Automatic synthesis of cine viability MRI images for evaluation of coronary heart disease

• Published in: 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society Vol. 2014; pp. 5117 - 5120
• Main Authors: Hassanein, Azza S., Khalifa, Ayman M., Al-Atabany, Walid, El-Wakad, Mohamed T., Shapiro, Brian, Ibrahim, El-Sayed H.
• Format: Conference Proceeding Journal Article
• Language: English
• Published: United States IEEE 01-01-2014
• Subjects: Algorithms; Computer Simulation; Computer vision; Coronary Artery Disease - diagnosis; Coronary Artery Disease - physiopathology; Diastole; Heart; Humans; Image Enhancement - methods; Magnetic resonance imaging; Magnetic Resonance Imaging, Cine - methods; Myocardium; Myocardium - pathology; Phantoms, Imaging; Strain; Systole; Tracking
• ISSN: 1094-687X; 1557-170X; 1558-4615
• DOI: 10.1109/EMBC.2014.6944776

Coronary heart disease (CHD) is the leading cause of death worldwide. Cardiac magnetic resonance imaging (MRI) is a valuable imaging modality, as it can noninvasively provide information about myocardial function, viability, and morphology. Viability delayed-enhancement (DE) images are acquired at a single timeframe while myocardial functional (tagged) images are acquired as a cine loop of timeframes throughout the cardiac cycle. In this work, we propose a method for estimating DE images at all timeframes in the cardiac cycle without additional scan time to show both viability and functional information in the same image. The method is based on generating a dense motion field of the heart from the acquired tagged images, and then applying the extracted field to the acquired DE image. The developed technique is accurate in generating cine DE images and providing simultaneous information about myocardial viability and wall motion for comprehensive patient evaluation and optimal treatment selection.