Quantification of microvasculature parameters based on optoacoustic angiography data

Abstract

Optoacoustic (OA) angiography allows high-contrast three-dimensional (3D) visualization of hemoglobin-containing structures ranging from micrometers to millimeters. However, due to the large amount of 3D data acquired by modern high-throughput OA systems the resulting OA vasculature images might be difficult to analyze visually. This problem is especially relevant for monitoring of angiogenesis of experimental tumors, which blood vessels tend to be smaller and more tortuous compared to vasculature of healthy tissue. In this paper a novel algorithm for OA image processing is proposed to quantify vessel structure parameters automatically. The algorithm is based on creation of vasculature graphs which parameters (lengths of branches, number of branches, etc) can serve as a numerical characterization of vasculature: vessel density, vessel length, etc. The results of testing the developed algorithm on numerical simulation phantoms and in vivo OA images of tumor models in a mouse demonstrate a statistically significant difference of all the extracted parameters for tumor and normal tissue. The results show a high potential of the proposed approach for OA angiography in different applications including clinical and experimental oncology.