Visualizing thyroid health: a pictorial journey through 2017 ACR TI-RADS and common thyroid pathologies

With the advent of high-resolution ultrasonography (HRUS), more thyroid nodules are being detected than ever before, and they are being identified at an earlier stage. It poses a challenge for radiologists and clinicians in deciding what to do next. Most nodules are benign and require no follow-up and intervention. Even highly suspicious nodules can be followed up, if the size is small. Variations in HRUS interpretation among radiologists are common, with frequent misidentifications between spongiform and solid-cystic lesions, hypoechoic and very hypoechoic nodules, and microcalcification and hyperechoic foci with comet-tail artifacts. Cystic lesions with echogenic contents are often confused with solid nodules, cystic papillary carcinoma thyroid is often confused with colloid cysts. The 2017 ACR TI-RADS (American College of Radiology Thyroid Imaging Reporting and Data System) aims to standardize the interpretation of thyroid nodules and guide further management. Rather than giving specific diagnosis like colloid cyst, adenomatous nodule and papillary carcinoma; ACR TI-RADS classifies nodules from TI-RADS 1 to TI-RADS 5 based on HRUS characteristics and recommends further management. What the authors often read are textual contents that are theoretical, and in practice, the authors get confused while interpreting the characteristics of thyroid nodules. This review offers a detailed visual overview of the 2017 ACR TI-RADS and common thyroid conditions, explaining key features through imaging data and examples for consistent interpretation. Combining textual explanations with visual aids, this article provides practical guidance for interpreting thyroid nodules for radiologists, and clinicians seeking a clear understanding of thyroid imaging and pathology.

Differential diagnosis of thyroid nodules by DCE-MRI based on compressed sensing volumetric interpolated breath-hold examination: A feasibility study

OBJECTIVES

To explore the potential and performance of quantitative and semi-quantitative parameters derived from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) based on compressed sensing volumetric interpolated breath-hold (CS-VIBE) examination in the differential diagnosis of thyroid nodules.

MATERIALS AND METHODS

A total of 208 patients with 259 thyroid nodules scheduled for surgery operation were prospectively recruited. All participants underwent routine and DCE-MRI. DCE-MRI quantitative parameters [Ktrans, Kep, Ve], semi-quantitative parameters [wash-in, wash-out, time to peak (TTP), arrival time (AT), peak enhancement intensity (PEI), and initial area under curve in 60 s (iAUC)] and time-intensity curve (TIC) types were analyzed. Differential diagnostic performances were assessed using area under the receiver operating characteristic curve (AUC) and compared with the Delong test.

RESULTS

Ktrans, Kep, Ve, wash-in, wash-out, PEI and iAUC were statistically significantly different between malignant and benign nodules (P < 0.001). Among these parameters, ROC analysis revealed that Ktrans showed the highest diagnostic performance in the differentiation of benign and malignant nodules, followed by wash-in. ROC analysis also revealed that Ktrans achieved the best diagnostic performance for distinguishing papillary thyroid carcinoma (PTC) from non-PTC, follicular adenoma (FA) from non-FA, nodular goiter (NG) from non-NG, with AUC values of 0.854, 0.895 and 0.609, respectively. Type III curve is frequently observed in benign thyroid nodules, accounting for 77.4% (82/106). While malignant nodules are more common in type II, accounting for 57.5% (88/153).

CONCLUSION

Thyroid examination using CS-VIBE based DCE-MRI is a feasible, non-invasive method to identify benign and malignant thyroid nodules and pathological types.

Thyroid Nodule Characterization: Overview and State of the Art of Diagnosis with Recent Developments, from Imaging to Molecular Diagnosis and Artificial Intelligence

Ultrasound (US) is the primary tool for evaluating patients with thyroid nodules, and the risk of malignancy assessed is based on US features. These features help determine which patients require fine-needle aspiration (FNA) biopsy. Classification systems for US features have been developed to facilitate efficient interpretation, reporting, and communication of thyroid US findings. These systems have been validated by numerous studies and are reviewed in this article. Additionally, this overview provides a comprehensive description of the clinical and laboratory evaluation of patients with thyroid nodules, various imaging modalities, grayscale US features, color Doppler US, contrast-enhanced US (CEUS), US elastography, FNA biopsy assessment, and the recent introduction of molecular testing. The potential of artificial intelligence in thyroid US is also discussed.

Implementing active surveillance for low-risk thyroid carcinoma into clinical practice: collaborative recommendations for Latin America

The incidence of thyroid cancer is increasing globally, but mortality rates have remained steady. Many patients with thyroid cancer have low-risk, nonmetastatic intrathyroidal tumors smaller than 2 cm. Active surveillance has shown benefits in these patients, but the adoption of this approach remains below standard in Latin America. The purpose of this article is to identify ways to improve the incorporation of active surveillance into clinical practice for patients with low-risk thyroid carcinoma in Latin America, taking into consideration cultural and geographic factors. Current recommendations include three steps involving patient participation. The first step, which consists of the initial clinical examination, has eight factors requiring special attention. Anxiety must be managed while considering individual, disease-related, cognitive, and environmental aspects. Terms like "overdiagnosis", "incidentaloma," and "overtreatment" must be explained to the patient. Implementing precise terminology contributes to adequate disease perception, substantially reducing stress and anxiety. Clarifying the nonprogressive nature of thyroid cancer helps dispel myths surrounding the disease. The second step includes advice about procedures and guidelines for patients who choose active surveillance. Flexible monitoring techniques should be implemented, with regular check-ins scheduled based on patient needs. Reasons for adjusting treatment must be clearly communicated to the patient, and changes in preference regarding active surveillance should be considered in advance. The third step includes assistance during follow-up. Patients must be educated about ultrasound results and receive surgical indications from specialized physicians. The effectiveness of active surveillance can be reinforced by explaining to the patients the dynamics of changes in nodule size using clear and concise visual aids.

Comparative analysis of the image quality and diagnostic performance of the zooming technique with diffusion-weighted imaging using different b-values for thyroid papillary carcinomas and benign nodules

Objective

To compare image quality and diagnostic performance using different b-values for the zooming technique with diffusion-weighted imaging (ZOOMit-DWI) in thyroid nodules.

Materials and methods

A total of 51 benign thyroid nodules and 50 thyroid papillary carcinomas were included. ZOOMit-DWI was performed with b-values of 0, 500, 1000, 1500 and 2000 s/mm2. The sharpness was evaluated as subjective index. The signal intensity ratio (SIR), signal-to-noise ratio (SNR) and apparent diffusion coefficient (ADC) were measured as objective indices. Pairwise comparisons were performed among the different b-value groups using the Friedman test. A receiver operating characteristic curve of the ADC value was used to evaluate diagnostic performance. The DeLong test was used to compare diagnostic effectiveness among the different b-value groups.

Results

In both the papillary carcinoma group (P = 0.670) and the benign nodule group (P = 0.185), the sharpness of nodules was similar between b-values of 1000 s/mm2and 1500 s/mm2. In the papillary carcinoma group, the SIRnodule was statistically higher in DWI images with a b-value of 1500 s/mm2than in DWI images with b-values of 500 s/mm2(P = 0.004), 1000 s/mm2(P = 0.002), and 2000 s/mm2(P = 0.003). When the b-values were 1500 s/mm2(P = 0.008) and 2000 s/mm2(P = 0.009), the SIRnodule significantly differed between the papillary carcinoma group and the benign nodule group. When b = 500 s/mm2, the ADC had an AUC of 0.888. When b = 1000 s/mm2, the ADC had an AUC of 0.881. When b = 1500 s/mm2, the ADC had an AUC of 0.896. When b = 2000 s/mm2, the ADC had an AUC of 0.871. The DeLong test showed comparable diagnostic effectiveness among the different b-value groups except for between b-values of 2000 s/mm2and 1500 s/mm2, with a b-value of 2000 s/mm2showing lower effectiveness.

Conclusion

This study suggests that 1500 s/mm2may be a suitable b-value to differentiate benign and malignant thyroid nodules in ZOOMit-DWI images, which yielded better image quality.

Ultrasound radiomics based XGBoost model to differential diagnosis thyroid nodules and unnecessary biopsy rate: Individual application of SHapley additive exPlanations

OBJECTIVES

Radiomics-based eXtreme gradient boosting (XGBoost) model was developed to differentiate benign thyroid nodules from malignant thyroid nodules and to prevent unnecessary thyroid biopsies, including positive and negative effects.

METHODS

The study evaluated a data set of ultrasound images of thyroid nodules in patients retrospectively, who initially received ultrasound-guided fine-needle aspiration biopsy (FNAB) for diagnostic purposes. According to ACR TI-RADS, a total of five ultrasound feature categories and the maximum size of the nodule were determined by four radiologists. A radiomics score was developed by the LASSO algorithm from the ultrasound-based radiomics features. An interpretative method based on Shapley additive explanation (SHAP) was developed. XGBoost was compared with ACR TI-RADS for its diagnostic performance and FNAB rate and was compared with six other machine learning models to evaluate the model performance.

RESULTS

Finally, 191 thyroid nodules were examined from 177 patients. The radiomics score were calculated using 8 features, which were selected among 789 candidate features generated from the ultrasound images. The model yielded an AUC of 93% in the training cohort and 92% in the test cohort. It outperformed traditional machine learning models in assessing the nature of thyroid nodules. Compared with ACR TI-RADS, the FNAB rate decreased from 34% to 30% in training and from 35% to 41% in test.

CONCLUSIONS

The radiomics-based XGBoost model proposed could distinguish benign and malignant thyroid nodules, thereby reduced significantly the number of unnecessary FNAB. It was effective in making preoperative decisions and managing selected patients using the SHAP visual interpretation tools.

Reporting of Full-Length Femur Imaging to Detect Incomplete Atypical Femur Fractures: 2023 Official Positions of the International Society for Clinical Densitometry

Incomplete atypical femur fractures (iAFFs) are associated with the long-term use of anti-resorptive therapies. Although X-rays are typically used to screen for iAFFs, images from dual-energy X-ray absorptiometry (DXA) offer an alternate method for detecting iAFFs. Although a previous 2019 ISCD Official Position on this subject exists, our task force aimed to update the literature review and to propose recommendations on reporting findings related to iAFFs that may be observed on DXA images. The task force recommended that full-length femur imaging (FFI) from DXA can be used as a screening tool for iAFFs. The presence of focal lateral cortical thickening and transverse lucencies should be reported, if identified on the FFI. This task force proposed a classification system to determine the likelihood of an iAFF, based on radiographic features seen on the FFI. Lastly, the task force recommended that the clinical assessment of prodromal symptoms (pain) is not required for the assessment of FFI.

Benign thyroid nodules classified as ACR TI-RADS 4 or 5: Imaging and histological features

BACKGROUND

American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) being most widely applied in clinical practice, there is an overlap in US imaging manifestations between benign and malignant thyroid nodules.

OBJECTIVES

To analyze the imaging and histological characteristics of pathological benign thyroid nodules categorized as American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) 4 or 5, and to explore the correlation between the suspicious sonographic signs resulting in the misdiagnoses and the histopathological features.

MATERIALS AND METHODS

Overall, 227 benign thyroid nodules (215 patients) in ACR TI-RADS 4 or 5 sampled through surgical excision were analyzed between December 2020 and August 2022. We retrospectively reread the ultrasound (US) images of the pathological discordant cases, after which we performed a systematic analysis focusing on the histopathological characteristics of thyroid lesions and recorded the findings. Qualitative US features and pathological significance of the thyroid nodules were analyzed using the chi-square and Fisher's exact tests.

RESULTS

The pathological type of 227 thyroid nodules (n = 103 in ACR TI-RADS 4 and n = 124 in ACR TI-RADS 5) was nodular goiter together with other histopathological features, namely, fibrosis (n = 103, 45.4 %), calcification (n = 70, 30.8 %), adenomatous hyperplasia (n = 31, 13.7 %), follicular epithelial hyperplasia (n = 23, 10.1 %), Hashimoto's thyroiditis (n = 18, 7.9 %), and cystic degeneration (n = 16, 7.1 %). Fibrosis was the most common histopathological feature in both ACR TI-RADS 4 (n = 42, 40.8 %) and 5 (n = 61, 49.2 %) categories of benign thyroid nodules. Thyroid nodules with fibrosis demonstrated sonographic features of "taller than wide" (p < 0.05), while lesions with follicular epithelial hyperplasia were likely to be detected with irregular and/or lobulated margins and very hypoechoic on US (p < 0.05 for both).

CONCLUSION

Benign thyroid nodules with histopathological findings such as fibrosis are associated with suspicious US features, which may give inappropriately higher TIRADS stratification.

Quantitative evaluation of diffusion-weighted MRI for differentiating benign and malignant thyroid nodules larger than 4 cm

PURPOSE

Our study aimed to diagnose benign or malignant thyroid nodules larger than 4 cm using quantitative diffusion-weighted imaging (DWI) analysis.

METHODS

Eighty-two thyroid nodules were investigated retrospectively and divided them into benign (n = 62) and malignant groups (n = 20). We calculated quantitative features DWI and apparent diffusion coefficient (ADC) signal intensity standard deviation (DWISD and ADCSD), DWI and ADC signal intensity ratio (DWISIR and ADCSIR), mean ADC and minimum ADC value (ADCmean and ADCmin) and ADC value standard deviation (ADCVSD). Univariate and multivariate logistic regression were conducted to identify independent predictors, and develop a prediction model. We performed receiver operating characteristic (ROC) analysis to determine the optimal threshold of risk factors, and constructed combined threshold models. Our study calculated diagnostic performance including area under the ROC curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and unnecessary biopsy rate of all models were calculated and compared them with the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) result.

RESULTS

Two independent predictors of malignant nodules were identified by multivariate analysis: DWISIR (P = 0.007) and ADCmin (P < 0.001). The AUCs for multivariate prediction model, combined DWISIR and ADCmin thresholds model, combined DWISIR and ADCSIR thresholds model and ACR-TIRADS were 0.946 (0.896-0.996), 0.875 (0.759-0.991), 0.777 (0.648-0.907) and 0.722 (0.588-0.857). The combined DWISIR and ADCmin threshold model had the lowest unnecessary biopsy rate of 0%, compared with 56.3% for ACR-TIRADS.

CONCLUSION

Quantitative DWI demonstrated favorable malignant thyroid nodule diagnostic efficacy. The combined DWISIR and ADCmin thresholds model significantly reduced the unnecessary biopsy rate.

The diagnostic value of ultrasound on different-sized thyroid nodules based on ACR TI-RADS

OBJECTIVES

The thyroid nodule is one of the most common endocrine system diseases. Risk classification models based on ultrasonic features have been created by multiple professional societies, including the American College of Radiology (ACR), which published the Thyroid Imaging Reporting and Data System (TI-RADS) in 2017. The effect of the size in the diagnostic value of ultrasound remains not well defined. The purposes of our study aims to explore diagnostic value of the ACR TI-RADS on different-sized thyroid nodules.

METHODS

A total of 1183 thyroid nodules were selected from 952 patients with thyroid nodules confirmed by surgical pathology from January 2021 to October 2022. Based on the maximum diameters of the nodules, they were stratified into groups A ( ≤ 10 mm), B ( > 10 mm, < 20 mm) and C ( ≥ 20 mm). The ultrasonic features of the thyroid nodules in each group were evaluated and scored based on ACR TI-RADS, and the receiver operating characteristic curve (ROC) was plotted to determine the optimal cut-off value for the ACR TI-RADS scores and categories in each group. Finally, the diagnostic efficacy of ACR TI-RADS on different-sized thyroid nodules was analyzed.

RESULTS

Among the 1183 thyroid nodules, 340 were benign, 10 were low-risk and 833 were malignant. For the convenience of statistical analysis, low-risk thyroid nodules were classified as malignant in this study. The ACR TI-RADS scores and categorical levels of malignant thyroid nodules in each group were higher than those of benign ones (p < 0.05). The areas under the ROCs (AUCs) plotted based on scores were 0.741, 0.907, and 0.904 respectively in the three groups, and the corresponding optimal cut-off values were > 6 points, > 5 points and > 4 points respectively. While the AUCs of the ACR TI-RADS categories were 0.668, 0.855, and 0.887 respectively in each group, with the optimal cut-off values were all > TR4. Besides, for thyroid nodules of larger sizes, ACR TI-RADS exhibited weaker sensitivity with lower positive prediction value (PPV), but the specificity and negative prediction value (NPV) were both higher, presenting with statistically significant differences (p < 0.05).

CONCLUSION

For thyroid nodules of different sizes, the diagnostic efficacy of ACR TI-RADS varies as well. The system shows better diagnostic efficacy on thyroid nodules of > 10 mm than on those ≤ 10 mm. Considering the favorable prognosis of thyroid microcarcinoma and the low diagnostic efficacy of ACR TI-RADS on it, the scoring and classification of thyroid micro-nodules can be left out in appropriate cases, so as to avoid the over-diagnosis and over-treatment of thyroid microcarcinoma to a certain extent.

Prediction of cytology-histology discrepancy when Bethesda cytology reports benign results for thyroid nodules in women: with special emphasis on pregnancy

Objectives: Benign category of Bethesda classification is generally well known to carry a false-negative rate of 0-3%. The current study was designed to investigate the rate of false-negative cytology in patients who underwent thyroidectomy for presumably benign thyroid diseases. Predictive risk factors for false results and malignancy were evaluated along with cytology-histology discrepant cases.Materials and methods: Females who underwent thyroidectomy between May 2014 and December 2022 were included. Demographics, ultrasound (US) features, fine-needle aspiration (FNA) diagnosis, surgical indications and outcomes, final histology reports, risk factors, and malignancy rate were recorded. Cytology-histology discrepant cases were further evaluated for interpretation errors and risk factors. Statistical analyses were performed using Fisher's exact and Mann-Whitney U tests.Results: Of 581 women with a benign thyroid disease who underwent thyroidectomy, 91 was diagnosed as incidental carcinoma (15.6%) and most was T1a (4.9 ± 2.7 mm, 95.6%). Final histology reports revealed mostly papillary carcinoma (93.4%). Predictors of malignancy such as age, family history, previous radiation exposure, and iodine-deficient diet did not help in risk stratification (p > 0.05, for each). However, FNA taken during pregnancy was determined as a risk factor (n = 7, 7.6%, p < 0.05) since it may cause a delay in diagnosis. Cytology-histology discrepant cases were seen to be mostly due to sampling errors (45%, p < 0.05), followed by misinterpretations (37.3%, p < 0.05). There was no reason for discrepancy in 17.5%, and this was linked to inherent nature of thyroid nodule with overlapping cytologic features. Best identifiable risk factor for misinterpretation was pregnancy as well (n = 5, 14.7%, p < 0.05).Conclusions: Risk of malignancy in a presumably benign thyroid disease should not be ignored. Radiology-cytology correlation by an experienced dedicated team may help in decreasing sampling errors. Physiologic changes caused by pregnancy may shade malignant transformation in thyrocytes, and it would be appropriate to be cautious about benign FNA taken during this period.

Deep learning approaches for differentiating thyroid nodules with calcification: a two-center study

BACKGROUND

Calcification is a common phenomenon in both benign and malignant thyroid nodules. However, the clinical significance of calcification remains unclear. Therefore, we explored a more objective method for distinguishing between benign and malignant thyroid calcified nodules.

METHODS

This retrospective study, conducted at two centers, involved a total of 631 thyroid nodules, all of which were pathologically confirmed. Ultrasound image sets were employed for analysis. The primary evaluation index was the area under the receiver-operator characteristic curve (AUROC). We compared the diagnostic performance of deep learning (DL) methods with that of radiologists and determined whether DL could enhance the diagnostic capabilities of radiologists.

RESULTS

The Xception classification model exhibited the highest performance, achieving an AUROC of up to 0.970, followed by the DenseNet169 model, which attained an AUROC of up to 0.959. Notably, both DL models outperformed radiologists (P < 0.05). The success of the Xception model can be attributed to its incorporation of deep separable convolution, which effectively reduces the model's parameter count. This feature enables the model to capture features more effectively during the feature extraction process, resulting in superior performance, particularly when dealing with limited data.

CONCLUSIONS

This study conclusively demonstrated that DL outperformed radiologists in differentiating between benign and malignant calcified thyroid nodules. Additionally, the diagnostic capabilities of radiologists could be enhanced with the aid of DL.

Concordance of the ACR TI-RADS Classification With Bethesda Scoring and Histopathology Risk Stratification of Thyroid Nodules

Importance

Although most thyroid nodules are benign, 10% to 15% of them harbor cancer. Thyroid ultrasonography is useful for risk stratification of nodules, and American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) classification provides recommendations for fine-needle aspiration cytology (FNAC) based on objective ultrasonographic features of these nodules.

Objective

To validate the concordance of ACR TI-RADS classification with Bethesda classification and histopathology.

Design, Setting, and Participants

This retrospective cohort study was performed to evaluate the concordance of ACR TI-RADS classification with Bethesda classification and histopathology and was conducted in Singapore General Hospital Outpatient Otolaryngology clinic in March 2021 to May 2021. Data analysis was performed in May 2021.

Main Outcomes and Measures

Results were deemed concordant when ACR TI-RADS recommendations aligned with Bethesda scores. Conversely, results were classified as nonconcordant with Bethesda scores and/or histopathology results when nodules that were recommended for FNAC yielded benign results or nodules that were not recommended for FNAC yielded malignant results.

Results

A total of 446 patients (370 women [83%]; mean [range] age, 60 [24-89] years) who underwent ultrasonography of the thyroid and ultrasonography-guided thyroid FNACs were identified. A total of 492 of 630 nodules (78.1%) were benign on FNAC (Bethesda II). Score 3 ACR TI-RADS nodules yielded the highest negative predictive values: 94.6% (95% CI, 92.9%-95.9%; P < .001) compared with Bethesda scoring and 100.0% (95% CI, 15.8%-100.0%; P = .003) compared with histopathology. Score 4 or 5 ACR TI-RADS nodules yielded positive predictive values of 2.8% and 16.2%, respectively, compared with Bethesda scoring and 6.1% and 66.7%, respectively, compared with histopathology. Small (<1.5 cm) ACR TI-RADS nodules of scores of 4 and 5 that were not recommended for FNAC yielded a malignant risk of 5.7% and 25.0% on Bethesda 5 and 6, respectively. On surgical excision, 5 of 46 (10.9%) ACR TI-RADS 4 nodules and 15 of 21 (71.4%) of ACR TI-RADS 5 nodules were confirmed to be malignant. Among nodules initially not recommended for FNAC, histopathology-proven cancer was found in 4 of 13 (30.7%) and 3 of 6 (50.0%) of nodules, respectively.

Conclusions and Relevance

These findings suggest that ACR TI-RADS score 3 nodules have a low risk of cancer and should be considered for FNAC only if nodules are 2.5 cm or larger. Patients with small (<1.5 cm) ACR TI-RADS 4 and 5 nodules should be appropriately counseled for FNAC to exclude cancer.

Correlation of ACR TI-RADS and Patient Outcomes in a Real-World Cohort Presenting for Thyroid Ultrasonography

Context

The American College of Radiology Thyroid Image Reporting and Data System (ACR TI-RADS) was developed to predict malignancy risk in thyroid nodules using ultrasound features. TI-RADS was derived from a database of patients already selected for fine-needle aspiration (FNA), raising uncertainty about applicability to unselected patients.

Objective

We aimed to assess the effect of ACR TI-RADS reporting in unselected patients presenting for thyroid ultrasound in a real-world setting.

Methods

Records for all patients presenting for thyroid ultrasonography in Canterbury, New Zealand, were reviewed across two 18-month periods, prior to and after implementation of TI-RADS reporting. Patient outcomes were compared between the 2 periods. Malignancy rates were calculated for nodules 10 mm or larger with a definitive FNA or histology result.

Results

A total of 1210 nodules were identified in 582 patients prior to implementation of TI-RADS; 1253 nodules were identified in 625 patients after implementation of TI-RADS. TI-RADS category was associated with malignancy rate (0% in TR1 and TR2, 3% in TR3, 5% in TR4, 12% in TR5; P = .02); however, 63% of nodules were graded TR3 or TR4, for which malignancy rate did not meaningfully differ from baseline risk. After implementation of TI-RADS there was a small reduction in the proportion of patients proceeding to FNA (49% vs 60%; P < .01) or surgery (14% vs 18%; P < .05), with no difference in cancer diagnoses (3% vs 4%, not significant).

Conclusion

TI-RADS category is associated with malignancy rate and may alter clinical decision-making in a minority of patients; however, it is nondiscriminatory in the majority of nodules. In this study of unselected patients, nodules classified as TR5 and thus considered "highly suspicious" for cancer had only a modest risk of malignancy.

Analysis of 665 thyroid nodules using both EU-TIRADS and ACR TI-RADS classification systems

BACKGROUND

Ultrasound-based classification systems allow stratification of thyroid nodules to recommend fine-needle aspiration (FNA) based on their malignancy risk. However, these have discrepancies that may have an impact in thyroid cancer detection. We aimed to compare European Thyroid Association (EU-TIRADS) and American College of Radiology (ACR TI-RADS), in terms of FNA indication and diagnostic performance.

METHODS

Retrospective study of 665 thyroid nodules from 598 patients who underwent ultrasound and fine-needle aspiration at a tertiary-care institution between January 1st of 2016 and July 31st of 2019. Based on their sonographic features they were classified according to the EU-TIRADS and ACR TI-RADS classification and then their cytological results were obtained. Differences in FNA indications according to these two classifications were analysed. In patients who underwent surgical removal of the nodules, the final pathological diagnosis was obtained.

RESULTS

A statistically significant association was found between EU-TIRADS and ACR TI-RADS classification systems (p < 0.001). ACR TI-RADS allowed greatest reduction in FNA performed (32% vs 24.5%). A different risk category was obtained in 174 (26.1%) nodules, mostly higher with EU-TIRADS. The indication to FNA changed in 54 (8.1%) nodules (49 only indicated following EU-TIRADS recommendations), of which 4 had Bethesda IV and 5 had Bethesda III cytology. The FNA indication in a higher number of nodules using EU-TIRADS was due to difference in the dimensional threshold for FNA on low-risk nodules; to the fact that hypoechogenicity in a mixed nodule ascribes it moderate risk, while using ACR TI-RADS it would only be considered of low risk, and to the use of isolated sonographic features, namely marked hypoechogenicity, microcalcifications and irregular margins, to automatically categorize a nodules as high risk in EU-TIRADS, while ACR TI-RADS requires a group of potentially suspicious features to consider a nodule of high risk. The analysis of pathology proven nodules revealed equally good sensitivity of both systems in the detection of malignancy, but weak specificity, slightly greater with ACR TI-RADS (27.1% vs 18.6%).

CONCLUSIONS

The EU-TIRADS and ACR TI-RADS are both suitable to assess thyroid nodules and through risk stratification avoid unnecessary FNA. FNA was less performed using ACR TI-RADS, which was slightly more efficiency in excluding malignancy.

Increased workload without clinical benefit: Results following implementation of the ACR-TIRADS system for thyroid nodules

OBJECTIVE

The ACR-TIRADS system for stratifying thyroid nodule malignancy risk has been widely promoted and implemented. We audited its introduction at a large public hospital in Auckland, New Zealand.

DESIGN

Audit of outcomes following thyroid nodule fine needle aspiration (FNA) before/after ACR-TIRADS.

PATIENTS

Individuals undergoing thyroid FNA 2017-2019.

MEASUREMENTS

From medical records, we obtained details from the pre-FNA ultrasound (nodule size, TIRADS points/levels, radiologist recommendation for FNA), Bethesda (B) cytology classification, histology and post-FNA follow-up.

RESULTS

Four hundred and twenty-two individuals had 564 FNAs, 163 had surgery and 54 (13%) had cancer in the primary nodule. 37/54 (69%) cancers were papillary thyroid carcinoma (median size 25 mm, 87% ≥10 mm, 61% ≥20 mm). Following ACR-TIRADS introduction, FNA recommendations increased greater than twofold, FNAs performed by 71%-83%, and the monthly rate of FNAs and operations by 60% and 40%, respectively. However, the proportion of cancers/FNA remained similar (9.9% post-TIRADS vs. 8.7% pre-TIRADS). The proportions of FNA results remained stable for B2-B4 categories, but doubled (11% vs. 5%) for B5-B6: 15 FNAs were needed to identify an additional B5/B6 lesion. TIRADS-5 nodules had a higher proportion of B5/B6 (20%) and a lower proportion of B2 (30%) than TIRADS-3 (2%, 57%, respectively) and TIRADS-4 (9%, 56%) nodules. About 5 additional cancers/year were diagnosed, but they were more often small (49% vs. 8% <2 cm, 17% vs. 0% <1 cm).

CONCLUSION

ACR-TIRADS introduction increased workload (FNAs and operations), without increasing the proportion of cancers/FNA. It led to a few more cancers being diagnosed, but many were small and of uncertain clinical significance.

Clinical study of ultrasonic evaluation of T/N staging of differentiated thyroid carcinoma using AJCC 8th staging criteria

Objective

To explore the value of ultrasound in evaluating T/N staging of differentiated thyroid carcinoma (DTC).

Methods

The clinical data of 1206 patients with DTC in our hospital from January 2018 to December 2020 were retrospectively analyzed. Cervical ultrasound was performed before surgery, and the standard ultrasound images of thyroid nodules and cervical lymph nodes I to VII were retained. According to the 8th TNM staging guidelines of AJCC DTC, the T/N stages were assessed by preoperative ultrasonic data. Then, the sensitivity, specificity, negative predicted value, positive predicted value (PPV), and diagnostic value of ultrasound T/N staging were assessed using postoperative pathological staging as the reference.

Results

Ultrasonic T-stage had good consistency to pathological T stage in T4a and T4b tumors (kappa value>0.75), and moderate consistency to pathological T stage in T1, T2 and T3a tumors (kappa value between 0.4 and 0.75). ultrasonic T-stage had a sensitivity higher than 66%, except in T3b assessment (13/44, 29.5%, 95%CI: 16.1%-43.0%). All ultrasonic T-stage had specificity higher than 93%, except in T1b assessment (734/889, 82.6%, 95%CI: 80.1%-85.1%). The PPV of ultrasonic T1a to T4b was 94.3% (494/524), 61.0% (242/397), 54.4% (87/160), 34.3% (12/35), 20.3% (13/64), 100% (22/22) and 100% (4/4), respectively. The diagnostic accuracy values were 83% in T1a, 81% in T1b, 91% in T2, 98% in T3a, 93% in T3b, 99% in T4a and 100% in T4b. Nltrasonic N-stage had poor consistency to pathological N stage in any N stages (kappa value<0.3). The PPV of ultrasonic N0, N1, N1a and N1b was 61.0% (542/889), 55.2% (37/67), 48.2% (53/110), and 24.3% (34/140), respectively.

Conclusion

Ultrasound has a good consistency and high accuracy in assessing the T-stage of DTC. However, the consistency and accuracy were poor in N-staging. It has a certain reference value in reducing excessive surgical treatment of DTC.

Diagnostic Accuracy of Five Different Classification Systems for Thyroid Nodules: A Prospective, Comparative Study

OBJECTIVE

To compare the diagnostic performance of five different thyroid ultrasound classification systems, and determine which system is optimal for evaluating thyroid nodules and reducing the unnecessary biopsy rate.

METHODS

In this prospective study, 1,010 nodules referred for biopsy during a 2-year period were classified using five classification systems: the Kwak Thyroid Imaging Reporting and Data System (Kwak TI-RADS), the European TI-RADS (EU TI-RADS, the Korean TI-RADS (K TI-RADS), the American College of Radiology TI-RADS (ACR TI-RADS), and the American Thyroid Association (ATA) classification. After fine needle aspiration biopsy, all classifications were compared for all nodules and also particularly for nodules sized 1-3 cm. Sensitivity, specificity, and interobserver agreement were evaluated for each classification system.

RESULTS

Of the 939 nodules (after exclusion of Bethesda 3 nodules) finally classified according to the surgical histopathology and cytology results, 73 (7.8%) were malignant and 866 nodules were benign (92.2%). The sensitivity was highest (94.5%) for the ACR TI-RADS and lowest for the Kwak TI-RADS (69%). After exclusion of small (<1 cm) and large nodules (>3 cm); while sensitivity was highest for ATA (97.8%), ACR TI-RADS was the second best classification (91.3%). There was substantial agreement among all classification systems except the Kwak TI-RADS (fair agreement).

CONCLUSIONS

The ACR TI-RADS was the most sensitive ultrasound risk stratification system for all nodules, while the Kwak TI-RADS was the most specific, ie, the most capable of excluding benign nodules based on the combined cytological and histopathological results. ATA and ACR-TIRADS were the most sensitive classification systems for nodules 1 to 3 cm in size. The ACR TI-RADS had higher sensitivity than the Bethesda classification system when compared according to the histopathological results.

Tips for improving consistency of thyroid nodule interpretation with ACR TI-RADS

Thyroid nodules are very common in the general population. Most are benign and even those that are malignant are typically slow-growing and do not require treatment. Overdiagnosis and overtreatment of thyroid nodules has resulted in significant healthcare costs. ACR TI-RADS was developed to address these concerns, and reduce the number of unnecessary biopsies and follow-up intervals. ACR TI-RADS offers a point-based risk stratification system centered on five sonographic features: consistency, echogenicity, shape, margins and echogenic foci. While the system has noticeable benefits and comparable accuracy with other available risk stratification systems (ATA, EU-TIRADS and K-TIRADS), there are inherent challenges relating to suboptimal inter-reader agreement. In this article, we include 10 educational tips that may be helpful to the ultrasound practitioner for improving the consistency of nodule interpretation with ACR TI-RADS.

Consistency of TI-RADS Reporting in Community-Based Imaging Centers vs. a Large Tertiary Hospital

OBJECTIVE

In our country, thyroid nodules are sonographically evaluated in health maintenance organization (HMO) imaging centers, and patients are referred to tertiary hospitals for ultrasound-guided fine needle aspiration (FNA) biopsy when indicated. We evaluated the concordance in Thyroid Imaging Reporting and Data System (TI-RADS) classification reporting between these sites.

METHODS

We conducted a retrospective cohort study reviewing the sonographic features of thyroid nodules evaluated both at the HMO and a large tertiary center between January 2018 and December 2019. The primary outcome was concordance between the TI-RADS classification at both sites. Additional endpoints included correlation of TI-RADS to the Bethesda category following FNA and correlation of TI-RADS with malignancy on final pathology at each site.

RESULTS

The records of 336 patients with 370 nodules were reviewed. The level of concordance was poor (19.8%), with 277 (74.8%) nodules demonstrating higher TI-RADS and 20 (5.4%) lower TI-RADS at the HMO compared to the hospital (p<0.001, weighted Kappa = 0.120). FNA results were available for 236 (63.8%) nodules. The Bethesda category strongly correlated with the hospital TI-RADS (p<0.001), yet not with HMO TI-RADS (p=0.123). In the 57 nodules surgically removed, a strong correlation was identified between malignancy on final pathology and TI-RADS documented at the hospital (p<0.001), yet not at the HMO (p=0.259).

CONCLUSIONS

There is poor agreement between TI-RADS classification on ultrasound performed in the HMO compared to a tertiary hospital. The hospital TI-RADS strongly correlated with Bethesda category and final risk of malignancy unlike the HMO.

Risk stratification of indeterminate thyroid nodules using ultrasound and machine learning algorithms

BACKGROUND

Indeterminate thyroid nodules (Bethesda III) are challenging to characterize without diagnostic surgery. Auxiliary strategies including molecular analysis, machine learning models, and ultrasound grading with Thyroid Imaging, Reporting and Data System (TI-RADS) can help to triage accordingly, but further refinement is needed to prevent unnecessary surgeries and increase positive predictive values.

DESIGN

Retrospective review of 88 patients with Bethesda III nodules who had diagnostic surgery with final pathological diagnosis.

MEASUREMENTS

Each nodule was retrospectively scored through TI-RADS. Two deep learning models were tested, one previously developed and trained on another data set, mainly containing determinate cases and then validated on our data set while the other one trained and tested on our data set (indeterminate cases).

RESULTS

The mean TI-RADS score was 3 for benign and 4 for malignant nodules (p = .0022). Radiological high risk (TI-RADS 4,5) and low risk (TI-RADS 2,3) categories were established. The PPV for the high radiological risk category in those with >10 mm nodules was 85% (CI: 70%-93%). The NPV for low radiological risk in patients >60 years (mean age was 100% (CI: 83%-100%). The area under the curve (AUC) value of our novel classifier was 0.75 (CI: 0.62-0.84) and differed significantly from the chance-level (p < .00001).

CONCLUSIONS

Novel radiomic and radiologic strategies can be employed to assist with preoperative diagnosis of indeterminate thyroid nodules.

Reducing the Number of Unnecessary Thyroid Nodule Biopsies With the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS)

Introduction

Thyroid nodules are exceedingly common, occurring in up to 76% of adults. Less than 10% are palpable, and the majority are detected incidentally with an estimated prevalence of 68%, 25%, and 18% using ultrasound (US), CT, and MRI, respectively. The rising use of imaging over the last four decades has led to a significant increase in nodule detection or ‘over-identification,’ fine-needle aspiration (FNA), a higher reported incidence of thyroid cancer, and thyroidectomy. The purpose of this study is to provide a descriptive experience with thyroid nodule FNAs one year prior and one year after the implementation of the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) at a prototypical community hospital.

Methods

A total of 104 patients with 114 thyroid nodules underwent US-guided FNA at Bluewater Health from January 1, 2018, to March 31, 2020, with available cytological results (The Bethesda System). The study population was divided into two cohorts (January 1, 2018, to December 31, 2018 - ‘local best practice cohort’, and March 1, 2019, to March 31, 2020 - ‘ACR TI-RADS cohort’) based on the implementation of the ACR TI-RADS guidelines in March 2019.

Results

The local best practice cohort (January 1, 2018, to December 31, 2018) comprised 57 thyroid nodules in 52 patients (mean age 66 ± 12; 40 Women). The ACR TI-RADS cohort (March 1, 2019, to March 31, 2020) comprised 57 thyroid nodules in 52 patients (mean age 61 ± 16; 41 Women). There were no statistical differences with respect to age, gender, or thyroid nodule location. Our results show a dramatic decrease in the number of unnecessary FNAs if ACR TI-RADS was implemented from January to December 2018. Thirty (52.6%) of the previously sampled thyroid nodules using the local best practice guidelines would have been followed as per ACR TI-RADS.

Conclusion

ACR TI-RADS is a reliable classification system in routine practice that significantly reduces the number of unnecessary thyroid FNAs with higher specificity compared to local best practice guidelines.

Dual-source dual-energy computed tomography-derived quantitative parameters combined with machine learning for the differential diagnosis of benign and malignant thyroid nodules

Background

This study aimed to investigate the ability of quantitative parameter-derived dual-source dual-energy computed tomography (DS-DECT) combined with machine learning to distinguish between benign and malignant thyroid nodules.

Methods

Patients with thyroid nodules and pathological surgical results who underwent preoperative DS-DECT were selected. Quantitative parameter-derived DS-DECT was applied to classify benign and malignant nodules. Then, machine learning and binary logistic regression analysis models were constructed using the DS-DECT quantitative parameters to distinguish between benign and malignant nodules. The receiver operating characteristic curve was used to assess the diagnostic performance. The DeLong test was used to compare the diagnostic efficacy.

Results

One hundred and thirty patients with 139 confirmed thyroid nodules were involved in the study. The malignant group had a significantly higher iodine concentration_nodule (arterial phase) (P=0.001), normalized iodine concentration (arterial phase) (P=0.002), iodine concentration difference (P<0.001), spectral curve slope (nonenhancement) (P=0.007), spectral curve slope (arterial phase) (P=0.001), effective atomic number (nonenhancement) (P<0.001), and effective atomic number (arterial phase) (P=0.039) than the benign group. The binary logistic regression analysis model had an AUC (area under the curve) of 0.76, a sensitivity of 0.821, and a specificity of 0.667. The machine learning model had an AUC of 0.86, a sensitivity of 0.822, specificity of 0.791 in the training cohort, an AUC of 0.84, a sensitivity of 0.727, and specificity of 0.750 in the testing cohort.

Conclusions

Multiple quantitative parameters of DS-DECT combined with machine learning could differentiate between benign and malignant thyroid nodules.

Diagnostic grading of parotid lesions by conventional ultrasound: a pilot study

OBJECTIVES

To provide a graded diagnosis of benign and malignant lesions in the parotid gland by conventional ultrasound, and thus to predict the probability of malignancy of the lesions.

METHODS

Retrospective analysis of conventional ultrasound images of 150 patients with parotid lesions by two observers. Parotid lesions were classified into seven patterns and then categorized into eight grades: Grade 0, unsatisfied illustration on ultrasound; Grade 1, normal parotid gland; Grade 2, definitively benign; Grade 3, probably benign; Grade 4, indeterminate; Grade 5, probably malignant; Grade 6, highly suggestive malignant and Grade 7, already had malignant diagnosis. Combined with the pathological results, the conventional ultrasound diagnostic grade of parotid lesions was evaluated for predicting the probability of malignancy.

RESULTS

There was excellent interobserver agreement of both readers for patterns and grades (K = 0.89 and 0.90, p < 0.01). The proportions of the malignancies in conventional ultrasound Grade 2, 3, 4, 5 and 6 according to the two readers 0 and 0, 0 and 0, 8.7% and 8.8%, 54.2 and 50%, 100 and 100%, respectively. The sensitivity, specificity and area under ROC curve(AUC) were 64.0%, 91.2%, 0.809 and 64.0%, 89.6%, 0.802, respectively, using Grade 5 of the two readers as the best grade for diagnosing benign and malignant parotid lesions.

CONCLUSION

The conventional ultrasound diagnostic grade of parotid lesions can be used to evaluate the risk of malignancy and will be helpful to improve the imaging diagnosis and clinical treatment.

Evaluation of the efficacy of EU-TIRADS and ACR-TIRADS in risk stratification of pediatric patients with thyroid nodules

BACKGROUND

Pediatric thyroid nodules have a lower prevalence but a higher rate of malignancy (ROM) than those in adults. Ultrasound features suspected of malignancy lead to fine needle aspiration biopsy (FNAB) and subsequent cytological determination, upon which management is decided. Based on the characteristics of ultrasound, to standardize clinician decisions and avoid unnecessary FNAB, the European Thyroid Association and the American Radiology College have established guidelines for Thyroid Imaging, Reporting and Data System (EU-TIRADS and ACR-TIRADS) for ROM stratification of thyroid nodules. The aim of this study is to evaluate the diagnostic performance of ACR-TIRADS and EU-TIRADS in pediatric age.

MATERIALS AND METHODS

Subjects younger than 18 years of age with thyroid nodules greater than 0.5 cm observed in the 2000-2020 period were included.

RESULTS

Data from 200 subjects were collected. The overall ROM was 13%, rising to 26% if nodules with a diameter >1 cm were considered. Patients with a malignant nodule were more likely to have a higher EU-TIRADS score (p=0.03). Missed cancer diagnoses were 26.9%. Using the EU-TIRADS system, 40% of FNABs could have been avoided, while this scoring system would have resulted in FNAB being performed in 12% of cases where the assessment of ultrasound features would not recommend FNAB. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were 73.1%, 57.1%, 73.1%, and 50%, respectively. Even considering the ACR-TIRADS, a higher score correlated with a higher ROM (p<0.001). This system missed 6 diagnoses of cancer (23.1%). Using the ACR-TIRADS system, 45.3% of FNABs could have been avoided, while FNAB should have been performed in 12% of cases where it was not recommended by ultrasound characteristics. Sensitivity, specificity, PPV and NPV were 76.9%, 50%, 76.9%, and 42.9%, respectively.

CONCLUSION

The present study confirms the correspondence of the EU-TIRADS and ACR-TIRADS categories with respect to malignancy but indicates not entirely satisfactory performance compared to FNAB alone. However, the use of the two TIRADS systems should be encouraged in multicentre studies to increase their performance and establish paediatric-specific points in the scoring criteria.

Reconceptualize tall-cell variant papillary thyroid microcarcinoma: From a "sonographic histology" perspective

OBJECTIVE

This study aimed to examine the relationship between sonographic features and histological manifestations in the tall-cell variant of papillary thyroid microcarcinoma (TCV-PTMC), thus proposing the concept of "sonographic histology" and examine its value in the clinical management of the aggressive tall-cell variant.

METHODS

This study retrospectively included 104 participants who were admitted to Peking University Third Hospital from 2015 to 2022 and were histopathologically confirmed as having TCV-PTMC or classical PTMC. We mainly compared the general characteristics, sonographic characteristics, and pathological specimens between the two cohorts.

RESULTS

Hypoechoic nodules with a localized central isoechoic lesion and hypoechoic halo around nodules were most often observed in TCV-PTMC, which correlated with circumferentially distributed tumor epithelium and densely distributed tumor stroma histopathologically. Additionally, TCV-PTMC showed nodules with a more regular margin and less microcalcification than classical PTMC, which led to an underestimation of the risk of TCV-PTMC.

CONCLUSION

The good association between the ultrasound echo pattern and tissue cell arrangement was defined as sonographic histology in this study and can be applied in the preoperative identification of TCV-PTMC. This concept may provide novel insight for the identification of special subtypes of thyroid tumors and may modify pitfalls of the Thyroid Imaging Reporting and Data System in aggressive variants of microcarcinoma.

Texture and shape analysis of diffusion-weighted imaging for thyroid nodules classification using machine learning

PURPOSE

To assess whether the integration between (a) functional imaging features that will be extracted from diffusion-weighted imaging (DWI); and (b) shape and texture imaging features as well as volumetric features that will be extracted from T2-weighted magnetic resonance imaging (MRI) can noninvasively improve the diagnostic accuracy of thyroid nodules classification.

PATIENTS AND METHODS

In a retrospective study of 55 patients with pathologically proven thyroid nodules, T2-weighted and diffusion-weighted MRI scans of the thyroid gland were acquired. Spatial maps of the apparent diffusion coefficient (ADC) were reconstructed in all cases. To quantify the nodules' morphology, we used spherical harmonics as a new parametric shape descriptor to describe the complexity of the thyroid nodules in addition to traditional volumetric descriptors (e.g., tumor volume and cuboidal volume). To capture the inhomogeneity of the texture of the thyroid nodules, we used the histogram-based statistics (e.g., kurtosis, entropy, skewness, etc.) of the T2-weighted signal. To achieve the main goal of this paper, a fusion system using an artificial neural network (NN) is proposed to integrate both the functional imaging features (ADC) with the structural morphology and texture features. This framework has been tested on 55 patients (20 patients with malignant nodules and 35 patients with benign nodules), using leave-one-subject-out (LOSO) for training/testing validation tests.

RESULTS

The functionality, morphology, and texture imaging features were estimated for 55 patients. The accuracy of the computer-aided diagnosis (CAD) system steadily improved as we integrate the proposed imaging features. The fusion system combining all biomarkers achieved a sensitivity, specificity, positive predictive value, negative predictive value, F1-score, and accuracy of 92.9 % (confidence interval [CI]: 78.9 % -- 99.5 % ), 95.8 % (CI: 87.4 % -- 99.7 % ), 93 % (CI: 80.7 % -- 99.5 % ), 96 % (CI: 88.8 % -- 99.7 % ), 92.8 % (CI: 83.5 % -- 98.5 % ), and 95.5 % (CI: 88.8 % -- 99.2 % ), respectively, using the LOSO cross-validation approach.

CONCLUSION

The results demonstrated in this paper show the promise that integrating the functional features with morphology as well as texture features by using the current state-of-the-art machine learning approaches will be extremely useful for identifying thyroid nodules as well as diagnosing their malignancy.

The impact of the use of the ACR-TIRADS as a screening tool for thyroid nodules in a cancer center

BACKGROUND

The Thyroid Imaging Reporting and Data System (TIRADS) was created to assess risk of thyroid nodules through ultrasound. Plenty classifications methods for thyroid nodules have already been created, but none of them have yet achieved global utilization. This study analyzed the performance of the American College of Radiology (ACR) TIRADS, its reproducibility and the impact of its utilization as a screening method in a large Cancer Center cohort.

METHODS

Thyroid nodules which underwent fine-needle aspiration (FNA) in a 1-year period were selected, with their ultrasound images retrospectively classified according to the ACR TI-RADS. Cytological evaluation of the nodules and final histology (whenever available) was used to assess risk of neoplasm (RON) and risk of malignancy (ROM) associated to each ACR-TIRADS category. Further analyses were also carried out according to recommendation or not of FNA by the ACR-TIRADS and nodule size. Inter-observer agreement for the system was also assessed.

RESULTS

A total of 1112 thyroid nodules were included. RON for each category according to final cytological diagnosis was 0% for TR1 and TR2, 2.1% for TR3; 15.6% for TR4 and 68.9% for TR5. No significant difference was observed between the RON of the categories for cases above or below 1.0 cm. Nodules that met the criteria for FNA had 3 times greater chance of a positive outcome. Substantial agreement (kappa 0.77) was seen between two different observers.

CONCLUSIONS

ACR TI-RADS scoring system has demonstrated to be an accurate method to stratify thyroid nodules in a Cancer Center, with a high reproducibility.

Diagnostic performance rates of the ACR-TIRADS and EU-TIRADS based on histopathological evidence

PURPOSE

In this study, we aimed to assess the effectiveness of malignancy stratification algorithms of the American College of Radiology (ACR) and European Thyroid Association (ETA) in the delineation of thyroid nodules using a database of nodules that were unequivocally diagnosed by means of histopathological examination and meticulously matched with the imaged nodules.

METHODS

A total of 165 patients having 251 thyroid nodules with histopathologically proven definitive diagnoses during a 5-year period were included in this study. All patients had preoperatively undergone ultrasonography (US) examination, and US characteristics of the thyroid nodules were retrospectively analyzed and assigned in compliance with the thyroid imaging reporting and data system categories recommended by the ACR (ACR-TIRADS) and ETA (EU-TIRADS). The diagnostic effectiveness in the delineation of thyroid nodules and unnecessary fine-needle aspiration (FNAB) rates were evaluated.

RESULTS

Overall, 189 nodules (75.30%) were diagnosed as benign, while 62 nodules (24.70%) were reported to be malignant based on histopathological assessment. Sensitivity and specificity rates were 71% and 75% for ACR-TIRADS and 73% and 80% for EU-TIRADS. The area under the curve values were 0.78 and 0.80 for ACR-TIRADS and EU-TIRADS, respectively. The unnecessary FNAB rates were 61% for ACR-TIRADS and 64% for EU-TIRADS as per the recommended criteria of each algorithm.

CONCLUSION

The diagnostic performance of both malignancy stratification systems was signified to be moderate and sufficient in a cohort of nodules with definite histopathological diagnosis. In light of our results, we demonstrated the strengths and weaknesses of the ACR- and EU-TIRADS for physicians who should be familiar with them for optimal management of thyroid nodules.

Overview of the Ultrasound Classification Systems in the Field of Thyroid Cytology

The increasing application of ultrasound (US) in recent years has led to a greater number of thyroid nodule diagnoses. Consequently, the number of fine needle aspirations performed to evaluate these lesions has increased. Although the majority of thyroid nodules are benign, identifying methods to define specific lesions and tailor risk of malignancy has become vital. Some of the tools employed to stratify thyroid nodule risk include clinical factors, thyroid US findings, and reporting systems for thyroid cytopathology. Establishing high concordance between US features and cytologic diagnoses might help reduce healthcare costs by diminishing unnecessary thyroid procedures and treatment. This review aims to review radiology US classification systems that influence the practice of thyroid cytology.

Ultrasound Image Classification of Thyroid Nodules Using Machine Learning Techniques

Background and Objectives: Thyroid nodules are lumps of solid or liquid-filled tumors that form inside the thyroid gland, which can be malignant or benign. Our aim was to test whether the described features of the Thyroid Imaging Reporting and Data System (TI-RADS) could improve radiologists' decision making when integrated into a computer system. In this study, we developed a computer-aided diagnosis system integrated into multiple-instance learning (MIL) that would focus on benign-malignant classification. Data were available from the Universidad Nacional de Colombia. Materials and Methods: There were 99 cases (33 Benign and 66 malignant). In this study, the median filter and image binarization were used for image pre-processing and segmentation. The grey level co-occurrence matrix (GLCM) was used to extract seven ultrasound image features. These data were divided into 87% training and 13% validation sets. We compared the support vector machine (SVM) and artificial neural network (ANN) classification algorithms based on their accuracy score, sensitivity, and specificity. The outcome measure was whether the thyroid nodule was benign or malignant. We also developed a graphic user interface (GUI) to display the image features that would help radiologists with decision making. Results: ANN and SVM achieved an accuracy of 75% and 96% respectively. SVM outperformed all the other models on all performance metrics, achieving higher accuracy, sensitivity, and specificity score. Conclusions: Our study suggests promising results from MIL in thyroid cancer detection. Further testing with external data is required before our classification model can be employed in practice.

Convolutional Neural Network to Stratify the Malignancy Risk of Thyroid Nodules: Diagnostic Performance Compared with the American College of Radiology Thyroid Imaging Reporting and Data System Implemented by Experienced Radiologists

BACKGROUND AND PURPOSE

Comparison of the diagnostic performance for thyroid cancer on ultrasound between a convolutional neural network and visual assessment by radiologists has been inconsistent. Thus, we aimed to evaluate the diagnostic performance of the convolutional neural network compared with the American College of Radiology Thyroid Imaging Reporting and Data System (TI-RADS) for the diagnosis of thyroid cancer using ultrasound images.

MATERIALS AND METHODS

From March 2019 to September 2019, seven hundred sixty thyroid nodules (≥10 mm) in 757 patients were diagnosed as benign or malignant through fine-needle aspiration, core needle biopsy, or an operation. Experienced radiologists assessed the sonographic descriptors of the nodules, and 1 of 5 American College of Radiology TI-RADS categories was assigned. The convolutional neural network provided malignancy risk percentages for nodules based on sonographic images. Sensitivity, specificity, accuracy, positive predictive value, and negative predictive value were calculated with cutoff values using the Youden index and compared between the convolutional neural network and the American College of Radiology TI-RADS. Areas under the receiver operating characteristic curve were also compared.

RESULTS

Of 760 nodules, 176 (23.2%) were malignant. At an optimal threshold derived from the Youden index, sensitivity and negative predictive values were higher with the convolutional neural network than with the American College of Radiology TI-RADS (81.8% versus 73.9%, P = .009; 94.0% versus 92.2%, P = .046). Specificity, accuracy, and positive predictive values were lower with the convolutional neural network than with the American College of Radiology TI-RADS (86.1% versus 93.7%, P < .001; 85.1% versus 89.1%, P = .003; and 64.0% versus 77.8%, P < .001). The area under the curve of the convolutional neural network was higher than that of the American College of Radiology TI-RADS (0.917 versus 0.891, P = .017).

CONCLUSIONS

The convolutional neural network provided diagnostic performance comparable with that of the American College of Radiology TI-RADS categories assigned by experienced radiologists.

The global epidemic of thyroid cancer overdiagnosis illustrated using 18 months of consecutive nodule biopsy correlating clinical priority, ACR-TIRADS and Bethesda scoring

Low thyroid cancer mortality worldwide has not been altered by decades of increasing radiological, pathological and surgical intervention for thyroid nodules. Ultrasound-based risk stratification of thyroid nodules, such as TIRADS, has been introduced to reduce intervention for the 'global epidemic' of thyroid cancer 'overdiagnosis'. This article illustrates the use of TIRADS at a New Zealand tertiary centre, during its introduction, with all nodules undergoing fine-needle aspiration biopsy (FNAB) correlated with clinical referral priority and cytological Bethesda score. The correlation between TIRADS and Bethesda score was not significant but cytology had a strong association with clinical priority. Accuracy of TIRADS was poor though the risk of malignancy for TIRADS 5 nodules was 5.1 times those rated as TIRADS 3. After TIRADS was introduced, there was no significant trend in the proportion of malignant nodules diagnosed by FNAB. Despite an incomplete TIRADS programme, the ACR targets of malignancy rates were achieved. The number of patients, as well as the number of nodules per patient, referred for FNAB continues to rise. Changing papillary thyroid cancer nomenclature and other control measures by health policymakers, such as adjustments to payment systems, may be justified. Radiologists are wasting precious health resources that can be better deployed. The use of TIRADS is expensive and a symptom of health policy failure. Clear recommendations from professional societies to not report incidental small thyroid nodules may be a useful start. Whether TIRADS merits continuing use and promotion should be further investigated.

SWE combined with ACR TI-RADS categories for malignancy risk stratification of thyroid nodules with indeterminate FNA cytology

OBJECTIVES

To compare the diagnostic efficacy of shear wave elastography (SWE) comnined with ACR TI-RADS categories for malignancy risk stratification of thyroid nodules with interminate FNA cytology.

METHODS

The clinical data, sonographic features, ACR TI-RADS grading and shear wave elastography images of 193 patients of surgical pathologically proven thyroid nodules with interminate FNA cytology were retrospectively analyzed. The diagnostic efficacy of ACR TI-RADS categories, the maximum Young's modulus (Emax) of SWE and the combination of the two were calculated respectively.

RESULTS

The ROC curves were drawn using surgical pathology results as the gold standard. The ROC curves indicated that the cut-off value of ACR TI-RADS and Emax of SWE was TR5 and 41.2 kPa respectively, and the area under the ROC curve (AUC) was 0.864 (95% CI: 0.879-0.934) and 0.858 (95% CI: 0.796-0.920) respectively. The diagnostic sensitivity, specificity and accuracy of ACR TI-RADS was 81.4% (127/156), 84.8% (31/37), and 81.9% (158/193), respectively. That of SWE Emax was 80.8% (126/156), 78.4% (29/37), and 80.3% (155/193), respectively. After SWE combined with ACR TI-RADS, the sensitivity, specificity and accuracy was 94.2% (147/156), 75.7% (28/37), and 90.7% (175/193), respectively.

CONCLUSIONS

ACR TI-RADS classification system and shear wave elastography had high diagnostic efficacy for thyroid nodules with interminate FNA cytology. The combination of the two could improve diagnostic sensitivity and accuracy, and could help to differentiate benign and malignant thyroid nodules with interminate FNA cytology.

Update on ACR TI-RADS: Successes, Challenges, and Future Directions, From the AJR Special Series on Radiology Reporting and Data Systems

The American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) is an ultrasound-based risk stratification system (RSS) for thyroid nodules that was released in 2017. Since publication, research has shown that ACR TI-RADS has a higher specificity than other RSSs and reduces the number of unnecessary biopsies of benign nodules compared with other systems by 19.9-46.5%. The risk of missing significant cancers using ACR TI-RADS is mitigated by the follow-up recommendations for nodules that do not meet criteria for biopsy. In practice, after a nodule's ultrasound features have been enumerated, the ACR TI-RADS points-based approach leads to clear management recommendations. Practices seeking to implement ACR TI-RADS must engage their radiologists in understanding how the system addresses the problems of thyroid cancer overdiagnosis and unnecessary surgeries by reducing unnecessary biopsies. This review compares ACR TI-RADS to other RSSs and explores key clinical questions faced by practices considering its implementation. We also address the challenge of reducing interobserver variability in assigning ultrasound features. Finally, we highlight emerging imaging techniques and recognize the ongoing international effort to develop a system that harmonizes multiple RSSs, including ACR TI-RADS.

Atypia of undetermined significance/follicular lesions of undetermined significance: What radiologists need to know

Atypia of undetermined significance/follicular lesions of undetermined significance (AUS/FLUS) refers to an intermediate histologic category of thyroid nodules in The Bethesda System for Reporting Thyroid Cytopathology. Although the risk of malignancy in this category was originally cited as 5-15%, recent literature has suggested higher rates of related malignancy ranging from 38% to 55%. Malignant nodules warrant surgery with total thyroidectomy or thyroid lobectomy, whereas benign nodules can be observed or followed with serial ultrasounds (US) based on their imaging characteristics. The management of nodules with a cytopathologic diagnosis of AUS/FLUS can be difficult because theses nodules lie between the extremes of benign and malignant. The management options for such nodules include observation, repeat fine-needle aspiration, and surgery. The use of molecular genetics, the identification of suspicious US characteristics, and the recognition of additional clinical factors are all important in the development of an appropriate, tailored management approach. Institutional factors also play a crucial role.

Ultrasound grading of thyroid nodules using the BTA U-scoring guidelines - Is there evidence of intra-and interobserver variability?

Introduction

U-score ultrasound classification (graded U1-U5) is widely used to grade thyroid nodules based on benign and malignant sonographic features. It is well established that ultrasound is an operator-dependent imaging modality and thus more susceptible to subjective variances between operators when using imaging-based scoring systems. We aimed to assess whether there is any intra- or interobserver variability when U-scoring thyroid nodules and whether previous thyroid ultrasound experience has an effect on this variability.

Methods

A total of 14 ultrasound operators were identified (five experienced thyroid operators, five with intermediate experience and four with no experience) and were asked to U-score images from 20 thyroid cases shown as a single projection, with and without Doppler flow. The cases were subsequently rescored by the 14 operators after six weeks. The first and second round U-scores for the three operator groups were then analysed using Fleiss' kappa to assess interobserver variability and Cochran's Q test to determine any intraobserver variability.

Results

We found no significant interobserver variability on combined assessment of all operators with fair agreement in round 1 (Fleiss' kappa = 0.30, p <0.0001) and slight agreement in round 2 (Fleiss' kappa = 0.19, p < 0.0001). Cochran's Q test revealed no significant intraobserver variability in all 14 operators between round 1 and round 2 (all p>0.05).

Conclusions

We found no statistically significant inter- or intraobserver variability in the U-scoring of thyroid nodules between all participants reinforcing the validity of this scoring method in clinical practice, allaying concerns regarding potential subjective biases in reporting.

Hydrodissection and programmed stop sedation in 100 % of benign thyroid nodules treated with radiofrequency ablation

PURPOSE

To describe our group experience in treatment of benign symptomatic thyroid nodules using radiofrequency ablation technique always associated to routine pre-procedure hydrodissection and under sedation with programmed stop.

METHODS

Dual-center, retrospective study conducted between April 2018 and January 2020. A total of 52 symptomatic benign thyroid nodules were treated in 34 patients with ultrasound-guided percutaneous radiofrequency ablation. The technique of choice was moving-shot technique and 100 % patients underwent pre-procedural hydrodissection with 5% glucose solution, plus conscious sedation with programmed stop during procedure.

RESULTS

Most nodules were solid or almost completely solid (n = 45, 88.3 % of nodules), followed by cystic composition (n = 4, 7.8 %) and mixed (n = 2, 3.9 %). As for location, most were on the right lobe (n = 29, 56.9 %), followed by the left lobe (n = 17, 33.3 %) and isthmus (n = 5, 9.8 %). The average volume of nodules before ablation was 18.2 ± 20.5 mL. Volumetric reduction rates at one, three, six and twelve months after ablation were 46.6 %, 64.5 %, 76.1 % and 88.8 %, respectively. No complications strictly related to procedure were reported. No more than 5 min were added to total time of ablative treatment considering routine hydrodissection and stop programmed sedation.

CONCLUSIONS

Minimally invasive therapies applied to thyroid allow the preservation of healthy thyroid parenchyma and provide a very effective volumetric reduction of symptomatic benign thyroid nodules. Hydrodissection with 5 % glucose solution, conscious sedation and patient stimulation with programmed stop during procedure may provide greater safety to procedure, and, in our experience, could be done routinely in all patients.

Molecular testing and thyroid nodule management in North America

The incidence of thyroid cancer is rising for a variety of reasons. At the same time, the nomenclature revision of non-invasive encapsulated follicular-variant PTC to noninvasive follicular neoplasm with papillary-like nuclear features (NIFTP) has modified the incidence of thyroid cancer. Given that thyroid neoplasia is a molecular event, it is important for the thyroid physician to evaluate each patient systematically. Most thyroid cancers are sporadic; however, some are familial and may be associated with syndromes with genetic implications. Advances in radiologic imaging have made ultrasonography a near equivalent of gross examination. The American College of Radiology Thyroid Imaging, Reporting and Data System (ACR TI-RADS) classifies nodules from TR1 to TR5 and is valuable in determining which patients should be guided toward fine-needle aspiration (FNA) sampling. While FNA procedures and processing may be varied, the key elements are cytologic diagnosis and collection of samples for potential molecular testing. The Bethesda System for Reporting Thyroid Cytology (BSRTC) is commonly used and categorizes each FNA specimen into one of six diagnoses. The indeterminate diagnoses with risk of malignancy (ROM) ranging from 10-75% comprise approximately 30% of thyroid FNA cases and for these, molecular testing is beneficial. In North America, the two most common molecular platforms are Veracyte Afirma GSC and ThyroSeq v3. Both panels cover an extensive array of genomic alterations associated with thyroid neoplasia and a negative result from either test effectively refines the ROM of an Atypia of Undetermined Significance/Follicular Lesion of Undetermined Significance (AUS/FLUS) or Follicular Neoplasm/Suspicious for a Follicular Neoplasm (FN/SFN) diagnosis to 3-4%. Given that the refined ROMs are comparable to that of a Benign BSRTC diagnosis, these patients are recommended for observation of their nodules. However, differences exist in the implication of Afirma GSC-Suspicious and ThyroSeq v3-Positive molecular results with regard to the probability of cancer. For either test, the molecular test result should be integrated with other clinical parameters to determine if surgery is indicated and, if so, the extent of surgery.

Comparison of different systems of ultrasound (US) risk stratification for malignancy in elderly patients with thyroid nodules. Real world experience

PURPOSE

To comparatively assess the performance of three sonographic classification systems, American Thyroid Association (ATA), the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS), and American Association of Clinical Endocrinologists (AACE)/American College of Endocrinology (ACE)/Associazione Medici Endocrinologi (AME) in identifying malignant nodules in an elderly population.

METHODS

Cross-sectional study of patients referred for fine needle aspiration biopsy in an academic center for the elderly. One nodule/patient was considered. Nodules classified Bethesda V/VI were considered malignant. Receiver operating characteristics (ROC) curves were established and compared to evaluate diagnostic performance. Malignancy among biopsies below the size cutoff for each ultrasound classification was also compared.

RESULTS

One thousand, eight hundred sixty-seven patients (92% females); median (Q1-Q3), age 71 (67-76) years, were studied showing 82.8% benign (Bethesda II) and 2.6% malignant cytology. The three classifications correctly identified malignancy (P < 0.01). Nonetheless, in the ATA and AACE/ACE/AME 16 and 2 malignant nodules, respectively, were unclassifiable. Including unclassified malignant nodules (n = 1234, malignant = 50), comparison of the ROC curves showed lower performance of ATA [area under the curve (AUC) = ATA (0.49) vs. ACR TI-RADS (0.62), p = 0.008 and ATA vs. AACE/ACE/AME (0.59), p = 0.022]. Proportion of below size cutoff biopsies for ATA, ACR TI-RADS, and AACE/ACE/AME was different [16, 42, and 29% (all p < 0.001)], but no differences in malignancy rate were observed in these nodules.

CONCLUSION

The present study is the first to validate in elderly patients these classifications showing that AACE/ACE/AME and ACR TI-RADS can predict thyroid malignancy more accurately than the ATA when unclassifiable malignant nodules are considered. Moreover, in this aged segment of the population, the use of ACR TI-RADS avoided more invasive procedures.

The Diagnostic Role of Computed Tomography for ACR TI-RADS 4-5 Thyroid Nodules With Coarse Calcifications

Objectives: Coarse calcifications are prone to cause echo attenuation during ultrasonography (US) and hence affect the classification of benign and malignant nodules. This study aimed to investigate the diagnostic role of computed tomography (CT) for differentiating the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) 4–5 nodules with coarse calcifications.

Methods: CT data of 216 ACR TI-RADS 4–5 nodules with coarse calcifications confirmed by surgery and pathology in 207 patients were analyzed retrospectively. Halo sign, artifacts, and CT values (i.e., Hounsfield unit) of the nodules were determined by two radiologists. Univariate analysis and binary logistic regression were used to determine the relationship of halo sign, artifact, and CT value with benign nodules. A predictive model for benign nodules with coarse calcifications was then constructed. The receiver operating characteristic (ROC) curve was used to analyze the predictive value of halo sign, artifact, CT value, and logistic regression model.

Results: Of the 216 ACR TI-RADS 4–5 nodules with coarse calcifications, 170 were benign and 46 were malignant. There were 92 benign and 7 malignant nodules with halo sign (χ² = 22.067, P < 0.001), and 79 benign and 10 malignant nodules with artifacts (χ² = 9.140, P < 0.001). The CT values of benign and malignant nodules were 791 (543–1,025) Hu and 486 (406–670) Hu, respectively (Z = −5.394, P < 0.001). Binary logistic regression demonstrated that the halo sign, artifact, and CT value were independent predictors for benign nodules with coarse calcifications. The area under the ROC curve (AUC) of halo sign, artifact, CT value and regression model for predicting benign nodules with coarse calcifications were 0.776, 0.711, 0.784, and 0.850, respectively, and the optimal threshold of CT value was 627.5 Hu.

Conclusion: Halo sign, artifact, and CT value > 627.5 Hu were helpful for identifying ACR TI-RADS 4–5 thyroid benign nodules with coarse calcifications. The diagnostic performance of the logistic regression model was higher than that of any single indicator. Accurate identification of these indicators could identify benign nodules and reduce unnecessary surgical trauma.

Hounsfield Unit Values in ACR TI-RADS 4-5 Thyroid Nodules with Coarse Calcifications: An Important Imaging Feature Helpful for Diagnosis

Purpose

The purpose of this study is to investigate the diagnostic role of Hounsfield unit (HU) values on noncontrast computed tomography (CT) for differentiating benignity from malignancy in the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) 4-5 nodules with coarse calcifications.

Patients and Methods

CT images of 216 ACR TI-RADS 4-5 nodules with coarse calcifications from 207 patients who underwent surgery in our hospital between 2017 and 2019 were retrospectively reviewed. The average HU values (AHUVs) and maximum HU values (MHUVs) of the nodules were measured on noncontrast CT. The distribution of AHUVs and MHUVs in benign and malignant nodules with coarse calcifications was analyzed using the Mann-Whitney test. Receiver operating characteristic (ROC) curves were used to identify the best cut-off values. Diagnostic performances were assessed according to the area under the ROC curve (AUC), sensitivity and specificity.

Results

Of the 216 ACR TI-RADS 4-5 nodules with coarse calcifications, 170 were benign and 46 were malignant. The AHUVs of benign and malignant nodules were 791 HU [interquartile range (IQR), 543-1025 HU] and 486 HU (IQR, 406-670 HU), respectively (P < 0.001). The MHUVs of benign and malignant nodules were 1084 HU (IQR, 717-1477 HU) and 677 HU (IQR, 441-986 HU), respectively (P < 0.001). The AUCs for AHUVs and MHUVs for predicting benign nodules with coarse calcifications were 0.759 and 0.732, and the cut-off values were 627.5 HU and 806.0 HU, with sensitivities of 67.6% and 68.8% and specificities of 73.9% and 67.4%, respectively. The sensitivity and specificity of the combination were 68.8% and 76.1%.

Conclusion

AHUVs and MHUVs were helpful in differentiating benignity from malignancy in ACR TI-RADS 4-5 nodules with coarse calcifications. This may provide an important basis for reducing misdiagnosis and unnecessary aspiration or surgical trauma.