Effects of global signal regression and subtraction methods on resting-state functional connectivity using arterial spin labeling data

Publication date: September 2018
Source:Magnetic Resonance Imaging, Volume 51
Author(s): João Paulo Santos Silva, Luciana da Mata Mônaco, André Monteiro Paschoal, Ícaro Agenor Ferreira de Oliveira, Renata Ferranti Leoni
BackgroundArterial spin labeling (ASL) is an established magnetic resonance imaging (MRI) technique that is finding broader applications in functional studies of the healthy and diseased brain. To promote improvement in cerebral blood flow (CBF) signal specificity, many algorithms and imaging procedures, such as subtraction methods, were proposed to eliminate or, at least, minimize noise sources. Therefore, this study addressed the main considerations of how CBF functional connectivity (FC) is changed, regarding resting brain network (RBN) identification and correlations between regions of interest (ROI), by different subtraction methods and removal of residual motion artifacts and global signal fluctuations (RMAGSF).MethodsTwenty young healthy participants (13 M/7F, mean age = 25 ± 3 years) underwent an MRI protocol with a pseudo-continuous ASL (pCASL) sequence. Perfusion-based images were obtained using simple, sinc and running subtraction. RMAGSF removal was applied to all CBF time series. Independent Component Analysis (ICA) was used for RBN identification, while Pearson’ correlation was performed for ROI-based FC analysis.ResultsTemporal signal-to-noise ratio (tSNR) was higher in CBF maps obtained by sinc subtraction, although RMAGSF removal had a significant effect on maps obtained with simple and running subtractions. Neither the subtraction method nor the RMAGSF removal directly affected the identification of RBNs. However, the number of correlated and anti-correlated voxels varied for different subtraction and filtering methods. In an ROI-to-ROI level, changes were prominent in FC values and their statistical significance.ConclusionsOur study showed that both RMAGSF filtering and subtraction method might influence resting-state FC results, especially in an ROI level, consequently affecting FC analysis and its interpretation. Taking our results and the whole discussion together, we understand that for an exploratory assessment of the brain, one could avoid removing RMAGSF to not bias FC measures, but could use sinc subtraction to minimize low-frequency contamination. However, CBF signal specificity and frequency range for filtering purposes still need to be assessed in future studies.