Automatic Stereology of Biological Tissue Using 3-D VCS

DESCRIPTION (provided by applicant): The studies in Phase II continue the effort begun in Phase I to equip a commercially available stereology system (Stereologer) with image analysis capability to automatically sample and quantify features of biological interest in tissue sections. The investigators have adapted image analysis algorithms, developed in part by a collaborator's missile ballistic systems research program, into an auto-detection and auto-analysis program called Verified Computerized Stereoanalysis (VCS). Phase I demonstrated the ability of VCS to quantify size parameters of proliferating cells in tissue sections with equal accuracy to the gold standard (manual click) approach, but with a significant 8-fold improvement in throughput efficiency. Operationally, the VCS program acquires an internal target of color pixels associated with the feature of interest, while the user performs manual data collection for the first section from the initial case in the study. Once the user verifies an acceptable level of accuracy relative to manual data collection (gold standard), the program can be switched into fully automatic mode, a combination of motorized stage control for systematic-random sampling; auto-detection of stained microscopic features of interest; and, auto-analysis of global and local size parameters and their variation based on state-of-the-art stereological principles. These investigations found that biological features that label (stain) proteins with specific immunological-based probes, followed by amplification of the signal with chromogen reactions or fluorescence, stimulate the most robust response from the VCS algorithm. Phase II will expand VCS to the 3-D analysis of all 1st-order (number, length, surface area, and volume) and 2nd-order (variation, spatial distribution) stereological parameters (Aim 1); validate 3-D VCS against the gold standard approach and identify the principal tissue processing and staining procedures to increase algorithm robustness (Aim 2); and, develop StereoTutorials and on-line documentation to assist the conversion of current users of computerized stereology systems from manual to automatic VCS approaches (Aim 3). The long-term goal for VCS is to increase the throughput efficiency for stereoanalyses of parameters on tissue sections without a loss of accuracy; reduce research costs in terms of time and labor; and, accelerate scientific progress toward improvements in health and the management of disease. Solid evidence that the PI and colleagues can successfully commercialize the VCS program in Phase III is demonstrated by worldwide sales and support of the Stereologer and other stereology resources for the past decade.