Dynamic contrast enhanced MRI (DCE MRI) allows clinicians to better detect the downstream effects of coronary artery disease on myocardial tissue. DCE MRI of the heart is typically conducted through the acquisition of 2-4 short axis slices. However, this acquisition scheme provides incomplete coverage of the left ventricle and limits the visualization and quantification of the affected tissue. Radial simultaneous multi-slice (SMS) has been shown to improve DCE cardiac perfusion by providing complete coverage of the left ventricle. This comes with a cost, however: data undersampling and advanced reconstruction techniques significantly increase the computational time required to obtain images. To improve image quality and reduce the reconstruction time, we used a standard U-net architecture in order to learn the iterative compressed sensing reconstruction with total variation constraints.