Quantitative analysis of ultrasound contrast flow behavior in carotid plaque neovasculature

Intraplaque neovascularization is considered as an important indication for plaque vulnerability. We propose a semiautomatic algorithm for quantification of neovasculature, thus, enabling assessment of plaque vulnerability. The algorithm detects and tracks contrast spots using multidimensional dynamic programming. Classification of contrast tracks into blood vessels and artifacts was performed. The results were compared with manual tracking, visual classification and maximal intensity projection. In 28 plaques, 97% of the contrast spots were detected. In 89% of the objects, the automatic tracking determined the contrast motion with an average distance of less than 0.5 mm from the manual marking. Furthermore, 75% were correctly classified into artifacts and vessels. The automated neovascularization grading agreed within 1 grade with visual analysis in 91% of the cases, which was comparable to the interobserver variability of visual grading. These results show that the method can successfully quantify features that are linked to vulnerability of the carotid plaque.