Coronary centerline extraction from CT coronary angiography images using a minimum cost path approach

The application and large-scale evaluation of minimum cost path approaches for coronary centerline extraction from computed tomography coronary angiography (CTCA) data and the development and evaluation of a novel method to reduce the user-interaction time.

A semiautomatic method based on a minimum cost path approach is evaluated for two different cost functions. The first cost function is based on a frequently used vesselness measure and intensity information, and the second is a recently proposed cost function based on region statistics. User interaction is minimized to one or two mouse clicks distally in the coronary artery. The starting point for the minimum cost path search is automatically determined using a newly developed method that finds a point in the center of the aorta in one of the axial slices. This step ensures that all computationally expensive parts of the algorithm can be precomputed.

The performance of the aorta localization procedure was demonstrated by a success rate of 100% in 75 images. The success rate and accuracy of centerline extraction was quantitatively evaluated on 48 coronary arteries in 12 images by comparing extracted centerlines with a manually annotated reference standard. The method was able to extract 88% and 47% of the vessel center-lines correctly using the vesselness/intensity and region statistics cost function, respectively. For only the proximal part of the vessels these values were 97% and 86%, respectively. Accuracy of centerline extraction, defined as the average distance from correctly automatically extracted parts of the centerline to the reference standard, was 0.64 mm for the vesselness/intensity and 0.51 mm for the region statistics cost function. The interobserver variability was 99% for the success rate measure and 0.42 mm for the accuracy measure. Qualitative evaluation using the best performing cost function resulted in successful centerline extraction for 233 out of the 252 coronaries (92%) in 63 additional CTCA images.

The presented results, in combination with minimal user interaction and low computation time, show that minimum cost path approaches can effectively be applied as a preprocessing step for subsequent analysis in clinical practice and biomedical research.