Clinical diagnostic value of American College of Radiology thyroid imaging report and data system in different kinds of thyroid nodules

To diagnose primary and secondary squamous cell carcinoma of the thyroid with ultrasound malignancy risk stratification

Objectives

This study aimed to investigate the clinico-ultrasound features of primary squamous cell carcinoma of the thyroid (PSCCT) and secondary SCCT (SSCCT) and evaluate the accuracy of fine needle aspiration (FNA) recommendation for SCCT with American College of Radiology-Thyroid Imaging and Reporting Data System (ACR-TIRADS) and Chinese-TIRADS (C-TIRADS).

Materials and methods

We retrieved 26 SCCT patients (11 PSCCT, 15 SSCCT) from our hospital's pathology database (5,718 patients with thyroid malignancy) over 23 years. Medical records and ultrasound data of the 26 patients with 27 SCCTs were analyzed retrospectively, and each SCCT focus was categorized based on the two TIRADSs.

Results

For 26 patients (21 males, 5 females) with an age range of 42-81 years, rapidly enlarging thyroid/neck nodules (18/26, 69.2%), dysphagia (7/26, 26.9%), hoarseness (6/26, 23.1%), dyspnea (5/26, 19.6%), cough (4/26, 15.4%), neck pain (2/26, 7.7%), B symptoms (2/26, 7.7%), and blood in sputum (1/26, 3.8%) were presented at diagnosis. Five asymptomatic patients (5/26, 19.2%) were detected by ultrasound. Hoarseness was more common in PSCCT (5/11, 45.5%) than in SSCCT (1/15, 6.7%) (P=0.032). For 27 SCCTs with a mean size of 3.7 ± 1.3 cm, the ultrasound features consisted of solid (25/27, 92.6%) or almost completely solid composition (2/27, 7.4%), hypoechoic (17/27, 63%) and very hypoechoic echogenicity (10/27, 37%), irregular/lobulated margin with extra-thyroidal extension (27/27, 100%), taller-than-wide shape (13/27, 48.1%), punctate echogenic foci (6/27, 22.2%), hypervascularity (23/27, 85.2%) and involved neck lymph (13/26, 50.0%). A total of 27 SCCTs were evaluated as high malignancy risk stratification (≥TR4 and 4B) by the two TIRADSs and recommended FNA in 96.3-100% (26/27, 27/27). Pathologically, more than half of PSCCTs (7/12, 58.3%) and a quarter of SSCCTs (4/15, 26.7%) were poorly differentiated, while moderately and well-differentiated grades were observed in 5 PSCCTs and 11 SSCCTs (P=0.007). Thirteen patients (50.0%) underwent surgery with radical operation in 5 cases (5/13, 38.5%).

Conclusion

SCCT is an extremely rare and aggressive malignancy with a male predominance. PSCCT and SSCCT had similar clinical and ultrasound features except for tumor differentiation and the symptom of hoarseness. SCCT showed a high malignancy risk stratification in ACR-TIRADS and C-TIRADS, with a high rate of FNA recommendation.

Deep learning predicts cervical lymph node metastasis in clinically node-negative papillary thyroid carcinoma

OBJECTIVES

Precise determination of cervical lymph node metastasis (CLNM) involvement in patients with early-stage thyroid cancer is fairly significant for identifying appropriate cervical treatment options. However, it is almost impossible to directly judge lymph node metastasis based on the imaging information of early-stage thyroid cancer patients with clinically negative lymph nodes.

METHODS

Preoperative US images (BMUS and CDFI) of 1031 clinically node negative PTC patients definitively diagnosed on pathology from two independent hospitals were divided into training set, validation set, internal test set, and external test set. An ensemble deep learning model based on ResNet-50 was built integrating clinical variables, BMUS, and CDFI images using a bagging classifier to predict metastasis of CLN. The final ensemble model performance was compared with expert interpretation.

RESULTS

The ensemble deep convolutional neural network (DCNN) achieved high performance in predicting CLNM in the test sets examined, with area under the curve values of 0.86 (95% CI 0.78-0.94) for the internal test set and 0.77 (95% CI 0.68-0.87) for the external test set. Compared to all radiologists averaged, the ensemble DCNN model also exhibited improved performance in making predictions. For the external validation set, accuracy was 0.72 versus 0.59 (p = 0.074), sensitivity was 0.75 versus 0.58 (p = 0.039), and specificity was 0.69 versus 0.60 (p = 0.078).

CONCLUSIONS

Deep learning can non-invasive predict CLNM for clinically node-negative PTC using conventional US imaging of thyroid cancer nodules and clinical variables in a multi-institutional dataset with superior accuracy, sensitivity, and specificity comparable to experts.

CRITICAL RELEVANCE STATEMENT

Deep learning efficiently predicts CLNM for clinically node-negative PTC based on US images and clinical variables in an advantageous manner.

KEY POINTS

• A deep learning-based ensemble algorithm for predicting CLNM in PTC was developed. • Ultrasound AI analysis combined with clinical data has advantages in predicting CLNM. • Compared to all experts averaged, the DCNN model achieved higher test performance.

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.

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.

Comparison of the effectiveness of lauromacrogol injection for ablation and microwave ablation in the treatment of predominantly cystic thyroid nodules: a multicentre study

PURPOSE

To compare the therapeutic efficacy and safety of microwave ablation (MWA) and lauromacrogol injection for ablation (LIA) for benign predominantly cystic thyroid nodules.

MATERIALS AND METHODS

In this retrospective study, 85 patients with predominantly cystic thyroid nodules (PCTNs) who underwent microwave ablation (MWA) or lauromacrogol injection for ablation (LIA) between June 2019 and August 2022 at three hospitals were included in our research. Forty-six patients were treated with microwave ablation, and thirty-nine patients were treated with lauromacrogol injection for ablation. The baseline characteristics, nodal volume, volume reduction rate (VRR), and incidence of postoperative complications were compared between these two groups.

RESULTS

After treatment, there were significant differences in the thyroid nodule volume and the volume reduction rate (VRR) at different follow-up times between the groups (p < 0.001). There were no significant differences in the nodal volume or the volume reduction rate (VRR) between the MWA group and the LIA group at 1, 3, 6, and 12 months (p > 0.05). Of note, no serious intraoperative or postoperative complications occurred in the corresponding group.

CONCLUSION

MWA and LIA are very effective and safe strategies for the treatment of predominantly cystic thyroid nodules. However, LIA is more advantageous in that it is less expensive and has a shorter length of hospital stay than MWA.

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.

Accuracy of fine-needle aspiration cytopathology to differentiate malignant and benign thyroid nodules with ≥4 cm diameter: A retrospective study

BACKGROUND

Thyroid nodules (TN) are commonly present in the general population and are usually pathologically benign. An initial diagnosis with fine-needle aspiration (FNA) cytopathology could help clinical decision-making with fewer complications. As the previous studies suggest surgical procedures for >4 cm TNs, we aimed to investigate the accuracy of preoperative FNA cytology to predict malignancy risk in these nodules in a sample of the Iranian population.

METHODS

Patients with ≥4 cm TNs who had preoperative FNA cytology, underwent nodulectomy and had a histopathological report were included. Each patient's preoperative demographic, ultrasonographic, and cytology data were gathered. After surgery, resected samples were assessed pathologically and diagnosed as benign or malignant. Finally, data were analyzed to evaluate the presurgical accuracy of the FNA cytology.

RESULTS

We identified 41 (51.25%) patients with malignant legions among our study population (N = 80). The pathology reports were indeterminate in 3 patients with follicular neoplasm. Bethesda scores were substantially higher in patients with malignancy. The sensitivity, specificity, and false-negative rate of FNA cytology reports using the Bethesda system were 73.7%, 74.2%, and 26.3%, respectively. There was no association between malignancy and TNs' size, neither their volume nor their highest diameter.

CONCLUSION

FNA cytology is not as sensitive and specific in nodules>4 cm as in smaller ones. However, it can still be used alongside other diagnostic procedures in malignancy screening. Clinicians should make more complex decisions considering various influential factors to avoid missing malignant lesions and reduce diverse probable complications of highly invasive diagnostic surgery. Further prospective research on >4 cm TNs and their multiple features' association with malignancy is required for more precise judgment.

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.

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.