Literature DB >> 21073963

Physiological noise effects on the flip angle selection in BOLD fMRI.

J Gonzalez-Castillo1, V Roopchansingh, P A Bandettini, J Bodurka.   

Abstract

This work addresses the choice of imaging flip angle in blood oxygenation level dependent (BOLD) functional magnetic resonance imaging (fMRI). When noise of physiological origin becomes the dominant noise source in fMRI timeseries, it causes a nonlinear dependence of the temporal signal-to-noise ratio (TSNR) versus signal-to-noise ratio (SNR) that can be exploited to perform BOLD fMRI at angles well below the Ernst angle without any detrimental effect on our ability to detect sites of neuronal activation. We show, both experimentally and theoretically, that for situations where available SNR is high and physiological noise dominates over system/thermal noise, although TSNR still reaches it maximum for the Ernst angle, reduction of imaging flip angle well below this angle results in negligible loss in TSNR. Moreover, we provide a way to compute a suggested imaging flip angle, which constitutes a conservative estimate of the minimum flip angle that can be used under given experimental SNR and physiological noise levels. For our experimental conditions, this suggested angle equals 7.63° for the grey matter compartment, while the Ernst angle=77°. Finally, using data from eight subjects with a combined visual-motor task we show that imaging at angles as low as 9° introduces no significant differences in observed hemodynamic response time-course, contrast-to-noise ratio, voxel-wise effect size or statistical maps of activation as compared to imaging at 75° (an angle close to the Ernst angle). These results suggest that using low flip angles in BOLD fMRI experimentation to obtain benefits such as (1) reduction of RF power, (2) limitation of apparent T(1)-related inflow effects, (3) reduction of through-plane motion artifacts, (4) lower levels of physiological noise, and (5) improved tissue contrast is feasible when physiological noise dominates and SNR is high.
Copyright © 2010 Elsevier Inc. All rights reserved.

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Year:  2010        PMID: 21073963      PMCID: PMC3020268          DOI: 10.1016/j.neuroimage.2010.11.020

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


  34 in total

1.  Neuroimaging at 1.5 T and 3.0 T: comparison of oxygenation-sensitive magnetic resonance imaging.

Authors:  G Krüger; A Kastrup; G H Glover
Journal:  Magn Reson Med       Date:  2001-04       Impact factor: 4.668

2.  Brodmann's areas 17 and 18 brought into stereotaxic space-where and how variable?

Authors:  K Amunts; A Malikovic; H Mohlberg; T Schormann; K Zilles
Journal:  Neuroimage       Date:  2000-01       Impact factor: 6.556

3.  Impact of signal-to-noise on functional MRI.

Authors:  T B Parrish; D R Gitelman; K S LaBar; M M Mesulam
Journal:  Magn Reson Med       Date:  2000-12       Impact factor: 4.668

4.  7T vs. 4T: RF power, homogeneity, and signal-to-noise comparison in head images.

Authors:  J T Vaughan; M Garwood; C M Collins; W Liu; L DelaBarre; G Adriany; P Andersen; H Merkle; R Goebel; M B Smith; K Ugurbil
Journal:  Magn Reson Med       Date:  2001-07       Impact factor: 4.668

5.  Physiological noise in oxygenation-sensitive magnetic resonance imaging.

Authors:  G Krüger; G H Glover
Journal:  Magn Reson Med       Date:  2001-10       Impact factor: 4.668

6.  Reproducibility of visual activation during checkerboard stimulation in functional magnetic resonance imaging at 4 Tesla.

Authors:  A Miki; G T Liu; S A Englander; J Raz; T G van Erp; E J Modestino; C J Liu; J C Haselgrove
Journal:  Jpn J Ophthalmol       Date:  2001 Mar-Apr       Impact factor: 2.447

7.  Assessment of reliability in functional imaging studies.

Authors:  Karsten Specht; Klaus Willmes; N Jon Shah; Lutz Jäncke
Journal:  J Magn Reson Imaging       Date:  2003-04       Impact factor: 4.813

8.  Signal-to-noise ratio and parallel imaging performance of a 16-channel receive-only brain coil array at 3.0 Tesla.

Authors:  Jacco A de Zwart; Patrick J Ledden; Peter van Gelderen; Jerzy Bodurka; Renxin Chu; Jeff H Duyn
Journal:  Magn Reson Med       Date:  2004-01       Impact factor: 4.668

9.  Functional Magnetic Resonance Imaging (fMRI) reproducibility and variance components across visits and scanning sites with a finger tapping task.

Authors:  Viktoria-Eleni Gountouna; Dominic E Job; Andrew M McIntosh; T William J Moorhead; G Katherine L Lymer; Heather C Whalley; Jeremy Hall; Gordon D Waiter; David Brennan; David J McGonigle; Trevor S Ahearn; Jonathan Cavanagh; Barrie Condon; Donald M Hadley; Ian Marshall; Alison D Murray; J Douglas Steele; Joanna M Wardlaw; Stephen M Lawrie
Journal:  Neuroimage       Date:  2009-07-23       Impact factor: 6.556

10.  The intrinsic signal-to-noise ratio in NMR imaging.

Authors:  W A Edelstein; G H Glover; C J Hardy; R W Redington
Journal:  Magn Reson Med       Date:  1986-08       Impact factor: 4.668

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  38 in total

1.  Physiological noise reduction using volumetric functional magnetic resonance inverse imaging.

Authors:  Fa-Hsuan Lin; Aapo Nummenmaa; Thomas Witzel; Jonathan R Polimeni; Thomas A Zeffiro; Fu-Nien Wang; John W Belliveau
Journal:  Hum Brain Mapp       Date:  2011-09-23       Impact factor: 5.038

2.  Three-dimensional acquisition of cerebral blood volume and flow responses during functional stimulation in a single scan.

Authors:  Ying Cheng; Peter C M van Zijl; James J Pekar; Jun Hua
Journal:  Neuroimage       Date:  2014-08-23       Impact factor: 6.556

3.  The influence of spatial resolution and smoothing on the detectability of resting-state and task fMRI.

Authors:  Erin K Molloy; Mary E Meyerand; Rasmus M Birn
Journal:  Neuroimage       Date:  2013-09-08       Impact factor: 6.556

4.  More than BOLD: Dual-spin populations create functional contrast.

Authors:  Amanda J Taylor; Jung H Kim; Vimal Singh; Elizabeth J Halfen; Josef Pfeuffer; David Ress
Journal:  Magn Reson Med       Date:  2019-08-18       Impact factor: 4.668

Review 5.  Impacting the effect of fMRI noise through hardware and acquisition choices - Implications for controlling false positive rates.

Authors:  Lawrence L Wald; Jonathan R Polimeni
Journal:  Neuroimage       Date:  2016-12-28       Impact factor: 6.556

6.  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

7.  Optimized simultaneous ASL and BOLD functional imaging of the whole brain.

Authors:  Vincent J Schmithorst; Luis Hernandez-Garcia; Jennifer Vannest; Akila Rajagopal; Greg Lee; Scott K Holland
Journal:  J Magn Reson Imaging       Date:  2013-09-24       Impact factor: 4.813

8.  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

9.  Characterization and reduction of cardiac- and respiratory-induced noise as a function of the sampling rate (TR) in fMRI.

Authors:  Dietmar Cordes; Rajesh R Nandy; Scott Schafer; Tor D Wager
Journal:  Neuroimage       Date:  2013-12-16       Impact factor: 6.556

10.  fMRI hemodynamics accurately reflects neuronal timing in the human brain measured by MEG.

Authors:  Fa-Hsuan Lin; Thomas Witzel; Tommi Raij; Jyrki Ahveninen; Kevin Wen-Kai Tsai; Yin-Hua Chu; Wei-Tang Chang; Aapo Nummenmaa; Jonathan R Polimeni; Wen-Jui Kuo; Jen-Chuen Hsieh; Bruce R Rosen; John W Belliveau
Journal:  Neuroimage       Date:  2013-04-13       Impact factor: 6.556

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