Accelerated cardiac perfusion imaging using k-t SENSE with SENSE training

Abstract

In k-t sensitivity encoding (SENSE), MR data acquisition performed in parallel by multiple coils is accelerated by sparsely sampling the k-space over time. The resulting aliasing is resolved by exploiting spatiotemporal correlations inherent in dynamic images of natural objects. In this article, a modified k-t SENSE reconstruction approach is presented, which aims at improving the temporal fidelity of first-pass, contrast-enhanced myocardial perfusion images at high accelerations. The proposed technique is based on applying parallel imaging on the training data in order to increase their spatial resolution. At a net acceleration of 5.8 (k-t factor = 8, training profiles = 11) accurate representations of dynamic signal-intensities were achieved. The efficacy of this approach as well as limitations due to noise amplification were investigated in computer simulations and in vivo experiments.