A computational method for quantifying left ventricle (LV) remodeling using 3D mesh models reconstructed from magnetic resonance imaging is proposed. The underlying geometry of the LV mesh is obtained by using a quadric fitting method, and its quantification is performed by using a curvedness shape descriptor. To achieve robustness, we have performed detailed studies of the effects of n-ring parameter selection on the accuracy of this method with in vitro and in vivo LV models. We have found that curvedness calculations based on a 5-ring selection can accurately depict anomalies in LV shape despite the presence of noise due to manual image segmentation. Our studies show that patients after myocardial infarction exhibit significant LV shape alteration in terms of curvedness, in particular at the apex. The diastole-to-systole change in regional curvedness was significantly lower suggesting regional differences in hypokinesis due to infarcted myocardium. This approach may add new insights into ventricular deformation and enable better discrimination between normal and pathologic conditions.
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