Over the past decade, there has been a small contingent of laboratories developing magnetic resonance imaging (MRI)-guided intravascular techniques and applications. While these efforts have followed in the footsteps of MRI-guided surgical technologies (1,2), intravascular techniques do not carry the requirement for an open access scanner, and hence higher imaging performance during procedures can be achieved. The concept of precise real-time tracking of an active catheter in a standard MRI scanner was fully realized more than 15 years ago by Dumoulin and colleagues (3). Interventional MRI has subsequently developed into the obvious method for delivery of numerous therapies. This review addresses the recent developments and state-of-the-art of a number of aspects of interventional cardiovascular MRI.
REAL-TIME IMAGINGOne of the principal enabling technologies for guiding intravascular procedures is real-time imaging. When catheter tracking was first implemented, special pulse sequences were required to obtain the catheter position from a few rapid projections; for some applications, this is now unnecessary due to the ability of modern scanners to provide up to 30 frames per second. There is obviously a tradeoff between spatial resolution and temporal resolution, but this is fully adjustable in an interactive system. One of the significant developments for real-time imaging is the use of multiple receiver systems used in conjunction with specially designed coil arrays to enable parallel imaging techniques. In this next section, some of these techniques are briefly described.
PARALLEL IMAGING METHODSParallel imaging is a rapid imaging method that can be applied to real-time imaging. Parallel imaging exploits the difference in sensitivity profiles between individual coil elements in a receive array to reduce the number of gradient encoding steps required for imaging. Parallel imaging uses R-fold k-space undersampling to achieve an acceleration factor of rate R. The alias artifacts (R uniformly spaced ghosts) caused by k-space undersampling are then cancelled by the parallel image reconstruction algorithm. Parallel image reconstruction may be performed in the k-space domain, for example, by using SiMultaneous Acquisition of Spatial Harmonics (SMASH) (4), or in the image domain, for example, by using the sensitivity encoding method (SENSE) (5).