Thyroglobulin-to-tumor volume ratio combined with ultrasound features for diagnosing thyroid follicular neoplasms.

OBJECTIVE

Current preoperative diagnostics inadequately differentiate benign from malignant thyroid follicular neoplasms. This study evaluated the diagnostic utility of thyroid function markers and contrast-enhanced ultrasound (CEUS) features in differentiating follicular thyroid adenoma (FTA) from follicular thyroid carcinoma (FTC), focusing on a novel parameter: the thyroglobulin-to-tumor volume ratio (Tg/Vol ratio).

METHODS

We retrospectively analyzed 432 resected thyroid follicular neoplasms. A comprehensive comparison was performed regarding baseline characteristics, thyroid function profiles, and CEUS features between FTA and FTC groups through univariate and multivariate binary logistic regression. Diagnostic performance was determined via receiver operating characteristic (ROC) curve analysis. The prevalence of FTC across serum marker subgroups was assessed, followed by the development of a multivariate diagnostic model integrating the Tg/Vol ratio with CEUS characteristics.

RESULTS

Among 432 patients (352 females, 81.5%) with a median age of 47 years, multivariate logistic regression analysis revealed three independent predictors of FTC: capsular involvement (odds ratio [OR] = 9.958, 95% confidence interval [CI]: 2.453 - 40.424, p = 0.001), Tg/Vol ratio >7.412 (OR = 3.508, 95% CI: 1.388 - 8.868, p = 0.008), and male gender (OR = 3.474, CI: 1.751 - 6.891, p < 0.001). Subgroup analyses revealed higher FTC prevalence in patients with Tg > 409.18 μg/L (20.41%, p = 0.002) and Tg/Vol ratio > 20.68 (20.41%, p = 0.009). The combined diagnostic model incorporating Tg/Vol ratio and CEUS features demonstrated 69.4% sensitivity, 77.0% specificity, and the area under the curve(AUC) of 0.769.

CONCLUSION

While elevated preoperative Tg correlates with malignant potential, but the Tg/Vol ratio emerges as a more robust preoperative discriminator. The combined diagnostic model incorporating Tg/Vol ratio and CEUS features significantly improves FTC detection accuracy.