Iterative projection reconstruction of time-resolved images using highly-constrained back-projection (HYPR)

Abstract

Highly-constrained back-projection (HYPR) is a technique for the reconstruction of sparse, highly-undersampled time-resolved image data. A novel iterative HYPR (I-HYPR) algorithm is presented and validated in computer simulations. The reconstruction method is then applied to cerebral perfusion MRI simulated as a radial acquisition and contrast-enhanced angiography of the head to assess feasibility in accelerating acquisitions requiring high temporal resolution and accurate representation of contrast kinetics. The I-HYPR algorithm is shown to be more robust than standard HYPR in these applications in which the sparsity condition is not met or in which quantitative information is required. Specifically, iterative reconstruction of undersampled perfusion and contrast-enhanced angiography data improved accuracy of the representation of contrast kinetics and increased the temporal separation of arterial and venous contrast kinetics. The I-HYPR reconstruction may have important diagnostic applications in settings requiring high temporal resolution and quantitative signal dynamics. Because I-HYPR allows relaxation of the sparsity requirements for the composite frame, the iterative reconstruction can enable novel acquisition strategies that independently optimize the quality of the composite and temporal resolution of the dynamic frames. © 2007 Wiley-Liss, Inc.