KEYWORDS: Tumors, 3D image processing, Image segmentation, In vivo imaging, Statistical analysis, 3D modeling, Confocal microscopy, Image resolution, Image analysis, 3D metrology
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.
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