Automated in vivo change analysis of tumor vasculature from two-photon confocal image time series

摘要

Automated methods are described for in vivo quantitation of changes in tumor vasculature. The tumor subsurface is imaged non-invasively over time with two-photon confocal microscopy aided by a variety of chronic animal window preparations. This results in time series of three-dimensional (3-D) image stacks for each specimen at high resolution (768x512x32 voxels, 8 bits/voxel, every 24 hours for 7 days), imaging depth and signal-to-background ratio. Next, automated image analysis allows detection and quantitation of vascular changes in a rapid and objective manner without manual tedium. We describe a fast new algorithm for fully automated 3-D tracing (50 seconds to trace a 10 MB stack on a Dell 1 GHz Pentium III personal computer). A variety of measurements including tortuosity, length, thickness, and branching order are generated and analyzed. Quantitative validation of the performance of the tracing algorithm against manual tracing resulted in 81% concordance. This enables a broader set of change analysis studies including testing the efficacy of anti-angiogenic therapies and deriving vessel growth parameters that may be correlated with physiological and gene expression profiles in tumor.