Impact of the ultrasonography assessment method on the malignancy risk and diagnostic performance of five risk stratification systems in thyroid nodules

The Utility of Contrast-Enhanced Ultrasound (CEUS) in Assessing the Risk of Malignancy in Thyroid Nodules

BACKGROUND

Ultrasonography is a primary method used in the evaluation of thyroid nodules, but no single feature of this method predicts malignancy with high accuracy. Therefore, this paper aims to assess the utility of contrast-enhanced ultrasound (CEUS) in the differential diagnosis of thyroid nodules.

METHODS

The study group comprised 188 adult patients (155 women and 33 men) who preoperatively underwent CEUS of a thyroid nodule classified as Bethesda categories II-VI after fine-needle aspiration biopsy. During the CEUS examination, 1.5 mL of SonoVue contrast was injected intravenously, after which 15 qualitative CEUS enhancement patterns were analysed.

RESULTS

The histopathologic results comprised 65 benign thyroid nodules and 123 thyroid carcinomas. The dominant malignant CEUS features, such as hypo- and heterogeneous enhancement and slow wash-in phase, were evaluated, whereas high enhancement, ring enhancement, and a slow wash-out phase were assessed as predictors of benign lesions. Two significant combinations of B-mode and CEUS patterns were noted, namely, hypoechogenicity with heterogeneous enhancement and non-smooth margins with hypo- or iso-enhancement.

CONCLUSIONS

The preliminary results indicate that CEUS is a useful tool in assessing the risk of malignancy of thyroid lesions. The combination of the qualitative enhancement parameters and B-mode sonographic features significantly increases the method's usefulness.

Malignancy risk stratification and subcategorization of K-TIRADS intermediate suspicion thyroid nodules: a retrospective multicenter study

PURPOSE

This study aimed to develop the ultrasonography (US) criteria for risk stratification of the Korean Thyroid Imaging Reporting and Data System (K-TIRADS) 4 nodules, and to evaluate the diagnostic yield of a modified biopsy criterion in a multicenter cohort.

METHODS

In total, 1,542 K-TIRADS 4 nodules (≥1 cm) were included in the study. US criteria for the subcategorization of K-TIRADS 4 nodules were developed based on high-risk US features. The diagnostic yields and false referral rates of biopsy criterion 1 (size cut-off of 1 cm), biopsy criterion 2 (size cut-off of 1.5 cm), and modified biopsy criterion 3 (size cut-off of 1 cm for K-TIRADS 4B and 1.5 cm for K-TIRADS 4A) were evaluated.

RESULTS

The five high-risk US features (solid composition, marked hypoechogenicity, macrocalcification, punctate echogenic foci, and irregular margin) independently increased the malignancy risk of the K-TIRADS 4 nodules (P<0.001). The K-TIRADS 4 nodules could be subcategorized into higher- and lower-risk subcategories according to the number of high-risk US features: K-TIRADS 4B (≥2 US features) and K-TIRADS 4A (≤1 US feature). The modified biopsy criterion increased the diagnostic yield by 7.8% compared with criterion 2 and reduced the false referral rate by 15.3% compared with criterion 1 (P<0.001).

CONCLUSION

The K-TIRADS 4 nodules were subcategorized as K-TIRADS 4B and K-TIRADS 4A based on high-risk US features. The modified biopsy criterion 3 showed a similar diagnostic yield and reduced false referral rate compared to criterion 1.

Ultrasonographic predictors of thyroid cancer in Bethesda III and IV thyroid nodules

Background

Bethesda III and IV thyroid nodules continue to be difficult to manage. Although molecular testing may assist in decision-making, it is expensive, not widely available, and not without pitfalls. The objective of this study is to assess whether certain thyroid ultrasonographic features may predict the risk of thyroid cancer in patients with Bethesda III and IV thyroid nodules and be used as additional decision-making tools to complement cytopathological results in deciding on diagnostic thyroidectomy.

Methods

We retrospectively evaluated the ultrasonographic features of Bethesda categories III and IV thyroid nodules in patients who underwent subsequent thyroidectomy. We used the final histopathological examination of the surgical specimens as the gold-standard test and analyzed individual preoperative ultrasonographic features as predictors of malignancy.

Results

Of the 278 patients who were diagnosed with Bethesda III and IV thyroid nodules on fine needle aspiration cytology (FNAC), 111 (39.9%) had thyroid cancer, and 167 (59.9%) exhibited benign nodules. The malignancy rate was higher in patients with Bethesda IV nodules (28/50, 56%) than those with Bethesda III nodules (83/228, 36.4%; p=0.016). In univariate analysis, hypoechogenicity (55.6% in malignant vs. 35.3% in benign, p=0.006) and calcifications (54.5 in malignant vs. 35.4% in benign, p=0.008) were significantly different between the benign and malignant pathology groups, whereas the size of the dominant nodule, number of nodules, irregular borders, taller-than-wide shape, and the presence of lymph nodes were comparable between the two groups. These two ultrasonographic features (hypoechogenicity and calcifications) remained significantly associated with the risk of malignancy in multivariate logistic regression analysis (for hypoechogenicity, p=0.014, odds ratio: 2.1, 95% CI:1.0-3.7 and for calcifications, p=0.019, odds ratio: 1.98, 95% CI:1.12-3.50). The sensitivity, specificity, positive and negative predictive values, and accuracy were 31.5%, 83%, 55.6%,64.7%, and 62.6%, for hypoechogenicity, respectively and 32.4%, 82%, 54.5%, 67.8%, and 62%, for calcification, respectively.

Conclusions

Hypoechogenicity and calcifications in Bethesda III and IV thyroid nodules are strong predictors of thyroid cancer and associated with a two-fold increased risk of malignancy.

Real-Time Ultrasonography and the Evaluation of Static Images Yield Different Results in the Assessment of EU-TIRADS Categories

The studies on the effectiveness of various TIRADS in the diagnostics of thyroid nodules differ in the method of ultrasound image assessment: real time (rtUS) vs. static ultrasonography (stUS). The aim of the study was to evaluate the impact of those two methods on the categorization of nodules in EU-TIRADS. Three experienced raters assessed 842 nodules in routine rtUS and reassessed with the use of sUS. Reproducibility of the assessment of malignancy risk features and categorization of nodules with EU-TIRADS was estimated with Krippendorff's alpha coefficient (Kα). The reproducibility of EU-TIRADS categories on sUS in relation to rtUS was in range 70.9-76.5% for all raters (Kα: 0.60-0.68) with the highest reproducibility for category 3 (80.0-86.5%) and the lowest for category 5 (48.7-77.8%). There was a total disagreement of the identification of microcalcifications on sUS in relation to rtUS, a strongly variable reproducibility of marked hypoechogenicity (12.5-84.6%, Kα: 0.14-0.48) and a tendency toward more frequent identification of the non-oval shape on sUS. The percentage of agreement for each pair of raters in assigning the EU-TIRADS category on sUS was in the range 71.6-72.3% (Kα: 0.60-0.62). The method of sonographic image evaluation influences the nodule's feature assessment and, eventually, the categorization within EU-TIRADS.

A Reappraisal of Suspicious Sonographic Features of Thyroid Nodules: Shape Is Not an Independent Predictor of Malignancy

CONTEXT

For the correct clinical application of the sonographic risk-stratification systems, the definition of independent risk features that are foundational to each system is crucial.

OBJECTIVE

The aim of this study was to identify the gray-scale sonographic features independently associated with malignancy, and to compare different definitions.

METHODS

This prospective, diagnostic accuracy study took place in a single thyroid nodule referral center. All patients consecutively referred to our center for fine-needle aspiration cytology of a thyroid nodule between November 1, 2015 and March 30, 2020, were enrolled before cytology. Each nodule was examined by 2 experienced clinicians to record the sonographic features on a rating form. Histologic (when available) or cytologic diagnosis was used as the reference standard. For each single sonographic feature and definition, the sensitivity, specificity, positive and negative predictive values, and diagnostic odds ratios (DOR) were calculated. The significant predictors were then included in a multivariable regression model.

RESULTS

The final study cohort consisted of 903 nodules in 852 patients. A total of 76 nodules (8.4%) were malignant. Six features were independent predictors of malignancy: suspicious lymph node (DOR 16.23), extrathyroidal extension (DOR 6.60), irregular or infiltrative margins (DOR 7.13), marked hypoechogenicity (DOR 3.16), solid composition (DOR 3.61), and punctate hyperechoic foci (including microcalcifications and indeterminate foci; DOI 2.69). Taller-than-wide shape was not confirmed as an independent predictor.

CONCLUSION

We identified the key suspicious features of thyroid nodules and provided a simplified definition of some debated ones. Malignancy rate increases with number of features.

Malignancy Risk of Thyroid Nodules That Are Not Classifiable by the American Thyroid Association Ultrasound Risk Stratification System: A Systematic Review and Meta-Analysis

Background: Sonographic evaluation is fundamental to thyroid nodule assessment. The American Thyroid Association (ATA) ultrasound risk stratification system (USRSS) is widely used, but the appearance of some nodules has been considered nonclassifiable (NC-ATA). The risk of malignancy (RoM) of NC-ATA nodules varies widely between studies, leading to uncertainty in clinical management. The aim of this study was to comprehensively evaluate the prevalence and malignancy risk of NC-ATA nodules. Methods: A systematic review was performed searching PubMed/MEDLINE and EMBASE to identify original studies of thyroid nodules classified using the ATA USRSS from 2016 to 2022 and reporting the outcome of NC-ATA nodules. Meta-analysis was conducted to obtain pooled RoM estimates and meta-regression sensitivity analyses were used to explore sources of between-study heterogeneity. Results: Of 6377 screened studies, 135 underwent full-text review, and 16 studies reporting 21,271 nodules were included. Within these, the pooled prevalence of NC-ATA nodules was 7.8% (1872 nodules; [confidence interval; CI 5.1-11.1]). The pooled RoM estimate for NC-ATA nodules was 20.3% [CI 13.0-28.7] and there was significant heterogeneity between studies (I2 = 92.8%, p < 0.001). NC-ATA nodule RoM estimates were significantly different by study type: single-center versus multicenter studies (24.8% vs. 12.3%, respectively, p = 0.031) and study design: retrospective versus prospective studies (25.1% vs. 8.5%, respectively, p = 0.003). No significant difference was observed in RoM based on inclusion of <1 cm nodules or geographic region. Meta-regression analysis showed study design and use of surgical histology for diagnostic criteria contributed significantly to differences in the reported RoM estimates. Conclusion: In this first meta-analysis comprehensively assessing the RoM of NC-ATA nodules, the malignancy risk was found to be comparable with the current ATA USRSS intermediate suspicion category. Significant heterogeneity was observed between studies and limits the interpretation of these results. In future iterations of the ATA USRSS that seek into incorporate categorization of NC-ATA nodules, these meta-analysis data may help to inform proper malignancy risk stratification. The study protocol was registered on PROSPERO, the international prospective register of systematic reviews (CRD42020182498), on July 14, 2020.

A prospective comparison of ACR-TIRADS and EU-TIRADS in thyroid nodule assessment for FNA-US

OBJECTIVE

Prospective data on the accuracy of ultrasound (US) classification systems in thyroid nodules are still scarce. The aim of this study is to compare the accuracy of the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) and European (EU)-TIRADS classification systems.

DESIGN AND PATIENTS

Consecutive patients with one or more thyroid nodule(s) who underwent fine-needle aspiration (FNA) under ultrasonographic guidance (FNA-US) were prospectively evaluated.

MEASUREMENTS

Clinical evaluation and US data were collected. The reference standard used for this study was FNA-US cytology and histopathological diagnosis.

RESULTS

A total of 186 thyroid nodules in 166 patients were evaluated, resulting in 168 nodules from 149 patients with conclusive benign or malignant results. Sensitivity, specificity, negative predictive value (NPV) and false negative (FN) were 100.0%, 28.7%, 100.0% and 0.0%, respectively, for ACR-TIRADS; and 90.0%, 19.1%, 96.8% and 9.1% (n = 1), respectively, for EU-TIRADS. The number of unnecessary FNA-US indicated by ACR-TIRADS was lower than EU-TIRADS (71.3% vs. 80.9%, p = .017), and the number of possibly avoided FNA-US was higher (26.7% vs. 17.8%). Using the same threshold of ACR-TIRADS to indicate FNA-US in EU-TIRADS 3 nodules (2.5 cm), there was an improvement in specificity (30.6%) and avoided FNA-US (28.6%). The best performance of both systems was demonstrated when FNA-US would be indicated only in highly suspicious nodules and/or in the presence of lymphadenopathy, with 85.7% and 89.3% of possibly avoided FNA-US for ACR-TIRADS and EU-TIRADS, respectively, without increasing FN.

CONCLUSION

Both systems presented high sensitivity, but low specificity in selecting nodules for FNA-US. The use of nodular size for FNA-US selection is questioned.

Accuracy of Ultrasound Diagnosis of Thyroid Nodules Based on Artificial Intelligence-Assisted Diagnostic Technology: A Systematic Review and Meta-Analysis

BACKGROUND

Ultrasonography (US) is the most common method of identifying thyroid nodules, but US images require an experienced surgeon for identification. Many artificial intelligence (AI) techniques such as computer-aided diagnostic systems (CAD), deep learning (DL), and machine learning (ML) have been used to assist in the diagnosis of thyroid nodules, but whether AI techniques can improve the diagnostic accuracy of thyroid nodules still needs to be explored.

OBJECTIVE

To clarify the accuracy of AI-based thyroid nodule US images for differentiating benign and malignant thyroid nodules.

METHODS

A search strategy of "subject terms + key words" was used to search PubMed, Cochrane Library, Embase, Web of Science, China Biology Medicine (CBM), and China National Knowledge Infrastructure (CNKI) for studies on AI-assisted diagnosis of thyroid nodules based on US images. The summarized receiver operating characteristic (SROC) curve and the pooled sensitivity and specificity were used to assess the performance of the diagnostic tests. The quality assessment of diagnostics accuracy studies-2 (QUADAS-2) tool was used to assess the methodological quality of the included studies. The Review Manager 5.3 and Stata 15 were used to process the data. Subgroup analysis was based on the integrity of data collection.

RESULTS

A total of 25 studies with 17,429 US images of thyroid nodules were included. AI-assisted diagnostic techniques had better diagnostic efficacy in the diagnosis of benign and malignant thyroid nodules: sensitivity 0.88 (95% CI: (0.85-0.90)), specificity 0.81 (95% CI: 0.74-0.86), diagnostic odds ratio (DOR) 30 (95% CI: 19-46). The SROC curve indicated that the area under the curve (AUC) was 0.92 (95% CI: 0.89-0.94). Threshold effect analysis showed a Spearman correlation coefficient: 0.17 < 0.5, suggesting no threshold effect for the included studies. After a meta-regression analysis of 4 different subgroups, the results showed a statistically significant effect of mean age ≥50 years on heterogeneity. Compared with studies with an average age of ≥50 years, AI-assisted diagnostic techniques had higher diagnostic performance in studies with an average age of <50 years (0.89 (95% CI: 0.87-0.92) vs. 0.80 (95% CI: 0.73-0.88)), (0.83 (95% CI: 0.77-0.88) vs. 0.73 (95% CI: 0.60-0.87)).

CONCLUSIONS

AI-assisted diagnostic techniques had good diagnostic efficacy for thyroid nodules. For the diagnosis of <50 year olds, AI-assisted diagnostic technology was more effective in diagnosis.