Differentiation of Thyroid Nodules Difficult to Diagnose With Contrast-Enhanced Ultrasonography and Real-Time Elastography

Diagnostic value of CEUS combined with C-TIRADS for indeterminate FNA cytological thyroid nodules

OBJECTIVES

To investigate the diagnostic value of CEUS combined with C-TIRADS for indeterminate FNA cytological thyroid nodules.

METHODS

The clinical data, ultrasonic images, C-TIRADS categories and CEUS images of 192 patients with indeterminate FNA cytological thyroid nodules confirmed by the surgical pathology were analyzed retrospectively. The diagnostic efficacy of CEUS, C-TIRADS and CEUS-TIRADS were calculated.

RESULTS

The AUCs of CEUS, C-TIRADS and CEUS-TIRADS were 0.905 (95% CI: 0.862∼0.949), 0.881 (95% CI: 0.825∼0.938) and 0.954 (95% CI: 0.922∼0.986), respectively. The sensitivity, specificity, PPV, NPV, accuracy, LR- and LR+ were 84.7% (116/137), 85.5% (47/55), 93.5% (116/124), 69.1% (47/68), 84.9% (163/192), 0.179, 5.82 and 84.7% (116/137), 83.6% (46/55), 92.8% (116/125), 68.7% (46/67), 84.4% (162/192), 0.183, 5.17, 92.7% (127/137), 89.1% (49/55), 95.5% (127/133), 83.1% (49/59), 91.7% (176/192), 0.082, and 8.50, respectively. Compared with CEUS and C-TIRADS, CEUS-TIRADS had improved the AUC, sensitivity and accuracy (all P < 0.05).

CONCLUSIONS

CEUS and C-TIRADS had high diagnostic values in indeterminate FNA cytological thyroid nodules. CEUS-TIRADS improved AUC, diagnostic sensitivity and accuracy, and helped to distinguish indeterminate FNA cytological 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.

Evaluation of the ultrasound findings of thyroid gland enlargement in Cape Coast Teaching Hospital, Ghana: A retrospective cross-sectional study

Background and Aim

Goiter is a major source of morbidity in the world, especially in the developing world, where dietary iodine deficiency, a known cause of this condition, is endemic. The diagnosis is mostly by ultrasonography (USG) scan, which can give anatomical, pathological, and functional information for the management of goiter. This study aimed to determine the commonest ultrasound findings of goiter in Ghana.

Method

The records of all 213 patients with goiter diagnosed by USG scan over a 5-year period were retrieved. Data collected were sociodemographics, ultrasound features, thyroid nodules diameter, and Thyroid Imaging Reporting and Data System (TI-RADS) scores, which were analyzed using GNU PSPP, version 1.2.0-3. χ 2 and two-tailed independent samples t-test were also employed, with p ≤ 0.05.

Results

A total of 213 patients with goiter diagnosed by USG scan were obtained over the study period. The mean age of the participants was 50.01 ± 17.27 years, with an age range of 16-92 years and females constituting the majority (82.16%). The commonest ultrasound features were well-defined solid nodules. The lesion sites for most patients were the whole thyroid (28.17%), both lobes (24.41%), and the right lobe (20.19%). The mean difference in sizes of cysts and solid nodules among genders was 0.26 (CI: -0.14 to 0.67, p = 0.20) and 0.12 (CI: -0.43 to 0.66, p = 0.67), respectively. The TI-RADS score featured TI-RADS 4 (36.62%), TI-RADS 1 (28.17%), TI-RADS 3 (25.82%), TI-RADS 5 (5.16%), and TI-RADS 2 (4.23%). Solid nodules (49.32%, p = 0.001) and cysts (35.71%, p = 0.003) were more common within 41-60 years and less frequent in those <21 years. A p ≤ 0.05 was considered significant in this study.

Conclusion

The predominant ultrasound features were well-defined solid nodules, simple cysts, and solid nodules with cystic changes, mostly located in the entire thyroid gland and least located in the isthmus only. Cysts and solid nodules were mostly seen in the 41-60 years age group.

Thyroid ultrasound and its ancillary techniques

Ultrasound (US) of the thyroid has been used as a diagnostic tool since the late 1960s. US is the most important imaging tool for diagnosing thyroid disease. In the majority of cases a correct diagnosis can already be made in synopsis of the sonographic together with clinical findings and basal thyroid hormone parameters. However, the characterization of thyroid nodules by US remains challenging. The introduction of Thyroid Imaging Reporting and Data Systems (TIRADSs) has improved diagnostic accuracy of thyroid cancer significantly. Newer techniques such as elastography, superb microvascular imaging (SMI), contrast enhanced ultrasound (CEUS) and multiparametric ultrasound (MPUS) expand diagnostic options and tools further. In addition, the use of artificial intelligence (AI) is a promising tool to improve and simplify diagnostics of thyroid nodules and there is evidence that AI can exceed the performance of humans. Combining different US techniques with the introduction of new software, the use of AI, FNB as well as molecular markers might pave the way for a completely new area of diagnostic accuracy in thyroid disease. Finally, interventional ultrasound using US-guided thermal ablation (TA) procedures are increasingly proposed as therapy options for benign as well as malignant thyroid diseases.

Diagnostic value of qualitative and quantitative parameters of contrast-enhanced ultrasound for differentiating differentiated thyroid carcinomas from benign nodules

Objective

To explore the diagnostic value of contrast-enhanced ultrasound (CEUS) of qualitative and quantitative parameters for differentiating differentiated thyroid cancers from benign nodules.

Method

A total of 290 thyroid nodules that were pathologically confirmed were enrolled in this study. The univariate analysis was performed for the clinical characteristics and CEUS qualitative and quantitative parameters of the inside and peripheral zone of nodules, including age, gender, nodule size, intensity of enhancement, homogeneity, wash-in and wash-out patterns, margin after CEUS, ring enhancement, peak intensity, sharpness, time to peak(TP), and area under the curve(AUC), and the meaningful indicators in the single-factor analysis were further included in multivariate logistic regression analysis.

Results

Multivariate analysis showed that there were significant differences in age (p=0.031), nodule size (p<0.001), heterogeneous enhancement (p<0.001), hypo-enhancement (p=0.001), unclear margin after CEUS(p=0.007), inside peak (p<0.001), and outside sharpness(p<0.001) between benign and malignant nodules. However, there were no significant differences in gender, ring enhancement, wash-in, wash-out, outside TP, outside AUC between benign and malignant thyroid nodules (P>0.05, for all).

Conclusion

CEUS might be useful in the differential diagnosis of differentiated thyroid cancers and benign nodules, which could provide a certain basis for clinical treatment.

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 Sonographic Appearance and Survival Outcomes of 69 Cases of Primary Thyroid Lymphoma Over 10 Years

OBJECTIVES

To investigate ultrasound appearance and the survival outcomes for patients with primary thyroid lymphoma (PTL).

METHODS

Ultrasonic images and clinical characteristics from pathologically confirmed 69 PTL patients (2008-2019) were retrospectively analyzed. The clinical characteristics, ultrasonic characters, and prognostic factors were analyzed. Survival curves were plotted using the Kaplan-Meier method. Univariate and multivariate analyses were performed.

RESULTS

Of the 69 study patients, 23 were indolent PTL and 46 were aggressive PTL. Age (>70 years old) and elevated lactate dehydrogenase levels were statistically different clinical features between aggressive and indolent PTL. From ultrasonic images, 34 cases were nodular, 11 diffuse, and 24 mixed pattern. Mixed types displayed high invasiveness (45.7%) while diffuse types displayed higher inertness (39.1%), with statistically significant differences (P = .000). Invaded thyroid capsule and increased chaotic vascularity also showed significant differences between aggressive and indolent PTL. We also observed statistical difference in overall survival rates between aggressive and indolent PTL (P = .032). Single factor K-M analyses showed that age >70 years, aggressive pathology, and Ki67 >30% were positively correlated with the risk of poor PTL survival (P < .05).

CONCLUSIONS

Multimodal ultrasound provides accurate ultrasonographic information and facilitates PTL invasiveness diagnostics for improved clinical treatment. In addition, PTL patients aged >70 years, with aggressive pathology, and Ki67 >30% were more likely to have a poor survival outcome.

Differential diagnosis of diffuse sclerotic thyroid papillary carcinoma and Hashimoto's thyroiditis using fine-needle aspiration cytology, BRAFV600E , and ultrasound elastography

BACKGROUND

The diffuse sclerosing variant of papillary thyroid carcinoma (DSV-PTC) has ultrasound findings that are similar to Hashimoto's thyroiditis (HT), resulting in under-diagnosis. DSV-PTC combined with HT is also common, so early and accurate diagnosis of DSV-PTC using a variety of diagnostic techniques, including FNAC, BRAF^V600E mutation detection, and ultrasound elastography, is critical.

OBJECTIVE

To assess the diagnostic value of fine-needle aspiration cytology (FNAC) and BRAF^V600E detection in combination with ultrasound elastography in the diagnosis of DSV-PTC.

METHODS

We performed a retrospective analysis of 40 patients with pathologically confirmed DSV-PTC and 43 patients with HT admitted to our hospital's ultrasound department between January 2015 and December 2020. Preoperative FNAC, BRAF^V600E mutation detection, and ultrasound elastography imaging were all performed on all patients. For a definitive diagnosis, the results of these tests were compared to postoperative pathological findings. The diagnostic value of FNAC, BRAF^V600E mutation detection, ultrasound elasticity imaging, and their combination for DSV-PTC diagnosis was assessed.

RESULTS

The mean elastic strain rate ratio (E1/E2) of the 40 DSV-PTC cases was 5.75 ± 2.14, while that of the 43 HT cases was 2.81 ± 1.20. The receiver operating characteristic (ROC) curve was generated using the average value of E2/E1. The area under the ROC curve was 0.910, and the optimal E2/E1 cut-off value was 4.500. When FNAC, BRAF^V600E mutation detection, and ultrasound elasticity imaging detection were combined, the diagnostic sensitivity, specificity, negative predictive value, positive predictive value, and accuracy of DSV-PTC diagnosis were 92.5%, 95.3%, 93.2%, 94.9%, and 94.0%, respectively, which were significantly higher than the single technique (p < 0.05).

CONCLUSIONS

The use of FNAC, BRAF^V600E mutation detection, and ultrasound elastography in combination is more helpful in establishing an accurate diagnosis of DSV-PTC than using a single diagnostic technique alone.

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.

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.

High-performance sonographical multimodal imaging of non cystic thyroid lesions: Chances of the preoperative diagnostics in relation to histopathology

AIM:

To improve preoperative diagnostics of solid non-cystic thyroid lesions by using new high-performance ultrasound techniques: optimized B-mode morphology, elastography, Color-Coded Doppler-Sonography (CCDS) and contrast enhanced ultrasound (CEUS)

MATERIALS AND METHODS:

In 33 cases solid, non-cystic thyroid lesions were rated as TIRADS 3 and up from conventional B-mode examinations. Additional high resolution Power Doppler including HR- and Glazing-Flow as optimized macrovascularization techniques, shear wave elastography and CEUS were performed on these patients by one experienced examiner. For CEUS a bolus of 1–2.4 ml Sulfurhexafluorid microbubbles (SonoVue®, Bracco, Milan, Italy) was injected into a cubital vein and then the distribution kinetics of the contrast agent were documented from the early arterial phase (10 to 15 seconds after injection) to the late venous phase (5 minutes after injection). Postoperative histopathology was the diagnostic gold standard as it provides the most reliable proof.

RESULTS:

33 patients (13 males, 20 females; age 29 –77 years; mean 55 years; SD 13 years) were included in this study. 28 of them had benign regressive thyroid nodules, 3 had adenomas and 4 were diagnosed with carcinomas (3 were histologically identified as papillary thyroid carcinomas, one as a medullary thyroid carcinoma). The volume of the thyroid gland ranged from 6.6 to 401.3 cm² (mean 72.6±92.0 cm²).

The adenoma diameters ranged from 9 to 40 mm (mean 22±16 mm) and the carcinoma diameters ranged from 19 to 33 mm (mean 26±6 mm). The 3 adenomas had different echogenicities: One was completely echofree, one was hypoechoic and one isoechoic. The 4 carcinomas however were equally characterized as hypoechoic and echofree. Two of three adenomas and all of the carcinomas showed an incomplete or diffuse margin. Micro-calcifications were found in one adenoma and in every carcinoma. However, no micro-calcifications were observed in cases of benign regressive nodules.

Performing shear-wave elastography the adenomas showed lower values than the carcinomas: The tissue velocity of the adenomas ranged from 2.86 m/s to 3.85 m/s (mean 3.32±0.5 m/s) and in carcinomas from 3.89 m/s to 5.66 m/s (mean 4.18±0.3 m/s).

Marginal hypervascularization was detected in two adenomas after applying CCDS. One adenoma was hypovascularized. The four carcinomas showed an irregular extreme hypervascularization along their margins as well as an irregular central normo- or hypervascularization in CCDS. The additional HR-Flow helped reducing artefacts.

In CEUS the dynamic capillary microvascularization of all carcinomas was very irregular with early enhancement and followed by partial or complete wash-out. In CEUS two adenomas had no wash-out and the other one showed a partial wash-out.

CONCLUSION:

Using modern multimodal imaging offers new possibilities for the differentiation between benign and malignant thyroid lesions. It is a very important diagnostic tool in addition to the B-Mode TIRADS classification and eases the decision between TIRADS 3, 4 and 5. However, additional multicenter studies are required for more detailed evaluations.

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.

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.

[Imaging of Mediastinal Tumors]

In computed tomography, the mediastinum is split into ventral prevascular, middle visceral and dorsal paravertebral compartments. Each compartment contains specific tumours which will be presented and discussed briefly. The focus is on image-based analysis of morphological signs to differentiate between entities using X-rays, ultrasound, CT and MRI. It is however difficult to differentiate between various types of lesions based on morphology and to estimate the grade of malignancy. For this reason, functional imaging techniques like PET and MRI are essential tools for detailed and non-invasive work-up. If a histological tissue examination is required, these tissue samples can be acquired using CT guided biopsies with high diagnostic yield and low complication rates.