title: Evaluation of cardiac magnetic resonance imaging parameters to detect anatomically and hemodynamically significant coronary artery disease.
abstract: BACKGROUND
  Cardiac magnetic resonance (cMR) perfusion imaging is a promising technique to assess coronary artery disease (CAD). Our objective was to evaluate accuracy of various cMR imaging parameters to detect significant CAD as compared with angiography or fractional flow reserve (FFR).
  
  
  METHODS
  We prospectively enrolled 37 patients who underwent coronary angiography, FFR, and cMR perfusion imaging. Semiquantitative assessments, namely maximum up-slope and peak-intensity indexes, were derived from time-intensity ratios between rest and stress. Myocardial perfusion reserve (MPR), calculated using Fermi deconvolution technique, was the quantitative cMR imaging parameter. Qualitative assessments were visually performed by independent analysts. Accuracy of quantitative, semiquantitative, and qualitative cMR imaging data was compared with quantitative coronary angiography in 108 segments and FFR in 44 segments.
  
  
  RESULTS
  Sensitivity and specificity for hemodynamically significant CAD (FFR < or = 0.75) were 92.9% and 56.7%, respectively, for MPR (cutoff, 2.06). Area under the curve to detect FFR < or = 0.75 was 0.78 for MPR (P < .01), 0.63 for up-slope (P = NS), and 0.66 (P = NS) for peak intensity. Sensitivity and specificity for anatomically significant CAD (> 50% diameter stenosis [DS]) were 87.2% and 49.2%, respectively, for MPR (cutoff, 2.06). Area under the curve was 0.75 for MPR, 0.69 for up-slope, and 0.65 for peak intensity to detect > 50% DS (all P < .05). Visual assessment yielded sensitivity of 78.6% and specificity of 65.5% to predict FFR < or = 0.75 and sensitivity of 74.5% and specificity of 67.2% to predict > 50% DS.
  
  
  CONCLUSIONS
  Myocardial perfusion reserve appears to be the most accurate index to detect anatomical and hemodynamically significant CAD. Standardization of such quantitative methods, with minimal operator dependency, would be useful for clinical and research applications.
authors.affiliation: Division of Cardiology and Cardiovascular Imaging Core Laboratories, University of Florida, Jacksonville, FL 32209, USA.
authors.forename: Hideki
authors.initials: H
authors.lastname: Futamatsu
authors.forename: Norbert
authors.initials: N
authors.lastname: Wilke
authors.forename: Chris
authors.initials: C
authors.lastname: Klassen
authors.forename: Steven
authors.initials: S
authors.lastname: Shoemaker
authors.forename: Dominick J
authors.initials: DJ
authors.lastname: Angiolillo
authors.forename: Alan
authors.initials: A
authors.lastname: Siuciak
authors.forename: Kino
authors.initials: K
authors.lastname: Morikawa-Futamatsu
authors.forename: Nobuaki
authors.initials: N
authors.lastname: Suzuki
authors.forename: Franz
authors.initials: F
authors.lastname: von Ziegler
authors.forename: Theodore A
authors.initials: TA
authors.lastname: Bass
authors.forename: Marco A
authors.initials: MA
authors.lastname: Costa
mesh_terms: D000368:Aged; D001783:Blood Flow Velocity; D017023:Coronary Angiography; D003324:Coronary Artery Disease / Q000175:diagnosis* / Q000503:physiopathology; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D011446:Prospective Studies; D012680:Sensitivity and Specificity