SynthesisFrontiers in endocrinology2023
Diagnostic efficiency among Eu-/C-/ACR-TIRADS and S-Detect for thyroid nodules: a systematic review and network meta-analysis.
Synthesis in Frontiers in endocrinology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed.
- Article
- Artificial intelligence in thyroid nodules and cancer: clinical validation and real-world performance.Endocrine connections · 2026Article
- Diagnostic Accuracy of Combined Fine-Needle Aspiration Biopsy and Ultrasonography for Malignancy in Bethesda III-IV Thyroid Nodules.Journal of clinical medicine · 2026Article
- Machine Learning for diagnosis of malignant thyroid nodules based on thyroid ultrasound: Systematic review and meta-analysis of studies with external datasets.European journal of radiology open · 2026Article
- A multicenter, clinically interpretable prediction model for malignancy risk in C-TIRADS 3-4 thyroid nodules.Frontiers in oncology · 2026Article
- Nomogram integrating BRAF V600E, serum biomarkers, and ultrasound features for malignancy risk stratification in C-TIRADS category 3 and 4 thyroid nodules.Frontiers in medicine · 2026Article
- Microcalcification and Irregular Margins as Key Predictors of Thyroid Cancer: Integrated Analysis of EU-TIRADS, Bethesda, and Histopathology.Medicina (Kaunas, Lithuania) · 2025Article
- Nationwide web survey on implementing the 2023 ETA guidelines for second-line management thyroid nodules with atypia of undetermined significance.Hormones (Athens, Greece) · 2025Article
- The value of C-TIRADS combined with multidimensional indicators in the diagnosis of papillary thyroid carcinoma.Gland surgery · 2025Article
- The effect of thyroid nodule location in ultrasound on the diagnosis of papillary thyroid carcinoma.Discover oncology · 2025Article
- Article
- Application of artificial intelligence in the ultrasonographic diagnosis of thyroid nodules.Journal of ultrasonography · 2025Article
- Dual-stage artificial intelligence-powered screening for accurate classification of thyroid nodules: enhancing fine needle aspiration biopsy precision.Quantitative imaging in medicine and surgery · 2025Article
- LLM evaluation for thyroid nodule assessment: comparing ACR-TIRADS, C-TIRADS, and clinician-AI trust gap.Frontiers in endocrinology · 2025Article
- Value of a BRAFFrontiers in endocrinology · 2025Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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