Automatic detection of plaques with severe stenosis in coronary Vessels of CT Angiography

Coronary artery disease is the end result of the accumulation of atheromatous plaques within the walls of coronary arteries and is the leading cause of death worldwide. Computed tomography angiography (CTA) has been proved to be very useful for accurate noninvasive diagnosis and quantification of plaques. However, the existing methods to measure the stenosis in the plaques are not accurate enough in mid and distal segments where the vessels become narrower. To alleviate this, we propose a method that consists of three stages namely, automatic extraction of coronary vessels; vessels straightening; lumen extraction and stenosis evaluation. In the first stage, the coronary vessels are segmented using a parametric approach based on circular vessel model at each point on the centerline. It is assumed that centerline information is available in advance. Vessel straightening in the second stage performs multi-planar reformat (MPR) to straighten the curved vessels. MPR view of a vessel helps to visualize and measure the plaques better. On the straightened vessel, lumen and vessel wall are segregated using a nearest neighbor classification. To detect the plaques with severe stenosis in the vessel lumen, we propose a "Diameter Luminal Stenosis" method for analyzing the smaller segments of the vessel. Proposed measurement technique identifies the segments that have plaques and reports the top three severely stenosed segments. Proposed algorithm is applied on 24 coronary vessels belonging to multiple cases acquired from Sensation 64 - slice CT and initial results are promising.