Automated computational framework of blood vessel quantification in chick chorioallantoic membrane angiogenesis

Chick chorioallantoic membrane (CAM) angiogenesis assay has been widely used for finding drugs targeting new blood vessel development in cancer research. In addition to the setup materials and protocols, laboratory findings depend on the quantification and analysis of microscopic blood vessel images. However, it is still a challenging problem because of the high complexity of blood vessel branching structures. We applied preprocessing on CAM microscopic images by keeping the integrity of minor branches in the vessel structure. We then proposed an efficient way to automatically extract blood vessel centerlines based on vector tracing starting from detected seed points. Finally, all branches were coded to construct an abstract model of the branching structure, which enabled more accurate modeling for in-depth analysis. The framework was applied in quantifying Icaritin (ICT) inhibition effects on angiogenesis in a CAM model. Experimental results showed the high accuracy in blood vessel quantification and modeling compared with semimanual measurements. Meanwhile, a set of blood vessel growth indicators were extracted to provide fully automated analysis for angiogenesis assays. Further analysis proved that ICT took effect in a dose-dependent manner which could be applied in suppressing tumor blood vessel growth.