Abstract
OBJECTIVE: To systematically evaluate the diagnostic performance of high-frequency ultrasound and its sonographic features in the early detection of thyroid cancer through a meta-analysis. METHODS: A comprehensive search was conducted in PubMed, Embase, and Web of Science for studies published up to December 31, 2024. Studies assessing the diagnostic performance of high-frequency ultrasound and ultrasound-guided procedures for thyroid cancer were included based on predefined criteria. Extracted data included sensitivity, specificity, and the diagnostic relevance of sonographic features (e.g., nodule size, margin irregularity, echogenicity, calcifications, and vascularity). Study quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies (QUADAS) tool. Meta-analytic methods were applied to pool diagnostic accuracy measures. Publication bias was evaluated using funnel plots. RESULTS: A total of 14 studies were included. Combined diagnostic approaches, particularly high-frequency ultrasound combined with ultrasound-guided fine-needle aspiration biopsy (US-FNAB), demonstrated high sensitivity (ranging from 0.814 to 0.975) and specificity (ranging from 0.833 to 0.976). Key sonographic features significantly associated with malignancy included hypoechogenicity, microcalcifications, and irregular margins. Pooled analysis showed that microcalcifications and irregular margins were strong predictors for malignancy, with an overall Peto odds ratios (OR) of 39.47 [28.88, 53.94] for irregular margins (P<0.001). Minimal publication bias was observed for most features, although mild asymmetry was noted in analyses involving microcalcifications. CONCLUSION: High-frequency ultrasound, particularly when combined with ultrasound-guided biopsy or contrast-enhanced ultrasound, provides high diagnostic accuracy for thyroid cancer. Specific features, such as hypoechogenicity, microcalcifications, and irregular margins, are valuable in differentiating malignant from benign thyroid nodules. Future studies should aim to standardize ultrasound-based diagnostic criteria and explore the use of multimodal imaging techniques to improve early thyroid cancer detection.