Geometric Quantitative Coronary Arteriography

Abstract

The application of dual energy (DE) subtraction techniques to quantitative coronary arteriography (QCA) has the advantage of removing the tissue signal surrounding the vessel profile. We have compared the performance of two geometric QCA algorithms on DE-subtracted and -unsubtracted images to determine, for each, if DE subtraction is advantageous. The two algorithms under study were an edge detection algorithm and a Fourier analysis-based algorithm. For each algorithm, linear regression analysis was performed of measured cross-sectional area (CSA) versus actual CSA of coronary vessel phantoms. The edge detection algorithm was found to have improved precision (P less than .05) when applied to the DE-subtracted images. The Fourier analysis algorithm, however, was not effected by the DE subtraction. Among the unsubtracted image results, the Fourier measurements were more accurate (P less than .05) than the edge detection measurements. We conclude that the benefits to edge detection QCA of DE tissue subtraction outweigh the disadvantages of increased image noise and possible misregistration artifacts. However, the Fourier algorithm is relatively insensitive to tissue signal variations.