PURPOSE Current four dimensional magnetic resonance imaging (4D-MRI) techniques lack sufficient temporal/spatial resolution and consistent tumor contrast. To overcome these limitations, this study presents the development and initial evaluation of a new strategy for 4D-MRI which is based on retrospective k-space reordering. METHODS We simulated a k-space reordered 4D-MRI on a 4D digital extended cardiac-torso (XCAT) human phantom. A 2D echo planar imaging MRI sequence [frame rate (F) = 0.448 Hz; image resolution (R) = 256 × 256; number of k-space segments (NKS) = 4] with sequential image acquisition mode was assumed for the simulation. Image quality of the simulated "4D-MRI" acquired from the XCAT phantom was qualitatively evaluated, and tumor motion trajectories were compared to input signals. In particular, mean absolute amplitude differences (D) and cross correlation coefficients (CC) were calculated. Furthermore, to evaluate the data sufficient condition for the new 4D-MRI technique, a comprehensive simulation study was performed using 30 cancer patients' respiratory profiles to study the relationships between data completeness (Cp) and a number of impacting factors: the number of repeated scans (NR), number of slices (NS), number of respiratory phase bins (NP), NKS, F, R, and initial respiratory phase at image acquisition (P0). As a proof-of-concept, we implemented the proposed k-space reordering 4D-MRI technique on a T2-weighted fast spin echo MR sequence and tested it on a healthy volunteer. RESULTS The simulated 4D-MRI acquired from the XCAT phantom matched closely to the original XCAT images. Tumor motion trajectories measured from the simulated 4D-MRI matched well with input signals (D = 0.83 and 0.83 mm, and CC = 0.998 and 0.992 in superior-inferior and anterior-posterior directions, respectively). The relationship between Cp and NR was found best represented by an exponential function (CP=1001-e(-0.18NR) , when NS = 30, NP = 6). At a CP value of 95%, the relative error in tumor volume was 0.66%, indicating that NR at a CP value of 95% (NR,95%) is sufficient. It was found that NR,95% is approximately linearly proportional to NP (r = 0.99), and nearly independent of all other factors. The 4D-MRI images of the healthy volunteer clearly demonstrated respiratory motion in the diaphragm region with minimal motion induced noise or aliasing. CONCLUSIONS It is feasible to generate respiratory correlated 4D-MRI by retrospectively reordering k-space based on respiratory phase. This new technology may lead to the next generation 4D-MRI with high spatiotemporal resolution and optimal tumor contrast, holding great promises to improve the motion management in radiotherapy of mobile cancers.