Modeling SSFP functional MRI contrast in the brain

Abstract

Steady-state free precession (SSFP) has recently been proposed for function MRI because of the potential for reducing image distortion and signal dropout. Several different contrast mechanisms have been suggested to explain the reported observations, but there has been limited work comparing theory with experiment in the brain. Moreover, the detailed work that has considered oxygen-dependent signal in SSFP outside the brain has focused on R(2) effects in the pass band, and largely neglected the signal contrast that occurs due to off-resonance effects. The article describes a model for SSFP functional contrast based on the convolution of the theoretical SSFP profile with the underlying frequency distribution. It is demonstrated that such a model must account for the effects of diffusion, which can alter the apparent R(2) and linespread. Monte Carlo simulations are used to calibrate corrections for these terms. This new model has the computational efficiency of the convolution model while encapsulating information from more time-consuming Monte Carlo simulations. This corrected convolution model is shown to agree well with experimental data, and model predictions and limitations are discussed.