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Abstract #0650

A Novel Method for Cine-CMR Automated Assessment of Left Ventricular Diastolic Dysfunction

Keigo Kawaji1,2, Noel Christopher Codella2, Christopher W. Chu3, Richard B. Devereux3, Martin R. Prince2, Yi Wang1,2, Jonathan W. Weinsaft2,3

1Biomedical Engineering, Cornell University, Ithaca, NY, USA; 2Radiology, Weill Cornell Medical College, New York, USA; 3Medicine/Division of Cardiology, Weill Cornell Medical College, New York, USA

Cardiac magnetic resonance (CMR) is a well-established standard for assessment of LV systolic function, but assessment of diastolic function is limited and currently requires additional imaging, which can be time-consuming. We present a novel automated approach based upon an LV segmentation algorithm (LV-METRIC) that assesses diastolic function from SSFP cine-CMR by generating ventricular filling profiles. Our results demonstrate that automated segmentation using LV-METRIC can generate multiple diastolic parameters that are rapidly derivable, require no additional imaging beyond standard cine-CMR, and agree with echocardiographic measures of diastolic function.