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A GPU Implementation of Compressed Sensing Reconstruction of 3 D Radial ( Kooshball ) Acquisition for High-Resolution Cardiac MRI

INTRODUCTION: 3D non-Cartesian sampling trajectories allow high isotropic spatial resolution, better depiction of cardiac anatomy and ease of image prescription in whole heart cardiac MRI. 3D acquisition using stack of spirals or radials with Cartesian sampling in kz and 3D radial sampling (kooshball) have been previously used to image cardiac anatomy [1-4]. 3D kooshball imaging sequence allows respiratory self-gating, excellent motion and flow insensitivity and improved scan efficiency. However, these imaging techniques suffer from long scan and reconstruction time. While highly under-sampled 3D kooshball is more forgiving in terms of artifacts than Cartesian acquisition, the streaking artifacts could impact the clinical interpretation. Compressed sensing (CS) reconstruction [5] has the potential to remove these artifacts; however even a feasibility study of this approach with 3D non-Cartesian sampling has been limited mainly due to high computational burden associated with iterative CS reconstructions. In this study, we sought to implement and evaluate an iterative 3D CS reconstruction method for high-resolution kooshball whole heart imaging on Graphics Processing Units (GPU). The resulting speedup was compared with a sequential C++ implementation on CPU.