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Proceedings Paper

Metrics of carotid plaque-surface morphology
Author(s): Peter J. Yim; J. Kevin Demarco
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Paper Abstract

Studies of the coronary and carotid arteries have found that plaques with irregular surfaces are more likely to produce cardiac infarction and stroke, respectively. The aim of this project was the development of methods for quantifying irregularity of plaque surface. Three metrics for quantifying surface irregularity were developed that are insensitive to variability of vessel diameter. These metrics include (1) Ratio of surface area to square-root of volume (RSASRV) (2) Mean of absolute value of minor principal curvature (MAVMPC) and (3) Radial variation within vessel cross sections (RVWVCS). For computing RVWVCS, a vessel axis was determined by Ordered Region Growing Skeletonization. RVWVCS is the within-group mean-square-error of the distance of the surface to the vessel axis where the vertices are grouped according to their match to the closest point on the vessel axis. These metrics are applied to triangulated surface of the carotid artery in the vicinity of the stenosis. The surface was reconstructed from contrast-enhanced magnetic resonance angiography by the Isosurface Deformable Model. The stenotic region was selected by manual placement of a 2-cm-long bounding box around the region, excluding the external carotid artery if necessary. The metrics were applied to three carotid arteries with a moderate degree of stenosis. These three cases exhibited mild, moderate and severe plaque-surface irregularity, respectively, as determined by visual impression. The ranking of the irregularity of the carotid arteries was in 100% agreement with visual impression for all three metrics. All three metrics should be given further consideration for quantification of plaque-surface irregularity.

Paper Details

Date Published: 14 April 2005
PDF: 4 pages
Proc. SPIE 5746, Medical Imaging 2005: Physiology, Function, and Structure from Medical Images, (14 April 2005); doi: 10.1117/12.595828
Show Author Affiliations
Peter J. Yim, Univ. of Medicine and Dentristy of New Jersey (United States)
J. Kevin Demarco, Michigan State Univ. (United States)


Published in SPIE Proceedings Vol. 5746:
Medical Imaging 2005: Physiology, Function, and Structure from Medical Images
Amir A. Amini; Armando Manduca, Editor(s)

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