Literature DB >> 22079450

Phase stability in fMRI time series: effect of noise regression, off-resonance correction and spatial filtering techniques.

Gisela E Hagberg1, Marta Bianciardi, Valentina Brainovich, Antonino Mario Cassara, Bruno Maraviglia.   

Abstract

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 5 mrad (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 0.0017 ppm, which is close to the dHb contribution to the GM/WM phase contrast.
Copyright © 2011 Elsevier Inc. All rights reserved.

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Year:  2011        PMID: 22079450     DOI: 10.1016/j.neuroimage.2011.10.095

Source DB:  PubMed          Journal:  Neuroimage        ISSN: 1053-8119            Impact factor:   6.556


  11 in total

1.  Physiological noise in human cerebellar fMRI.

Authors:  Wietske van der Zwaag; João Jorge; Denis Butticaz; Rolf Gruetter
Journal:  MAGMA       Date:  2015-04-18       Impact factor: 2.310

2.  Evaluation of different cerebrospinal fluid and white matter fMRI filtering strategies-Quantifying noise removal and neural signal preservation.

Authors:  Marek Bartoň; Radek Mareček; Lenka Krajčovičová; Tomáš Slavíček; Tomáš Kašpárek; Petra Zemánková; Pavel Říha; Michal Mikl
Journal:  Hum Brain Mapp       Date:  2018-11-07       Impact factor: 5.038

3.  Enhanced phase regression with Savitzky-Golay filtering for high-resolution BOLD fMRI.

Authors:  Robert L Barry; John C Gore
Journal:  Hum Brain Mapp       Date:  2014-01-17       Impact factor: 5.038

4.  Direct neural current imaging in an intact cerebellum with magnetic resonance imaging.

Authors:  Padmavathi Sundaram; Aapo Nummenmaa; William Wells; Darren Orbach; Daniel Orringer; Robert Mulkern; Yoshio Okada
Journal:  Neuroimage       Date:  2016-02-17       Impact factor: 6.556

Review 5.  In vivo B0 field shimming methods for MRI at 7T.

Authors:  Jason P Stockmann; Lawrence L Wald
Journal:  Neuroimage       Date:  2017-06-07       Impact factor: 6.556

6.  Investigation of BOLD fMRI resonance frequency shifts and quantitative susceptibility changes at 7 T.

Authors:  Marta Bianciardi; Peter van Gelderen; Jeff H Duyn
Journal:  Hum Brain Mapp       Date:  2013-07-29       Impact factor: 5.038

Review 7.  Methods for cleaning the BOLD fMRI signal.

Authors:  César Caballero-Gaudes; Richard C Reynolds
Journal:  Neuroimage       Date:  2016-12-09       Impact factor: 6.556

8.  GLMdenoise: a fast, automated technique for denoising task-based fMRI data.

Authors:  Kendrick N Kay; Ariel Rokem; Jonathan Winawer; Robert F Dougherty; Brian A Wandell
Journal:  Front Neurosci       Date:  2013-12-17       Impact factor: 4.677

9.  Modified human contrast sensitivity function based phase mask for susceptibility-weighted imaging.

Authors:  Wei-Hsin Wang; David C Reutens; Zhengyi Yang; Giang Nguyen; Viktor Vegh
Journal:  Neuroimage Clin       Date:  2014-04-30       Impact factor: 4.881

10.  Suppressing Respiration Effects when Geometric Distortion Is Corrected Dynamically by Phase Labeling for Additional Coordinate Encoding (PLACE) during Functional MRI.

Authors:  Zahra Faraji-Dana; Fred Tam; J Jean Chen; Simon J Graham
Journal:  PLoS One       Date:  2016-06-03       Impact factor: 3.240

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