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Current Cardiology Reviews


ISSN (Print): 1573-403X
ISSN (Online): 1875-6557

Assessment of Cardiac Performance with Magnetic Resonance Imaging

Author(s): Alistair A. Young

Volume 2, Issue 4, 2006

Page: [271 - 282] Pages: 12

DOI: 10.2174/157340306778772904

Price: $65


A quantitative assessment of regional cardiac performance is required for the diagnosis of disease, evaluation of severity and the quantification of treatment effect. MRI allows the noninvasive quantification of motion and deformation in the heart, including the precise assessment of all components of deformation in all regions of the heart throughout the cardiac cycle. In recent years, these imaging protocols have become standardized in both the research and clinical settings. However, adoption in the routine clinical environment has been hindered by the complex and time-consuming nature of the image post-processing. Model-based image analysis procedures provide a powerful mechanism for the fast, accurate assessment of cardiac MRI data and lend themselves to biophysical analysis and standardized functional mapping procedures. This paper reviews the current state of the art in MRI assessment of cardiac performance with an emphasis on mathematical modeling analysis procedures. Firstly, fast and accurate evaluation of mass and volume is discussed using interactive 4D modeling techniques. Analysis of tissue function, strain and strain rate is then reviewed. Mathematical models of regional tissue function and wall motion allow registration between cases and across groups, enabling quantification of multidimensional patterns of wall motion between disease and treatment groups. Finally, information on myocardial tissue kinematics can be incorporated into biophysical models of cardiac mechanics and used to gain an understanding of how physiological tissue parameters such as contractility, ventricular compliance and electrical activation combine to effect whole heart function.

Keywords: Cardiac performance, magnetic resonance imaging, strain, mathematical modeling

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