title: Magnetic resonance myocardial perfusion imaging at 3.0 Tesla for the identification of myocardial ischaemia: comparison with coronary catheter angiography and fractional flow reserve measurements.
abstract: OBJECTIVE
  To assess image quality and diagnostic performance of 3.0 Tesla (3T) cardiac magnetic resonance (CMR) myocardial perfusion imaging with a dual radiofrequency source to detect functional relevant coronary artery disease (CAD), using coronary angiography and invasive pressure-derived fractional flow reserve (FFR) as reference standard.
  
  
  RESULTS
  We included 116 patients with suspected or known CAD, who underwent 3T adenosine myocardial perfusion CMR (resolution 2.97 × 2.97 mm) and coronary angiography plus FFR measurements in intermediate lesions. Image quality of myocardial perfusion CMR was graded on a 4-point scale (1 = poor to 4 = excellent). Diagnostic accuracy was assessed by ROC analyses using a 16-myocardial segment-based summed perfusion score (0 = normal to 3 = transmural perfusion defect) and by determining sensitivity, specificity, positive and negative predictive value on the coronary vessel territory and the patient level. Diagnostic image quality was achieved for all stress myocardial perfusion CMR studies with an average quality score of 2.5, 3.1, and 3.0 for LAD, LCX, and RCA territories. The ability of the myocardial perfusion CMR perfusion score to detect significant coronary artery stenosis yielded an area under the curve of 0.93 on ROC analysis. Values for sensitivity, specificity, positive and negative predictive value on a vessel territory level and the patient level were 89, 95, 87, 96% and 85, 87, 77, 92%, respectively.
  
  
  CONCLUSIONS
  In patients with suspected or known significant CAD, 3T myocardial perfusion CMR with standard perfusion protocols provides consistently high image quality and an excellent diagnostic performance.
authors.affiliation: Department of Cardiology and Intensive Care Medicine, Heart Centre Munich-Bogenhausen, Munich, Germany.
authors.forename: Ullrich
authors.initials: U
authors.lastname: Ebersberger
authors.forename: Marcus R
authors.initials: MR
authors.lastname: Makowski
authors.forename: U Joseph
authors.initials: UJ
authors.lastname: Schoepf
authors.forename: Ulrich
authors.initials: U
authors.lastname: Platz
authors.forename: Fabian
authors.initials: F
authors.lastname: Schmidtler
authors.forename: Johanna
authors.initials: J
authors.lastname: Rose
authors.forename: Anne
authors.initials: A
authors.lastname: Kessel
authors.forename: Patricia
authors.initials: P
authors.lastname: Roth
authors.forename: Diethmar
authors.initials: D
authors.lastname: Antoni
authors.forename: Bernhard
authors.initials: B
authors.lastname: Schnackenburg
authors.forename: Thomas
authors.initials: T
authors.lastname: Helmberger
authors.forename: Johannes
authors.initials: J
authors.lastname: Rieber
authors.forename: Ellen
authors.initials: E
authors.lastname: Hoffmann
authors.forename: Alexander W
authors.initials: AW
authors.lastname: Leber
mesh_terms: D000368:Aged; D006328:Cardiac Catheterization / Q000379:methods; D015331:Cohort Studies; D017023:Coronary Angiography / Q000379:methods*; D003324:Coronary Artery Disease / Q000175:diagnosis* / Q000000981:diagnostic imaging; D005260:Female; D005500:Follow-Up Studies; D053805:Fractional Flow Reserve, Myocardial; D006801:Humans; D019028:Magnetic Resonance Imaging, Cine / Q000379:methods*; D008297:Male; D008875:Middle Aged; D017202:Myocardial Ischemia / Q000175:diagnosis* / Q000000981:diagnostic imaging; D055414:Myocardial Perfusion Imaging / Q000379:methods*; D015588:Observer Variation; D012372:ROC Curve; D012189:Retrospective Studies; D018570:Risk Assessment; D012680:Sensitivity and Specificity; D012720:Severity of Illness Index
keywords: 3.0 Tesla; Coronary artery disease; Fractional flow reserve; Magnetic resonance imaging; Myocardial perfusion