Evaluation of preprocessing steps to compensate for magnetic field distortions due to body movements in BOLD fMRI

Barry, Robert L.; Williams, Joy M.; Klassen, L. Martyn; Gallivan, Jason P.; Culham, Jody C.; Menon, Ravi S.

doi:10.1016/j.mri.2009.07.005

« Previous Next »Magnetic Resonance Imaging
Volume 28, Issue 2 , Pages 235-244, February 2010

Evaluation of preprocessing steps to compensate for magnetic field distortions due to body movements in BOLD fMRI

Robert L. Barry
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, Schulich School of Medicine and Dentistry, The University of Western Ontario, London, Ontario, Canada N6A 5K8
- Graduate Program in Biomedical Engineering, The University of Western Ontario, London, Ontario, Canada N6A 5B9
Joy M. Williams
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, Schulich School of Medicine and Dentistry, The University of Western Ontario, London, Ontario, Canada N6A 5K8
L. Martyn Klassen
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, Schulich School of Medicine and Dentistry, The University of Western Ontario, London, Ontario, Canada N6A 5K8
Jason P. Gallivan
- Graduate Program in Neuroscience, The University of Western Ontario, London, Ontario, Canada N6A 5B8
Jody C. Culham
- Graduate Program in Neuroscience, The University of Western Ontario, London, Ontario, Canada N6A 5B8
- Department of Psychology, The University of Western Ontario, London, Ontario, Canada N6A 5C2
Ravi S. Menon
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, Schulich School of Medicine and Dentistry, The University of Western Ontario, London, Ontario, Canada N6A 5K8
- Graduate Program in Biomedical Engineering, The University of Western Ontario, London, Ontario, Canada N6A 5B9
- Graduate Program in Neuroscience, The University of Western Ontario, London, Ontario, Canada N6A 5B8
- Department of Diagnostic Radiology and Nuclear Medicine, The University of Western Ontario, London, Ontario, Canada N6A 5K8
- Corresponding author.

Received 4 February 2009; received in revised form 26 June 2009; accepted 4 July 2009. published online 20 August 2009.

Abstract

Blood oxygenation level-dependent (BOLD) functional magnetic resonance imaging (fMRI) is currently the dominant technique for non-invasive investigation of brain functions. One of the challenges with BOLD fMRI, particularly at high fields, is compensation for the effects of spatiotemporally varying magnetic field inhomogeneities (ΔB₀) caused by normal subject respiration and, in some studies, movement of the subject during the scan to perform tasks related to the functional paradigm. The presence of ΔB₀ during data acquisition distorts reconstructed images and introduces extraneous fluctuations in the fMRI time series that decrease the BOLD contrast-to-noise ratio. Optimization of the fMRI data-processing pipeline to compensate for geometric distortions is of paramount importance to ensure high quality of fMRI data. To investigate ΔB₀ caused by subject movement, echo-planar imaging scans were collected with and without concurrent motion of a phantom arm. The phantom arm was constructed and moved by the experimenter to emulate forearm motions while subjects remained still and observed a visual stimulation paradigm. These data were then subjected to eight different combinations of preprocessing steps. The best preprocessing pipeline included navigator correction, a complex phase regressor and spatial smoothing. The synergy between navigator correction and phase regression reduced geometric distortions better than either step in isolation and preconditioned the data to make them more amenable to the benefits of spatial smoothing. The combination of these steps provided a 10% increase in t-statistics compared to only navigator correction and spatial smoothing and reduced the noise and false activations in regions where no legitimate effects would occur.

Keywords: Functional magnetic resonance imaging, Echo-planar imaging, Preprocessing, Geometric distortions, Body movements, Navigator correction, Phase regression, Spatial smoothing