Segmentation of wall and plaque in in vitro vascular MR images

Abstract

Atherosclerosis leads to heart attack and stroke, which are major killers in the western world. These cardiovascular events frequently result from local rupture of vulnerable atherosclerotic plaque. Non-invasive assessment of plaque vulnerability would dramatically change the way in which atherosclerotic disease is diagnosed, monitored, and treated. In this paper, we report a computerized method for segmentation of arterial wall layers and plaque from high-resolution volumetric MR images. The method uses dynamic programming to detect optimal borders in each MRI frame. The accuracy of the results was tested in 62 T1-weighted MR images from six vessel specimens in comparison to borders manually determined by an expert observer. The mean signed border positioning errors for the lumen, internal elastic lamina, and external elastic lamina borders were -0.1 +/- 0.1, 0.0 +/- 0.1, and -0.1 +/- 0.1 mm, respectively. The presented wall layer segmentation approach is one of the first steps towards non-invasive assessment of plaque vulnerability in atherosclerotic subjects.