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.