Preoperative diagnosis of lateral cervical lymph node metastasis in papillary thyroid carcinoma: a multimodal ultrasound model integrating super-resolution ultrasound.

BACKGROUND

Accurate preoperative diagnosis of lateral lymph node metastasis (LLNM) in papillary thyroid carcinoma (PTC) is critical but remains challenging.

OBJECTIVE

To evaluate the diagnostic value of a multimodal model integrating super-resolution ultrasound (SRUS) for the preoperative diagnosis of suspicious lateral cervical lymph nodes (LNs) in PTC.

METHODS

This prospective study enrolled consecutive participants with PTC and suspicious lateral LNs from January to November 2025. All LNs underwent US, color Doppler flow imaging (CDFI), contrast-enhanced ultrasound (CEUS), SRUS, fine needle aspiration cytology (FNAC) and fine needle aspiration thyroglobulin (FNA-Tg), with surgical pathology as the reference standard. Three generalized estimating equations models were constructed: US+CDFI, US+CEUS, and US+CEUS+SRUS. Receiver operating characteristic curves were plotted for these models, FNAC and FNA-Tg; and sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were calculated. The nomogram based on the optimal model was constructed and assessed.

RESULTS

A total of 149 lateral LNs (74 metastatic, 75 non-metastatic) from 112 participants (median age, 46 years [IQR, 35–54 years]; 72 female) were analyzed. The multimodal US+CEUS+SRUS model achieved an area under the curve (AUC) of 0.961(95% CI: 0.933, 0.988), superior to both the US+CDFI (AUC, 0.851; 95% CI: 0.791, 0.911; P < 0.001) and US+CEUS (AUC, 0.921; 95% CI: 0.878, 0.964; P = 0.040) models. It outperformed FNAC (AUC, 0.858; 95% CI: 0.806, 0.910; P < 0.001) and demonstrated comparable to FNA-Tg (AUC, 0.961; 95% CI: 0.928, 0.994; P = 0.989). Five independent predictors were identified: microcalcifications, abnormal hyperechogenicity, centripetal/synchronous enhancement, microvascular complexity level > 1.64, and mean density > 9.82. The resultant nomogram showed excellent discrimination, calibration and clinical utility.

CONCLUSION

The multimodal US+CEUS+SRUS model provides an accurate, non-invasive strategy for preoperative diagnosis LLNM in PTC.