Comparison of the diagnostic performance of the modified Korean Thyroid Imaging Reporting and Data System for thyroid malignancy with three international guidelines

Superior Diagnostic Yield of Core Needle Biopsy Over Fine Needle Aspiration in Diagnosing Follicular-Patterned Neoplasms: A Multicenter Study Focusing on Bethesda IV Results

OBJECTIVE

To compare the diagnostic outcomes of core needle biopsy (CNB) and fine-needle aspiration (FNA) using Bethesda IV as a test-positive criterion for diagnosing follicular-patterned neoplasms in a large multicenter cohort.

MATERIALS AND METHODS

This retrospective study included 5463 thyroid nodules ≥1 cm from 4883 patients (4019 females, 864 males; mean age 53.8 years) that underwent FNA or CNB across 26 hospitals in Korea between June and September 2015. The final diagnosis in cases diagnosed as Bethesda IV (follicular neoplasm) in biopsies were confirmed by surgical pathology. The primary study outcome was the diagnostic yield, defined as the proportion of nodules with follicular-patterned neoplasms confirmed at surgery after receiving Bethesda IV results on biopsy (FNA or CNB), among all that underwent biopsy. Secondary outcomes included false referral rate (FRR) and positive predictive value (PPV). All nodules were analyzed before matching (823 and 4640 nodules for CNB and FNA, respectively) and after nodule matching in a 1:2 ratio (799 and 1571 nodules, respectively) according to age, sex, nodule size, and Korean Thyroid Imaging Reporting and Data System (K-TIRADS) category. Additionally, the diagnostic yields of various histological subtypes of follicular-patterned neoplasms and nodule subgroups were analyzed.

RESULTS

CNB demonstrated a significantly higher diagnostic yield than FNA both before (9.0% vs. 0.5%; P < 0.001) and after matching (9.0% vs. 0.6%; P < 0.001). CNB consistently had higher diagnostic yields than FNA for most histological subtypes and all subgroups. FRR was not significantly different between the CNB and FNA groups after matching (0.4% vs. 0.1%; P = 0.337). The PPV was consistently greater than 90% for both methods, with no significant difference.

CONCLUSION

CNB had a higher diagnostic yield than FNA for follicular-patterned neoplasms, with no significant difference in FRR using Bethesda IV as the test-positive criterion.

The European Thyroid Imaging and Reporting Data System as a Remedy for the Overdiagnosis and Overtreatment of Thyroid Cancer: Results from the EUROCRINE Surgical Registry

BACKGROUND

The European Thyroid Imaging and Reporting Data System (EU-TIRADS) aims to reduce the overdiagnosis of thyroid cancer (TC) by guiding the selection of nodules for fine-needle aspiration biopsy (FNAB). This study sought to validate EU-TIRADS nodule selection criteria using data from EUROCRINE, an extensive international endocrine surgery registry.

METHOD

We reviewed indications for FNAB among patients with TC compared to those with benign disease who underwent surgery between March 2020 and March 2022, considering preoperative EU-TIRADS scores and dominant nodule size (FNAB is recommended in Category 5 (˃10 mm or ˂10 mm with suspicious lymph nodes), 4 (˃15 mm), and 3 (˃20 mm)). Patients were categorized into three risk groups: minimal risk (patients with papillary microcarcinoma), high risk (patients with pT3b stage or higher, pN1b, or pM1), and low-moderate risk (all other patients). We conducted a Receiver Operating Characteristic (ROC) analysis to assess the diagnostic accuracy of the EU-TIRADS.

RESULTS

We analyzed 32,008 operations. Approximately 68% of the surgical records included EU-TIRADS classifications. The EU-TIRADS exhibited diagnostic accuracy across high-volume sites, with a median ROC Area Under the ROC Curve (AUC) of 0.752, indicating its effectiveness in identifying malignancy. Among the cases, 7907 patients had TC. Notably, 55% of patients with TC underwent FNAB despite not initially meeting the EU-TIRADS criteria. These patients were distributed across the minimal- (58%), low-moderate- (36%), and high-risk (5.8%) categories. Of the patients with TC recommended for FNAB, 78% were deemed low-moderate risk, 21% high risk, and only 0.7% minimal risk.

CONCLUSION

The EU-TIRADS offers effective preoperative malignancy risk stratification. Promoting the proper use of the EU-TIRADS in clinical practice is essential to mitigate the overdiagnosis and overtreatment of low-risk TC.

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.

Artificial Intelligence Model Assisting Thyroid Nodule Diagnosis and Management: A Multicenter Diagnostic Study

CONTEXT

It is not clear how to integrate artificial intelligence (AI)-based models into diagnostic workflows.

OBJECTIVE

To develop and validate a deep-learning-based AI model (AI-Thyroid) for thyroid cancer diagnosis, and to explore how this improves diagnostic performance.

METHODS

The system was trained using 19 711 images of 6163 patients in a tertiary hospital (Ajou University Medical Center; AUMC). It was validated using 11 185 images of 4820 patients in 24 hospitals (test set 1) and 4490 images of 2367 patients in AUMC (test set 2). The clinical implications were determined by comparing the findings of six physicians with different levels of experience (group 1: 4 trainees, and group 2: 2 faculty radiologists) before and after AI-Thyroid assistance.

RESULTS

The area under the receiver operating characteristic (AUROC) curve of AI-Thyroid was 0.939. The AUROC, sensitivity, and specificity were 0.922, 87.0%, and 81.5% for test set 1 and 0.938, 89.9%, and 81.6% for test set 2. The AUROCs of AI-Thyroid did not differ significantly according to the prevalence of malignancies (>15.0% vs ≤15.0%, P = .226). In the simulated scenario, AI-Thyroid assistance changed the AUROC, sensitivity, and specificity from 0.854 to 0.945, from 84.2% to 92.7%, and from 72.9% to 86.6% (all P < .001) in group 1, and from 0.914 to 0.939 (P = .022), from 78.6% to 85.5% (P = .053) and from 91.9% to 92.5% (P = .683) in group 2. The interobserver agreement improved from moderate to substantial in both groups.

CONCLUSION

AI-Thyroid can improve diagnostic performance and interobserver agreement in thyroid cancer diagnosis, especially in less-experienced physicians.

Comparison of diagnostic performance of two ultrasound risk stratification systems for thyroid nodules: a systematic review and meta-analysis

OBJECTIVES

To assume the ideal cut-off values and diagnostic performance of two thyroid imaging reporting and data systems published by the Korean Thyroid Association/Korean Society of Thyroid Radiology (Korean TI-RADS) and the American Thyroid Association (ATA TI-RADS).

METHODS

Eighteen studies with 25,422 patients from PubMed, SCOPUS, Embase, Web of Science, and Cochrane Library databases up to August 2022. True and false positive and negative values with characteristics were extracted.

RESULTS

The highest area under the receiver operating characteristic curve (AUC) was 0.893 and 0.887 for Korean and ATA TI-RADS. High suspicion was judged as the best cut-off value with the highest AUC based on optimal sensitivity and specificity. In determining the risk of malignant thyroid nodules, high suspicion in Korean and ATA TI-RADS showed sensitivity as 71.3% and 73.5%, specificity as 7.9% and 86.4%, diagnostic odds ratios as 20.0289 and 20.9076, AUC as 0.893 and 0.887. There was no significant difference when directly comparing the diagnostic accuracy of both TI-RADS.

CONCLUSION

The two risk stratification systems had good diagnostic performance with high AUC and no significant differences. The ideal cut-off can depend on the medical condition or thyroid nodules, because the changes of cut-off point may reciprocally alter sensitivity and specificity.

Delayed Cancer Diagnosis in Thyroid Nodules Initially Treated as Benign With Radiofrequency Ablation: Ultrasound Characteristics and Predictors for Cancer

OBJECTIVE

Regrowth after radiofrequency ablation (RFA) of symptomatic large thyroid nodules, initially treated as benign, sometimes turns out to be malignancies. This study aimed to assess the ultrasound (US) characteristics of thyroid nodules initially treated as benign with RFA and later diagnosed as cancers, predictive factors for cancers masquerading as benign, and methods to avoid RFA in these cancers.

MATERIALS AND METHODS

We reviewed the medical records of 134 consecutive patients with 148 nodules who underwent RFA between February 2008 and November 2016 for the debulking of symptomatic thyroid nodules diagnosed as benign using US-guided biopsy. We investigated the pre-RFA characteristics of the thyroid nodules, changes at follow-up after RFA, and the final surgical pathology.

RESULTS

Nodule regrowth after RFA was observed in 36 (24.3%) of the 148 benign nodules. Twenty-two of the 36 nodules were surgically removed, and malignancies were confirmed in seven (19.4% of 36). Of the 22 nodules removed surgically, pre-RFA median volume (range) was significantly larger for malignant nodules than for benign nodules: 22.4 (13.9-84.5) vs. 13.4 (7.3-16.8) mL (P = 0.04). There was no significant difference in the regrowth interval between benign and malignant nodules (P = 0.49). The median volume reduction rate (range) at 12 months was significantly lower for malignant nodules than for benign nodules (51.4% [0-57.8] vs. 83.8% [47.9-89.6]) (P = 0.01). The pre-RFA benignity of all seven malignant nodules was confirmed using two US-guided fine-needle aspirations (FNAs), except for one nodule, which was confirmed using US-guided core-needle biopsy (CNB). Regrown malignant nodules were diagnosed as suspicious follicular neoplasms by CNB. Histological examination of the malignant nodules revealed follicular thyroid carcinomas, except for one follicular variant, a papillary thyroid carcinoma.

CONCLUSION

Symptomatic large benign thyroid nodules showing regrowth or suboptimal reduction after RFA may have malignant potential. The confirmation of these nodules is better with CNB than with FNA.

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.

Diagnostic Performance of Six Ultrasound Risk Stratification Systems for Thyroid Nodules: A Systematic Review and Network Meta-Analysis

BACKGROUND. Risk stratification systems for evaluating thyroid nodules on ultrasound use varying approaches to classify levels of suspicion for malignancy, leading to variable performance. OBJECTIVE. The purpose of this study was to perform a network meta-analysis comparing six risk stratification systems used to evaluate thyroid nodules on ultrasound in terms of their diagnostic performance for the detection of thyroid cancer. EVIDENCE ACQUISITION. Five bibliometric databases were searched for studies published through August 31, 2022, that compared at least two of six ultrasound risk stratification systems (the American Association of Clinical Endocrinologists, American College of Endocrinology, and Associazione Medici Endocrinologi [AACE/ACE/AME] system; American College of Radiology Thyroid Imaging Reporting and Data System [ACR TI-RADS]; the American Thyroid Association [ATA] risk stratification system; European Thyroid Association Thyroid Imaging Reporting and Data System [EU-TIRADS]; the Korean Thyroid Imaging Reporting and Data System [K-TIRADS] endorsed by the Korean Thyroid Association and the Korean Society of Thyroid Radiology; and the Thyroid Imaging Reporting and Data System developed by Kwak et al. [Kwak TIRADS]) in terms of their diagnostic performance for the detection of thyroid cancer, with cytologic or histologic evaluation used as a reference standard. The studies' risk of bias was evaluated using the Newcastle-Ottawa Scale. A meta-analysis of each system was performed to identify the risk category threshold that had the highest accuracy as well as the highest sensitivity and specificity at this threshold. Network meta-analysis was used to perform hierarchic ranking and identify the systems having the highest sensitivities and specificities at each system's most accurate threshold. EVIDENCE SYNTHESIS. The analysis included 39 studies with 49,661 patients. All studies were of fair (n = 17) or good (n = 22) quality. The most accurate risk category thresholds were class 3 (high risk) for the AACE/ACE/AME system, TR5 (highly suspicious) for ACR TI-RADS, EU-TIRADS 5 (high risk) for EU-TIRADS, 4c (moderate concern but not classic for malignancy) for Kwak TIRADS, K-TIRADS 5 (high suspicion) for K-TIRADS, and high suspicion for the ATA system. At these thresholds, the systems had sensitivity of 64-77% and specificity of 82-90%. Network meta-analysis identified the highest sensitivity and highest specificity for ACR TI-RADS, followed by K-TIRADS. CONCLUSION. Of six risk stratification systems, ACR TI-RADS had the highest diagnostic performance for the detection of thyroid nodules on ultrasound. CLINICAL IMPACT. This network meta-analysis can inform decisions regarding implementation of the risk stratification systems and can aid future system updates.

Diagnostic Performance of Ultrasound-Based Risk Stratification Systems for Thyroid Nodules: A Systematic Review and Meta-Analysis

BACKGRUOUND

This study investigated the diagnostic performance of biopsy criteria in four society ultrasonography risk stratification systems (RSSs) for thyroid nodules, including the 2021 Korean (K)-Thyroid Imaging Reporting and Data System (TIRADS).

METHODS

The Ovid-MEDLINE, Embase, Cochrane, and KoreaMed databases were searched and a manual search was conducted to identify original articles investigating the diagnostic performance of biopsy criteria for thyroid nodules (≥1 cm) in four widely used society RSSs.

RESULTS

Eleven articles were included. The pooled sensitivity and specificity were 82% (95% confidence interval [CI], 74% to 87%) and 60% (95% CI, 52% to 67%) for the American College of Radiology (ACR)-TIRADS, 89% (95% CI, 85% to 93%) and 34% (95% CI, 26% to 42%) for the American Thyroid Association (ATA) system, 88% (95% CI, 81% to 92%) and 42% (95% CI, 22% to 67%) for the European (EU)-TIRADS, and 96% (95% CI, 94% to 97%) and 21% (95% CI, 17% to 25%) for the 2016 K-TIRADS. The sensitivity and specificity were 76% (95% CI, 74% to 79%) and 50% (95% CI, 49% to 52%) for the 2021 K-TIRADS1.5 (1.5-cm size cut-off for intermediate-suspicion nodules). The pooled unnecessary biopsy rates of the ACR-TIRADS, ATA system, EU-TIRADS, and 2016 K-TIRADS were 41% (95% CI, 32% to 49%), 65% (95% CI, 56% to 74%), 68% (95% CI, 60% to 75%), and 79% (95% CI, 74% to 83%), respectively. The unnecessary biopsy rate was 50% (95% CI, 47% to 53%) for the 2021 K-TIRADS1.5.

CONCLUSION

The unnecessary biopsy rate of the 2021 K-TIRADS1.5 was substantially lower than that of the 2016 K-TIRADS and comparable to that of the ACR-TIRADS. The 2021 K-TIRADS may help reduce potential harm due to unnecessary biopsies.

Diagnostic Performance of Various Ultrasound Risk Stratification Systems for Benign and Malignant Thyroid Nodules: A Meta-Analysis

BACKGROUND

To evaluate the diagnostic performance of ultrasound risk-stratification systems for the discrimination of benign and malignant thyroid nodules and to determine the optimal cutoff values of individual risk-stratification systems.

METHODS

PubMed, Embase, SCOPUS, Web of Science, and Cochrane library databases were searched up to August 2022. Sensitivity and specificity data were collected along with the characteristics of each study related to ultrasound risk stratification systems.

RESULTS

Sixty-seven studies involving 76,512 thyroid nodules were included in this research. The sensitivity, specificity, diagnostic odds ratios, and area under the curves by K-TIRADS (4), ACR-TIRADS (TR5), ATA (high suspicion), EU-TIRADS (5), and Kwak-TIRADS (4b) for malignancy risk stratification of thyroid nodules were 92.5%, 63.5%, 69.8%, 70.6%, and 95.8%, respectively; 62.8%, 89.6%, 87.2%, 83.9%, and 63.8%, respectively; 20.7111, 16.8442, 15.7398, 12.2986, and 38.0578, respectively; and 0.792, 0.882, 0.859, 0.843, and 0.929, respectively.

CONCLUSION

All ultrasound-based risk-stratification systems had good diagnostic performance. Although this study determined the best cutoff values in individual risk-stratification systems based on statistical assessment, clinicians could adjust or alter cutoff values based on the clinical purpose of the ultrasound and the reciprocal changes in sensitivity and specificity.

Subcategorization of intermediate suspicion thyroid nodules based on suspicious ultrasonographic findings

PURPOSE

This study compared the malignancy risk of intermediate suspicion thyroid nodules according to the presence of suspicious ultrasonographic (US) findings.

METHODS

From January 2014 to December 2014, 299 consecutive intermediate suspicion thyroid nodules in 281 patients (mean age, 50.6±12.5 years) with final diagnoses were included in this study. Two radiologists retrospectively reviewed the US findings and subcategorized the intermediate suspicion category into nodules without suspicious findings and nodules with suspicious findings, including punctate echogenic foci, nonparallel orientation, or irregular margins. The malignancy rates were compared between the two subcategory groups.

RESULTS

Of the 299 intermediate suspicion thyroid nodules, 230 (76.9%) were subcategorized as nodules without suspicious findings and 69 (23.1%) as nodules with suspicious findings. The total malignancy rate was 33.4% (100/299) and the malignancy rate of nodules with suspicious findings was significantly higher than that of nodules without suspicious findings (47.8% vs. 29.1%, P=0.004). In nodules with suspicious findings, the most common suspicious finding was punctate echogenic foci (48/82, 58.5%) followed by nonparallel orientation (22/82, 26.8%) and irregular margins (12/82, 14.6%). Thirteen nodules had two suspicious findings simultaneously. A linearly increasing trend in the malignancy rate was observed according to the number of suspicious US findings (P for trend=0.001).

CONCLUSION

Intermediate suspicion thyroid nodules with suspicious findings showed a higher malignancy rate than those without suspicious findings. Further management guidelines for nodules with suspicious findings should differ from guidelines for nodules without suspicious findings, even in the same US category.

Development of a machine learning-based fine-grained risk stratification system for thyroid nodules using predefined clinicoradiological features

OBJECTIVE

We constructed and validated a machine learning-based malignancy risk estimation model using predefined clinicoradiological features, and evaluated its clinical utility for the management of thyroid nodules.

METHODS

In total, 5708 benign (n = 4597) and malignant (n = 1111) thyroid nodules were collected from 5081 consecutive patients treated in 26 institutions. Seventeen experienced radiologists evaluated nodule characteristics on ultrasonographic images. Eight predictive models were used to stratify the thyroid nodules according to malignancy risk; model performance was assessed via nested 10-fold cross-validation. The best-performing algorithm was externally validated using data for 454 thyroid nodules from a tertiary hospital, then compared to the Thyroid Imaging Reporting and Data System (TIRADS)-based interpretations of radiologists (American College of Radiology, European and Korean TIRADS, and AACE/ACE/AME guidelines).

RESULTS

The area under the receiver operating characteristic (AUROC) curves of the algorithms ranged from 0.773 to 0.862. The sensitivities, specificities, positive predictive values, and negative predictive values of the best-performing models were 74.1-76.6%, 80.9-83.4%, 49.2-51.9%, and 93.0-93.5%, respectively. For the external validation set, the ElasticNet values were 83.2%, 89.2%, 81.8%, and 90.1%, respectively. The corresponding TIRADS values were 66.5-85.0%, 61.3-80.8%, 45.9-72.1%, and 81.5-90.3%, respectively. The new model exhibited a significantly higher AUROC and specificity than did the TIRADS risk stratification, although its sensitivity was similar.

CONCLUSION

We developed a reliable machine learning-based predictive model that demonstrated enhanced specificity when stratifying thyroid nodules according to malignancy risk. This system will contribute to improved personalized management of thyroid nodules.

KEY POINTS

• The area under the receiver operating characteristic (AUROC) curve, sensitivity, and specificity of our model were 0.914, 83.2%, and 89.2%, respectively (derived using the validation dataset). • Compared to the TIRADS values, the AUROC and specificity are significantly higher, while the sensitivity is similar. • An interactive version of our AI algorithm is at http://tirads.cdss.co.kr .

[Clinical Application of the 2021 Korean Thyroid Imaging Reporting and Data System (K-TIRADS)]

In patients with thyroid nodules, ultrasonography (US) has been established as a primary diagnostic imaging method and is essential for treatment decision. The Korean Thyroid Imaging Reporting and Data System (K-TIRADS) is a pattern-based, US malignancy risk stratification system that can easily diagnose nodules during real-time ultrasound examinations. The 2021 K-TIRADS clarified the US criteria for nodule classification and revised the size thresholds for nodule biopsy, thereby reducing unnecessary biopsies for benign nodules while maintaining the appropriate sensitivity to detect malignant tumors in patients without feature of high risk thyroid cancer. Thyroid radiology practice has an important clinical role in the diagnosis and non-surgical treatment of patients with thyroid nodules, and should be performed according to standard practice guidelines for proper and effective clinical care.

Orientation of the ultrasound probe to identify the taller-than-wide sign of thyroid malignancy: a registry-based study with the Thyroid Imaging Network of Korea

PURPOSE

Although the taller-than-wide (TTW) sign has been regarded as one of the most specific ultrasound (US) features of thyroid malignancy, uncertainty still exists regarding the US probe's orientation when evaluating it. This study investigated which US plane would be optimal to identify the TTW sign based on malignancy risk stratification using a registry-based imaging dataset.

METHODS

A previous study by 17 academic radiologists retrospectively analyzed the US images of 5,601 thyroid nodules (≥1 cm, 1,089 malignant and 4,512 benign) collected in the webbased registry of Thyroid Imaging Network of Korea through the collaboration of 26 centers. The present study assessed the diagnostic performance of the TTW sign itself and fine needle aspiration (FNA) indications via a comparison of four international guidelines, depending on the orientation of the US probe (criterion 1, transverse plane; criterion 2, either transverse or longitudinal plane).

RESULTS

Overall, the TTW sign was more frequent in malignant than in benign thyroid nodules (25.3% vs. 4.6%). However, the statistical differences between criteria 1 and 2 were negligible for sensitivity, specificity, and area under the curve (AUC) based on the size effect (all P<0.05, Cohen's d=0.19, 0.10, and 0.07, respectively). Moreover, the sensitivity, specificity, and AUC of the four FNA guidelines were similar between criteria 1 and 2 (all P>0.05, respectively).

CONCLUSION

A longitudinal US probe orientation provided little additional diagnostic value over the transverse orientation in detecting the TTW sign of thyroid nodules.

Diagnostic Performance of ACR and Kwak TI-RADS for Benign and Malignant Thyroid Nodules: An Update Systematic Review and Meta-Analysis

(1) Background: To determine the optimal cut-off values of two risk stratification systems to discriminate malignant thyroid nodules and to compare the diagnostic performance; (2) Methods: True and false positive and negative data were collected, and methodological quality was assessed for forty-six studies involving 39,085 patients; (3) Results: The highest area under the receiver operating characteristic (ROC) curve (AUC) of ACR and Kwak TI-RADS were 0.875 and 0.884. Based on the optimal sensitivity and specificity, the highest accuracy values of ROC curves or diagnostic odds ratios (DOR) were taken as the cut-off values for TR4 (moderate suspicious) and 4B. The sensitivity, specificity, DOR, and AUC by ACR (TR4) and Kwak TI-RADS (4B) for malignancy risk stratification of thyroid nodules were 94.3% and 96.4%; 52.2% and 53.7%; 17.5185 and 31.8051; 0.786 and 0.884, respectively. There were no significant differences in diagnostic accuracy in any of the direction comparisons of the two systems; (4) Conclusions: ACR and Kwak TI-RADS had good diagnostic performances (AUCs > 85%). Although we determined the best cut-off values in individual risk stratification systems based on statistical assessment, clinicians can adjust the optimal cut-off value according to the clinical purpose of the ultrasonography because raising or lowering cut-points leads to reciprocal changes in sensitivity and specificity.

Malignancy risk stratification of thyroid nodules according to echotexture and degree of hypoechogenicity: a retrospective multicenter validation study

Various risk stratification systems show discrepancies in the ultrasound lexicon of nodule echotexture and hypoechogenicity. This study aimed to determine the malignancy risk of thyroid nodules according to their echotexture and degree of hypoechogenicity. From June to September 2015, we retrospectively evaluated 5601 thyroid nodules with final diagnoses from 26 institutions. Nodules were stratified according to the echotexture (homogeneous vs. heterogeneous) and degree of hypoechogenicity (mild, moderate, or marked). We calculated the malignancy risk according to composition and suspicious features. Heterogeneous hypoechoic nodules showed a significantly higher malignancy risk than heterogeneous isoechoic nodules (P ≤ 0.017), except in partially cystic nodules. Malignancy risks were not significantly different between homogeneous versus heterogeneous nodules in both hypoechoic (P ≥ 0.086) and iso- hyperechoic nodules (P ≥ 0.05). Heterogeneous iso-hyperechoic nodules without suspicious features showed a low malignancy risk. The malignancy risks of markedly and moderately hypoechoic nodules were not significantly different in all subgroups (P ≥ 0.48). Marked or moderately hypoechoic nodules showed a significantly higher risk than mild hypoechoic (P ≤ 0.016) nodules. The predominant echogenicity effectively stratifies the malignancy risk of nodules with heterogeneous echotexture. The degree of hypoechogenicity could be stratified as mild versus moderate to marked hypoechogenicity.

Diagnostic performance of the 2021 Korean thyroid imaging reporting and data system in pediatric thyroid nodules

OBJECTIVES

To evaluate the diagnostic performance of 2021 K-TIRADS biopsy criteria for detecting malignant thyroid nodules in a pediatric population, making comparisons with 2016 K-TIRADS.

METHODS

This retrospective study included pediatric patients with histopathologically confirmed diagnoses. The diagnostic performance of 2021 K-TIRADS was compared with that of 2016 K-TIRADS. Simulation studies were performed by changing biopsy cut-off sizes for K-TIRADS 5 to 1.0 cm (K-TIRADS_5-1.0cm) and 0.5 cm (K-TIRADS_5-0.5cm), and for K-TIRADS 4 to 1.0 cm (K-TIRADS_4-1.0cm) and 1.0-1.5 cm (K-TIRADS_4-1.0~1.5cm). Subgroup analysis was performed in small (< 1.5 cm) and large nodules (≥ 1.5 cm).

RESULTS

Two hundred seventy-seven thyroid nodules (54.9% malignant) from 221 pediatric patients were analyzed. All simulated 2021 K-TIRADS showed higher accuracy than 2016 K-TIRADS. Compared with 2021 K-TIRADS_5-1.0cm, 2021 K-TIRADS_5-0.5cm showed lower specificity (51.6% vs. 47.9%; p = 0.004) but higher sensitivity (77.2% vs. 90.3%; p < 0.001) and accuracy (62.7% vs. 68.9%; p < 0.001). Compared with 2021 K-TIRADS_4-1.0cm, 2021 K-TIRADS_4-1.0~1.5cm showed higher specificity (44.9% vs. 47.9%; p = 0.018) without significant difference in other diagnostic measures. Compared with 2016 K-TIRADS, 2021 K-TIRADS (biopsy cut-offs, 0.5 cm for K-TIRADS 5; 1.0-1.5 cm for K-TIRADS 4) showed higher sensitivity (34.0% vs. 67.3%; p < 0.001) while maintaining specificity (89.4% vs. 88.2%; p = 0.790) in small nodules, and higher specificity (5.9% vs. 25.4%; p < 0.001) while maintaining sensitivity (100% vs. 98.7%; p = 0.132) in large nodules.

CONCLUSIONS

In pediatric patients, 2021 K-TIRADS showed superior diagnostic accuracy to 2016 K-TIRADS, especially with a biopsy cut-off of 0.5 cm for K-TIRADS 5 and 1.0-1.5 cm for K-TIRADS 4.

KEY POINTS

• All simulated 2021 K-TIRADS showed higher accuracy than 2016 K-TIRADS. • 2021 K-TIRADS with cut-off size for K-TIRADS 5 of 0.5 cm showed lower specificity but higher sensitivity and accuracy than that of 1.0 cm. • Compared with 2016 K-TIRADS, 2021 K-TIRADS (biopsy cut-offs, 0.5 cm for K-TIRADS 5; 1.0-1.5 cm for K-TIRADS 4) showed higher sensitivity while maintaining specificity in small nodules, and higher specificity while maintaining sensitivity in large nodules.

Clinicoradiological Characteristics in the Differential Diagnosis of Follicular-Patterned Lesions of the Thyroid: A Multicenter Cohort Study

OBJECTIVE

Preoperative differential diagnosis of follicular-patterned lesions is challenging. This multicenter cohort study investigated the clinicoradiological characteristics relevant to the differential diagnosis of such lesions.

MATERIALS AND METHODS

From June to September 2015, 4787 thyroid nodules (≥ 1.0 cm) with a final diagnosis of benign follicular nodule (BN, n = 4461), follicular adenoma (FA, n = 136), follicular carcinoma (FC, n = 62), or follicular variant of papillary thyroid carcinoma (FVPTC, n = 128) collected from 26 institutions were analyzed. The clinicoradiological characteristics of the lesions were compared among the different histological types using multivariable logistic regression analyses. The relative importance of the characteristics that distinguished histological types was determined using a random forest algorithm.

RESULTS

Compared to BN (as the control group), the distinguishing features of follicular-patterned neoplasms (FA, FC, and FVPTC) were patient's age (odds ratio [OR], 0.969 per 1-year increase), lesion diameter (OR, 1.054 per 1-mm increase), presence of solid composition (OR, 2.255), presence of hypoechogenicity (OR, 2.181), and presence of halo (OR, 1.761) (all p < 0.05). Compared to FA (as the control), FC differed with respect to lesion diameter (OR, 1.040 per 1-mm increase) and rim calcifications (OR, 17.054), while FVPTC differed with respect to patient age (OR, 0.966 per 1-year increase), lesion diameter (OR, 0.975 per 1-mm increase), macrocalcifications (OR, 3.647), and non-smooth margins (OR, 2.538) (all p < 0.05). The five important features for the differential diagnosis of follicular-patterned neoplasms (FA, FC, and FVPTC) from BN are maximal lesion diameter, composition, echogenicity, orientation, and patient's age. The most important features distinguishing FC and FVPTC from FA are rim calcifications and macrocalcifications, respectively.

CONCLUSION

Although follicular-patterned lesions have overlapping clinical and radiological features, the distinguishing features identified in our large clinical cohort may provide valuable information for preoperative distinction between them and decision-making regarding their management.

2021 Korean Thyroid Imaging Reporting and Data System and Imaging-Based Management of Thyroid Nodules: Korean Society of Thyroid Radiology Consensus Statement and Recommendations

Incidental thyroid nodules are commonly detected on ultrasonography (US). This has contributed to the rapidly rising incidence of low-risk papillary thyroid carcinoma over the last 20 years. The appropriate diagnosis and management of these patients is based on the risk factors related to the patients as well as the thyroid nodules. The Korean Society of Thyroid Radiology (KSThR) published consensus recommendations for US-based management of thyroid nodules in 2011 and revised them in 2016. These guidelines have been used as the standard guidelines in Korea. However, recent advances in the diagnosis and management of thyroid nodules have necessitated the revision of the original recommendations. The task force of the KSThR has revised the Korean Thyroid Imaging Reporting and Data System and recommendations for US lexicon, biopsy criteria, US criteria of extrathyroidal extension, optimal thyroid computed tomography protocol, and US follow-up of thyroid nodules before and after biopsy. The biopsy criteria were revised to reduce unnecessary biopsies for benign nodules while maintaining an appropriate sensitivity for the detection of malignant tumors in small (1-2 cm) thyroid nodules. The goal of these recommendations is to provide the optimal scientific evidence and expert opinion consensus regarding US-based diagnosis and management of thyroid nodules.