Multidimensional MRI of Cardiac Motion

Methods for measuring deformation and motion of the human heart in-vivo are crucial in the assessment of cardiac function. Applications ranging from basic physiological research, through early detection of disease to follow-up studies, all benefit from improved methods of measuring the dynamics of the heart. This thesis presents new methods for acquisition, reconstruction and visualization of cardiac motion and deformation, based on magnetic resonance imaging. Local heart wall deformation can be quantified in a strain rate tensor field. This tensor field describes the local deformation excluding rigid body translation and rotation. The drawback of studying this tensor-valued quantity, as opposed to a velocity vector field, is the high dimensionality of the tensor. The problem of visualizing the tensor field is approached by combining a local visualization that displays all degrees of freedom for a single tensor with an overview visualization using a scalar field representation of the complete tensor field. The scalar field is obtained by iterated adaptive filtering of a noise field. Several methods for synchronizing the magnetic resonance imaging acquisition to the heart beat have previously been used to resolve individual heart phases from multiple cardiac cycles. In the present work, one of these techniques is extended to resolve two temporal dimensions simultaneously, the cardiac cycle and the respiratory cycle. This is combined with volumetric imaging to produce a five-dimensional data set. Furthermore, the acquisition order is optimized in order to reduce eddy current artifacts. The five-dimensional acquisition either requires very long scan times or can only provide low spatiotemporal resolution. A method that exploits the variation in temporal bandwidth over the imaging volume, k-t BLAST, is described and extended to two simultaneous temporal dimensions. The new method, k-t2 BLAST, allows simultaneous reduction of scan time and improvement of spatial resolution.