title: Cardiovascular magnetic resonance parameters of atherosclerotic plaque burden improve discrimination of prior major adverse cardiovascular events.
abstract: OBJECTIVE
  Patients with prior major cardiovascular or cerebrovascular events (MACE) are more likely to have future recurrent events independent of traditional cardiovascular disease risk factors. The purpose of this study was to determine if patients with traditional risk factors and prior MACE had increased cardiovascular magnetic resonance (CMR) plaque burden measures compared to patients with risk factors but no prior events.
  
  
  RESULTS
  Black blood carotid and thoracic aorta images were obtained from 195 patients using a rapid extended coverage turbo spin echo sequence. CMR measures of plaque burden were obtained by tracing lumen and outer vessel wall contours. Patients with prior MACE had significantly higher MR plaque burden (wall thickness, wall area and normalized wall index) in carotids and thoracic aorta compared to those without prior MACE (Wall thickness carotids: 1.03 +/- 0.03 vs. 0.93+/- 0.03, p = 0.001; SD wall thickness carotids: 0.137 +/- 0.0008 vs. 0.102 +/- 0.0004, p < 0.001; wall thickness aorta: 1.63 +/- 0.10 vs. 1.50 +/- 0.04, p = 0.009; SD wall thickness aorta: 0.186 +/- 0.035 vs. 0.139 +/- 0.012, p = 0.009 respectively). Plaque burden (wall thickness) and plaque eccentricity (standard deviation of wall thickness) of carotid arteries were associated with prior MACE after adjustment for age, sex, and traditional risk factors. Area under ROC curve (AUC) for discriminating prior MACE improved by adding plaque eccentricity to models incorporating age, sex, and traditional CVD risk factors as model inputs (AUC = 0.79, p = 0.05).
  
  
  CONCLUSIONS
  A greater plaque burden and plaque eccentricity is prevalent among patients with prior MACE.
authors.affiliation: Imaging Science Laboratories; Translational and Molecular Imaging Institute, Department of Radiology, Mount Sinai School of Medicine, New York, NY, USA. venkatesh.mani@mssm.edu
authors.forename: Venkatesh
authors.initials: V
authors.lastname: Mani
authors.forename: Paul
authors.initials: P
authors.lastname: Muntner
authors.forename: Samuel S
authors.initials: SS
authors.lastname: Gidding
authors.forename: Silvia H
authors.initials: SH
authors.lastname: Aguiar
authors.forename: Hamza
authors.initials: H
authors.lastname: El Aidi
authors.forename: Karen B
authors.initials: KB
authors.lastname: Weinshelbaum
authors.forename: Hiroaki
authors.initials: H
authors.lastname: Taniguchi
authors.forename: Rob
authors.initials: R
authors.lastname: van der Geest
authors.forename: Johan H C
authors.initials: JH
authors.lastname: Reiber
authors.forename: Sameer
authors.initials: S
authors.lastname: Bansilal
authors.forename: Michael
authors.initials: M
authors.lastname: Farkouh
authors.forename: Valentin
authors.initials: V
authors.lastname: Fuster
authors.forename: John E
authors.initials: JE
authors.lastname: Postley
authors.forename: Mark
authors.initials: M
authors.lastname: Woodward
authors.forename: Zahi A
authors.initials: ZA
authors.lastname: Fayad
mesh_terms: D000368:Aged; D001013:Aorta, Thoracic / Q000473:pathology; D001018:Aortic Diseases / Q000473:pathology; D019540:Area Under Curve; D002339:Carotid Arteries / Q000473:pathology; D002340:Carotid Artery Diseases / Q000473:pathology; D016009:Chi-Square Distribution; D015331:Cohort Studies; D003324:Coronary Artery Disease / Q000473:pathology*; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D008297:Male; D008875:Middle Aged; D012307:Risk Factors