Quantitative image analysis of histological sections of coronary arteries

The study of coronary arteries has evolved from examining gross anatomy and morphology to scrutinizing micro-anatomy and cellular composition. Technological advances such as high-resolution digital microscopes and high precision cutting devices have allowed examination of coronary artery morphology and pathology at micron resolution. We have developed a software toolkit to analyze histological sections. In particular, we are currently engaged in examining normal coronary arteries in order to provide the foundation for study of remodeled tissue. The first of two coronary arteries was stained for elastin and collagen. The second coronary artery was sectioned and stained for cellular nuclei and smooth muscle. High resolution light microscopy was used to image the sections. Segmentation was accomplished initially with slice-to-slice thresholding algorithms. These segmentation techniques choose optimal threshold values by modeling the tissue as one or more distributions. Morphology and image statistics were used to further differentiate the thresholded data into different tissue categories therefore refine the results of the segmentation. Specificity/sensitivity analysis suggests that automatic segmentation can be very effective. For both tissue samples, greater than 90% specificity was achieved. Summed voxel projection and maximum intensity projection appear to be effective 3-D visualization tools. Shading methods also provide useful visualization, however it is important to incorporate combined 2-D and 3-D displays. Surface rendering techniques (e.g. color mapping) can be used for visualizing parametric data. Preliminary results are promising, but continued development of algorithms is needed.