Mayo Foundation for Medical Education and Research

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Mostafa Fatemi

Azra Alizad

Yinong Wang

The present disclosure addresses a quantitative analysis of tumor vascularity patterns, with the goal of identifying biomarkers correlated with malignancy. Herein, we identify new types of quantitative ultrasound biomarkers of microvessel morphology that correlate with the state of the disease in question. We propose a novel method to automatically extract quantitative features related to the morphology and distribution of the vascular networks reconstructed from contrast-free ultrasound data. For instance, spatial vascularity pattern, bifurcation angle, Murray's deviation, fractal dimension and closet vessel distance were clearly depicted.

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Rochester, MN, United States of America

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