title: DTI template-based estimation of cardiac fiber orientations from 3D ultrasound.
abstract: OBJECTIVE
  Cardiac muscle fibers directly affect the mechanical, physiological, and pathological properties of the heart. Patient-specific quantification of cardiac fiber orientations is an important but difficult problem in cardiac imaging research. In this study, the authors proposed a cardiac fiber orientation estimation method based on three-dimensional (3D) ultrasound images and a cardiac fiber template that was obtained from magnetic resonance diffusion tensor imaging (DTI).
  
  
  METHODS
  A DTI template-based framework was developed to estimate cardiac fiber orientations from 3D ultrasound images using an animal model. It estimated the cardiac fiber orientations of the target heart by deforming the fiber orientations of the template heart, based on the deformation field of the registration between the ultrasound geometry of the target heart and the MRI geometry of the template heart. In the experiments, the animal hearts were imaged by high-frequency ultrasound, T1-weighted MRI, and high-resolution DTI.
  
  
  RESULTS
  The proposed method was evaluated by four different parameters: Dice similarity coefficient (DSC), target errors, acute angle error (AAE), and inclination angle error (IAE). Its ability of estimating cardiac fiber orientations was first validated by a public database. Then, the performance of the proposed method on 3D ultrasound data was evaluated by an acquired database. Their average values were 95.4% ± 2.0% for the DSC of geometric registrations, 21.0° ± 0.76° for AAE, and 19.4° ± 1.2° for IAE of fiber orientation estimations. Furthermore, the feasibility of this framework was also performed on 3D ultrasound images of a beating heart.
  
  
  CONCLUSIONS
  The proposed framework demonstrated the feasibility of using 3D ultrasound imaging to estimate cardiac fiber orientation of in vivo beating hearts and its further improvements could contribute to understanding the dynamic mechanism of the beating heart and has the potential to help diagnosis and therapy of heart disease.
authors.affiliation: Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia 30329.
authors.forename: Xulei
authors.initials: X
authors.lastname: Qin
authors.affiliation: Department of Radiology and Imaging Sciences, Emory University School of Medicine, Atlanta, Georgia 30329; Department of Biomedical Engineering, Emory University and Georgia Institute of Technology, Atlanta, Georgia 30329; Winship Cancer Institute of Emory University, Atlanta, Georgia 30329; and Department of Mathematics and Computer Science, Emory University, Atlanta, Georgia 30329.
authors.forename: Baowei
authors.initials: B
authors.lastname: Fei
mesh_terms: D000818:Animals; D038524:Diffusion Magnetic Resonance Imaging; D019560:Echocardiography, Three-Dimensional / Q000379:methods*; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D051381:Rats; D017207:Rats, Sprague-Dawley