title: Comparison of the Diagnostic Performance of Four Quantitative Myocardial Perfusion Estimation Methods Used in Cardiac MR Imaging: CE-MARC Substudy.
abstract: OBJECTIVE
  To compare the diagnostic performance of four tracer kinetic analysis methods to quantify myocardial perfusion from magnetic resonance (MR) imaging cardiac perfusion data sets in terms of their ability to lead to the diagnosis of myocardial ischemia.
  
  
  METHODS
  The study was approved by the regional ethics committee, and all patients gave written consent. A representative sample of 50 patients with suspected ischemic heart disease was retrospectively selected from the Clinical Evaluation of Magnetic Resonance Imaging in Coronary Heart Disease trial data set. Quantitative myocardial blood flow (MBF) was estimated from rest and adenosine stress MR imaging perfusion data sets by using four established methods. A matching diagnosis of both an inducible defect as assessed with single photon emission computed tomography and a luminal stenosis of 70% or more as assessed with quantitative x-ray angiography was used as the reference standard for the presence of myocardial ischemia. Diagnostic performance was evaluated with receiver operating characteristic (ROC) curve analysis for each method, with stress MBF and myocardial perfusion reserve (MPR) serving as continuous measures.
  
  
  RESULTS
  Area under the ROC curve with stress MBF and MPR as the outcome measures, respectively, was 0.86 and 0.92 for the Fermi model, 0.85 and 0.87 for the uptake model, 0.85 and 0.80 for the one-compartment model, and 0.87 and 0.87 for model-independent deconvolution. There was no significant difference between any of the models or between MBF and MPR, except that the Fermi model outperformed the one-compartment model if MPR was used as the outcome measure (P = .02).
  
  
  CONCLUSIONS
  Diagnostic performance of quantitative myocardial perfusion estimates is not affected by the tracer kinetic analysis method used.
authors.affiliation: From the Division of Medical Physics (J.D.B., S.P.S.) and Division of Cardiovascular and Diabetes Research (S.P. J.P.G.), Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Worsley Building, Leeds LS2 9JT, England; Department of Medical Physics and Engineering, Leeds Teaching Hospitals NHS Trust, Leeds, England (J.D.B.); School of Computing, University of Leeds, Leeds, England (D.R.M.); and Institute of Cardiovascular and Medical Sciences, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, Scotland (A.R.).
authors.forename: John D
authors.initials: JD
authors.lastname: Biglands
authors.forename: Derek R
authors.initials: DR
authors.lastname: Magee
authors.forename: Steven P
authors.initials: SP
authors.lastname: Sourbron
authors.forename: Sven
authors.initials: S
authors.lastname: Plein
authors.forename: John P
authors.initials: JP
authors.lastname: Greenwood
authors.forename: Aleksandra
authors.initials: A
authors.lastname: Radjenovic
mesh_terms: D000328:Adult; D000368:Aged; D057791:Cardiac Imaging Techniques; D003327:Coronary Disease / Q000175:diagnosis*; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D055414:Myocardial Perfusion Imaging / Q000379:methods*; D012189:Retrospective Studies