Methodology for jointly assessing myocardial infarct extent and regional contraction in 3-D CMRI.

Automated extraction of quantitative parameters from cardiac magnetic resonance images is crucial for the management of patients with myocardial infarct. This paper proposes a postprocessing procedure to jointly analyze Cine and delayed-enhanced (DE) acquisitions, in order to provide an automatic quantification of myocardial contraction and enhancement parameters and a study of their relationship. For that purpose, the following processes are performed: 1) DE/Cine temporal synchronization and 3-D scan alignment, 2) 3-D DE/Cine rigid registration in a region about the heart, 3) myocardium segmentation on Cine-MRI and superimposition of the epicardial and endocardial contours on the DE images, 4) quantification of the myocardial infarct extent (MIE), 5) study of the regional contractile function using a new index, the amplitude to time ratio (ATR). The whole procedure was applied to ten patients with clinically proven myocardial infarction. The comparison between the MIE and the visually assessed regional function scores demonstrated that the MIE is highly related to the severity of the wall motion abnormality. In addition, it was shown that the newly developed regional myocardial contraction parameter (ATR) decreases significantly in delayed enhanced regions. This largely automated approach enables the combined study of regional MIE and left ventricular function.

An automated myocardial segmentation in cardiac MRI.

In this paper we present an automatic approach to segment Cardiac Magnetic Resonance (CMR) images. A preprocessing step that consists in filtering the image using connected operators (area opening and closing filters) is applied in order to homogenize the cavity and solve the problems due to the papillary muscles. Thereby the GVF snake algorithm is applied with one point clicked in the cavity as initialization and an optimized tuning of parameters for the endocardial contour extraction. The epicardial border is then obtained using the endocardium as initialization. The performance of the proposed method was assessed by experimentation on thirty-nine CMR images. A high agreement between manual and automatic contours was obtained with correlation scores of 0.96 for the endocardium and 0.90 for the epicardium. Overlapping percentage, mean and maximum distances between the two contours show a good performance of the method.