Noise Reduction in Arterial Spin Labeling Based Functional Connectivity Using Nuisance Variables - PubMed (original) (raw)
Noise Reduction in Arterial Spin Labeling Based Functional Connectivity Using Nuisance Variables
Kay Jann et al. Front Neurosci. 2016.
Abstract
Arterial Spin Labeling (ASL) perfusion image series have recently been utilized for functional connectivity (FC) analysis in healthy volunteers and children with autism spectrum disorders (ASD). Noise reduction by using nuisance variables has been shown to be necessary to minimize potential confounding effects of head motion and physiological signals on BOLD based FC analysis. The purpose of the present study is to systematically evaluate the effectiveness of different noise reduction strategies (NRS) using nuisance variables to improve perfusion based FC analysis in two cohorts of healthy adults using state of the art 3D background-suppressed (BS) GRASE pseudo-continuous ASL (pCASL) and dual-echo 2D-EPI pCASL sequences. Five different NRS were performed in healthy volunteers to compare their performance. We then compared seed-based FC analysis using 3D BS GRASE pCASL in a cohort of 12 children with ASD (3f/9m, age 12.8 ± 1.3 years) and 13 typically developing (TD) children (1f/12m; age 13.9 ± 3 years) in conjunction with NRS. Regression of different combinations of nuisance variables affected FC analysis from a seed in the posterior cingulate cortex (PCC) to other areas of the default mode network (DMN) in both BOLD and pCASL data sets. Consistent with existing literature on BOLD-FC, we observed improved spatial specificity after physiological noise reduction and improved long-range connectivity using head movement related regressors. Furthermore, 3D BS GRASE pCASL shows much higher temporal SNR compared to dual-echo 2D-EPI pCASL and similar effects of noise reduction as those observed for BOLD. Seed-based FC analysis using 3D BS GRASE pCASL in children with ASD and TD children showed that noise reduction including physiological and motion related signals as nuisance variables is crucial for identifying altered long-range connectivity from PCC to frontal brain areas associated with ASD. This is the first study that systematically evaluated the effects of different NRS on ASL based FC analysis. 3D BS GRASE pCASL is the preferred ASL sequence for FC analysis due to its superior temporal SNR. Removing physiological noise and motion parameters is critical for detecting altered FC in neurodevelopmental disorders such as ASD.
Keywords: arterial spin labeling (ASL); blood oxygenation level dependent (BOLD); cerebral blood flow (CBF); default mode network (DMN); functional connectivity (FC); noise reduction.
Figures
Figure 1
Statistical t-maps displaying the spatial pattern of the DMNs as identified by Seed based Correlation analysis from a PCC seed (Lower left, green) on pCASL and BOLD datasets.
Figure 2
Dice Similarity Coefficients (DSCs) between the spatial maps of the DMNs after different stages of noise reduction (NRS1–5). Template DMN derived from Shirer et al. (2012). Combined DMN computed as one-sample _t_-test across spatial correlation maps of all subjects and NRS. Clusters along the diagonal indicate that WM/CSF regression has large effect on similarity. Specifically after WM/CSF correction (NRS4/5) DSC values to the template DMN are increased (green rectangle and also bar-plots below cluster-plots), indicating increased spatial specificity of the DMN.
Figure 3
Region-to-Region correlation between two template areas of the DMN: the PCC and the ACC/mPFC (shown in green in the small inlet figure). Overall BOLD exhibits stronger correlation values than ASL. Noise reduction shows similar behavior in FC changes for both BOLD datasets (solid lines) as well as the 3D BS GRASE pCASL data (blue dashed line), while showing little effect for 2D pCASL. A more regionally detailed analysis of these effects is displayed in Figure 4.
Figure 4
Voxel-wise repeated-measures ANOVA F-maps highlighting the areas with significant FC changes after NRS. Results are limited to areas within the DMNs as displayed in Figure 1. Box plots display the regional FC values for NRS1–5. Generally physiological noise reduction (WM and CSF fluctuations) reduced FC significantly (bars above box plots indicate significance between NRS-FC values). Motion correction had more subtle effects on FC but nevertheless significant increases can be seen in several areas mainly in the frontal cortex.
Figure 5
Distance dependence of FC changes between NRS4 and NRS5 (indicating motion correction effects only, after correction for physiological noise). Scatter plots reveal that FC between more distant areas is increased more than for proximal areas. Red lines represent the linear fit between distance and ΔFC (see also equations).
Figure 6
Boxplots indicating tSNR increases after different noise reduction strategies (NRS1–5) in all analyzed MRI sequences. Significant effects were found for all but the 2D dual-echo pCASL datasets.
Figure 7
Group differences between typically developing (TD) children and children with autism spectrum disorder (ASD) for different NRS in 3D BS GRASE pCASL data: NRS1 no noise reduction, NRS4 WM/CSF fluctuations removed, NRS5 WM/CSF and motion regression. While seed based FC (from PCC) in NRS1 did not reveal differences in frontal areas, NRS5 clearly delineates reduced long-range connections in ASD compared to TD.
References
- Alsop D. C., Detre J. A., Golay X., Günther M., Jeroen H., Hernandez-Garcia L., et al. (2015). Recommended Implementation of Arterial Spin Labeled Perfusion MRI for clinical applications: a consensus of the ISMRM Perfusion Study Group and the European Consortium for ASL in Dementia. Magn. Reson. Med. 73, 102–116. 10.1002/mrm.25197 -DOI -PMC -PubMed
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