title: Cine viability magnetic resonance imaging of the heart without increased scan time.
abstract: Cardiac magnetic resonance imaging (MRI) provides information about myocardial morphology, function, and viability from cine, tagged, and late gadolinium enhancement (LGE) images, respectively. While the cine and tagged images are acquired in a time-resolved fashion, the LGE images are acquired at a single timeframe. The purpose of this work is to develop a method for generating cine LGE images without additional scan time. The motion field is extracted from the tagged images, and is then used to guide the deformation of the infarcted region from the acquired LGE image at the acquired timeframe to any other timeframe. Major techniques for motion estimation, including harmonic phase (HARP) and optical flow analysis, are tested in this work for motion estimation. The proposed method is tested on numerical phantom and images from four human subjects. The generated cine LGE images showed both viability and wall motion information in the same set of images without additional scan time or image misregistration problems. The band-pass optical flow analysis resulted in the most accurate motion estimation compared to other methods, especially HARP, which fails to track points at the myocardial boundary. Infarct transmurality from the generated images showed good agreement with myocardial strain, and wall thickening showed good agreement with that measured from conventional cine images. In conclusion, the developed technique allows for generating cine LGE images that enable simultaneous display of wall motion and viability information. The generated images could be useful for estimating myocardial contractility reserve and for treatment prognosis.
authors.affiliation: Helwan University, Cairo, Egypt.
authors.forename: Azza S
authors.initials: AS
authors.lastname: Hassanein
authors.affiliation: Helwan University, Cairo, Egypt.
authors.forename: Ayman M
authors.initials: AM
authors.lastname: Khalifa
authors.affiliation: University of Michigan, Ann Arbor, USA. Electronic address: elsayei@umich.edu.
authors.forename: El-Sayed H
authors.initials: el-SH
authors.lastname: Ibrahim
mesh_terms: D000465:Algorithms; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D019028:Magnetic Resonance Imaging, Cine / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D018487:Ventricular Dysfunction, Left / Q000473:pathology*
keywords: Cine imaging; Coronary artery disease; Delayed enhancement; Tagging