Computational tool for morphological analysis of cultured neonatal rat cardiomyocytes.

Abstract

This study describes the development and evaluation of a semiautomatic myocyte edge-detector using digital image processing. The algorithm was developed in Matlab 6.0 using the SDC Morphology Toolbox. Its conceptual basis is the mathematical morphology theory together with the watershed and Euclidean distance transformations. The algorithm enables the user to select cells within an image for automatic detection of their borders and calculation of their surface areas; these areas are determined by adding the pixels within each myocyte's boundaries. The algorithm was applied to images of cultured ventricular myocytes from neonatal rats. The edge-detector allowed the identification and quantification of morphometric alterations in cultured isolated myocytes induced by 72 hours of exposure to a hypertrophic agent (50 μM phenylephrine). There was a significant increase in the mean surface area of the phenylephrine-treated cells compared with the control cells (p<;0.05), corresponding to cellular hypertrophy of approximately 50%. In conclusion, this edge-detector provides a rapid, repeatable and accurate measurement of cell surface areas in a standardized manner. Other possible applications include morphologic measurement of other types of cultured cells and analysis of time-related morphometric changes in adult cardiac myocytes.