Abstract
In EPI‐fMRI acquisitions, various readout bandwidth (BW) values are used as a function of gradients' characteristics of the MR scanner system. Echo spacing (ES) is another fundamental parameter of EPI‐fMRI sequences, but the employed ES value is not usually reported in fMRI studies. Nyquist ghost is a typical EPI artifact that can degrade the overall quality of fMRI time series. In this work, the authors assessed the basic effect of BW and ES for two clinical 1.5 T MR scanner systems (scanner‐A, scanner‐B) on Nyquist ghost of gradient‐echo EPI‐fMRI sequences. BW range was: scanner‐A, 1953‐3906 Hz/pixel; scanner‐B, 1220‐2894 Hz/pixel. ES range was: scanner‐A, scanner‐B: 0.75‐1.33 ms. The ghost‐to‐signal ratio of time series acquisition (GSRts) and drift of ghost‐to‐signal ratio (DRGSR) were measured in a water phantom. For both scanner‐A (93% of variation) and scanner‐B (102% of variation) the mean GSRts significantly increased with increasing BW. GSRts values of scanner‐A did not significantly depended on ES. On the other hand, GSRts values of scanner‐B significantly varied with ES, showing a downward trend (81% of variation) with increasing ES. In addition, a GSRts spike point at ES=1.05ms indicating a potential resonant effect was revealed. For both scanners, no significant effect of ES on DRGSR was revealed. DRGSR values of scanner‐B did not significantly vary with BW, whereas DRGSR values of scanner‐A significantly depended on BW showing an upward trend from negative to positive values with increasing BW. GSRts and DRGSR can significantly vary with BW and ES, and the specific pattern of variation may depend on gradients performances, EPI sequence calibrations and functional design of radiofrequency coil. Thus, each MR scanner system should be separately characterized. In general, the employment of low BW values seems to reduce the intensity and temporal variation of Nyquist ghost in EPI‐fMRI time series. On the other hand, the use of minimum ES value might not be entirely advantageous when the MR scanner is characterized by gradients with low performances and suboptimal EPI sequence calibration.PACS numbers: 87.61.‐c, 87.61.Qr, 87.61.Hk
Highlights
Functional magnetic resonance imaging based on blood-oxygen-level-dependent (BOLD) contrast[1] has advanced the field of brain research by noninvasively enabling imaging of brain function with a spatial and temporal resolution on the order of millimetres and seconds, respectively. fMRI techniques[2] have been widely used to detect human brain activity changes associated with motor, sensory or cognitive processes.[3]The BOLD response is an indirect measure of neural activity
The relationship between BOLD contrast and cerebral oxygen metabolism can be influenced by a number of physiological factors.[4,5] in fMRI the signal changes associated with BOLD contrast depend on static magnetic field strength, hardware characteristics of the MR scanner system, radio frequency (RF) coils configuration, in addition to acquisition parameters in terms of acquisition sequence, repetition time, echo time and voxel size.[6,7] Logothetis[5] has recently analyzed the potential limits of fMRI applications from a theoretical analysis of physiological processes involved in BOLD effect
The specific pattern of variation may depend on each single MR scanner system in terms of gradient characteristics, echo planar imaging (EPI) sequence calibrations and functional design of radiofrequency coil
Summary
Functional magnetic resonance imaging (fMRI) based on blood-oxygen-level-dependent (BOLD) contrast[1] has advanced the field of brain research by noninvasively enabling imaging of brain function with a spatial and temporal resolution on the order of millimetres and seconds, respectively. fMRI techniques[2] have been widely used to detect human brain activity changes associated with motor, sensory or cognitive processes.[3]The BOLD response is an indirect measure of neural activity. The relationship between BOLD contrast and cerebral oxygen metabolism can be influenced by a number of physiological factors.[4,5] in fMRI the signal changes associated with BOLD contrast depend on static magnetic field strength, hardware characteristics of the MR scanner system, radio frequency (RF) coils configuration, in addition to acquisition parameters in terms of acquisition sequence, repetition time, echo time and voxel size.[6,7] Logothetis[5] has recently analyzed the potential limits of fMRI applications from a theoretical analysis of physiological processes involved in BOLD effect. Some studies have performed comparison analyses of the effect of processing parameters of fMRI time series on activation maps.[26,27,28]
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