Contrast-Enhanced Ultrasound for Diagnosing Thyroid Nodules With Indeterminate Cytology: A Retrospective Study

A small number of thyroid nodules cannot be clearly diagnosed using ultrasound-guided fine needle aspiration biopsy. Contrast-enhanced ultrasound (CEUS) has high diagnostic performance for thyroid nodules. We explored the value of CEUS for diagnosing thyroid nodules with indeterminate cytology.

Between September 2019 and July 2022, 27,646 patients with thyroid nodule(s) underwent conventional ultrasound (CUS) in our hospital. From these patients, 597 nodules were subjected to CEUS and ultrasound-guided fine needle aspiration biopsy and 116 thyroid nodules with indeterminate cytology diagnose were enrolled in this study. The independent risk factors for predicting malignancy were determined using univariate and multivariate logistic regression analyses. Receiver operating characteristic (ROC) curves were drawn for CUS, CEUS, and CEUS combined with CUS. The area under the curve (AUC) was calculated and compared.

Of the 116 thyroid nodules, 40 (34.5%) were benign and 76 (65.5%) were malignant. Univariate analysis showed that the shape, echogenicity, margin, microcalcification, enhancement intensity, enhancement homogeneity, wash in, and wash out were significantly different between benign and malignant thyroid nodules (all p < 0.05). Multivariate logistic regression analysis showed that taller-than-wide, irregular margin, microcalcification, hypo-enhancement, heterogeneity enhancement, synchronous/slower wash in, and synchronous/slower wash out were independent risk factors for malignancy (all p < 0.05). ROC curve analysis showed that the AUC of CUS and CEUS were 0.769 and 0.848, respectively. No significant difference was observed in the AUC between the two modalities (p > 0.05). However, the AUC (0.934) of the CUS combined with CEUS was significantly higher than that of CEUS or CUS alone (both p < 0.05).

CEUS is helpful in diagnosing thyroid nodules with indeterminate cytology. CUS combined with CEUS is highly valuable for predicting malignancy.