title: Intramyocardial strain estimation from cardiac cine MRI.
abstract: OBJECTIVE
  Functional strain is one of the important clinical indicators for the quantification of heart performance and the early detection of cardiovascular diseases, and functional strain parameters are used to aid therapeutic decisions and follow-up evaluations after cardiac surgery. A comprehensive framework for deriving functional strain parameters at the endocardium, epicardium, and mid-wall of the left ventricle (LV) from conventional cine MRI data was developed and tested.
  
  
  METHODS
  Cine data were collected using short TR-/TE-balanced steady-state free precession acquisitions on a 1.5T Siemens Espree scanner. The LV wall borders are segmented using a level set-based deformable model guided by a stochastic force derived from a second-order Markov-Gibbs random field model that accounts for the object shape and appearance features. Then, the mid-wall of the segmented LV is determined based on estimating the centerline between the endocardium and epicardium of the LV. Finally, a geometrical Laplace-based method is proposed to track corresponding points on successive myocardial contours throughout the cardiac cycle in order to characterize the strain evolutions. The method was tested using simulated phantom images with predefined point locations of the LV wall throughout the cardiac cycle. The method was tested on 30 in vivo datasets to evaluate the feasibility of the proposed framework to index functional strain parameters.
  
  
  RESULTS
  The cine MRI-based model agreed with the ground truth for functional metrics to within 0.30 % for indexing the peak systolic strain change and 0.29 % (per unit time) for indexing systolic and diastolic strain rates. The method was feasible for in vivo extraction of functional strain parameters.
  
  
  CONCLUSIONS
  Strain indexes of the endocardium, mid-wall, and epicardium can be derived from routine cine images using automated techniques, thereby improving the utility of cine MRI data for characterization of myocardial function. Unlike traditional texture-based tracking, the proposed geometrical method showed the ability to track the LV wall points throughout the cardiac cycle, thus permitting more accurate strain estimation.
authors.affiliation: BioImaging Laboratory, Bioengineering Department, University of Louisville, Lutz Hall, Room 423, Louisville, KY, 40292, USA.
authors.forename: Ahmed
authors.initials: A
authors.lastname: Elnakib
authors.forename: Garth M
authors.initials: GM
authors.lastname: Beache
authors.forename: Georgy
authors.initials: G
authors.lastname: Gimel'farb
authors.forename: Ayman
authors.initials: A
authors.lastname: El-Baz
mesh_terms: D002318:Cardiovascular Diseases / Q000473:pathology*; D004699:Endocardium / Q000473:pathology*; D006352:Heart Ventricles / Q000473:pathology*; D006801:Humans; D019028:Magnetic Resonance Imaging, Cine / Q000379:methods*; D009206:Myocardium / Q000473:pathology*