Nonconvex Compressive Sensing with Parallel Imaging for Highly Accelerated 4D CE-MRA

Joshua D. Trzasko¹, Clifton R. Haider¹, Eric A. Borisch¹, Stephen J. Riederer¹, Armando Manduca¹

CAPR is a state-of-the-art Cartesian acquisition paradigm for time-resolved 3D contrast-enhanced MR angiography that typically employs Tikhonov and partial Fourier methods for image reconstruction. When operating at extreme acceleration rates, such reconstructions can exhibit significant noise amplification and Gibbs artifacts, potentially inhibiting diagnosis. In this work, an offline reconstruction framework for both view-shared and non-view-shared CAPR time-series acquisitions based on nonconvex Compressive Sensing is proposed and demonstrated to both suppress noise amplification and improve vessel conspicuity.