title: Model-based registration for dynamic cardiac perfusion MRI.
abstract: OBJECTIVE
  To assess the accuracy of a model-based approach for registration of myocardial dynamic contrast-enhanced (DCE)-MRI corrupted by respiratory motion.
  
  
  METHODS
  Ten patients were scanned for myocardial perfusion on 3T or 1.5T scanners, and short- and long-axis slices were acquired. Interframe registration was done using an iterative model-based method in conjunction with a mean square difference metric. The method was tested by comparing the absolute motion before and after registration, as determined from manually registered images. Regional flow indices of myocardium calculated from the manually registered data were compared with those obtained with the model-based registration technique.
  
  
  RESULTS
  The mean absolute motion of the heart for the short-axis data sets over all the time frames decreased from 5.3+/-5.2 mm (3.3+/-3.1 pixels) to 0.8+/-1.3 mm (0.5+/-0.7 pixels) in the vertical direction, and from 3.0+/-3.7 mm (1.7+/-2.1 pixels) to 0.9+/-1.2 mm (0.5+/-0.7 pixels) in the horizontal direction. A mean absolute improvement of 77% over all the data sets was observed in the estimation of the regional perfusion flow indices of the tissue as compared to those obtained from manual registration. Similar results were obtained with two-chamber-view long-axis data sets.
  
  
  CONCLUSIONS
  The model-based registration method for DCE cardiac data is comparable to manual registration and offers a unique registration method that reduces errors in the quantification of myocardial perfusion parameters as compared to those obtained from manual registration.
authors.affiliation: Electrical and Computer Engineering Department, University of Utah, Salt Lake City, Utah 84108, USA.
authors.forename: Ganesh
authors.initials: G
authors.lastname: Adluru
authors.forename: Edward V R
authors.initials: EV
authors.lastname: DiBella
authors.forename: Matthias C
authors.initials: MC
authors.lastname: Schabel
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D003324:Coronary Artery Disease / Q000150:complications / Q000175:diagnosis*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008955:Models, Cardiovascular; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D018487:Ventricular Dysfunction, Left / Q000175:diagnosis* / Q000209:etiology