A Multiparametric Approach Integrating Multimodal Ultrasound and Serum TPO-Ab for Differentiating Thyroid Carcinoma...

To evaluate whether a multiparametric approach combining grayscale ultrasound (2D-US), contrast-enhanced ultrasound (CEUS), and serum anti-thyroid peroxidase antibody (TPO-Ab) improves the differentiation of benign from malignant thyroid nodules (TNs) in patients with Hashimoto's thyroiditis (HT) and to assess the stability of the combined diagnostic model through internal validation.

This retrospective study enrolled 600 HT patients with 650 pathologically confirmed TNs. All patients underwent 2D-US; CEUS was performed in 475, TPO-Ab testing in 452, and shear wave elastography (SWE) in an exploratory subset of 88 patients. The primary combined diagnostic model was developed using logistic regression (LR) on the subset of patients with complete 2D-US, CEUS, and TPO-Ab data. Internal validation was performed via stratified 5-fold cross-validation. Six machine learning classifiers were additionally compared to assess model robustness.

Among single modalities, 2D-US showed the highest cross-validated area under the curve (AUC) (LR: 0.831). CEUS and TPO-Ab alone yielded limited discrimination (AUC 0.671 and 0.621, respectively). The combined model integrating 2D-US, CEUS, and TPO-Ab achieved a cross-validated AUC of 0.849 with sensitivity of 77.3% and specificity of 77.8%, outperforming any single modality. Among the 6 classifiers evaluated, LR demonstrated the most stable performance and the best balance between sensitivity and specificity.

Integrating multimodal ultrasound with serum TPO-Ab significantly improves the differentiation of TNs in HT, with the combined LR model demonstrating robust performance after internal validation. This multiparametric approach may serve as a supplementary tool for risk stratification in surgical candidates, but prospective external validation is required before clinical implementation.