Rapid analysis of vessel elements (RAVE): a tool for studying physiologic, pathologic and tumor angiogenesis.

Abstract

Quantification of microvascular network structure is important in a myriad of emerging research fields including microvessel remodeling in response to ischemia and drug therapy, tumor angiogenesis, and retinopathy. To mitigate analyst-specific variation in measurements and to ensure that measurements represent actual changes in vessel network structure and morphology, a reliable and automatic tool for quantifying microvascular network architecture is needed. Moreover, an analysis tool capable of acquiring and processing large data sets will facilitate advanced computational analysis and simulation of microvascular growth and remodeling processes and enable more high throughput discovery. To this end, we have produced an automatic and rapid vessel detection and quantification system using a MATLAB graphical user interface (GUI) that vastly reduces time spent on analysis and greatly increases repeatability. Analysis yields numerical measures of vessel volume fraction, vessel length density, fractal dimension (a measure of tortuosity), and radii of murine vascular networks. Because our GUI is open sourced to all, it can be easily modified to measure parameters such as percent coverage of non-endothelial cells, number of loops in a vascular bed, amount of perfusion and two-dimensional branch angle. Importantly, the GUI is compatible with standard fluorescent staining and imaging protocols, but also has utility analyzing brightfield vascular images, obtained, for example, in dorsal skinfold chambers. A manually measured image can be typically completed in 20 minutes to 1 hour. In stark comparison, using our GUI, image analysis time is reduced to around 1 minute. This drastic reduction in analysis time coupled with increased repeatability makes this tool valuable for all vessel research especially those requiring rapid and reproducible results, such as anti-angiogenic drug screening.