Unnecessary Fine-needle Aspiration Research Articles

Risk of TIRADS-based inappropriate FNAC in autonomous thyroid nodules is clinically negligible.

Thyroid nodule (TN) is usually managed according to Thyroid Imaging And Reporting Data Systems (TIRADS) with the major aim to reduce as much as possible unnecessary fine-needle aspiration cytologies (UN-FNACs). Since the assessment of autonomously functioning thyroid nodule (AFTN) according to TIRADS is heterogeneous, that virtually benign entity may increase the rate of UN-FNAC. This study retrospectively analyzed the appropriateness of TIRADS-based FNAC indication in AFTNs, also looking at the impact of TSH and nodule size. Cases diagnosed with AFTN on scintigraphy were searched. Patients who had undergone AFTN treatment, were on medications or supplementation that could affect thyroid function, or had multiple AFTNs were excluded. The AFTNs were assessed according to ACR-TIRADS. Forty-eight AFTNs were included and a 37.5% of cases had FNAC indication according to TIRADS. The FNAC indication rate of patients with TSH lower than 0.4 mIU/L was significantly higher than the remaining ones (p = 0.0078). The most accurate cut-off of TSH and AFTN size associated with UN-FNAC was ≤0.41 mIU/L and >22 mm, respectively. The multivariate analysis showed that both TSH and nodule size were independent predictors of UN-FNAC with OR 6.65 and 6.46, respectively. According to these data, the rate of FNAC indication dropped up to 4.16%. Inappropriate FNACs in AFTNs are primarily observed in patients with low TSH and large AFTN. Since these cases typically undergo scintigraphy, the risk of TIRADS-based UN-FNAC is clinically negligible. There is no need for integrating other imaging procedures into the TIRADS model.

Comparison of ultrasound risk stratification systems for pediatric thyroid nodules.

There is currently insufficient data to validate adult-based US risk stratification systems (RSSs) for the identification of malignant thyroid nodules in a pediatric population. From October 2016 and May 2023, 173 thyroid nodules of pediatric patients (age ≤ 18 years) with definitive pathology results and ultrasound (US) examination within 1 month before surgery or fine-needle aspiration (FNA) biopsy in our institution were enrolled in this study. The clinical and US characteristics of these nodules were retrospectively reviewed and categorized according to the ACR-TIRADS, C-TIRADS, and ATA guidelines. The diagnostic performance of US-based FNA criteria (original and simulating) of the three guidelines in thyroid cancer detection was estimated. The three RSSs had similar AUC according to the categories(0.849-0.852, all P > 0.05). When combined with the original FNA criteria of the three RSSs to manage the nodules, the FNA rate of ACR-TIRADS and C-TIRADS were significantly less than ATA guidelines (53.18% vs. 64.63%, P < 0.05, and 52.60% vs. 64.63%, P < 0.05). The missed malignancy rate (MMR) and unnecessary FNA rate (UFR) of ATA guidelines (50.00%, 35.85%) was highest among the three RSSs, followed by the C-TIRADS (37.80%, 19.57%) and the ACR-TIRADS (37.04%, 19.57%). When nodules < 1cm with the highest category in each RSS biopsied, that is when using the simulating FNA thresholds, the MMR was reduced overall (all P < 0.001), without a change in the UFR (all P > 0.05). All the three RSSs showed a substantial improvement in accuracy and malignant detection rate (all P < 0.05). The ACR-TIRADS, C-TIRADS, and ATA guidelines showed high missed malignancy rates when using their original recommended FNA criteria. When nodules < 1cm with the highest category in each RSS biopsied, the missed malignancy rate of each RSS was decreased. Decreasing the FNA thresholds for highly suspicious malignant nodules may therefore be an effective means of managing malignant thyroid nodules in pediatric patients.

Dual-modal radiomics nomogram based on contrast-enhanced ultrasound to improve differential diagnostic accuracy and reduce unnecessary biopsy rate in ACR TI-RADS 4–5 thyroid nodules

BackgroundAmerican College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS, TR) 4 and 5 thyroid nodules (TNs) demonstrate much more complicated and overlapping risk characteristics than TR1-3 and have a rather wide range of malignancy possibilities (> 5%), which may cause overdiagnosis or misdiagnosis. This study was designed to establish and validate a dual-modal ultrasound (US) radiomics nomogram integrating B-mode ultrasound (BMUS) and contrast-enhanced ultrasound (CEUS) imaging to improve differential diagnostic accuracy and reduce unnecessary fine needle aspiration biopsy (FNAB) rates in TR 4–5 TNs.MethodsA retrospective dataset of 312 pathologically confirmed TR4-5 TNs from 269 patients was collected for our study. Data were randomly divided into a training dataset of 219 TNs and a validation dataset of 93 TNs. Radiomics characteristics were derived from the BMUS and CEUS images. After feature reduction, the BMUS and CEUS radiomics scores (Rad-score) were built. A multivariate logistic regression analysis was conducted incorporating both Rad-scores and clinical/US data, and a radiomics nomogram was subsequently developed. The performance of the radiomics nomogram was evaluated using calibration, discrimination, and clinical usefulness, and the unnecessary FNAB rate was also calculated.ResultsBMUS Rad-score, CEUS Rad-score, age, shape, margin, and enhancement direction were significant independent predictors associated with malignant TR4-5 TNs. The radiomics nomogram involving the six variables exhibited excellent calibration and discrimination in the training and validation cohorts, with an AUC of 0.873 (95% CI, 0.821–0.925) and 0.851 (95% CI, 0.764–0.938), respectively. The marked improvements in the net reclassification index and integrated discriminatory improvement suggested that the BMUS and CEUS Rad-scores could be valuable indicators for distinguishing benign from malignant TR4-5 TNs. Decision curve analysis demonstrated that our developed radiomics nomogram was an instrumental tool for clinical decision-making. Using the radiomics nomogram, the unnecessary FNAB rate decreased from 35.3 to 14.5% in the training cohort and from 41.5 to 17.7% in the validation cohorts compared with ACR TI-RADS.ConclusionThe dual-modal US radiomics nomogram revealed superior discrimination accuracy and considerably decreased unnecessary FNAB rates in benign and malignant TR4-5 TNs. It could guide further examination or treatment options.

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.

A comprehensive comparative assessment of eight risk stratification systems for thyroid nodules in the elderly population.

This study aims to investigate the diagnostic value of eight risk stratification systems (RSSs) for thyroid nodules in the elderly and explore the reasons in comparison with a younger group. Cases of thyroid nodules that underwent ultrasound examination with thyroidectomy or fine-needle aspiration (FNA) at our hospital between August 2013 and March 2023 were collected. The patients were categorized into two groups: an elderly group (aged ≥60) and a younger group (aged <60). Eight RSSs were applied to evaluate these nodules respectively. The malignant rate in the elderly group was significantly lower than that in the younger group (28.2% vs. 49.6%, P=0.000). There were statistically significant differences in nodule diameter, multiplicity, composition, echogenicity, orientation, margin, and echogenic foci between the elderly and younger groups (P<0.05). Among the eight RSSs evaluated in elderly adults, the artificial intelligence-based Thyroid Imaging Reporting and Data System (AI TIRADS) demonstrated the highest overall diagnostic efficacy, but with relatively high unnecessary FNA rate (UFR) and missed cancer rate (MCR) of 55.0% and 51.3%, respectively. By modifying the size thresholds, the new AI TI-RADS achieved the lowest UFR and MCR while maintaining nearly the lowest FNA rate (FNAR) among all the RSSs (P=0.172, 0.162, compared to the ACR and original AI, respectively, but P<0.05 compared to the other six RSSs). Among the eight RSS systems, AI demonstrated higher diagnostic efficacy in the elderly population. However, the size thresholds for FNA needed to be adjusted.

Diagnostic Performance of ACR TI-RADS and ATA Guidelines in the Prediction of Thyroid Malignancy: A Prospective Single Tertiary Center Study and Literature Review.

This study sought to compare two common risk stratification systems in terms of their diagnostic performance for the evaluation of thyroid malignancy. The American College of Radiology (ACR) Thyroid Imaging, Reporting and Data System (TI-RADS) and the American Thyroid Association (ATA) guidelines were compared among 571 thyroid nodules with definitive fine needle aspiration (FNA) cytology or postoperative histopathology. Ultrasound characteristics such as composition, echogenicity, shape, margin, size, and vascularity were assessed for each thyroid nodule. Diagnostic performance measures were determined and compared through receiver operating characteristic (ROC) curves, and decision curve analysis (DCA). Of 571 nodules, 65 (11.4%) were malignant. The AUC, sensitivity, specificity, positive predictive value, and negative predictive value were 0.691, 49.2%, 84.9%, 29.6%, and 92.8% for ATA guideline, and 0.776, 72.3%, 79.2%, 30.9%, and 95.7%, for ACR TI-RADS, respectively. ACR TI-RADS was more sensitive (p = 0.003), while the ATA guideline was more specific (p < 0.001). DCA demonstrated that the ACR TI-RADS provided a greater net benefit than the ATA guideline. In addition, the net reduction in unnecessary biopsies is higher for ACR TI-RADS than ATA guidelines. The total number of indicated biopsies and unnecessary FNA rates were lower in ACR TI-RADS compared to ATA guideline (293 vs. 527 and 80.2 vs. 87.8). ACR TI-RADS presented no biopsy indication in seven malignant nodules (all categorized as TR2), whereas ATA guideline missed one. Hypoechogenicity was the most significant predictor of malignancy (OR = 8.34, 95% CI: 3.75-19.45), followed by a taller-than-wide shape (OR = 6.73, 95% CI: 3.07-14.77). Our findings suggest that each system has particular advantages in the evaluation of thyroid nodules. ACR TI-RADS reduces unnecessary FNA rates, however, malignant nodules categorized as TR2 might be missed using this system. Further evaluation of this group of nodules using Doppler and other ultrasound modalities is recommended.

Computed Tomography Imaging of COVID-19 Vaccination–related Axillary Lymphadenopathy: Updated Review of Literature

As of September 2022, approximately 606 million cases of COVID-19 have been reported and 6.5 million deaths have occurred worldwide [1]. COVID-19 vaccination programs are in progress around the world to control the pandemic [2]. Till September 2022 approximately 12.6 billion doses of the vaccine have been globally administered [3]. It has been found that reactive hyperplasia of the ipsilateral axillary nodes and sometimes contralateral node is a side effect of vaccination [4]. The frequency of imaging-detected lymphadenopathy ranged between 14.5 to 53% [5]. Cancer patients undergoing active treatment or follow-up surveillance undergo frequent cross-sectional imaging which incidentally detects vaccine-related lymphadenopathy. A Chest CT scan is the most used imaging modality for lung cancer monitoring and lung screening for metastasis of other malignancies. Thus, incidentally detected COVID-19-associated axillary lymph node enlargement is seen in these patients who undergo frequent chest CT scans including the axilla. It is difficult to differentiate lymph node enlargement due to Covid vaccination from lymph node metastasis on imaging. This can lead to unnecessary fine needle aspiration cytology or biopsy thus increasing the patient’s cost and public health burden [6][7][8]. This systematic review aims to evaluate the published literature evidence of axillary lymphadenopathy after COVID-19 vaccination and its imaging features on Chest CT.

Correlation of the ultrasound thyroid imaging reporting and data system with cytology findings among patients in Uganda

BackgroundUltrasonography is a noninvasive modality for the initial assessment of thyroid nodules. The American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS) has demonstrated good performance in differentiating malignant thyroid nodules. However, the combination of ACR TI-RADS categories and cytology has not been studied extensively, in Uganda. The study aims to correlate ACR TI-RADS with cytology among patients referred for US-guided fine-needle aspiration at Mulago National Referral Hospital.MethodsThis was a hospital-based cross-sectional study that recruited 132 patients with thyroid nodules. Spearman’s correlation was used to establish a relationship between TI-RADS and cytology findings. The diagnostic accuracy of TI-RADS was assessed using sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios.ResultsOf 132 study participants, 90% (n = 117) were females, and the mean age was 41 ± 13 years. One hundred sixty-one thyroid nodules were analyzed. More than half of the thyroid nodules (54.7%, n = 87) were solid or almost solid, 96.9% (n = 154) were shaped wider than tall, 57.2% (n = 91) had smooth margins, 83.7% (n = 133) were hyperechoic or isoechoic, and 88.7% (n = 141) had no echogenic foci. TI-RADS 3 was the most common at 42.9% (n = 69). The proportions of malignancy for TI-RADS 4 and TI-RADS 5 were 73.3% and 85.7%, respectively. The correlation between ACR TI-RADS and the Bethesda system of thyroid classification scores was r = 0.577. The sensitivity, specificity, positive and negative predictive values, and positive and negative likelihood ratios of ACR TI-RADS were 90.9%, 98.5%, 90%, 99.3%, 62.3, and 0.1, respectively.ConclusionWe found that ACR TI-RADS classification is an appropriate and noninvasive method for assessing thyroid nodules in routine practice. It can safely reduce the number of unnecessary fine-needle aspiration in a significant proportion of benign thyroid lesions. Thyroid nodules classified as TI-RADS 3 should be followed routinely. ACR TI-RADS should be standardized as the screening tool in resource-limited areas.

Recent Advances of TIRADS Classification of Thyroid Nodules by Ultrasound

Background Thyroid nodules are abnormal growths of thyroid tissue which commonly arise within an otherwise normal thyroid gland. They may be hyperplasia or a thyroid neoplasm, but only a small percentage of the latter are thyroid cancers. Small, asymptomatic nodules are common, and many people who have them are unaware of them. Thyroid nodules can be felt as a lump in the throat. When they are large, they can sometimes be seen as a lump in the front of the neck. Objectives The aim of this work was to improve the management of the patients and to reduce cost-effectiveness by decreasing number of unnecessary fine needle aspiration cytology (FNAC). Patients and Methods This study was conducted on 50 patients with thyroid nodules detected by clinical palpation or incidentally noted during neck imaging for other reasons. There were 33females (74%) and 17 males (26%). Their ages ranged from 41 to 50 years. All patients in the study were subjected to full history taking, thorough clinical examination. Gray scale Ultrasound and color Doppler examination were done to all patients. The nodules were classified into TIRADS categories and the risk of malignancy was calculated for each category. Results All the nodules with TIRADS 1 were benign. In TIRADS 2 there were 10 benign and 1 malignant nodules. In TIRADS 3 there were 4 benign and 1 malignant nodules. In TIRADS 4 there were 2 benign nodules and 4 benign nodules while in TIRADS 5 there were 2 benign and 4 malignant nodules. There was a statistically significant difference between the two groups. There was a statistically significant difference between the two groups with benign and malignant nodules regarding the texture of the nodules. Solid texture was higher in the malignant nodules and spongiform texture was common in the benign nodules while the cystic and mixed texture were comparable between the two groups. Hypoechoic nodules were higher in the malignant nodules, however, there was no statistically significant difference between the two groups with benign and malignant nodules regarding the echogenicity of the nodules. There was a statistically significant difference between the two groups with benign and malignant nodules regarding the echogenic foci. Conclusion The major ultrasound features seen associated with malignancy were microcalcifications, taller than wider shape of the nodule, hypoechoic and marked hypoechoic echopattern of the nodule, irregular borders and presence of suspicious cervical lymph nodes.

A Deep Learning Framework for the Characterization of Thyroid Nodules from Ultrasound Images Using Improved Inception Network and Multi-Level Transfer Learning.

In the past few years, deep learning has gained increasingly widespread attention and has been applied to diagnosing benign and malignant thyroid nodules. It is difficult to acquire sufficient medical images, resulting in insufficient data, which hinders the development of an efficient deep-learning model. In this paper, we developed a deep-learning-based characterization framework to differentiate malignant and benign nodules from the thyroid ultrasound images. This approach improves the recognition accuracy of the inception network by combining squeeze and excitation networks with the inception modules. We have also integrated the concept of multi-level transfer learning using breast ultrasound images as a bridge dataset. This transfer learning approach addresses the issues regarding domain differences between natural images and ultrasound images during transfer learning. This paper aimed to investigate how the entire framework could help radiologists improve diagnostic performance and avoid unnecessary fine-needle aspiration. The proposed approach based on multi-level transfer learning and improved inception blocks achieved higher precision (0.9057 for the benign class and 0.9667 for the malignant class), recall (0.9796 for the benign class and 0.8529 for malignant), and F1-score (0.9412 for benign class and 0.9062 for malignant class). It also obtained an AUC value of 0.9537, which is higher than that of the single-level transfer learning method. The experimental results show that this model can achieve satisfactory classification accuracy comparable to experienced radiologists. Using this model, we can save time and effort as well as deliver potential clinical application value.

Comparison of the C-TIRADS, ACR-TIRADS, and ATA guidelines in malignancy risk stratification of thyroid nodules.

To compare the diagnostic performance in determining the malignancy of thyroid nodules and the fine needle aspiration (FNA) recommendations of the guidelines set forth by the Superficial Organ and Vascular Ultrasound Group of the Society of Ultrasound in Medicine of the Chinese Medical Association in 2020 [2020 Chinese Thyroid Imaging Reporting and Data System (C-TIRADS)], the American College of Radiology in 2017 (2017 ACR-TIRADS) and the American Thyroid Association in 2015 (2015 ATA guidelines). From January 2021 to December 2021, 1,228 thyroid nodules with definitive postoperative histopathology and ultrasound (US) examination within 3 months before surgery in Shantou Central Hospital were enrolled in this study. We collected the data in 2022. The participants formed a consecutive series. The clinical and US features of the nodules were retrospectively reviewed and categorized according to the 2020 C-TIRADS, the 2017 ACR-TIRADS and the 2015 ATA guidelines. The diagnostic performance and unnecessary FNA rates of the three guidelines were calculated. The 2017 ACR-TIRADS had the highest diagnostic performance [area under the receiver operating characteristic curve (AUROC) 0.938], followed by the 2020 C-TIRADS (AUROC 0.933) and the 2015 ATA guidelines (AUROC 0.928). The ATA guidelines had the highest specificity (93.38%), accuracy (92.10%) and positive predictive value (PPV) (80.56%) among the three guidelines. There were no significant differences in the sensitivity and negative predictive value (NPV) among the three guidelines. The sensitivity, specificity, PPV, NPV and accuracy of the FNA recommendations based on the C-TIRADS were 84.25%, 58.76%, 38.92%, 92.28% and 64.82%, respectively, which were higher than those of the ACR-TIRADS (57.53%, 42.94%, 23.93%, 76.43% and 46.42%, respectively) and the ATA guidelines (62.67%, 13.25%, 18.39%, 53.22% and 25.00%, respectively). Compared with the ACR-TIRADS (76.07%) and the ATA guidelines (81.61%), the C-TIRADS showed advantages in the unnecessary FNA rate (61.08%), especially in nodules larger than 20 mm. The 2020 C-TIRADS, the 2017 ACR-TIRADS and the 2015 ATA guidelines can effectively predict the malignancy risk of thyroid nodules. Compared with the 2017 ACR-TIRADS and the 2015 ATA guidelines, the 2020 C-TIRADS may offer a meaningful reduction in FNA recommendations with the highest efficacy in distinguishing thyroid carcinoma.

Comparative Study of C-TIRADS, ACR-TIRADS, and EU-TIRADS for Diagnosis and Management of Thyroid Nodules

Chinese Thyroid Imaging Reporting and Data Systems (C-TIRADS) was developed to provide a more simplified tool for stratifying thyroid nodules. Here we aimed to validate the efficacy of C-TIRADS in distinguishing benign from malignant and in guiding fine-needle aspiration biopsies in comparison with the American College of Radiology TIRADS (ACR-TIRADS) and European TIRADS (EU-TIRADS). This study retrospectively included 3438 thyroid nodules (≥10mm) in 3013 patients (mean age, 47.1 years±12.9) diagnosed between January 2013 and November 2019. Ultrasound features of the nodules were evaluated and categorized according to the lexicons of the three TIRADS. We compared these TIRADS by using the area under the receiver operating characteristic curve (AUROC), the area under the precision-recall curve (AUPRC), sensitivity, specificity, net reclassification improvement (NRI), and unnecessary fine-needle aspiration biopsy (FNAB) rate. Of the 3438 thyroid nodules, 707 (20.6%) were malignant. C-TIRADS showed higher discrimination performance (AUROC, 0.857; AUPRC, 0.605) than ACR-TIRADS (AUROC, 0.844; AUPRC, 0.567) and EU-TIRADS (AUROC, 0.802; AUPRC, 0.455). The sensitivity of C-TIRADS (85.3%) was lower than that of ACR-TIRADS (89.1%) but higher than that of EU-TIRADS (78.4%). The specificity of C-TIRADS (76.9%) was similar to that of EU-TIRADS (78.9%) and higher than that of ACR-TIRADS (69.5%). The unnecessary FNAB rate was lowest with C-TIRADS (21.2%), followed by ACR-TIRADS (41.7%) and EU-TIRADS (58.3%). C-TIRADS obtained significant NRI for recommending FNAB over ACR-TIRADS (19.0%, P<0.001) and EU-TIRADS (25.5%, P<0.001). C-TIRADS may be a clinically applicable tool to manage thyroid nodules, which warrants thorough tests in other geographic settings.

Ultrasonography-based radiomics and computer-aided diagnosis in thyroid nodule management: performance comparison and clinical strategy optimization.

To compare ultrasonography (US) feature-based radiomics and computer-aided diagnosis (CAD) models for predicting malignancy in thyroid nodules, and to evaluate their utility for thyroid nodule management. This prospective study included 262 thyroid nodules obtained between January 2022 and June 2022. All nodules previously underwent standardized US image acquisition, and the nature of the nodules was confirmed by the pathological results. The CAD model exploited two vertical US images of the thyroid nodule to differentiate the lesions. The least absolute shrinkage and operator algorithm (LASSO) was applied to choose radiomics features with excellent predictive properties for building a radiomics model. Ultimately, the area under the receiver operating characteristic curve (AUC) and calibration curves were assessed to compare diagnostic performance between the models. DeLong's test was used to analyze the difference between groups. Both models were used to revise the American College of Radiology Thyroid Imaging Reporting and Data Systems (ACR TI-RADS) to provide biopsy recommendations, and their performance was compared with the original recommendations. Of the 262 thyroid nodules, 157 were malignant, and the remaining 105 were benign. The diagnostic performance of radiomics, CAD, and ACR TI-RADS models had an AUC of 0.915 (95% confidence interval (CI): 0.881-0.947), 0.814 (95% CI: 0.766-0.863), and 0.849 (95% CI: 0.804-0.894), respectively. DeLong's test showed a statistically significant between the AUC values of models (p < 0.05). Calibration curves showed good agreement in each model. When both models were applied to revise the ACR TI-RADS, our recommendations significantly improved the performance. The revised recommendations based on radiomics and CAD showed an increased sensitivity, accuracy, positive predictive value, and negative predictive value, and decreased unnecessary fine-needle aspiration rates. Furthermore, the radiomics model's improvement scale was more pronounced (33.3-16.7% vs. 33.3-9.7%). The radiomics strategy and CAD system showed good diagnostic performance for discriminating thyroid nodules and could be used to optimize the ACR TI-RADS recommendation, which successfully reduces unnecessary biopsies, especially in the radiomics model.

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

BackgroundUltrasound-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.MethodsRetrospective 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.ResultsA 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%).ConclusionsThe 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.

Fine-Needle Aspiration Biopsy Evaluation-Oriented Thyroid Carcinoma Auxiliary Diagnosis.

Thyroid carcinoma is one of the most common diseases with an increasing incidence worldwide in recent years. In clinical diagnosis, medical practitioners normally take a preliminary thyroid nodule grading so that highly suspected thyroid nodules can be taken into the fine-needle aspiration (FNA) biopsy to evaluate the malignancy. However, subjective misinterpretations might lead to ambiguous risk stratification of thyroid nodules and unnecessary FNA biopsy. We propose a thyroid carcinoma auxiliary diagnosis method for fine-needle aspiration biopsy evaluation. Through integration of several deep learning models into a multibranch network for thyroid nodule risk stratification in the Thyroid Imaging Reporting and Data System (TIRADS) with pathological features and cascading of a discriminator, our proposed method provides an intelligent auxiliary diagnosis to assist medical practitioners in determining the necessity for further FNA. Experimental results revealed that not only was the rate at which nodules are falsely diagnosed as malignant nodules effectively reduced, which avoids the unnecessary high cost and pain of aspiration biopsy, but also previously missing detected cases were identified with high possibility. By comparing the physicians' diagnosis alone with machine-assisted diagnosis, physicians' diagnostic performance improved with the aid of our proposed method, illustrating that our model can be very helpful in clinical practice. Our proposed method might help medical practitioners avoid subjective interpretations and inter-observer variability. For patients, reliable diagnosis is provided and unnecessary painful diagnostics can be avoided. In other superficial organs such as metastatic lymph nodes and salivary gland tumors, the proposed method might also provide a reliable auxiliary diagnosis for risk stratification.

Study on diagnosis of thyroid nodules based on convolutional neural network.

An artificial intelligence (AI) algorithm based on convolutional neural networks was used in ultrasound diagnosis in order to evaluate its performance in judging the nature of thyroid nodules and nodule classification. Atotal of 105patients with thyroid nodules confirmed by surgery or biopsy were retrospectively analyzed. The properties, characteristics, and classification of thyroid nodules were evaluated by sonographers and by AI to obtain combined diagnoses. Receiver operating characteristic curves were generated to evaluate the performance of AI, the sonographer, and their combined effort in diagnosing the nature of thyroid nodules and classifying their characteristics. In the diagnosis of thyroid nodules with solid components, hypoechoic appearance, indistinct borders, Anteroposterior/transverse diameter ratio> 1(A/T>1), and calcification performed by sonographers and by AI, the properties exhibited statistically significant differences. Sonographers had asensitivity of 80.7%, specificity of 73.7%, accuracy of 79.0%, and area under the curve (AUC) of 0.751 in the diagnosis of benign and malignant thyroid nodules. AI had asensitivity of 84.5%, specificity of 81.0%, accuracy of 84.7%, and AUC of 0.803. The combined AI and sonographer diagnosis had asensitivity of 92.1%, specificity of 86.3%, accuracy of 91.7%, and AUC of 0.910. The efficacy of acombined diagnosis for benign and malignant thyroid nodules is higher than that of an AI-based diagnosis alone or asonographer-based diagnosis alone. The combined diagnosis can reduce unnecessary fine-needle aspiration biopsy procedures and better evaluate the necessity of surgery in clinical practice.

The diagnostic efficacy and inappropriate biopsy rate of ACR TI-RADS and ATA guidelines for thyroid nodules in children and adolescents.

This study is aimed at evaluating the diagnostic efficacy and unnecessary fine-needle aspiration (FNA) rate of ultrasound-based risk stratification for thyroid nodules in the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TI-RADS) and the American Thyroid Association (ATA) risk stratification systems. Children and adolescents with pathology confirmed thyroid nodules were retrospectively included in this study. A total of 217 thyroid nodules from multicenter of Union Medical College Hospital, China Japan Friendship Hospital and Civil Aviation Hospital were included, the diagnostic efficiency and unnecessary FNA rate were calculated according to ACR and ATA guidelines. Among all thyroid nodules, 139 nodules were malignant, and 78 nodules were benign. Choosing ATA high suspicion and ACR TI-RADS TR5 as benign and malignant cut-off points, the area under the curve and sensitivity of ATA were higher than ACR (AUC: 0.887 vs 0.840, p=0.0037; sensitivity 81.3% vs 71.0%, P <0.049;specificity 96.2% vs 97.4%, p=1.000;specificity both 85.9%); choosing high/intermediate suspicion in ATA and ACR TR4/5 as benign and malignant cut-off points, the two guidelines demonstrated similar diagnostic efficacy (AUC:0.890 vs 0.897, p=0.6038, sensitivity 92.1% vs 93.5%, P =0.817;specificity both 85.9%, p=1.000). The inappropriate FNA rate of ACR guideline was relatively lower (ATA 42.9% vs ACR 27.2%, P <0.001). If ACR TI-RADS TR5 nodules less than 1.0cm were included in the FNA indication, the unnecessary biopsy rate would be further reduced to 17.9%. This study indicated that both ATA and ACR TI-RADS risk stratification systems could provide a feasible differential diagnosis of benign and malignant thyroid nodules, while the ACR risk stratification system demonstrates a lower rate of inappropriate FNA rate. In addition, it was necessary to further study the minimum FNA threshold of thyroid nodules in Children and adolescents in order to reduce the missed biopsy rate of malignant nodules.

Comparison of Various Ultrasound-Based Malignant Risk Stratification Systems on an Occasion for Assessing Thyroid Nodules in Hashimoto's Thyroiditis.

To compare the diagnostic performance and unnecessary ultrasound-guided fine-needle aspiration (US-FNA) biopsy rate of the 2015 American Thyroid Association (ATA), 2016 Korean Society of Thyroid Radiology (KSThR), and 2017 American College of Radiology (ACR) guidelines for patients with and without Hashimoto's thyroiditis (HT). This retrospective study included 716 nodules from 696 consecutive patients, which were classified using the categories defined by the three guidelines: ATA, KSThR, and ACR. The malignancy risk in each category was calculated and the diagnostic performance and unnecessary fine-needle aspiration (FNA) rates of the three guidelines were compared. In total, 426 malignant and 290 benign nodules were identified. Patients with malignant nodules had lower total thyroxine levels and higher thyroid-stimulating hormone, thyroid peroxidase antibody, and thyroglobulin antibody levels than those without malignant nodules (all P<0.01). The margin difference was significant in non-HT patients (P<0.01), but comparable in HT patients (P=0.55). The calculated malignancy risks of high and intermediate suspicion nodules in the ATA and KSThR guidelines and moderately suspicious nodules in the ACR guidelines were significantly lower in non-HT patients compared with HT patients (P<0.05). The ACR guidelines showed the lowest sensitivity, highest specificity, and lowest unnecessary FNA rates in patients with and without HT. Compared to non-HT patients, HT patients had significantly lower unnecessary FNA rates (P<0.01). HT was associated with a higher malignancy rate of thyroid nodules with intermediate suspicion according to the ATA, KSThR, and ACR guidelines. The three guidelines, especially ACR, were likely to be more effective and could allow a greater reduction in the percentage of benign nodules biopsied in patients with HT.

The TNAPP web-based algorithm improves thyroid nodule management in clinical practice: A retrospective validation study.

The detection of thyroid nodules has been increasing over time, resulting in an extensive use of fine-needle aspiration (FNA) and cytology. Tailored methods are required to improve the management of thyroid nodules, including algorithms and web-based tools. To assess the performance of the Thyroid Nodule App (TNAPP), a web-based, readily modifiable, interactive algorithmic tool, in improving the management of thyroid nodules. One hundred twelve consecutive patients with 188 thyroid nodules who underwent FNA from January to December 2016 and thyroid surgery were retrospectively evaluated. Neck ultrasound images were collected from a thyroid nodule registry and re-examined to extract data to run TNAPP. Each nodule was evaluated for ultrasonographic risk and suitability for FNA. The sensitivity, specificity, positive and negative predictive values, and overall accuracy of TNAPP were calculated and compared to the diagnostic performance of the other two algorithms by the American Association of Clinical Endocrinology/American College of Endocrinology/Associazione Medici Endocrinologi (AACE/ACE/AME), which it was derived from the American College of Radiology Thyroid Imaging Reporting and Data System (ACR TI-RADS). TNAPP performed better in terms of sensitivity (>80%) and negative predictive value (68%) with an overall accuracy of 50.5%, which was similar to that found with the AACE/ACE/AME algorithm. TNAPP displayed a slightly better performance than AACE/ACE/AME and ACR TI-RADS algorithms in selectively discriminating unnecessary FNA for nodules with benign cytology (TIR 2 - Bethesda class II: TNAPP 32% vs. AACE/ACE/AME 31% vs. ACR TI-RADS 29%). The TNAPP reduced the number of missed diagnoses of thyroid nodules with suspicious and highly suspicious cytology (TIR 4 + TIR 5 - Bethesda classes V + VI: TNAPP 18% vs. AACE/ACE/AME 26% vs. ACR TI-RADS 20.5%). A total of 14 nodules that would not have been aspirated were malignant, 13 of which were microcarcinomas (92.8%). The TNAPP algorithm is a reliable, easy-to-learn tool that can be readily employed to improve the selection of thyroid nodules requiring cytological characterization. The rate of malignant nodules missed because of inaccurate characterization at baseline by TNAPP was lower compared to the other two algorithms and, in almost all the cases, the tumors were microcarcinomas. TNAPP's use of size >20mm as an independent determinant for considering or recommending FNA reduced its specificity. TNAPP performs well compared to AACE/ACE/AME and ACR-TIRADS algorithms. Additional retrospective and, ultimately, prospective studies are needed to confirm and guide the development of future iterations that incorporate different risk stratification systems and targets for diagnosing malignancy while reducing unnecessary FNA procedures.

American Thyroid Association and Thyroid Imaging Reporting and Data System developed by the American College of Radiology: which one is better at predicting malignancy risk?

The aim of this study was to compare the capacity of American Thyroid Association and Thyroid Imaging Reporting and Data System developed by the American College of Radiology in predicting malignancy risk of thyroid nodules and to verify which one is better at avoiding unnecessary fine needle aspiration. This was a cross-sectional study with 565 thyroid nodules, followed at a tertiary care hospital, in an iodine-replete area. Those were classified as American Thyroid Association and Thyroid Imaging Reporting and Data System developed by the American College of Radiology systems and stratified according to the Bethesda classification of fine needle aspiration. The values of sensibility, specificity, positive predictive value, and negative predictive value accuracy were calculated. Also, the percentage of unnecessary biopsies was presented. The mean age of the individuals was 58.2±13.5 [26-90] years for benign nodules and 41.7±15.6 [23-66] years for malignant nodules (p=0.002). Regarding gender, 92.6% (n=150) of the individuals with benign nodules and 85.7% (n=06) with malignant nodules were females (p=0.601). For American Thyroid Association, 90.9% of sensibility, 51.4% of specificity, 52.6% of accuracy, 10.2% of positive predictive value, and 98.9% of negative predictive value were found. For Thyroid Imaging Reporting and Data System developed by the American College of Radiology, 90.9% of sensibility, 49.7% of specificity, 52.1% of accuracy, 9.9% of positive predictive value, and 98.9% of negative predictive value were found. .Notably, 12.3% of unnecessary fine needle aspiration were found in American Thyroid Association and 44.4% were found in Thyroid Imaging Reporting and Data System developed by the American College of Radiology. Both Thyroid Imaging Reporting and Data System developed by the American College of Radiology and American Thyroid Association are able to predict the malignancy risk of thyroid nodules. Thyroid Imaging Reporting and Data System developed by the American College of Radiology was better at avoiding unnecessary fine needle aspiration.