title: Cardiac magnetic resonance imaging derived quantification of myocardial ischemia and scar improves risk stratification and patient management in stable coronary artery disease.
abstract: BACKGROUND
  Quantification of myocardial ischemia and necrosis might ameliorate prognostic models and lead to improved patient management. However, no standardized consensus on how to assess and quantify these parameters has been established. The aim of this study was to quantify these variables by cardiac magnetic resonance imaging (CMR) and to establish possible incremental implications in cardiovascular risk prediction.
  
  
  METHODS
  This study is a retrospective analysis of patients with known or suspected coronary artery disease (CAD) referred for adenosine perfusion CMR was performed. Myocardial ischemia and necrosis were assessed and quantified using an algorithm based on standard first-pass perfusion imaging and late gadolinium enhancement (LGE). The combined primary endpoint was defined as cardiac death, non-fatal myocardial infarction, and stroke.
  
  
  RESULTS
  845 consecutive patients were enrolled into the study. During the median follow-up of 3.64 [1.03; 10.46] years, 61 primary endpoints occurred. Patients with primary endpoint showed larger extent of ischemia (10.7 ± 12.25% vs. 3.73 ± 8.29%, p < 0.0001) and LGE (21.09 ± 15.11% vs. 17.73 ± 10.72%, p < 0.0001). A risk prediction model containing the extent of ischemia and LGE proved to be superior in comparison to all other models (χ² increase: from 39.678 to 56.676, integrated discrimination index: 0.3851, p = 0.0033, net reclassification index: 0.11516, p = 0.0071). The ben-eficial effect of revascularization tended to be higher in patients with greater extents of ischemia, though statistical significance was not reached.
  
  
  CONCLUSIONS
  Quantification of myocardial ischemia and LGE was shown to significantly improve existing risk prediction models and might thus lead to an improvement in patient management.
authors.forename: Dominik
authors.initials: D
authors.lastname: Buckert
authors.forename: Maciej
authors.initials: M
authors.lastname: Cieslik
authors.forename: Raid
authors.initials: R
authors.lastname: Tibi
authors.forename: Michael
authors.initials: M
authors.lastname: Radermacher
authors.forename: Wolfgang
authors.initials: W
authors.lastname: Rottbauer
authors.affiliation: Heart Clinic Ulm, Ulm, Germany, Germany. peter.bernhardt@herzklinik-ulm.de.
authors.forename: Peter
authors.initials: P
authors.lastname: Bernhardt
mesh_terms: D000328:Adult; D000368:Aged; D003324:Coronary Artery Disease / Q000150:complications / Q000175:diagnosis / Q000628:therapy*; D005260:Female; D005500:Follow-Up Studies; D005858:Germany; D006801:Humans; D015994:Incidence; D019028:Magnetic Resonance Imaging, Cine / Q000379:methods*; D008297:Male; D008875:Middle Aged; D009203:Myocardial Infarction / Q000175:diagnosis* / Q000453:epidemiology / Q000209:etiology; D017202:Myocardial Ischemia / Q000175:diagnosis* / Q000209:etiology / Q000503:physiopathology; D009206:Myocardium / Q000473:pathology*; D011379:Prognosis; D015203:Reproducibility of Results; D012189:Retrospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D012720:Severity of Illness Index; D013318:Stroke Volume; D013997:Time Factors; D016277:Ventricular Function, Left / Q000502:physiology*
keywords: cardiac magnetic resonance imaging; coronary artery disease; prognosis and outcomes; quantification of ischemia and necrosis; risk stratification