences in the gray scale and elastography of the nodules between the two groups and the accuracy of different diagnostic methods.

RESULTS

The accuracies of gray-scale ultrasound and shear wave elastography in the ⩽ 5 mm group were found to be lower than those in the > 5 mm group, and the gray-scale accuracy was slightly higher than that of shear wave elastography in both groups (p< 0.05). The largest AUC (area under the curve) of elastic parameters in the ⩽ 5 mm and > 5 mm groups was found for Emax and Esd, respectively. Based on a combination of these two parameters, the accuracies of the two groups were significantly higher than those of the parameters or gray scale alone (p< 0.05) and were 84.62% and 85.48%, respectively.

CONCLUSION

Shear wave elastography is valuable in the diagnosis of benign and malignant thyroid nodules using ultrasonography. When combining gray-scale ultrasound and shear wave elastography, the diagnostic accuracy is obviously improved, especially for ⩽ 5 mm small thyroid nodules.