A Combined Model of Ultrasound Viscoelasticity and Inflammatory Indices for Differentiating Benign and Malignant Breast Lesions

Background : Differentiating breast lesions relies on imaging and pathological biopsy. Ultrasound viscoelastic imaging quantitatively assesses tissue stiffness, while systemic inflammatory parameters reflect the host's immune status. This study aimed to develop and validate a combined model utilizing both viscoelastic and inflammatory parameters to improve diagnostic accuracy. Methods: This retrospective study enrolled 184 patients with 205 breast masses. All participants underwent preoperative ultrasound viscoelasticity examination (Shear Wave Elastography) and blood tests. Viscoelastic parameters (Young's modulus, viscosity) and inflammatory indices (SII, NLR, PLR, LMR) were analyzed. The Least Absolute Shrinkage and Selection Operator (LASSO) regression was used for feature selection, and a multivariate logistic regression model was constructed. Diagnostic performance was evaluated using Receiver Operating Characteristic (ROC) analysis. Results: Malignant lesions exhibited significantly higher viscoelastic and inflammatory parameters compared to benign lesions. The combined model achieved an area under the curve (AUC) of 0.95 (95% CI: 0.91-0.98), with a sensitivity of 86.96% and a specificity of 89.55%, significantly outperforming any single parameter. Conclusion: The integration of ultrasound viscoelasticity and systemic inflammatory indices provides a powerful non-invasive tool for distinguishing benign from malignant breast lesions, holding significant potential to optimize clinical decision-making and reduce unnecessary biopsies.