Ultrafast ultrasound localization microscopy for differential diagnosis of reactive hyperplasia and metastatic cervical lymph nodes: a pilot study.

Background: Cervical lymph nodes (LNs) play pivotal roles in immune surveillance and oncologic spread. This study investigates the clinical utility of ultrafast ultrasound localization microscopy (ULM) for distinguishing reactive hyperplasia from metastatic cervical LNs, aiming to improve diagnostic precision beyond conventional ultrasound (US) capabilities. Methods: We prospectively analyzed 135 histopathologically confirmed LNs (scheduled for December 2023 to October 2024) using multimodal US assessment: conventional two-dimensional (2D) imaging, superb microvascular imaging (SMI), and ULM. Quantitative parameters [vessel diameter, vascular index (VI), microvascular density (MVD)] and qualitative flow patterns were systematically evaluated against pathological standards. Diagnostic performance was assessed through multivariable logistic regression and receiver operating characteristic (ROC) analysis. Results: Metastatic LNs demonstrated significantly larger mean vessel diameters (155.6±24.9 vs. 138.5±33.2 μm; P<0.001), increased MVD (49.9%±17.1% vs. 38.2%±22.0%; P=0.022), and chaotic microvascular architecture compared to reactive LNs. Multivariate analysis identified three independent predictors: long-to-short axis (L/S) ≥2 [odds ratio (OR) =0.236; 95% confidence interval (CI) 0.067-0.840], heterogeneous vascular distribution (OR =29.977; 95% CI: 6.927-129.726), and elevated MVD (OR =1.046 per 1% increase; 95% CI: 1.011-1.084). The integrated 2D + SMI + ULM model demonstrated superior diagnostic efficacy [area under the curve (AUC) =0.913; sensitivity 78.4%, specificity 95.1%], significantly outperforming conventional 2D US alone (AUC =0.660). Conclusions: ULM enhances microvascular characterization of cervical LNs by revealing pathological angiogenesis patterns undetectable through standard ultrasonography. The synergistic combination of ULM with established US modalities achieves optimal diagnostic accuracy, providing a clinically actionable non-invasive approach for metastatic LNs identification. This paradigm may reduce unwarranted invasive procedures while improving pretreatment staging reliability.