Magnetic Resonance Imaging (MRI) requires expensive diagnostic equipment and is labor intensive. To evaluate the effective use of the MRI resources a curve of flow time versus throughput may be helpful in quantifying the trade-off between patient waiting time and resource utilization, and in providing insight into operational time losses and variability. This curve may be obtained by simulation. However, building a detailed simulation model of an MRI department requires expertise typically unavailable in hospitals. To overcome this difficulty, we seek for an appropriate aggregate model of the MRI department, either a simulation or an analytical model. The aggregate model parameters are to be determined from hospital patient arrival and departure times. We study three different aggregate models for use in the MRI setting. To be able to evaluate the prediction accuracy of the candidate aggregate models we use a detailed simulation model as virtual MRI department.