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Abstract #0733

Automated Cardiac Strain Estimation from 2D Cine DENSE MRI

Andrew D. Gilliam1, Xiaodong Zhong2, Kenneth C. Bilchick3, Frederick H. Epstein4

1Andrew D. Gilliam Consulting, Providence, RI, USA; 2MR R&D Collaborations, Siemens Healthcare, Atlanta, GA, USA; 3Cardiology, University of Virginia, Charlottesville, VA, USA; 4Radiology & Biomedical Engineering, University of Virginia, Charlottesville, VA, USA

Displacement encoding with stimulated echoes (DENSE) directly encodes tissue displacement into MR images, providing easy access to vital physiological information such as cardiac strain. Unfortunately, the quantification of displacement and strain from raw cine DENSE imagery currently relies on the manual delineation of cardiac anatomy. In this study, we present the first fully automated solution to estimate cardiac strain from 2D cine DENSE images. Results indicate good agreement between the innovative automated analysis algorithm and previously described methods.