An integrated automated analysis method for quantifying vessel stenosis and plaque burden from carotid MRI images: Combined postprocessing of MRA and vessel wall MR

Isabel M. Adame, Patrick J.H. De Koning, Boudewijn P.F. Lelieveldt, Bruce A. Wasserman, Johan H.C. Reiber, Rob J. Van Der Geest

Research output: Contribution to journalArticlepeer-review

26 Scopus citations

Abstract

BACKGROUND AND PURPOSE - We report the evaluation of a semiautomated method for in vivo assessment of the severity of carotid atherosclerosis with minimal user interaction that combines 3-dimensional contrast-enhanced magnetic resonance angiography (CE-MRA) and vessel wall magnetic resonance imaging (MRI). METHODS - Lumen and outer-wall contours were automatically detected, and stenosis and plaque burden were estimated. The method was tested on 22 subjects (352 postcontrast, T1-weighted cross sections and 3-dimensional CE-MRA). RESULTS - We observed good correlation with expert contours: lumen and outer-wall area (r=0.96) and the degree of stenosis (r=0.97). CONCLUSIONS - The fusion of MRA and MRI reduces user interaction and improves contour detection, providing reproducible parameters to assess the severity of atherosclerosis.

Original languageEnglish (US)
Pages (from-to)2162-2164
Number of pages3
JournalStroke
Volume37
Issue number8
DOIs
StatePublished - Aug 2006
Externally publishedYes

Keywords

  • Atherosclerosis
  • Carotid artery
  • Magnetic resonance angiography
  • Magnetic resonance imaging

ASJC Scopus subject areas

  • Clinical Neurology
  • Cardiology and Cardiovascular Medicine
  • Advanced and Specialized Nursing

Fingerprint

Dive into the research topics of 'An integrated automated analysis method for quantifying vessel stenosis and plaque burden from carotid MRI images: Combined postprocessing of MRA and vessel wall MR'. Together they form a unique fingerprint.

Cite this