An algorithm for quantifying advanced carotid artery atherosclerosis in humans using MRI and active contours

Gareth J. Adams, G. Wesley Vick, Cassius B. Bordelon, William Insull, Joel D. Morrisett

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

Abstract

A new algorithm for measuring carotid artery volumes and estimating atherosclerotic plaque volumes from MRI images has been developed and validated using pressure-perfusion-fixed cadaveric carotid arteries. Our method uses an active contour algorithm with the generalized gradient vector field force as the external force to localize the boundaries of the artery on each MRI cross-section. Plaque volume is estimated by an automated algorithm based on estimating the normal wall thickness for each branch of the carotid. Triplicate volume measurements were performed by a single observer on thirty-eight pairs of cadaveric carotid arteries. The coefficient of variance (COV) was used to quantify measurement reproducibility. Aggregate volumes were computed for nine contiguous slices bounding the carotid bifurcation. The median (mean ± SD) COV for the 76 aggregate arterial volumes was 0.93% (1.47% ± 1.52%) for the lumen volume, 0.95% (1.06% ± 0.67%) for the total artery volume, and 4.69% (5.39% ± 3.97%) for the plaque volume. These results indicate that our algorithm provides repeatable measures of arterial volumes and a repeatable estimate of plaque volume of cadaveric carotid specimens through analysis of MRI images. The algorithm also significantly decreases the amount of time necessary to generate these measurements.

Original languageEnglish (US)
Pages (from-to)1448-1457
Number of pages10
JournalProceedings of SPIE - The International Society for Optical Engineering
Volume4684 III
DOIs
StatePublished - 2002

Keywords

  • Active contour
  • Atherosclerosis
  • Carotid artery
  • Magnetic resonance imaging
  • Plaque quantitation

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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