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. 2019 Oct;9(8):638-648.
doi: 10.1089/brain.2019.0683. Epub 2019 Sep 26.

Factors Affecting Detection Power of Blood Oxygen-Level Dependent Signal in Resting-State Functional Magnetic Resonance Imaging Using High-Resolution Echo-Planar Imaging

Affiliations

Factors Affecting Detection Power of Blood Oxygen-Level Dependent Signal in Resting-State Functional Magnetic Resonance Imaging Using High-Resolution Echo-Planar Imaging

Elisabeth C Caparelli et al. Brain Connect. 2019 Oct.

Abstract

Latest developments in magnetic resonance imaging (MRI) hardware and software have significantly improved image acquisition for functional MRI (fMRI) techniques, including resting-state fMRI (rsfMRI). Specifically, with improvements in gradient and radiofrequency coils and advances in pulse sequence designs, functional images with higher spatiotemporal resolution can be achieved. However, while smaller voxel size has the benefit of resolving finer brain structures, it also decreases voxel-wise signal-to-noise ratio (SNR) and, subsequently, temporal SNR (tSNR), which is critical for the sensitivity of fMRI. Although the improved temporal resolution allows more image frames to be collected per unit time, the ability to detect brain activity by using the high spatiotemporal fMRI has not been fully characterized. Here, we aimed to evaluate the effects of spatial smoothing, scan length, sample size, seed size, and location on resting-state functional connectivity (rsFC) and tSNR by using data from the human connectome project. Results from this analysis show an important effect of smoothing on the rsFC strength (correlation values between the seed and the target) as well as on the tSNR. In contrast, while rsFC strength is not affected by sample size, the standard error decreases with the increasing number of participants, therefore improving the detection power for larger samples. Scan length and seed size seem to have a moderate effect on rsFC strength. Finally, seed location has an important impact on rsFC maps, as rsFC strength from cortical seeds seems higher than from sub-cortical seeds. In summary, our findings show that the choice of parameters can be critical for an rsfMRI study.

Keywords: detection power; functional connectivity; high resolution fMRI; resting-state fMRI.

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Conflict of interest statement

No competing financial interests exist.

Figures

<b>FIG. 1.</b>
FIG. 1.
Function connectivity pattern for the AMYL seed (full correlation, one sample t-tests), for the different scan lengths (5, 10, 14.4 min) and smoothing levels (FWHM = 2, 3, 4 mm), ALL = 98 (14.4 and 10 min runs) or 100 (5-min run) participants; puncorrected < 0.001, pcorrected < 0.05; MNI standard space; radiological convention. AMYL, left amygdala; FWHM, full width at half maximum; MNI, Montreal Neurological Institute.
<b>FIG. 2.</b>
FIG. 2.
FC pattern for the PCC seed for the different seed sizes (sphere: 7.3, 5, 3 mm radius, full correlation), 98 participants, 4-mm smoothing, 14.4-min rsfMRI run, one sample t-test; puncorrected < 0.001, pcorrected < 0.05; MNI standard space; radiological convention. ROI analysis in the MPFC, t-score = mean FC-strength/SE. Error bars shows the SE. FC, functional connectivity; MPFC, medial prefrontal cortex; PCC, posterior cingulate cortex; ROI, region-of-interest; rsfMRI, resting-state functional magnetic resonance imaging; SE, standard error.
<b>FIG. 3.</b>
FIG. 3.
ROI analysis for ALL = 98 (14.4 and 10-min runs) or 100 (5-min run) participants, at MPFC. Absolute values are displayed for different smoothing values (x-axis: 2, 3, 4 mm) and different scan lengths (5, 10, 14.4 min); t-score = mean FC-strength/SE. Error bars shows the SE. t-Score is displayed for INL(R). Cyan: ROI location, yellow: seed location. AMYR, right amygdala; INL, left insula; INL(R), left(right) insula; INR, right insula.
<b>FIG. 4.</b>
FIG. 4.
Effect size (mean FC strength/SD) values for the different smoothing levels (2, 3, 4 mm), scan lengths (5, 10, 14.4 min) and number of participants (ppts = 20, 40, 60, ALL). For the sub-groups (ppts = 20, 40, 60), the SD was calculated by using approach #1, SD = mean [SD(i)], with i = 1…100. For ALL = 98 (14.4 and 10 min runs) or 100 (5 min run) participants, the SD reflects the variability of the mean FC strength across the population. Minimum effect size to reach significance (Power = 80%, α = 0.05) is shown in red for their respective sample size. SD, standard deviation.
<b>FIG. 5.</b>
FIG. 5.
tSNR maps averaged across ALL = 98 (14.4 and 10-min runs) or 100 (5 min run) participants for the different smoothing levels (FWHM = 2, 3, 4 mm) and scan lengths (5, 10, 14.4 min). tSNR, temporal signal-to-noise ratio.

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