Measuring changes in cardiac motion patterns can assist in diagnosing the onset of arrhythmia and ischaemia and in the follow-up of treatment. This work presents a methodology for measuring such motion changes from MR images. Non-rigid registration is used to track cardiac motion in a sequence of 3D tagged MR images. We use a cylindrical coordinate system to subdivide the myocardium
into smaller anatomically meaningful regions and to express motion derived measurements such as displacement and strain for each myocardial region during the cardiac cycle. In the first experiment we have evaluated the proposed methods using synthetic image sequences where the ground truth was available. These images were generated using a cardiac motion simulator for tagged MRI. Normal and abnormal motion fields were produced by modifying parameters in
a small region of the myocardium. In the second experiment we have acquired two separate tagged MR image sequences from five healthy volunteers. Both acquisitions have been carried out without moving the volunteer inside the scanner, thus avoiding potential misregistration errors due to subject motion between scans. In
addition, one of volunteers was subjected to stress during one of the
scans. In the final experiment we acquired tagged MR images from a patient with super-ventricular tachyarrhythmia, before and after radio frequency ablation. The image acquisition and catheter intervention were performed with a combined X-ray and MRI system. Detection results were correct on synthetic data and no region was incorrectly classified as having significant changes in the repetition studies. Significant changes in motion pattern were measured in the stress and ablation studies. Furthermore, results seem to corroborate that the ablation regularised cardiac contraction.
Tagged magnetic resonance imaging (MRI) is unique in its ability to non-invasively image the motion and deformation of the heart in-vivo, but one of the fundamental reasons limiting its use in the clinical environment is the absence of automated tools to derive clinically useful information from tagged MR images. In this paper we present a novel and fully automated technique based on nonrigid image registration using multi-level free-form deformations (MFFDs) for the analysis of myocardial motion using tagged MRI. The novel aspect of our technique is its integrated nature for tag localization and deformation field reconstruction. To extract the motion field within the myocardium during systole we register a sequence of images taken during systole to a set of reference images taken at end-diastole, maximizing the mutual information between images. We use both short-axis and long-axis images of the heart to estimate the full four-dimensional motion field within the myocardium. We have validated our method using a cardiac motion simulator and we also present quantitative comparisons of cardiac motion from nine volunteers.