BME Frontiers · Published 2026-01-01 · DOI 10.34133/bmef.0295
Objective: Microvascular alterations are early biomarkers of many diseases, but clinical translation is hindered by the lack of noninvasive deep-tissue imaging tools with capillary resolution and standardized analysis approaches. Impact Statement: ULM-based Vascular Biomarker Automated Analysis (U-VBA) provides a standardized framework that bridges microvascular imaging reconstruction and automated biomarker analysis, with feasibility demonstration in animals models in vivo and clinical patient data. Introduction: Ultrasound localization microscopy (ULM) can overcome the diffraction limit but lacks generalizable imaging reconstruction and biomarker quantification pipelines. Methods: We developed U-VBA, integrating motion correction, cascaded denoising (singular value decomposition, high-pass filtering, and background subtraction), and a panel of 6 vascular biomarkers (density, intervessel distance, diameter, velocity, perfusion, and tortuosity). Performance was validated in various settings, including flow phantoms, chicken chorioallantoic membranes (n = 5), rabbit optic nerve injury models (n = 4), and a clinical patient cohort with cervical lymph node tumors (n = 39). Results: U-VBA achieved robust performance in flow phantoms and resolved the finest capillaries down to 16.2 μm in chorioallantoic membrane models. In rabbit eye models, it precisely captures the dynamic vascular changes and establishes the vascular biomarkers during elevated intraocular pressure and recovery. In the clinical cohort, we demonstrated the potential value of U-VBA, which leverages 4 biomarkers (intervessel distance, diameter, perfusion, and tortuosity) to differentiate 3 lymph node conditions, with 85% accuracy in 5-fold cross-validation. Conclusion: U-VBA standardizes ULM-based microvascular phenotyping and integrates into routine ultrasound workflows, offering a noninvasive tool for preclinical and clinical vascular biomarker analysis.
Abstract from DOAJ. Public domain (CC0 1.0).
Read the article at the publisher →