American College Of Radiology Thyroid Imaging Reporting And Data System Research Articles

Diagnostic Performance of European and American College of Radiology Thyroid Imaging Reporting and Data System Classification Systems in Thyroid Nodules Over 20 mm in Diameter

ObjectiveThe challenge of selecting thyroid nodules for fine needle aspiration (FNA) cytology has led to the development of the Thyroid Imaging Reporting and Data System, primarily in 2 formats: European Thyroid Imaging Reporting and Data System (EU-TIRADS) and American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS). Clinical observations suggest imperfect risk assessment for TIRADS 3 nodules ≥20 mm. This study aimed to evaluate the efficacy of TIRADS systems in distinguishing benign from malignant nodules in this subgroup. MethodsFrom May 2023 to March 2024, 1094 patients with thyroid nodules were referred for ultrasound at a University Hospital. Data on clinical, ultrasound, cytological, and histopathological parameters were collected. Nodules ≥20 mm were categorized by EU-TIRADS and ACR-TIRADS, and their predictive performance for malignancy was assessed through postthyroidectomy histopathology or FNA cytology (Bethesda classification). ResultsTwo hundred sixty-seven patients (mean age 60.3 ± 14.3 years; 46 men, 221 women) with 308 nodules were analyzed. Twenty-two malignancies and 286 benign nodules were recorded. Recalculating European Thyroid Imaging Reporting and Data System 3 performance using 25-mm and 30-mm thresholds (ACR-modified EU-TIRADS) avoided 24% and 41% of FNAs, respectively, while ACR-TIRADS would prevent 26.6% (P > .05). Two malignancies were missed. ConclusionEU-TIRADS and ACR-TIRADS show similar efficacy when using a 25 mm FNA threshold. Raising the cutoff for FNA in European Thyroid Imaging Reporting and Data System 3 nodules could reduce unnecessary procedures but may increase the risk of missed malignancies, impacting patient outcomes.

Performance of ACR-TIRADS in assessing thyroid nodules does not vary according to patient age.

A few studies have evaluated the performance of the American College of Radiology Thyroid Imaging Reporting And Data System (ACR-TIRADS) in pediatric and elderly patients and found differences between the latter two age groups and middle adulthood. Thus, the present study was undertaken to explore the possible variation of ACR-TIRADS performance across different ages of patients. A retrospective population undergoing thyroidectomy was selected to use histology as the reference standard. Ultrasound images were reviewed, and alignment of ACR-TIRADS with the corresponding histological diagnosis was made afterwards. Results of the age groups were compared. The ACR-TIRADS diagnostic performance was calculated considering the assessment of nodules across risk categories (i.e., from TR1 to TR5), rate of unnecessary FNAC (UN-FNAC), and rate of necessary but non-performed FNAC (NNP-FNAC). Overall, 114 patients with a total of 220 nodules (46 carcinomas) were included. The rate of UN-FNAC was 66.3%, being 93.1% in TR3, 82.1% in TR4, and 31.4% in TR5. There were 15 NNP-FNACs. No significant difference was observed between age groups in terms of sample size, nodule, cancer, and FNAC. The nodule assessment according to ACR-TIRADS categories did not vary across ages. Sensitivity and specificity recorded in three age tertiles were not significantly different. The present study shows that the performance of ACR-TIRADS is not significantly influenced by patient age.

A Multi-View Deep Learning Model for Thyroid Nodules Detection and Characterization in Ultrasound Imaging.

Thyroid Ultrasound (US) is the primary method to evaluate thyroid nodules. Deep learning (DL) has been playing a significant role in evaluating thyroid cancer. We propose a DL-based pipeline to detect and classify thyroid nodules into benign or malignant groups relying on two views of US imaging. Transverse and longitudinal US images of thyroid nodules from 983 patients were collected retrospectively. Eighty-one cases were held out as a testing set, and the rest of the data were used in five-fold cross-validation (CV). Two You Look Only Once (YOLO) v5 models were trained to detect nodules and classify them. For each view, five models were developed during the CV, which was ensembled by using non-max suppression (NMS) to boost their collective generalizability. An extreme gradient boosting (XGBoost) model was trained on the outputs of the ensembled models for both views to yield a final prediction of malignancy for each nodule. The test set was evaluated by an expert radiologist using the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS). The ensemble models for each view achieved a mAP0.5 of 0.797 (transverse) and 0.716 (longitudinal). The whole pipeline reached an AUROC of 0.84 (CI 95%: 0.75-0.91) with sensitivity and specificity of 84% and 63%, respectively, while the ACR-TIRADS evaluation of the same set had a sensitivity of 76% and specificity of 34% (p-value = 0.003). Our proposed work demonstrated the potential possibility of a deep learning model to achieve diagnostic performance for thyroid nodule evaluation.

Thyroid imaging reporting and data system with MRI morphological features for thyroid nodules: diagnostic performance and unnecessary biopsy rate

BackgroundTo assess MRI-based morphological features in improving the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) for categorizing thyroid nodules.MethodsA retrospective analysis was performed on 728 thyroid nodules (453 benign and 275 malignant) that postoperative pathology confirmed. Univariate and multivariate logistic regression analyses were used to find independent predictors of MRI morphological features in benign and malignant thyroid nodules. The improved method involved increasing the ACR-TIRADS level by one when there are independent predictors of MRI-based morphological features, whether individually or in combination, and conversely decreasing it by one. The study compared the performance of conventional ACR-TIRADS and different improved versions.ResultsAmong the various MRI morphological features analyzed, restricted diffusion and reversed halo sign were determined to be significant independent risk factors for malignant thyroid nodules (OR = 45.1, 95% CI = 23.2–87.5, P < 0.001; OR = 38.0, 95% CI = 20.4–70.7, P < 0.001) and were subsequently included in the final assessment of performance. The areas under the receiver operating characteristic curves (AUCs) for both the conventional and four improved ACR-TIRADSs were 0.887 (95% CI: 0.861–0.909), 0.945 (95% CI: 0.926–0.961), 0.947 (95% CI: 0.928–0.962), 0.945 (95% CI: 0.926–0.961) and 0.951 (95% CI: 0.932–0.965), respectively. The unnecessary biopsy rates for the conventional and four improved ACR-TIRADSs were 62.8%, 30.0%, 27.1%, 26.8% and 29.1%, respectively, while the malignant missed diagnosis rates were 1.1%, 2.8%, 3.7%, 5.4% and 1.2%.ConclusionsMRI morphological features with ACR-TIRADS has improved diagnostic performance and reduce unnecessary biopsy rate while maintaining a low malignant missed diagnosis rate.

Diagnostic Efficiency of ACR-TIRADS Score for Differentiating Benign and Malignant Thyroid Nodules of Various Pathological Types.

BACKGROUND Thyroid nodule prevalence reaches 65% in the general population. Hence, appropriate ultrasonic examination is key in disease monitoring and management. We investigated the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) score for diagnosis of benign and malignant thyroid nodules and pathological types. MATERIAL AND METHODS A retrospective study was conducted. According to ultrasound images, ultrasonic characteristics of benign and malignant thyroid nodules and different pathological types were analyzed using ACR-TIRADS score, and diagnostic value was determined. AUCs were compared for tumor diagnosis and differentiation. RESULTS Overall, 1675 thyroid nodules from 1614 patients were included. AUC value of papillary thyroid carcinoma (PTC) diagnosed with ACR-TIRADS was highest (0.955 [95% CI=0.946-0.965]), while that of follicular thyroid carcinoma (FTC) was lowest (0.877 [95% CI=0.843-0.912]). FTC had the highest sensitivity (95.1%) and lowest specificity (64.8%). When the cut-off value was 5.5 points, accuracy of diagnosing PTC and anaplastic thyroid carcinoma (ATC) was highest, 80.5% and 78.7% respectively. Comparison of the multi-index prediction model constructed by multivariable logistic regression analysis and prediction model constructed by ACR-TIRADS score showed, when evaluating PTC and ATC, the multi-index model was better: AUCs of PTC were 0.966 vs 0.955, and AUCs of ATC were 0.982 vs 0.952, respectively, (P<0.05). CONCLUSIONS ACR-TIRADS score-based ultrasound examination of thyroid nodules aids diagnosis of benign and malignant thyroid nodules. TIRADS criteria favor diagnosis of PTC (and ATC) over FTC. ACR-TIRADS score can help clinicians diagnose thyroid nodules quickly and earlier, exhibits good clinical value, and can prevent missed diagnoses.

Correlation of ultrasound features in the TIRADS scoring system with cytological findings in the FNAC of thyroid nodules and their association with the metabolic status

BackgroundThyroid nodules were widely encountered in the population, and the selection of thyroid nodules for fine needle aspiration cytology (FNAC) remains confusing. It is essential to investigate the risk factors associated with thyroid nodules.Aim of workThis study aimed to evaluate the accuracy of the American College of Radiology-Thyroid Imaging Reporting and Data System (ACR-TIRADS) scoring system in distinguishing malignant thyroid nodules from benign ones and its association with cytological examination of the FNAC of the thyroid nodules. Additionally, we seek to investigate any potential association between thyroid nodules and some metabolic derangements.Patients and methodsThe study included 111 Egyptian patients with euthyroid nodules whom were subjected to history taking, clinical examination, and laboratory investigations including thyroid profile, fasting blood sugar (FBS), glycosylated hemoglobin A1c (HbA1c), and lipid profile. Thyroid ultrasound and FNAC were done for all patients. Categorization of each nodule was done according to the TIRADS. Cytopathological diagnosis was done by Bethesda system cytology classification.ResultsThere were 19 malignant and 92 benign nodules. There was a statistically significant difference between benign and malignant nodules regarding TIRADS classification, taller-than-wide shape, solidity, border, presence of peripheral calcifications, or punctuate echogenic foci (p < 0.05). Taller-than-wide shape had the highest specificity followed by irregular margin (94.6% and 92.6%, respectively). Sensitivity, specificity, PPV, and NPV for ACR-TIRADS versus cytopathology were 73.7%, 57.6%, 26.4%, and 91.4% respectively with overall accuracy of 60.4%. The high sensitivity and NPV of the US-based TIRADS classification system have excellent utility for correctly classifying nodules as positive for malignant disease. As regards risks for thyroid nodules, results showed that most of the study population were obese [Body Mass Index (BMI) = 31.6 ± 6.3, Waist circumference (WC) = 107.4 ± 13.9]. TSH and hypercholesterolemia did not show a significant association with thyroid malignancy.ConclusionACR-TIRADS classification is of high significant value in classifying nodules as positive for malignant disease and for predicting the absence of malignant disease, reducing unnecessary nodule FNAC. Hypercholesterolemia and TSH value were not significantly associated with malignant thyroid nodules.

Diagnostic performance of ACR-TIRADS combined with superb microvascular imaging for differential diagnosis of mummified thyroid nodules and papillary thyroid carcinomas.

The aim was to investigate the ability of superb microvascular imaging (SMI) to improve the differential diagnosis of mummified thyroid nodules (MTNs) and papillary thyroid carcinomas (PTCs) using the 2017 American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS). We enrolled 110 cases of MTNs and 110 cases of PTCs confirmed by fine needle aspiration (FNA) or surgery. Conventional ultrasound (US) and the quantity of microvessels detected by SMI were analyzed for all nodules. Thyroid nodules were initially categorized by ACR-TIRADS based on US imaging features and then reclassified based on ACR-TIRADS combined with SMI blood-flow grade (SMI-TIRADS). We compared the diagnostic performances of ACR-TIRADS and SMI-TIRADS by receiver operating characteristic curve, sensitivity, specificity, accuracy, positive predictive value (PPV), and negative predictive value (NPV). US-detected margin, shape, and echogenic foci differed between MTNs and PTCs (P < 0.05). The SMI blood-flow grade was significantly greater in PTCs compared with MTNs (Χ2 = 158.78, P < 0.05). There was no significant difference in ACR-TIRADS indicators between MTNs and PTCs (Χ2 = 1.585, P = 0.453); however, reclassification by SMI-TIRADS showed significant differences between the groups (Χ2 = 129.521, P < 0.001). The area under the curve was significantly lower for ACR-TIRADS compared with SMI-TIRADS (0.517 vs 0.887, P < 0.05). SMI-TIRADS had significantly higher diagnostic value for distinguishing MTNs and PTCs than ACR-TIRADS (sensitivity: 91.82% vs 74.55%, P < 0.05; specificity: 84.55% vs 21.82%, P < 0.05; accuracy: 88.18% vs 48.18%, P < 0.05; PPV: 85.59% vs 48.81%, P < 0.05; and NPV: 91.18% vs 46.15%, P < 0.05). The detection of microvascular flow and large vessels in thyroid nodules by SMI resulted in high diagnostic specificity and sensitivity. ACR-TIRADS combined with SMI could effectively distinguish between MTNs and PTCs, to avoid unnecessary FNA or surgical excision.

Comparison of artificial intelligence, elastic imaging, and the thyroid imaging reporting and data system in the differential diagnosis of suspicious nodules.

Ultrasound is widely used for detecting thyroid nodules in clinical practice. This retrospective study aimed to assess the diagnostic efficacy of the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS), S-Detect, and elastography of the carotid artery for suspicious thyroid nodules and to determine the complementary value of artificial intelligence and elastography. Between January 2021 and November 2021, 101 consecutive patients with 138 thyroid nodules were enrolled in The First Hospital of China Medical University. All nodules were evaluated using ACR-TIRADS categories (TR), S-Detect, and elastography, and then the diagnostic performance of the different methods and the combined assessment were compared. The inclusion criteria were the following: (I) TR3, TR4, and TR5 nodules, which were defined as "suspicious nodules"; (II) patients who had surgical or cytopathological results after ultrasound examination; and (III) voluntary enrollment in this study. Meanwhile, the exclusion criteria were the following: (I) TR1 and TR2 nodules, (II) patients who had undergone fine-needle aspiration before ultrasound examination, and (III) inconclusive cytologic findings. A total of 71 patients (12 men and 59 women) with 94 suspicious thyroid nodules (42 benign nodules and 52 malignant nodules) were finally included in this study. S-Detect had a significantly better sensitivity than did ACR-TIRADS [S-Detect: 98.1%, 95% confidence interval (CI): 89.7-100.0%; ACR-TIRADS: 84.6%, 95% CI: 71.9-93.1%; P=0.036], but its specificity was much lower (S-Detect: 19.0%; 95% CI: 8.6-34.1%; ACR-TIRADS: 40.5%, 95% CI: 25.6-56.7%; P=0.032). The accuracy was not significantly different between S-Detect (62.8%; 95% CI: 52.2-72.5%) and ACR-TIRADS (64.9%; 95% CI: 54.4-74.5%) (P=0.761). The elasticity contrast index (ECI) was not definitively useful in identifying suspicious thyroid nodules (P=0.592). Compared with the use of ACR-TIRADS and S-Detect alone, the specificity (45.2%; 95% CI: 29.8-61.3%), positive predictive value (65.2%; 95% CI: 52.4-76.5%), accuracy (66.0%; 95% CI: 55.5-75.4%), and the area under the receiver operating characteristic curve (0.640; 95% CI: 0.534-0.736) of their combination were higher but not significantly so. At present, S-Detect cannot replace manual diagnosis, and the value of elastography of the carotid artery in diagnosing suspected thyroid nodules remains unclear.

Complexity of diagnosis and management of a giant thyroid nodule: A case report and a concise literature.

It is crucial for doctors to decide whether a thyroid nodule is benign or malignant when a patient presents with one, as it will significantly impact how the patient is managed in the future. However, it is not as straightforward to determine between the two; even a physical examination, thyroid function test, ultrasonography, and biopsy have been well performed. It can be more stressful if a patient has an increased risk of malignancy, such as age (below 20- and above 60-year-old), solid nodule, rapid growth, hoarseness, lymphadenopathy, and microcalcifications on the ultrasonography. The aim of this case was to present the management of a giant thyroid nodule with malignancy presentation and a benign biopsy finding. A 41-year-old male complained of a palpable neck mass, hoarseness, and dysphagia. The thyroid function test was normal. Ultrasonography revealed suspicion of malignancy with category 4 of American College of Radiology-Thyroid Imaging Reporting and Data System (ACR-TIRADS). The biopsy revealed follicular neoplasm, and was classified as Bethesda IV. The patient underwent a total thyroidectomy due to the large tumor size and symptoms. Histopathological findings post-surgery revealed a follicular thyroid adenoma. This case highlights a complex diagnosis and management of follicular thyroid neoplasm due to their potential for both benign and malignant. Comprehensive pre- and post-operative care is essential to determine the nature of nodules. Post-operative follow-up care might improve the patient's outcome and prevent complications.

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

PurposeOur study aimed to diagnose benign or malignant thyroid nodules larger than 4 cm using quantitative diffusion-weighted imaging (DWI) analysis.MethodsEighty-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.ResultsTwo 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.ConclusionQuantitative DWI demonstrated favorable malignant thyroid nodule diagnostic efficacy. The combined DWISIR and ADCmin thresholds model significantly reduced the unnecessary biopsy rate.

Diagnostic value of American College of Radiology Thyroid Imaging Reporting and Data System combined with elastography in differentiating clinically atypical subacute thyroiditis from papillary thyroid carcinoma: a single retrospective research

BackgroundCommon ultrasound imaging is hard to distinguish thyroid nodules of clinically atypical subacute thyroiditis (CAST) with papillary thyroid carcinoma (PTC). The purpose of this study was to investigate the diagnostic value of real-time elastography combined with American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) in differentiating these two lesions.ResultsCentripetal reduction echogenicity was only observed in the CAST nodules, with high specificity (100%) though low sensitivity (23.96%). Echogenic foci yielded good capability for differentiating PTC and CAST, with odds ratio (OR) of 36.572 and AUC of 0.788. Size and ES were independent factors to distinguish the two lesions with OR of 10.709 and 3.697, respectively. The combination of microcalcification, size < 10 mm and ES of 4 showed better AUC (0.885) than echogenic foci alone (p < 0.001). TI-RADS showed high sensitivity (91.23%) with specificity of 30.21% and AUC of 0.607 in predicting malignancy risk of PTC from CAST, while the AUC of ES and the combination of both methods were 0.508 and 0.585, respectively.ConclusionsCentripetal reduction echogenicity, echogenic foci, size and ES may assist in the differential diagnosis of CAST and PTC nodules. ACR TI-RADS is superior to ES and the combination of both methods for distinguishing these two lesions.

Contrast Enhancement Ultrasound Improves Diagnostic Accuracy for Thyroid Nodules: A Prospective Multicenter Study

Abstract Objective To evaluate potential improvements in the diagnosis of thyroid nodules when conventional ultrasound (US) is combined with contrast-enhanced US (CEUS). Methods We recruited 515 participants with 323 malignant and 192 benign nodules, who underwent both US and CEUS examinations at 8 different medical centers in China between October 2020 and October 2021. We assessed the malignancy of thyroid nodules in US using the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TIRADS). Diagnostic criteria for US and US + CEUS were developed by investigators based on evaluations of sonographic features. Using multivariate logistic regression and receiver operating characteristic (ROC) analysis, we compared diagnostic performance between the 2 methods based on criteria identified by investigators and via statistical models. Results On the basis of diagnostic criteria identified by investigators, we measured statistically significant differences in area under the curve (AUC) values between ACR TIRADS (0.83) and CEUS TIRADS (0.87; P &amp;lt; .001). On the basis of diagnostic regression models, we found statistically significant differences in AUC values between US (0.76) and US + CEUS (0.84; P = .001). Models based on US + CEUS outperformed those based on US alone (Akaike information criterion of 347.7 and significant improvement in integrated discrimination). These results were confirmed by similar analyses applied to a validation cohort. Conclusion The accuracy of conventional US for differentiating between benign and malignant thyroid nodules can be improved by combining this approach with CEUS.

A Systematic Review and Meta-analysis on Ultrasound Detection of Thyroid Cancer in China

Background: One major drawback of using ultrasound for diagnosing thyroid nodules is its limited ability to distinguish between benign and malignant nodules. In China, the common methods for risk stratification and guiding fine needle aspiration (FNA) in diagnosing thyroid nodules are the Chinese Thyroid Imaging Reports and Data Systems (C-TIRADS) and American College of Radiology-Thyroid Imaging Reporting and Data System (ACR-TIRADS). Objectives: This review seeks to assess the effectiveness of C-TIRADS and ACR-TIRADS in accurately identifying the risk of malignancy in Chinese patients suspected of thyroid cancer. Methods: A detailed search was conducted in PubMed, Google Scholar, Medline, Embase, Web of Science, Cochrane, and China National Knowledge Infrastructure (CNKI) databases from January 2018 to December 2022. The analysis only considered original articles from China reporting the use of C-TIRADS and ACR-TIRADS confirmed by histology and FNA. Results: This review analyzed 26 studies with a total of 23,064 thyroid nodules from 19,114 patients to compare the diagnostic performance of C-TIRADS and ACR-TIRADS in predicting malignancy risk in thyroid nodules. Although the malignancy rates in each risk category were similar between the two systems, the TIRADS showed better diagnostic performance than C-TIRADS in terms of pooled specificity (95.0 % vs. 66.8 % of C-TIRADS). However, the pooled analysis showed that C-TIRADS had a better pooled sensitivity (94.6 % vs. 76.5% of ACR-TIRADS). The diagnostic odds ratio was 1.37 (95 % CI: 0.75-2.51) for ACR-TIRADS and 0.89 (95 % CI: 0.36-2.16) for C-TIRADS. Conclusion: Based on the results, both C-TIRADS and ACR-TIRADS are effective in predicting the risk of malignancy in thyroid nodules with similar overall diagnostic accuracy. The combination of both systems can be beneficial in enhancing accuracy in suspicious or uncertain cases. The long-term experience of the trained radiologists can readily help in concluding the diagnosis. As no single system or combination of systems can provide a 100% accurate prediction of the malignancy of thyroid nodules, the ultimate diagnosis relies on the concluding assessment of experienced radiologists and the medical team.

AMERICAN COLLEGE OF RADIOLOGY THYROID IMAGING REPORTING AND DATA SYSTEM IN SOLITARY THYROID NODULES – A COMMUNITY-BASED SINGLE CENTRE REAL WORLD EXPERIENCE

Introduction: A solitary thyroid nodule (STN) is a palpable enlargement in a normally functioning thyroid. Diagnosing and treating STN requires a holistic approach. Ultrasonography (USG) is a standard screening tool to identify high-risk nodules that may require fine needle aspiration cytology (FNAC) (benign/malignant). Hence, the current analysis aimed to access the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) with the malignancy and the management of STN in routine clinical practice. Methods: The study was a retrospective analysis of STN patients electronic medical records (EMR) database and USG recorded from 2014 to 2022. We queried a single-center EMR database with the search terms “solitary thyroid nodule”, “autonomously functioning thyroid nodule” and “nontoxic multinodular goiter”. A total of 213 records were identified with STN diagnosis, 161 records have one USG report, and of which a 5-year follow-up of 88 records having at least 2 USG reports with at least 1-year time interval of follow-up data. To better identify benign and malignant nodules and optimize clinical management, ACR-TIRADS and The Bethesda System for Reporting Thyroid Cytopathology (TBSRTC) was adapted in clinic from 2017. Descriptive statistics was used to report the statistical analysis of data. Results: A total of 213 patients were identified with STN. The mean (SD) age is 45.2 (13.8) years. Of these, majority were female, 158 (75%) than male, 54 (25%). Of the total of 160 patients who had ACR TIRADs, 2 (1%) patients had score of 1, 97 (67%) had score 2, 46 (26%) had score 3, 16 (10%) had score 4, 3 (2%) had score 5. Ninety six (45%) patients had Bethesda categorization of nodule and it is observed in 3 (3%), 82 (82%), 8 (8%), 2 (2%), 1 (1%) belonged to class 1, 2, 3, 4, 5, respectively. At follow-up, 67 (76%) patients had no change in the ACR TIRAD nodule score, in 14 (16%) patients score decreased and in 7 (8%) patients increase in score. At baseline the mean (median) nodular volume is 24.2 (8.2) and at follow up 22.2 (6.7), percent change in the nodule volume is -17.7% (-16.0%). Further, of the 88 patients, 7 (9%) of patients had shown &gt;50% increase in the nodular volume. Conclusion: In this real-world data analysis of STN, we observed that the majority of the nodules are benign and nonprogressive, and very few patients had the risk of malignancy, indicating better treatment approaches to control the progression of this condition.

Assessment of thyroid nodule malignancy risk in medical radiation workers using ACR TI-RADS

BackgroundLow-dose radiation exposure brings medical radiation professionals at risk for thyroid parenchymal disease and nodules. ObjectiveTo classify thyroid nodules in medical radiation workers according to their risk, and to look into parenchymal disease and thyroid dysfunction. Design, setting and participantsRetrospective observational study in a tertiary health facility with 148 healthcare workers working in radiation-containing areas. Main outcome and measuresParticipants were divided into groups based on their sociodemographic characteristics, the department they worked in, and the number of years they had been in the profession. The levels of TSH, parenchymal heterogeneity, and thyroid nodule presence were compared between the groups. American College of Radiology (ACR) Thyroid Imaging – Reporting and Data System (TI-RADS) classification was used to evaluate thyroid nodules. ResultsThe presence of nodules was significantly more prevalent in patients over the age of 33 (p = 0.02). The majority of individuals (98%) had nodules that below the American College of Radiology (ACR) Thyroid Imaging – Reporting and Data System (TI-RADS) category 4. Age and professional experience both elevated TSH results (p = 0.015, p = 0.033). With age, parenchymal heterogeneity became more prominent (p = 0.04). For the parameters, there were no appreciable differences between the occupation and department. The results applied to both genders equally. ConclusionWith increasing long-term low-dose exposure, medical radiation workers are at risk for nodules and parenchymal disease. However, the majority of the nodules in our study were sonographically in the low risk group, therefore routine follow-up is advised.

Revised Thyroid Imaging Reporting and Data System (TIRADS): imitating the American College of Radiology TIRADS, a single-center retrospective study.

The incidence of thyroid lumps is more and more high in population, and most biopsies of thyroid nodules are benign. To develop a practical risk stratification system based on five ultrasound features to stratify the malignancy risk of thyroid neoplasms. This retrospective investigation enrolled 999 consecutive patients with 1,236 thyroid nodules who underwent ultrasound screening. Fine-needle aspiration and/or surgery was performed, and pathology results were obtained at the Seventh Affiliated Hospital of Sun Yat-sen University in Shenzhen, China, which is a tertiary referral center, from May 2018 to February 2022. Each thyroid nodule's score was calculated based on five ultrasound features: composition, echogenicity, shape, margin, and echogenic foci. Additionally, each nodule's malignancy rate was calculated. The chi-square test was used to test whether the malignancy rate was different among the three subcategories (scores of 4-6, 7-8, and 9 or more) of thyroid nodules. We proposed the revised Thyroid Imaging Reporting and Data System (R-TIRADS), and its sensitivity and specificity were compared to the two existing systems [the American College of Radiology TIRADS (ACR TIRADS) and the Korean Society of Thyroid Radiology TIRADS (K-TIRADS)]. The final dataset consisted of 425 nodules from 370 patients. The malignancy rates of three subcategories [malignancy rate: 28.8% (scores from 4-6), 64.7% (scores from 7-8), and 84.2% (scores of 9 or more)] were significantly different (P<0.01). The unnecessary biopsy rates of the three systems (ACR TIRADS, R-TIRADS, and K-TIRADS) were 28.7%, 25.2%, and 14.8%, respectively. The R-TIRADS presented better diagnostic performance than the ACR TIRADS or K-TIRADS [area under the curve: 0.79 (95% CI: 0.74-0.83) vs. 0.69 (95% CI: 0.64-0.75), P=0.046; 0.79 (95% CI: 0.74-0.83) vs. 0.66 (95% CI: 0.60-0.71), P=0.041, respectively]. The R-TIRADS had the highest sensitivity [0.746 (95% CI: 0.689-0.803)], followed by the K-TIRADS [0.399 (95% CI: 0.335-0.463), P=0.000] and ACR TIRADS [0.377 (95% CI: 0.314-0.441), P=0.000]. The R-TIRADS enables radiologists to diagnose thyroid nodules efficiently, and the number of unnecessary fine-needle aspirations can be considerably reduced.

Diagnostic value of a dynamic artificial intelligence ultrasonic intelligent auxiliary diagnosis system for benign and malignant thyroid nodules in patients with Hashimoto thyroiditis.

A dynamic artificial intelligence (AI) ultrasonic intelligent assistant diagnosis system (dynamic AI) is a joint application of AI technology and medical imaging, which can conduct real-time synchronous dynamic analysis of nodules from multiple sectional views with different angles. This study explored the diagnostic value of dynamic AI for benign and malignant thyroid nodules in patients with Hashimoto thyroiditis (HT) and its significance in guiding surgical treatment strategies. Data of 487 patients (154 with and 333 without HT) with 829 thyroid nodules who underwent surgery were collected. Differentiation of benign and malignant nodules was performed using dynamic AI, and diagnostic effects (specificity, sensitivity, negative predictive value, positive predictive value, accuracy, misdiagnosis rate and missed diagnosis rate) was assessed. Differences in diagnostic efficacy were compared among AI, preoperative ultrasound based on the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS), and fine needle aspiration cytology (FNAC) diagnoses. The accuracy, specificity and sensitivity of dynamic AI reached 88.06%, 80.19%, and 90.68%, respectively; besides, there was consistency with postoperative pathological consequences (κ=0.690; P<0.001). The diagnostic efficacy of dynamic AI was equivalent between patients with and without HT, and there were no significant differences in sensitivity, specificity, accuracy, positive predictive value, negative predictive value, missed diagnosis rate, and misdiagnosis rate. In patients with HT, dynamic AI had significantly higher specificity and a lower misdiagnosis rate than did preoperative ultrasound based on the ACR TI-RADS (P<0.05). Compared with FNAC diagnosis, dynamic AI had a significantly higher sensitivity and a lower missed diagnosis rate (P<0.05). Dynamic AI possessed an elevated diagnostic worth of malignant and benign thyroid nodules in patients with HT, which can provide a new method and valuable information for the diagnosis and development of management strategy of patients.

Abstract #1412895: Comparison of Radiological Features of ATA and TIRAD System of Evaluating Thyroid Nodules - A Prospective Study in a Tertiary Care Hospital of Pakistan

The occurrence of thyroid carcinoma had ascended through recent years. Excessive detection of thyroid nodules due to intensified use of thyroid ultrasonography and also increased FNAB (fine- needle aspiration biopsy) procedures are believed to cause the surge in the diagnosis of incidental papillary thyroid carcinomas. There have been two guidelines most commonly used in both clinical practice and scientific area; American Thyroid Association (ATA-2015) guideline and ACR-TIRADS (American College of Radiology - Thyroid Imaging Reporting and Data System) guideline. These guidelines have been established based on sonographic topographies and aim to distinguish nodules according to their doubt of malignancy to give recommendations for FNAB or follow-up. This study aims to compare the radiological features of ATA and TIRADS system of evaluating thyroid nodules. This was a prospective study, enrolling 105 patients. The patients presenting to Radiology Department of the study hospital with neck swelling/nodules for Ultrasound Neck and Thyroid were requested to participate in study after providing the informed consent. The participants must be of 18 years of age or above, however the patients with a known diagnosis of thyroid cancer or having recurrence of prior thyroid cancer were excluded. Proforma was filled as per ATA & ACR TI-RADS classification system. A few patients were followed with FNAB and Histopathology reports. Of all the nodules, 30 (28.5%) were benign, whereas 75 (71.5%) were malignant. ATA guidelines showed improved diagnostic efficiency than ACR TI-RADS (P<0.01). ACR TI-RADS confirmed a higher specificity (P<0.05), whereas the ATA outline had a higher sensitivity (P<0.01). The ACR-TIRADS and ATA guidelines performed better in differentiating nodules >1 cm. Both systems revealed good diagnostic presentation, however, ATA guidelines resulted in a superior number of thyroid biopsies or FNABs. Therefore, we believed that ACR-TIRADS is a better system in this regard, it can help us ruling out unnecessary biopsies.

Challenges in Risk Stratification of Solid Atypical Mixed Echogenicity Thyroid Nodules.

Background: To determine the prevalence and risk of malignancy (ROM) in solid atypical mixed echogenicity thyroid nodules (SAMENs) with sonographic patterns not classifiable by the 2015 American Thyroid Association Ultrasound Risk Stratification System (NC ATA). Methods: We searched our prospectively collected endocrine surgery thyroid nodule (TN) database, with particular attention to those solid nodules that were NC ATA. An algorithm assigned each into one of the five ATA risk groups per the 2015 American Thyroid Association Ultrasound Risk Stratification System (ATA USRSS). TNs that the algorithm could not assign to a risk group were deemed NC ATA and were subsequently analyzed. Additionally, we categorized this group using an algorithm based on the 2017 American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS). We were specifically interested in the characteristics that resulted in non-classification by the 2015 ATA USRSS and the fine needle aspiration biopsy (FNAB) cytology and surgical pathology results from the group. Results: We evaluated data from 5,040 nodules, of which 1,772 had surgical pathology. There were 150 solid nodules not classified by 2015 ATA USRSS, all of which demonstrated atypical features along with iso-, hetero-, hyper-and mixed echogenicity (solid atypical mixed echogenicity nodules-SAMENs). Sixty of these nodules were excised and sent for surgical pathology, while 90 were followed without surgical excision. Out of the 90 that did not undergo surgery, 82 underwent FNAB with cytologic evaluation. Of our 150 SAMENs, 40 were malignant by surgical histology and six were likely malignant by cytology (total SAMEN ROM without noninvasive follicular thyroid neoplasm with papillary-l ike nuclear features 31%). The most common sonographic pattern present in our SAMEN group consisted of an isoechoic solid component with microcalcifications (28/40-70% of all excised malignant nodules). In our excised malignant SAMENs, 50% demonstrated follicular-patterned neoplastic architecture while 48% displayed papillary architecture. Conclusion: Our study demonstrates that SAMENs with at least one suspicious sonographic feature: including (1) microcalcifications; (2) irregular or other suspicious margins,;opulation, and a higher ROM (31%) than the intermediate-risk group of the 2015 ATA USRSS (10-20%).

Abstract #1320576: Comparison of Radiological Features of American Thyroid Association and American College of Radiology - Thyroid Imaging Reporting and Data System of Evaluating Thyroid Nodules - A Prospective Study in a Tertiary Care Hospital of Pakistan

The occurrence of thyroid carcinoma had ascended through recent years. Excessive detection of thyroid nodules due to intensified use of thyroid ultrasonography and also increased fine-needle aspiration biopsy (FNAB) procedures are believed to cause the surge in the diagnosis of incidental papillary thyroid carcinomas. There have been 2 guidelines most commonly used in both clinical practice and scientific area: the American Thyroid Association (ATA-2015) and ACR-TIRADS (American College of Radiology - Thyroid Imaging Reporting and Data System) guidelines.