Diagnostic accuracy of ultrasound, CT and their combination in detecting cervical lymph node metastasis in patients with papillary thyroid cancer: a systematic review and meta-analysis.

Abstract

To determine the diagnostic accuracy of ultrasound (US), CT and their combination in detecting cervical lymph node metastasis (CLNM) in patients with papillary thyroid cancer (PTC). Medline (via PubMed), Web of Science, Embase were searched to identify studies published till 5 December 2021 that used US and CT to detect CLNM in patients with PTC. The primary outcomes were sensitivity, specificity and diagnostic ORs in neck-level-based (lymph nodes are analysed by neck level) or patient-based (lymph nodes are analysed by patient) analysis. Secondary outcomes were sensitivity, specificity and DORs in the central and lateral compartments. Fourteen studies (6167 patients with 11 601 neck lymph nodes) met the inclusion criteria. Based on the neck-level-based analysis, the pooled sensitivity, specificity and DORs were 0.35 (95% CI 0.34 to 0.37), 0.95 (95% CI 0.94 to 0.95) and 13.94 (95% CI 9.34 to 20.82) for US, were 0.46 (95% CI 0.44 to 0.47), 0.88 (95% CI 0.87 to 0.89) and 7.24 (95% CI 5.46 to 9.62) for CT, were 0.51 (95% CI 0.49 to 0.52), 0.85 (95% CI 0.84 to 0.86), 6.01 (95% CI 3.84 to 9.40) for the combination of US and CT. In the patient-based analysis, the pooled estimates of sensitivity, specificity and DOR were 0.41 (95% CI 0.36 to 0.46), 0.92 (95% CI 0.89 to 0.94) and 7.56 (95% CI 4.08 to 14.01) for US, were 0.49 (0.44 to 0.54), 0.91 (0.89 to 0.94), 9.40 (5.79 to 15.27) for CT, and were 0.64 (95% CI 0.57 to 0.71), 0.83 (95% CI 0.77 to 0.88), 8.59 (95% CI 5.37 to 13.76) for the combination of US and CT. These findings suggest US, with a DOR almost twice that of CT in the neck-level-based analysis, was superior to CT in detecting CLNM in patients with PTC, especially in the lateral compartment. The combination of US and CT increased the sensitivity from 41%-49% for the individual modalities to 64% for combined modalities in the patient-based analysis.