Application of quantitative morphological cytometry for evaluation of shear stress: potential for HCS systems. Bartek Rajwa * , Dominik Lenz, Bülent Bayraktar, Silas Leavesley, and J. Paul Robinson Purdue University Cytometry Laboratories, Bindley Bioscience Center, 1203 W. State Street, Purdue University, West Lafayette, IN 47907-2057, USA ABSTRACT Shear stress is known to have a significant effect on the state of cellular differentiation. It also induces morphologic responses including changes to cytoskeletal organization subsequently leading to changes in cell shape. In fact, fluid shear stress caused by blood flow is a major determinant of vascular remodeling and can lead to development of atherosclerosis. The morphological changes are usually evaluated using boundary-based shape descriptors or binary geometrical moments on manually segmented cells. Although any one of the many automated segmentation methods could be employed, these techniques are known to be complex and time consuming, and often require user input to operate properly, which is especially problematic for HCS systems. Therefore, development of robust, quantitative morphological measurements that are not dependent on precision and reproducibility of segmentation is extremely important for a substantial improvement of shear-stress analysis. The goals of this study were to find simple morphological descriptors that could be applied to cells isolated by tessellation in order to enable a high-throughput screening of morphological shear-stress response, and to determine the amount of fluid shear stress to which endothelial cells were exposed on the basis of changes in their morphology. The proposed technique is based on the monitoring of changes in cytoskeleton organization using texture descriptors, rather than on quantifying cell-boundary modifications. We showed that objects identified by Voronoi tessellation carried enough information about cytoskeleton texture of individual cells to create a robust classifier. Our approach provided higher discriminant and predictive powers, and better classification capability, than traditional boundary-based methods. The robustness of classification in the presence of segmentation difficulties makes the proposed approach particularly suitable for automated HCS systems. Keywords: image cytometry, microscopy, high-content screening, image analysis, automated classification. 1. INTRODUCTION The change of shape by endothelial cells coinciding with differentiation is a well-known response to shear stress and has been described in many reports 1-5 (Figure 1), but the provided quantitative evaluation has been incomplete and difficult to reproduce. The described changes in morphology include polarization of the cells and cell elongation in the direction of the shear vector. The quantitative analysis of morphological changes triggered by shear stress has been mostly limited to calculation of a form factor (defined as 4π·area/perimeter 2 ). Although the form factor, which was introduced to shear stress studies by Nerem and his colleagues in ‘80s 5-8 , is intuitively understandable and seemingly easy to calculate, in practice it is hard to determine and ambiguous owing to its boundary dependence. Therefore, development of a robust yet simple method for fast evaluation of morphological changes in cells exposed to shear stress, in a way that is not dependent on precisely segmented boundaries can be an important contribution to automated shear-stress analysis. * brajwa@purdue.edu; tel. (765) 494 0757 Photonics West 20–25 January 2007 San Jose, California USA Q:\Manuscripts\2007\SPIE\6441-20.pdf