Automatic vessel wall contour detection and quantification of wall thickness in in-vivo MR images of the human aorta

PURPOSE: To develop an automated technique to trace the contours of the lumen and outer boundary of the aortic wall, and measure aortic wall thickness in axial MR images. MATERIALS AND METHODS: The algorithm uses prior knowledge of vessel wall morphology. A geometrical model (ellipse) is deformed, translated and rotated to obtain a rough approximation of the contours. Model-matching is based on image gradient measurements. To enhance edges, the images were preprocessed using gray-level stretching. Refinement is performed by means of dynamic programming. Wall thickness is computed by measuring the distance between inner and outer contour of the aortic wall. RESULTS: The algorithm has been tested on high-resolution axial MR images from 28 human subjects of the descending thoracic aorta. The results demonstrate: High correspondence between automatic and manual area measurements: lumen (r = 0.99), outer (r = 0.96), and wall thickness (r = 0.85). CONCLUSION: Though further optimization is required, our algorithm is a powerful tool to automatically draw the boundaries of the aortic wall and measure aortic wall thickness in aortic wall devoid of major lesions. J. Magn. Reson. Imaging 2006. (c) 2006 Wiley-Liss, Inc.