TY - JOUR
T1 - Phase stability in fMRI time series
T2 - Effect of noise regression, off-resonance correction and spatial filtering techniques
AU - Hagberg, Gisela E.
AU - Bianciardi, Marta
AU - Brainovich, Valentina
AU - Cassara, Antonino Mario
AU - Maraviglia, Bruno
PY - 2012/2/15
Y1 - 2012/2/15
N2 - Although the majority of fMRI studies exploit magnitude changes only, there is an increasing interest regarding the potential additive information conveyed by the phase signal. This integrated part of the complex number furnished by the MR scanners can also be used for exploring direct detection of neuronal activity and for thermography. Few studies have explicitly addressed the issue of the available signal stability in the context of phase time-series, and therefore we explored the spatial pattern of frequency specific phase fluctuations, and evaluated the effect of physiological noise components (heart beat and respiration) on the phase signal. Three categories of retrospective noise reduction techniques were explored and the temporal signal stability was evaluated in terms of a physiologic noise model, for seven fMRI measurement protocols in eight healthy subjects at 3T, for segmented CSF, gray and white matter voxels. We confirmed that for most processing methods, an efficient use of the phase information is hampered by the fact that noise from physiological and instrumental sources contributes significantly more to the phase than to the magnitude instability. Noise regression based on the phase evolution of the central k-space point, RETROICOR, or an orthonormalized combination of these were able to reduce their impact, but without bringing phase stability down to levels expected from the magnitude signal. Similar results were obtained after targeted removal of scan-to-scan variations in the bulk magnetic field by the dynamic off-resonance in k-space (DORK) method and by the temporal off-resonance alignment of single-echo time series technique (TOAST). We found that spatial high-pass filtering was necessary, and in vivo a Gaussian filter width of 20mm was sufficient to suppress physiological noise and bring the phase fluctuations to magnitude levels. Stronger filters brought the fluctuations down to levels dictated by thermal noise contributions, and for 62.5mm 3 voxels the phase stability was as low as 5mrad (0.27°). In conditions of low SNR o and high temporal sampling rate (short TR); we achieved an upper bound for the phase instabilities at 0.0017ppm, which is close to the dHb contribution to the GM/WM phase contrast.
AB - Although the majority of fMRI studies exploit magnitude changes only, there is an increasing interest regarding the potential additive information conveyed by the phase signal. This integrated part of the complex number furnished by the MR scanners can also be used for exploring direct detection of neuronal activity and for thermography. Few studies have explicitly addressed the issue of the available signal stability in the context of phase time-series, and therefore we explored the spatial pattern of frequency specific phase fluctuations, and evaluated the effect of physiological noise components (heart beat and respiration) on the phase signal. Three categories of retrospective noise reduction techniques were explored and the temporal signal stability was evaluated in terms of a physiologic noise model, for seven fMRI measurement protocols in eight healthy subjects at 3T, for segmented CSF, gray and white matter voxels. We confirmed that for most processing methods, an efficient use of the phase information is hampered by the fact that noise from physiological and instrumental sources contributes significantly more to the phase than to the magnitude instability. Noise regression based on the phase evolution of the central k-space point, RETROICOR, or an orthonormalized combination of these were able to reduce their impact, but without bringing phase stability down to levels expected from the magnitude signal. Similar results were obtained after targeted removal of scan-to-scan variations in the bulk magnetic field by the dynamic off-resonance in k-space (DORK) method and by the temporal off-resonance alignment of single-echo time series technique (TOAST). We found that spatial high-pass filtering was necessary, and in vivo a Gaussian filter width of 20mm was sufficient to suppress physiological noise and bring the phase fluctuations to magnitude levels. Stronger filters brought the fluctuations down to levels dictated by thermal noise contributions, and for 62.5mm 3 voxels the phase stability was as low as 5mrad (0.27°). In conditions of low SNR o and high temporal sampling rate (short TR); we achieved an upper bound for the phase instabilities at 0.0017ppm, which is close to the dHb contribution to the GM/WM phase contrast.
KW - Gradient echo EPI
KW - Phase
KW - Physiological noise
KW - Retrospective correction
KW - Time series
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U2 - 10.1016/j.neuroimage.2011.10.095
DO - 10.1016/j.neuroimage.2011.10.095
M3 - Article
C2 - 22079450
AN - SCOPUS:84855179699
VL - 59
SP - 3748
EP - 3761
JO - NeuroImage
JF - NeuroImage
SN - 1053-8119
IS - 4
ER -