Cardiac-induced physiological noise in 3D gradient echo brain imaging: effect of k-space sampling scheme

The physiological noise in 3D image acquisition is shown to depend strongly on the sampling scheme. Five sampling schemes are considered: Linear, Centric, Segmented, Random and Tuned. Tuned acquisition means that data acquisition at k-space positions k and -k are separated with a specific time interval. We model physiological noise as a periodic temporal oscillation with arbitrary spatial amplitude in the physical object and develop a general framework to describe how this is rendered in the reconstructed image. Reconstructed noise can be decomposed in one component that is in phase with the signal (parallel) and one that is 90° out of phase (orthogonal). Only the former has a significant influence on the magnitude of the signal. The study focuses on fMRI using 3D EPI. Each k-space plane is acquired in a single shot in a time much shorter than the period of the physiological noise. The above mentioned sampling schemes are applied in the slow k-space direction and noise propagates almost exclusively in this direction. The problem then, is effectively one-dimensional. Numerical simulations and analytical expressions are presented. 3D noise measurements and 2D measurements with high temporal resolution are conducted. The measurements are performed under breath-hold to isolate the effect of cardiac-induced pulsatile motion. We compare the time-course stability of the sampling schemes and the extent to which noise propagates from a localized source into other parts of the imaging volume. Tuned and Linear acquisitions perform better than Centric, Segmented and Random.