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Although 2D echo-planar imaging (EPI) remains the dominant method for functional MRI (FMRI), 3D readouts are receiving more interest as these sequences have favorable signal-to-noise ratio (SNR) and enable imaging at a high isotropic resolution. Spoiled gradient-echo (SPGR) and balanced steady-state free-precession (bSSFP) are rapid sequences that are typically acquired with highly segmented 3D readouts, and thus less sensitive to image distortion and signal dropout. They therefore provide a powerful alternative for FMRI in areas with strong susceptibility offsets, such as deep gray matter structures and the brainstem. Unfortunately, the multi-shot nature of the readout makes these sequences highly sensitive to physiological fluctuations, and large signal instabilities are observed in the inferior regions of the brain. In this work a characterization of the source of these instabilities is given and a new method is presented to reduce the instabilities observed in 3D SPGR and bSSFP. Rapidly acquired single-slice data, which critically sampled the respiratory and cardiac waveforms, showed that cardiac pulsation is the dominant source of the instabilities. Simulations further showed that synchronizing the readout to the cardiac cycle minimizes the instabilities considerably. A real-time synchronization method was therefore developed, which utilizes parallel-imaging techniques to allow cardiac synchronization without alteration of the volume acquisition rate. The implemented method significantly improves the temporal stability in areas that are affected by cardiac-related signal fluctuations. In bSSFP data the tSNR in the brainstem increased by 45%, at the cost of a small reduction in tSNR in the cortical areas. In SPGR the temporal stability is improved by approximately 20% in the subcortical structures and as well as cortical gray matter when synchronization was performed.

Original publication

DOI

10.1016/j.neuroimage.2011.05.070

Type

Journal article

Journal

Neuroimage

Publication Date

15/08/2011

Volume

57

Pages

1364 - 1375

Keywords

Artifacts, Brain Mapping, Brain Stem, Humans, Image Interpretation, Computer-Assisted, Imaging, Three-Dimensional, Magnetic Resonance Imaging