Optimal k-space sampling for dynamic contrast-enhanced MRI with an application to MR renography

For time‐resolved acquisitions with k‐space undersampling, a simulation method was developed for selecting imaging parameters based on minimization of errors in signal intensity versus time and physiologic parameters derived from tracer kinetic analysis. Optimization was performed for time‐resolved angiography with stochastic trajectories (TWIST) algorithm applied to contrast‐enhanced MR renography. A realistic 4D phantom comprised of aorta and two kidneys, one healthy and one diseased, was created with ideal tissue time‐enhancement pattern generated using a three‐compartment model with fixed parameters, including glomerular filtration rate (GFR) and renal plasma flow (RPF). TWIST acquisitions with different combinations of sampled central and peripheral k‐space portions were applied to this phantom. Acquisition performance was assessed by the difference between simulated signal intensity (SI) and calculated GFR and RPF and their ideal values. Sampling of the 20% of the center and 1/5 of the periphery of k‐space in phase‐encoding plane and data‐sharing of the remaining 4/5 minimized the errors in SI (