Role of ultrasound in predicting telomerase reverse transcriptase (TERT) promoter mutation in follicular thyroid carcinoma.

Telomerase reverse transcriptase (TERT) promoter mutations are associated with tumor aggressiveness. This study aimed to demonstrate the ultrasonographic (US) features of TERT promoter-mutated follicular thyroid cancer (FTC) and evaluate their predictive performance. A total of 63 patients with surgically confirmed FTC between August 1995 and April 2021 were included. All data were available for analysis of preoperative US findings and TERT promoter mutation results. Genomic DNA was extracted from the archived surgical specimens to identify TERT promoter mutations. Logistic regression analysis was performed to compare US findings between TERT promoter-mutated and wild-type FTCs. Of the 63 patients with FTC, 10 (15.9%) had TERT promoter mutations. TERT promoter-mutated FTCs demonstrated significantly different US suspicion categories compared to wild-type FTCs (Ps = 0.0054 for K-TIRADS and 0.0208 for ACR-TIRADS), with a trend toward an increasing prevalence of the high suspicion category (40.0% for both K-TIRADS and ACR-TIRADS; Ps for trend = 0.0030 for K-TIRADS and 0.0032 for ACR-TIRADS). Microlobulated margins and punctate echogenic foci were independent risk factors associated with TERT promoter mutation in FTC (odds ratio = 9.693, 95% confidence interval = 1.666-56.401, p = 0.0115 for margins; odds ratio = 8.033, 95% confidence interval = 1.424-45.309, p = 0.0182 for punctate echogenic foci). There were no significant differences in the composition and echogenicity of the TERT promoter-mutated and wild-type FTCs. TERT promoter-mutated FTCs were categorized more frequently as high suspicion by the K-TIRADS and ACR-TIRADS. Based on US findings, the independent risk factors for TERT promoter mutations in FTC are microlobulated margins and punctate echogenic foci.

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

BACKGROUND: To assess MRI-based morphological features in improving the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) for categorizing thyroid nodules. METHODS: A 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. RESULTS: Among 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%. CONCLUSIONS: MRI morphological features with ACR-TIRADS has improved diagnostic performance and reduce unnecessary biopsy rate while maintaining a low malignant missed diagnosis rate.

Comparison of ultrasound risk stratification systems for pediatric thyroid nodules.

Background: 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. Methods: 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. Results: 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 < 1 cm 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). Conclusion: The ACR-TIRADS, C-TIRADS, and ATA guidelines showed high missed malignancy rates when using their original recommended FNA criteria. When nodules < 1 cm 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.

Localization and Risk Stratification of Thyroid Nodules in Ultrasound Images Through Deep Learning.

OBJECTIVE: Deep learning algorithms have commonly been used for the differential diagnosis between benign and malignant thyroid nodules. The aim of the study described here was to develop an integrated system that combines a deep learning model and a clinical standard Thyroid Imaging Reporting and Data System (TI-RADS) for the simultaneous segmentation and risk stratification of thyroid nodules. METHODS: Three hundred four ultrasound images from two independent sites with TI-RADS 4 thyroid nodules were collected. The edge connection and Criminisi algorithm were used to remove manually induced markers in ultrasound images. An integrated system based on TI-RADS and a mask region-based convolution neural network (Mask R-CNN) was proposed to stratify subclasses of TI-RADS 4 thyroid nodules and to segment thyroid nodules in the ultrasound images. Accuracy and the precision-recall curve were used to evaluate stratification performance, and the Dice similarity coefficient (DSC) between the segmentation of Mask R-CNN and the radiologist's contour was used to evaluate the segmentation performance of the model. RESULTS: The combined approach could significantly enhance the performance of the proposed integrated system. Overall stratification accuracy of TI-RADS 4 thyroid nodules, mean average precision and mean DSC of the proposed model in the independent test set was 90.79%, 0.8579 and 0.83, respectively. Specifically, stratification accuracy values for TI-RADS 4a, 4b and 4c thyroid nodules were 95.83%, 84.21% and 77.78%, respectively. CONCLUSION: An integrated system combining TI-RADS and a deep learning model was developed. The system can provide clinicians with not only diagnostic assistance from TI-RADS but also accurate segmentation of thyroid nodules, which improves the applicability of the system in clinical practice.

Determining the Best Thyroid Imaging Reporting and Data System: A Prospective Study Comparing the Diagnostic Performance of ACR, EU, and K TIRADS in the Evaluation of Thyroid Nodules.

Background Many different risk stratification systems have been formulated for thyroid nodules, differing in their fine-needle aspiration cytology (FNAC) indication, suggesting a lack of consensus around the world. Purpose This prospective study was conducted to find the best guideline for risk stratification, for a better malignancy yield, and with reduced rates of negative FNACs among three Thyroid Imaging, Reporting, and Data System (TIRADS) guidelines. Materials and Methods A total of 625 thyroid nodules with conclusive FNAC or histopathological diagnosis were included in the study. Various sonographic parameters were recorded. They were classified into categories as per the three guidelines and compared with FNAC diagnosis. The guidelines were evaluated in terms of sensitivity, specificity, predictive values, and diagnostic accuracy. Sensitivity and specificity were compared by McNemar's test. Results American College of Radiology (ACR) TIRADS had the highest diagnostic accuracy (56.8%), specificity (50.75%), positive predictive value (23.92%), lowest rates of negative FNACs (76.08%), and high negative predictive value (97.84 %). Korean (K) TIRADS had the maximum sensitivity (97.75%), highest negative predictive value (98.44%), and gross malignancy yield. European TIRADS was between the two other guidelines in most parameters with specificity like K TIRADS. Conclusion All the three guidelines are very good screening tools, with comparable high sensitivity. ACR TIRADS is better in terms of specificity and reduced rates of negative FNACs. Including the presence of a suspicious cervical lymph node as a criterion and more frequent follow-up might further improve the diagnostic performance of the guideline.

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

PURPOSE: This study aimed to develop the ultrasonography (US) criteria for risk stratification of the Korean Thyroid Imaging Reporting and Data System (K-TIRADS) 4 nodules, and to evaluate the diagnostic yield of a modified biopsy criterion in a multicenter cohort. METHODS: In total, 1,542 K-TIRADS 4 nodules (≥1 cm) were included in the study. US criteria for the subcategorization of K-TIRADS 4 nodules were developed based on high-risk US features. The diagnostic yields and false referral rates of biopsy criterion 1 (size cut-off of 1 cm), biopsy criterion 2 (size cut-off of 1.5 cm), and modified biopsy criterion 3 (size cut-off of 1 cm for K-TIRADS 4B and 1.5 cm for K-TIRADS 4A) were evaluated. RESULTS: The five high-risk US features (solid composition, marked hypoechogenicity, macrocalcification, punctate echogenic foci, and irregular margin) independently increased the malignancy risk of the K-TIRADS 4 nodules (P<0.001). The K-TIRADS 4 nodules could be subcategorized into higher- and lower-risk subcategories according to the number of high-risk US features: K-TIRADS 4B (≥2 US features) and K-TIRADS 4A (≤1 US feature). The modified biopsy criterion increased the diagnostic yield by 7.8% compared with criterion 2 and reduced the false referral rate by 15.3% compared with criterion 1 (P<0.001). CONCLUSION: The K-TIRADS 4 nodules were subcategorized as K-TIRADS 4B and K-TIRADS 4A based on high-risk US features. The modified biopsy criterion 3 showed a similar diagnostic yield and reduced false referral rate compared to criterion 1.

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

Objective: 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). Materials and methods: 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). Results: 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). Conclusion: 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.

Development and Validation of a Nomogram Based on Multimodality Ultrasonography Images for Differentiating Malignant from Benign American College of Radiology Thyroid Imaging, Reporting and Data System (TI-RADS) 3-5 Thyroid Nodules.

OBJECTIVE: The aim of the work described here was to develop and validate a predictive nomogram based on combined image features of gray-scale ultrasonography (US), elastosonography (ES) and contrast-enhanced US (CEUS) to differentiate malignant from benign American College of Radiology Thyroid Imaging, Reporting and Data System (ACR TI-RADS) 3-5 thyroid nodules. METHODS: Among 2767 thyroid nodules scanned by CEUS in Xijing Hospital between April 2014 and November 2018, 669 nodules classified as ACR TI-RADS 3-5 were included, with confirmed diagnosis and ES examination. Four hundred fifty-five nodules were set as a training cohort and 214 as a validation cohort. Images were categorized as gray-scale US ACR TI-RADS 3, TI-RADS 4 and TI-RADS 5; ES patterns of ES-1 and ES-2; and CEUS patterns of either heterogeneous hypo-enhancement, concentric hypo-enhancement, homogeneous hyper-/iso-enhancement, no perfusion, hypo-enhancement with sharp margin, island-like enhancement or ring-like enhancement. On the basis of multivariate logistic regression analysis, a predictive nomogram model was developed and validated by receiver operating characteristic curve analysis. RESULTS: In the training cohort, ACR TI-RADS 4 and 5, ES-2, heterogeneous hypo-enhancement, concentric hypo-enhancement and homogeneous hyper-/iso-enhancement were selected as predictors of malignancy by univariate logistic regression analysis. A predictive nomogram (combining indices of ACR TI-RADS, ES and CEUS) indicated excellent predictive ability for differentiating malignant from benign lesions in the training cohort: area under the receiver operating characteristic curve (AUC) = 0.93, 95% confidence interval (CI): 0.90-0.95. The prediction nomogram model was determined to have a sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of 0.84, 0.88, 0.91 and 0.81. In the validation cohort, the AUC of the prediction nomogram model was significantly higher than those of the single modalities (p < 0.005) . The AUCs of the validation cohort were 0.93 (95% CI: 0.89-0.96) and 0.93 (95% CI: 0.89-0.97), respectively, for senior and junior radiologists. The prediction nomogram model has a sensitivity, specificity, PPV and NPV of 0.86, 0.87, 0.87 and 0.86. CONCLUSION: A predictive nomogram model combining ACR TI-RADS, ES and CEUS exhibited potential clinical utility in differentiating malignant from benign ACR TI-RADS 3-5 thyroid nodules.

Evaluating Postoperative Outcomes and Investigating the Usefulness of EU-TIRADS Scoring in Managing Pediatric Thyroid Nodules Bethesda 3 and 4

Objective: The aim was to assess postoperative outcomes in pediatric thyroid nodules with atypia of undetermined significance (AUS/FLUS) or suspicious for a follicular neoplasm (SFN) and their respective the European-Thyroid Imaging Reporting and Data System (EU-TIRADS) scores. Methods: Forty-four pediatric patients at a single center with thyroid nodules classified as AUS/FLUS or SFN from August 2019 to December 2022 were retrospectively reviewed. Data on demographics, thyroid function, nodule size, and ultrasonographic features were collected. Postoperative pathologies were categorized into benign, low-risk, and malignant neoplasms according to the World Health Organization 2022 criteria, and EU-TIRADS was used for retrospective radiological scoring. Results: Among 21 (47.7%) of patients who had surgical intervention, 72% had Bethesda 3 and 28% had Bethesda 4 thyroid nodules. Post-surgical histopathological classifications were 43% benign, 19% low-risk, and 38% malignant. Of note, EU-TIRADS 3 and 5 scores were present in 44% and 56% of the benign cases, respectively. Malignant cases tended to produce higher EU-TIRADS scores, with 64% rated as EU-TIRADS 5. Bethesda category 4 nodules had a 66% malignancy rate, significantly higher than the 27% in category 3. Conclusion: A substantial proportion of histologically benign cases were classified as EU-TIRADS 5, suggesting that EU-TIRADS may lead to unnecessary biopsies in benign cases. Malignant cases were more likely to have a higher EU-TIRADS score, indicating a positive correlation with malignancy risk, particularly in Bethesda 4 cases. However, the EU-TIRADS system's predictive value for malignancy in Bethesda 3 cases was poorer.

An economically efficient strategy for diagnosing atypia of undetermined significance or follicular lesion of undetermined significance thyroid nodules with ultrasound-based risk stratification systems and BRAFV600E testing.

Background: The management of thyroid nodules classified as atypia of undetermined significance or follicular lesion of undetermined significance (AUS/FLUS) has been a subject of ongoing debate. Therefore, the aim of this study was to investigate a cost-effective approach for managing these nodules by combining BRAFV600E mutation analysis with the guidelines provided by the American Thyroid Association (ATA) or the American College of Radiology (ACR) Thyroid Imaging Reporting and Data System (TIRADS). Methods: This study included 762 AUS/FLUS nodules in 551 patients with a postoperative pathology. A preoperative BRAFV600E gene test and an evaluation using the ATA guidelines and ACR-TIRADS were performed. Two combined diagnostic approaches were employed: In method 1, all nodules underwent BRAFV600E gene testing, and nodules testing positive for BRAFV600E or for risk stratification systems (RSSs) were diagnosed as malignant, while those with negative results in both tests were considered benign. In method 2 (modified combination method), nodules were reclassified into low-risk (category 2 and 3 in the ATA guidelines and ACR-TIRADS), medium-risk (category 4), and high-risk (category 5) groups based on the malignancy rate of the RSSs. BRAFV600E gene testing was applied only with the medium-risk group. Nodules with positive BRAFV600E mutation were upgraded to the high-risk group, while negative cases remained in the medium-risk group. Results: Both malignancy rates and positive BRAFV600E mutation rates increased with the increase in RSS category (P<0.001). The combination of ACR with BRAFV600E gene testing significantly improved the area under the curve (AUC) compared to the use of ACR or BRAFV600E alone (the AUCs for ACR combined with BRAFV600E, modified ACR combined with BRAFV600E, ACR alone, and BRAFV600E alone were 0.875, 0.878, 0.832, and 0.839, respectively; P<0.05 for both combinations vs. ACR or BRAFV600E alone). Similarly, ATA combined with BRAFV600E showed significant improvements in AUC compared to ATA alone (the AUCs for ATA combined with BRAFV600E, modified ATA combined with BRAFV600E, and ATA alone were 0.851, 0.846, 0.809, respectively; P<0.001 for both combination methods vs. ATA alone), but there was no significant difference observed compared to using BRAFV600E alone (P=0.450 and P=0.680 for both combination methods vs. BRAFV600E). Notably, the AUC of ACR combined with BRAFV600E was greater than that of ATA combined with BRAFV600E (P=0.047 and P=0.007 for both combination methods, respectively). There were no significant differences in diagnostic performance between the two combination approaches (P=0.428 for ACR combined with BRAFV600E and P=0.314 for ATA combined with BRAFV600E). Performing BRAFV600E gene testing only on the medium-risk groups (modified combination method) significantly reduced the rate of BRAFV600E gene testing (P<0.001) without increasing the false-negative rate (P=0.818 and P=0.394 for ACR and ATA, respectively). Conclusions: Incorporating the BRAFV600E gene test exclusively for nodules in the medium-risk group significantly improved diagnostic efficacy, reduced the utilization of gene tests, and maintained a consistent false-negative rate.

Utility of Six Ultrasound-Based Risk Stratification Systems in the Diagnosis of AUS/FLUS Thyroid Nodules.

RATIONALE AND OBJECTIVES: To estimate the diagnostic performance of the currently used ultrasound (US)-based risk stratification systems (RSSs) (American Thyroid Association, American Association of Clinical Endocrinologists, American College of Endocrinology, and Association Medici Endocrinology Medical Guidelines for Clinical Practice for the Diagnosis and Management of Thyroid Nodules, European Thyroid Association Guidelines for Ultrasound Malignancy Risk Stratification of Thyroid Nodules in Adults [EU-TIRADS], American College of Radiology Thyroid Imaging Reporting and Data System [ACR-TIRADS], Chinese Guidelines for Ultrasound Malignancy Risk Stratification of Thyroid Nodules [C-TIRADS], and Thyroid Imaging Reporting and Data System Developed by Kwak et al [Kwak-TIRADS]) for atypia of undetermined significance or follicular lesion of undetermined significance (AUS/FLUS) thyroid nodules. MATERIALS AND METHODS: This retrospective study included 514 consecutive AUS/FLUS nodules in 481 patients with final diagnosis. The US characteristics were reviewed and classified using the categories defined by each RSS. The diagnostic performance was evaluated and compared using a generalized estimating equation method. RESULTS: Of the 514 AUS/FLUS nodules, 148 (28.8%) were malignant and 366 (71.2%) were benign. The calculated malignancy rate increased from the low-risk to high-risk categories for all RSSs (all P < .001). Interobserver correlation for both US features and RSSs showed substantial to almost perfect agreement. The diagnostic efficacy of Kwak-TIRADS (AUC=0.808) and C-TIRADS (AUC=0.804) were similar (P = .721) and higher than those of other RSSs (all P < .05). The EU-TIRADS and Kwak-TIRADS exhibited similar sensitivity (86.5% vs 85.1%, P = .739) and were only higher than that of the C-TIRADS (all P < .05). The specificity of C-TIRADS and ACR-TIRADS were similar (78.1% vs 72.1%, P = .06) and were higher than those of other RSSs (all P < .05). CONCLUSION: Currently used RSSs can provide risk stratification for AUS/FLUS nodules. Kwak-TIRADS and C-TIRADS have the highest diagnostic efficacy in identifying malignant AUS/FLUS nodules. A detailed knowledge of the benefits and shortcomings of the various RSSs is essential.

Thyroid nodule characterization using Spectral Detector Computed Tomography (SDCT) in comparison to ultrasound.

OBJECTIVE: To characterize thyroid nodules seen on Spectral Detector computed tomography (SDCT) in respect to their Thyroid Imaging Reporting and Data System (TI-RADS) category on Ultrasound (US). METHODS: We included patients that underwent US examination for the evaluation of thyroid nodules and contrast-enhanced SDCT examination of the neck/thorax, between the years 2018-2020. The SDCT and US were performed within 6 months of each other. Only patients with a visible thyroid nodule on SDCT were included. Attenuation measurements of the nodules in Hounsfield units (HU) were performed on the conventional CT images, virtual non-contrast (VNC) images and virtual monoenergetic images of 40 keV and 100 keV. The Iodine concentration, spectral slope and enhancement estimation results of the nodules were measured. We compared the spectral results between two groups of nodules, according to the US report: TI-RADS 2-3 and TI-RADS 4-5 groups. RESULTS: Thirty-eight nodules were included in the study, 22 nodules in the TI-RADS 2-3 group and 16 in the TI-RADS 4-5 group. The nodules of the TI-RADS 4-5 group had significantly higher Iodine concentration measurement, 4.6 ± 1.8 mg/ml, compared to 2.3 ± 1.2 mg/ml in the TI-RADS 2-3 group; significantly higher estimated enhancement, 3.9 ± 1.5, compared to 2.2 ± 0.7; and significantly higher calculated spectral slope, 5.6 ± 2.2 compared to 2.9 ± 1.5 (p < 0.001). CONCLUSION: Spectral results of SDCT may assist in differentiating intermediate-high risk (TI-RADS 4-5) from low risk (TI-RADS 2-3) thyroid nodules. ADVANCES IN KNOWLEDGE: SDCT offers additional information for the characterization of thyroid nodules.

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

Objective: 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. Methods: 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. Results: 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). Conclusion: Among the eight RSS systems, AI demonstrated higher diagnostic efficacy in the elderly population. However, the size thresholds for FNA needed to be adjusted.

Bilateral papillary thyroid cancer: pitfalls of ACR TI-RADS and evaluation of modified parameters.

PURPOSE: To explore modified parameters of the American College of Radiology Thyroid Imaging Reporting and Data System (TI-RADS) for evaluating contralateral nodules based on preoperative ultrasound features of papillary thyroid carcinoma (PTC) in the suspected lobe, thus guiding the management of bilateral PTC. METHODS: We retrospectively analyzed 389 consecutive patients with PTC (272 in training set, 117 in validation set) who underwent total thyroidectomy from March 2020 to March 2022. According to their postoperative pathological data, the patients were divided into unilateral and bilateral PTC groups. The clinicopathological features and sonographic characteristics of suspected nodules were compared between the groups, and further ultrasonic characteristics of TI-RADS grade (TR grade)-underestimated nodules were analyzed. RESULTS: Patients with a body mass index of ≥25 kg/m2 (P < 0.001), multifocality in the suspected lobe (P < 0.001), and TR > 3 isthmus nodules (P = 0.003) tended to have bilateral PTC. After modifying the TI-RADS classification for contralateral nodules using these three parameters, the area under the curve for diagnosing contralateral lesions increased from 0.79 (95% confidence interval, 0.74-0.84) to 0.83 (0.78-0.87) in the training set. The missed diagnosis rate of contralateral PTC decreased in both the training set [21.1% (28/133) to 4.5% (6/133)] and validation set [11.4% (8/70) to 2.9% (2/70)]. Preoperative ultrasound tended to underestimate the contralateral nodules with the presence of cystic components [100% (6/6)] and halo sign [73.3% (11/15)]. CONCLUSION: The modified TI-RADS classification based on the suspected lobe may facilitate effective preoperative malignant risk stratification of contralateral nodules in bilateral PTC.

Comparison of Diagnostic Values of ACR TI-RADS versus C-TIRADS Scoring and Classification Systems for the Elderly Thyroid Cancers.

Purpose: To compare the diagnostic value of the Thyroid Imaging Reporting and Data System (TI-RADS) of the American College of Radiology (ACR) versus the Chinese Thyroid Imaging Reporting and Data System (C-TIRADS) scoring and classification system for elderly thyroid cancers. Patients and Methods: A total of 512 nodules from 465 patients aged ≥60 with surgical pathology-proven thyroid nodules were enrolled in our study. The ultrasound features of thyroid nodules were independently evaluated by the ACR TI-RADS and C-TIRADS classification systems, and the receiver operating characteristic curve (ROC) was plotted. The optimal cut-off values of the ACR TI-RADS and C-TIRADS scoring and classification systems for diagnosing elderly thyroid nodules were estimated, and the diagnostic efficacy was analyzed. Results: The ACR TI-RADS and C-TIRADS scores and classifications of thyroid cancers were both higher than benign nodules (both P < 0.05). The area under the curve (AUC) of ACR TI-RADS and C-TIRADS scoring and classification systems were 0.861, 0.897, 0.879, and 0.900, respectively, and the AUC of the scoring system was greater than the classification system for both criteria. When the Youden index was the highest, the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of the ACR TI-RADS scoring and classification systems were consistent, ie, they were 89.66%, 41.70%, 89.93%, and 59.00%, respectively; the sensitivity, specificity, PPV, and NPV of the C-TIRADS scoring and classification systems were also consistent, ie, they were 88.71%, 44.26%, 90.23%, 59.69%, respectively. The diagnostic efficacy between the two systems was not statistically significant. Conclusion: ACR TI-RADS and C-TIRADS systems had relatively high diagnostic efficacy for elderly thyroid cancer. The diagnostic efficiency of the scoring systems of ACR TI-RADS and C-TIRADS were higher than the classification systems. In addition, the two systems had high clinical practical values, while there is still a significant risk of missed diagnosis.

Virtual touch tissue imaging for differential diagnosis in ACR TI-RADS category 3-4 thyroid nodules: Conservative and aggressive methods.

PURPOSE: Many Thyroid Imaging Reporting and Data System (TI-RADS) category 3-4 nodules are benign. Our study aimed to add virtual touch tissue imaging (VTI) to TI-RADS using two methods, namely conservative and aggressive, and to explore which method had better diagnostic performance and which method avoided more unnecessary biopsies. METHODS: From January 2016 to December 2021, we included 121 thyroid nodules classified as TI-RADS category 3-4 in 115 consecutive patients in this retrospective study. This study used the reference standard for pathological diagnosis by surgical resection or biopsy. The diagnostic performance of the different methods was evaluated and compared by receiver operating characteristic (ROC) and area under the ROC curve (AUC). RESULTS: In this study, the aggressive approach had the best diagnostic performance among TI-RADS alone, the conservative approach, and the aggressive approach (AUC: 0.863 versus 0.598, P = 0.0007; 0.863 versus 0.755, P = 0.0067). When we used an aggressive approach, 75.44% (43/57) of the 57 false-positive nodes diagnosed by TI-RADS were appropriately downgraded from TI-RADS category 4 to category 3, avoiding unnecessary biopsies. CONCLUSION: VTI improves the diagnostic performance of TI-RADS. The aggressive approach of combining the TI-RADS with VTI would help reduce unnecessary biopsies.

Diagnostic efficiency among Eu-/C-/ACR-TIRADS and S-Detect for thyroid nodules: a systematic review and network meta-analysis.

Background: The performance in evaluating thyroid nodules on ultrasound varies across different risk stratification systems, leading to inconsistency and uncertainty regarding diagnostic sensitivity, specificity, and accuracy. Objective: Comparing diagnostic performance of detecting thyroid cancer among distinct ultrasound risk stratification systems proposed in the last five years. Evidence acquisition: Systematic search was conducted on PubMed, EMBASE, and Web of Science databases to find relevant research up to December 8, 2022, whose study contents contained elucidation of diagnostic performance of any one of the above ultrasound risk stratification systems (European Thyroid Imaging Reporting and Data System[Eu-TIRADS]; American College of Radiology TIRADS [ACR TIRADS]; Chinese version of TIRADS [C-TIRADS]; Computer-aided diagnosis system based on deep learning [S-Detect]). Based on golden diagnostic standard in histopathology and cytology, single meta-analysis was performed to obtain the optimal cut-off value for each system, and then network meta-analysis was conducted on the best risk stratification category in each system. Evidence synthesis: This network meta-analysis included 88 studies with a total of 59,304 nodules. The most accurate risk category thresholds were TR5 for Eu-TIRADS, TR5 for ACR TIRADS, TR4b and above for C-TIRADS, and possible malignancy for S-Detect. At the best thresholds, sensitivity of these systems ranged from 68% to 82% and specificity ranged from 71% to 81%. It identified the highest sensitivity for C-TIRADS TR4b and the highest specificity for ACR TIRADS TR5. However, sensitivity for ACR TIRADS TR5 was the lowest. The diagnostic odds ratio (DOR) and area under curve (AUC) were ranked first in C-TIRADS. Conclusion: Among four ultrasound risk stratification options, this systemic review preliminarily proved that C-TIRADS possessed favorable diagnostic performance for thyroid nodules. Systematic review registration: https://www.crd.york.ac.uk/prospero, CRD42022382818.

Value of Artificial Intelligence in Improving the Accuracy of Diagnosing TI-RADS Category 4 Nodules.

OBJECTIVE: Considerable heterogeneity is observed in the malignancy rates of thyroid nodules classified as category 4 according to the Thyroid Imaging Reporting and Data System (TI-RADS). This study was aimed at comparing the diagnostic performance of artificial intelligence algorithms and radiologists with different experience levels in distinguishing benign and malignant TI-RADS 4 (TR4) nodules. METHODS: Between January 2019 and September 2022, 1117 TR4 nodules with well-defined pathological findings were collected for this retrospective study. An independent external data set of 125 TR4 nodules was incorporated for testing purposes. Traditional feature-based machine learning (ML) models, deep convolutional neural networks (DCNN) models and a fusion model that integrated the prediction outcomes from all models were used to classify benign and malignant TR4 nodules. A fivefold cross-validation approach was employed, and the diagnostic performance of each model and radiologists was compared. RESULTS: In the external test data set, the area under the receiver operating characteristic curve (AUROC) of the three DCNN-based secondary transfer learning models-InceptionV3, DenseNet121 and ResNet50-were 0.852, 0.837 and 0.856, respectively. These values were higher than those of the three traditional ML models-logistic regression, multilayer perceptron and random forest-at 0.782, 0.790, and 0.767, respectively, and higher than that of an experienced radiologist (0.815). The fusion diagnostic model we developed, with an AUROC of 0.880, was found to outperform the experienced radiologist in diagnosing TR4 nodules. CONCLUSION: The integration of artificial intelligence algorithms into medical imaging studies could improve the accuracy of identifying high-risk TR4 nodules pre-operatively and have significant clinical application potential.

Performance of European Thyroid Imaging Reporting and Data System in Stratifying Malignancy Risk of Thyroid Nodules: A Prospective Study.

Background: There is a limited number of studies reporting the performance of European Thyroid Imaging Reporting and Data System (EU-TIRADS) guideline in identifying thyroid nodule malignancy. We aimed to evaluate diagnostic accuracy of EU-TIRADS regardless of thyroid nodule size. Methods: During August 2019-November 2021, subjects with thyroid nodules were prospectively included. Sonographic characteristics were recorded and scored as per EU-TIRADS guideline. Finally, fine-needle aspiration (FNA) was performed, and cytological findings were reported. Results: Totally, 1266 thyroid nodules from 984 subjects were assessed, of which 295 nodules were smaller than 10 mm and 971 nodules were 10 mm or larger. Among nodules <10 mm, prevalence rates of malignancy for EU-TIRADS classes 2-5 were 0.0%, 3.7%, 20.6%, and 40.9%, respectively; these rates among nodules ≥10 mm were 2.3%, 4.0%, 19.3%, and 43.2%, respectively. The accuracy values of EU-TIRADS class 5 and EU-TIRADS class 4 or 5 in diagnosis of malignancy for nodules <10 mm were 86.4% and 79.7%, respectively; these rates for nodules ≥10 mm were 83.8% and 76.3%, respectively. Hypoechogenicity, microcalcification, ill-defined and irregular margins were predictors for malignancy regardless of thyroid nodule size. Conclusion: EU-TIRADS could provide an acceptable malignancy risk stratification that is helpful for better distinguishing benignity from malignancy, as well as preventing unnecessary FNA biopsies, in thyroid nodules irrespective of their size.

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

Background: 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). Methods: 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. Results: 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. Conclusions: 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.