title: Automated regional wall motion abnormality detection by combining rest and stress cardiac MRI: correlation with contrast-enhanced MRI.
abstract: OBJECTIVE
  To correlate an automated regional wall motion abnormality (RWMA) detection method based on combined rest and dobutamine-stress cardiac MRI with the assessment of myocardial infarction from contrast-enhanced MRI (CE-MRI), and to demonstrate that adding stress data improves the detection of scar segments compared with rest data alone.
  
  
  METHODS
  An automated RWMA detection method was built based on a statistical model of normokinetic myocardium from 41 healthy volunteers. The method was adapted to detect changes in RWMA from rest to stress. Twelve patients with myocardial infarction were included in the experiment. The correlation with CE-MRI was performed on two measurements: infarct transmurality and scar detection.
  
  
  RESULTS
  Compared with infarct transmurality, the probability of normokinetic motion decreased progressively as infarct transmurality increased. These probability values were 0.59 for non-scar segments, for <25% transmurality was 0.4 (SE=0.04), for 25-50% was 0.33 (SE=0.03), for 50-75% was 0.21 (SE=0.03) and for ≥75% was 0.10 (SE=0.03). For scar tissue detection, adding stress data significantly improved the performance (P<0.001, confidence interval=99.9%). The sensitivity, specificity, and accuracy increased by 34%, 30%, and 32%, respectively. The area under the receiver operating characteristics curve was 0.63 when rest-only data was used, but it was improved to 0.87 when stress data was added.
  
  
  CONCLUSIONS
  The presented automated RWMA assessment was capable of detecting wall motion improvements from rest to stress. The method correlated well with infarct transmurality from CE-MRI. Detection of scar regions was more accurate when rest and stress data were combined compared with rest data alone.
authors.affiliation: Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
authors.forename: Avan
authors.initials: A
authors.lastname: Suinesiaputra
authors.forename: Alejandro F
authors.initials: AF
authors.lastname: Frangi
authors.forename: Theodorus A M
authors.initials: TA
authors.lastname: Kaandorp
authors.forename: Hildo J
authors.initials: HJ
authors.lastname: Lamb
authors.forename: Jeroen J
authors.initials: JJ
authors.lastname: Bax
authors.forename: Johan H C
authors.initials: JH
authors.lastname: Reiber
authors.forename: Boudewijn P F
authors.initials: BP
authors.lastname: Lelieveldt
mesh_terms: D001331:Automation; D003287:Contrast Media / Q000494:pharmacology*; D003324:Coronary Artery Disease / Q000175:diagnosis* / Q000473:pathology; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007700:Kinetics; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D015233:Models, Statistical; D009038:Motion; D009206:Myocardium / Q000473:pathology*; D012372:ROC Curve; D015203:Reproducibility of Results
chemical_list: D003287:Contrast Media