Value of Contrast-Enhanced Ultrasound and Acoustic Radiation Force Impulse Imaging for the Differential Diagnosis of Benign and Malignant Thyroid Nodules

Diagnostic efficacy of the contrast-enhanced ultrasound thyroid imaging reporting and data system classification for benign and malignant thyroid nodules

Background

The 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.

Methods

The 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.

Results

Out 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).

Conclusions

In 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.

The common pathogenesis of nodular goiter in both sexes: An exploration into gene expression and signaling pathways

The past few years have witnessed an increasing incidence of nodular goiter (NG), with a well-documented higher prevalence in females than males. This gender disparity has led research to focus primarily on female subjects, potentially overlooking common pathogenic mechanisms in both sexes. In this study, we investigated the shared pathogenesis of NG in males and females. Utilizing a rat model and RNA sequencing, we identified differentially expressed genes associated with the disease. We further validated these findings in normal human thyroid cells and human papillary thyroid cancer cells. A randomized experiment was conducted with equal numbers of male and female rats divided into control and NG model groups. The NG model was established using propylthiouracil and various assessments such as thyroid ultrasonography, thyroid index, thyroid function, and thyroid histology were performed. Transcriptome analysis revealed numerous upregulated and downregulated genes in both male and female model groups. Key genes like KDR, FLT1, PDGFB, and CAV1, and pathways including PI3K-Akt, MAPK, Ras, fluid shear stress and atherosclerosis, calcium signaling, and Rap1 signaling pathways were linked with the disease. Western blot and immunofluorescence analysis confirmed these findings, which were further supported by cell-based experiments. In conclusion, our findings suggest that abnormal expression of specific genes and pathways leading to irregular cell growth, blood vessel formation, and inflammation may be common factors in the pathogenesis of NG in both males and females.

Diagnostic value of combined ultrasound contrast and elastography for differentiating benign and malignant thyroid nodules: a meta-analysis

The diagnostic value of contrast-enhanced ultrasound combined with ultrasound elastography for benign and malignant thyroid nodules is still controversial, so we used meta-analysis to seek controversial answers. The PubMed, OVID, and CNKI databases were searched according to the inclusion and exclusion criteria. The literature was selected from the establishment of each database to February 2024. The QUADAS-2 tool assessed diagnostic test accuracy. SROC curves and Spearman's correlation coefficient were made by Review Manager 5.4 software to assess the presence of threshold effects in the literature. Meta-Disc1.4 software was used for Cochrane-Q and χ2 tests, which be used to evaluate heterogeneity, with P-values and I2 indicating heterogeneity levels. The appropriate effect model was selected based on the results of the heterogeneity test. Stata18.0 software was used to evaluate publication bias. The diagnostic accuracy of contrast-enhanced ultrasound combined with ultrasound elastography for benign and malignant thyroid nodules was evaluated by calculating the combined sensitivity, specificity, positive likelihood ratio, negative likelihood ratio, DOR, and area under the SROC curve. A total of 31 studies included 3811 patients with 4718 nodules were analyzed. There is no heterogeneity caused by the threshold effect, but there is significant non-threshold heterogeneity. Combined diagnostic metrics were: sensitivity = 0.93, specificity = 0.91, DOR = 168.41, positive likelihood ratio = 10.60, and negative likelihood ratio = 0.07. The SROC curve area was 0.97. Contrast-enhanced ultrasound and elastography show high diagnostic accuracy for thyroid nodules, offering a solid foundation for early diagnosis and treatment.Trial registration. CRD42024509462.

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.

The predictive models based on multimodality ultrasonography for the differential diagnosis of thyroid nodules smaller than 10 mm

OBJECTIVE

The objective of this study was to establish a multimodality ultrasound prediction model based on conventional ultrasound (Con-US), shear wave elastography (SWE), and strain elastography (SE) and contrast-enhanced ultrasound (CEUS) and to explore their diagnostic values for thyroid nodules ≤ 10 mm.

METHODS

This retrospective study included 198 thyroid nodules (maximum diameter≤10 mm) in 198 thyroid surgery patients who were examined preoperatively with above-mentioned methods. The pathological findings of the thyroid nodules were used as the gold standard, and there were 72 benign nodules and 126 malignant nodules. The multimodal ultrasound prediction models were developed by logistic regression analysis based on the ultrasound image appearances. The diagnostic efficacy of these prediction models was then compared and internally cross-validated in a fivefold manner.

RESULTS

The specific features on CEUS (enhancement boundary, enhancement direction and decreased nodule area) and the parenchyma-to-nodule strain ratio (PNSR) on SE and SWE ratio were included in the prediction model. The Model one combining American College of Radiology Thyroid Imaging Reporting and Data Systems (ACR TI-RADS) score with PNSR and SWE ratio had the highest sensitivity (92.8%), while the Model three combining TI-RADS score with PNSR, SWE ratio and specific CEUS indicators had the highest specificity, accuracy, and AUC (90.2%,91.4%, and 0.958, respectively).

CONCLUSION

The multimodality ultrasound predictive models effectively improved the differential diagnosis of thyroid nodules smaller than 10 mm.

ADVANCES IN KNOWLEDGE

For the differential diagnosis of thyroid nodules ≤ 10 mm, both ultrasound elastography and CEUS could be effective complements to ACR TI-RADS.

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.

Role of color-coded virtual touch tissue imaging in suspected thyroid nodules

BACKGROUND

Conventional ultrasound (US) is the most widely used imaging test for thyroid nodule surveillance.

OBJECTIVE

We used the color-coded virtual touch tissue imaging (VTI) in the Acoustic Radiation Force Impulse (ARFI) technique to assess the hardness of the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) TR3-5 nodules. The ability of color-coded VTI (CV) to discriminate between benign and malignant nodules was investigated.

METHODS

In this retrospective study, US and CV were performed on 211 TR3-5 thyroid lesions in 181 consecutive patients. All nodules were operated on to obtain pathological results. A multivariate logistic regression model was chosen to integrate the data obtained from the US and CV.

RESULTS

The area under the receiver operating characteristic (ROC) curve for the model was 0.945 (95% CI, 0.914 to 0.976). The cutoff value of predictive probability for diagnosing malignant thyroid nodules was 10.64%, the sensitivity was 94.43%, and the specificity was 83.12%. Through comparing with US and CV, respectively, it had been observed that the regression model had the best performance (all P< 0.001). However, when the US was compared with CV, the difference was not significant (P= 0.3304).

CONCLUSIONS

A combination of US and CV should be recommended for suspected malignant thyroid nodules in clinical practice.

Performance of Contrast-Enhanced Ultrasound in Thyroid Nodules: Review of Current State and Future Perspectives

Ultrasound has been established as a baseline imaging technique for thyroid nodules. The main advantage of adding CEUS is the ability to assess the sequence and intensity of vascular perfusion and hemodynamics in the thyroid nodule, thus providing real-time characterization of nodule features, considered a valuable new approach in the determination of benign vs. malignant nodules. Original studies, reviews and six meta-analyses were included in this article. A total of 624 studies were retrieved, and 107 were included in the study. As recognized for thyroid nodule malignancy risk stratification by US, for acceptable accuracy in malignancy a combination of several CEUS parameters should be applied: hypo-enhancement, heterogeneous, peripheral irregular enhancement in combination with internal enhancement patterns, and slow wash-in and wash-out curve lower than in normal thyroid tissue. In contrast, homogeneous, intense enhancement with smooth rim enhancement and "fast-in and slow-out" are indicative of the benignity of the thyroid nodule. Even though overlapping features require standardization, with further research, CEUS may achieve reliable performance in detecting or excluding thyroid cancer. It can also play an operative role in guiding ablation procedures of benign and malignant thyroid nodules and metastatic lymph nodes, and providing accurate follow-up imaging to assess treatment efficacy.

Value of Conventional Ultrasonography with Contrast-Enhanced Ultrasonography in the Differential Diagnosis of Partial Cystic Thyroid Nodules

The value of contrast-enhanced ultrasonography (CEUS) in the diagnosis of malignant partial cystic thyroid nodules (PCTNs) remains unclear. Thus, in the present study, the data of patients with pathologically proven PCTNs who underwent CEUS in the Chinese PLA General Hospital from January 2016 to February 2019 were retrospectively reviewed, and the imaging characteristics of benign and malignant PCTNs were compared. A total of 177 PCTNs were enrolled in this study, including 58 (32.7%) malignant nodules and 119 (67.2%) benign nodules. Six characteristics significantly differed between malignant PCTNs and benign PCTNs in univariate comparison: position of the solid portion (χ² = 17.937, p < 0.001), microcalcifications (χ² = 81.382, p < 0.001), boundaries (χ² = 45.486, p < 0.001), echogenicity (χ² = 11.152, p = 0.004), intensity of enhancement (χ² = 40.656, p < 0.001) and uniformity of enhancement (χ² = 19.933, p < 0.001). Among these, microcalcifications, boundaries, position of the solid portion, and uniformity of enhancement were independent risk factors in the multivariate comparison. A logistic regression model for predicting benign and malignant PCTNs was established with a sensitivity, specificity, positive predictive value, negative predictive value and accuracy of 89.0% (95% confidence interval [CI]: 0.788-0.961), 91.0% (95% CI: 0.830-0.946), 81.0% (95% CI: 0.715-0.881), 95.0% (95% CI: 0.892-0.974) and 90.0% (95% CI: 0.844-0.938), respectively. The area under the receiver operating characteristic curve was 0.967 (95% CI: 0.944-0.990), which was significantly higher than that of conventional ultrasound only (0.747, 95% CI: 0.663-0.831, Z = 2.090, p = 0.0366). CEUS can be used in the diagnosis of PCTNs, and the four characteristics of malignant PCTNs proven by our study were microcalcifications, unclear boundaries, eccentric distributions of the solid parts and heterogeneous enhancement.

Hierarchical Temporal Attention Network for Thyroid Nodule Recognition Using Dynamic CEUS Imaging

Contrast-enhanced ultrasound (CEUS) has emerged as a popular imaging modality in thyroid nodule diagnosis due to its ability to visualize vascular distribution in real time. Recently, a number of learning-based methods are dedicated to mine pathological-related enhancement dynamics and make prediction at one step, ignoring a native diagnostic dependency. In clinics, the differentiation of benign or malignant nodules always precedes the recognition of pathological types. In this paper, we propose a novel hierarchical temporal attention network (HiTAN) for thyroid nodule diagnosis using dynamic CEUS imaging, which unifies dynamic enhancement feature learning and hierarchical nodules classification into a deep framework. Specifically, this method decomposes the diagnosis of nodules into an ordered two-stage classification task, where diagnostic dependency is modeled by Gated Recurrent Units (GRUs). Besides, we design a local-to-global temporal aggregation (LGTA) operator to perform a comprehensive temporal fusion along the hierarchical prediction path. Particularly, local temporal information is defined as typical enhancement patterns identified with the guidance of perfusion representation learned from the differentiation level. Then, we leverage an attention mechanism to embed global enhancement dynamics into each identified salient pattern. In this study, we evaluate the proposed HiTAN method on the collected CEUS dataset of thyroid nodules. Extensive experimental results validate the efficacy of dynamic patterns learning, fusion and hierarchical diagnosis mechanism.

Value of Combining Clinical Factors, Conventional Ultrasound, and Contrast-Enhanced Ultrasound Features in Preoperative Prediction of Central Lymph Node Metastases of Different Sized Papillary Thyroid Carcinomas

Purpose

Early and accurate preoperative diagnosis of central lymph node metastasis (CLNM) is crucial to improve surgical management of patients with clinical lymph node-negative papillary thyroid carcinoma (PTC). Towards improving diagnosis of CLNM, we assessed the value of combining preoperative clinical characteristics, conventional ultrasound, and contrast-enhanced ultrasound (CEUS) in preoperative prediction of CLNM of different sized PTCs.

Patients and Methods

Patients were divided according to tumor size: a PTC group (>10 mm) and a papillary thyroid microcarcinoma (PTMC) group (≤10 mm). We retrospectively analyzed the clinical and ultrasonographic features of 120 PTC patients and 165 PTMC patients. Multivariate logistic regression analysis was used to screen independent risk factors and establish prediction models. Receiver operating characteristic curves were used to determine the best cut-off values for continuous variables and assess the performance of prediction models.

Results

Independent risk predictors of CLNM for the PTC group were extrathyroidal extension in CEUS (OR=7.923), tumor size >14 mm (OR=5.491), and multifocality (OR=3.235). For the PTMC group, the independent risk factors were the distance from the thyroid capsule =0 mm (OR=4.629), male (OR=3.315), tumor size >5 mm (OR=3.304), and microcalcification (OR=2.560). The predictive model of combined method had better performance in predicting CLNM of PTC compared with models based on CEUS and conventional ultrasound alone (area under the curve: 0.832 vs 0.739, P=0.0011; 0.832 vs 0.678, P=0.0012). For PTMC, comparing with CEUS, the combined method and conventional ultrasound performed better than CEUS alone in predicting CLNM (area under the curve: 0.783 vs 0.636, P=0.0016; 0.738 vs 0.636, P=0.0196).

Conclusion

The predictive models of combined method obtained from significant preoperative clinical and ultrasonographic features can potentially improve the preoperative diagnosis and individual treatment of CLNM in patients with PTC and PTMC. CEUS may be helpful in predicting CLNM of PTC, but CEUS would be ineffective in predicting CLNM of PTMC.

Value of image-pro plus for assisting virtual touch tissue imaging in the diagnosis of thyroid nodules

PURPOSE

The value of virtual touch tissue imaging (VTI) with support of Image-Pro Plus (IPP) for diagnosing malignant thyroid tumors was assessed in the present study.

METHODS

In this retrospective study, we enrolled 160 patients with 198 thyroid nodules. TI-RADS, VTI grade, and VTI with support of IPP (VTI-IPP) were underwent for each nodule. With the pathological diagnosis as the gold standard, the receiver-operating characteristic curve (ROC) was drawn to evaluate the diagnostic performance of VTI-IPP, VTI, TI-RADS, VTI-IPP combinate with TI-RADS in thyroid carcinoma.

RESULTS

VTI-IPP score >2, VTI score >3, TI-RADS score >1, and VTI-IPP combine with TI-RADS score >4 expressed the highest diagnostic value for malignant thyroid nodules, the areas under the curve (AUC) were 0.939, 0.905, 0.925, and 0.967, respectively. The combination indicated the largest AUC, compared with VTI-IPP and TI-RADS, respectively (P = 0.0054 and 0.0009). The performance of VTI-IPP in diagnosing thyroid carcinomas was better than VTI (P = 0.0321).

CONCLUSION

Compare with VTI, VTI-IPP exhibited more excellent value in distinguishing between benign and malignant thyroid nodules. The value of malignant thyroid nodules diagnosis can be improved when VTI-IPP combines with TI-RADS.

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

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.

Differential diagnosis of thyroid nodules through a combination of multiple ultrasonography techniques: A decision-tree model

The present study aimed to establish a decision tree (DT) model by combining the parameters of conventional gray-scale ultrasonography (US), elastosonography (ES), color Doppler US (CDUS) and contrast-enhanced US (CEUS) for the differential diagnosis of thyroid nodules. A single-center, retrospective study of 321 thyroid nodules was conducted. For 222 nodules, parameters of conventional gray-scale US, CDUS, ES and CEUS were evaluated using univariate logistic regression. Factors for with P<0.10 were further assessed using multivariate logistic regression. Significant factors (P<0.05) were used to establish a DT. The diagnostic accuracy of this DT was then evaluated by its application to the other 99 nodules. After univariate logistic analysis, factors including gender, number of nodules and diffuse disease were excluded, due to P>0.10. The results of multivariate logistic analysis determined that the following factors were required for the DT: Extent of blood flow determined by CDUS (P=0.002), area ratio determined by ES (P=0.033), peak phase patterns determined by CEUS (P<0.001) and micro-calcification determined by conventional gray-scale US (P=0.015). When compared to the pathological or cytological results of 99 nodules, the resulting DT had a sensitivity of 98.6%, specificity of 80.1%, positive predictive value of 93.5% and negative predictive value of 95.5%. These results suggested that a DT combining conventional gray-scale US, ES, CDUS and CEUS may be helpful for differentiating between types of thyroid nodules.

Thyroid FNA: Is cytopathologist review of ultrasound features useful?

Cytopathologist review of thyroid ultrasound (US) has been proposed to be useful in diagnosis and patient triage. This review explores the implications for practicing cytopathologists of integrating US review into the thyroid fine-needle aspiration diagnosis. At present, there is no agreed-upon system for combining cytologic and US features and communicating those results as a single report. If cytologists are performing tasks that require expertise in US interpretation, then they should know and be fully conversant with US interpretation. Whether cytologists performing aspirations require expertise in US interpretation is not clear. Regardless, cytologists should avoid using US results to alter their cytologic interpretations unless they clearly communicate that this is what they are doing. An evidence-based integrated reporting system that would allow cytologists to clearly explain to other physicians exactly how they reached their interpretation might provide value beyond current standard practice.