Intrinsic Resting-State Functional Connectivity in the Human Spinal Cord at 3.0 T

Abstract

Purpose To apply resting-state functional magnetic resonance (MR) imaging to map functional connectivity of the human spinal cord. Materials and Methods Studies were performed in nine self-declared healthy volunteers with informed consent and institutional review board approval. Resting-state functional MR imaging was performed to map functional connectivity of the human cervical spinal cord from C1 to C4 at 1 × 1 × 3-mm resolution with a 3.0-T clinical MR imaging unit. Independent component analysis (ICA) was performed to derive resting-state functional MR imaging z-score maps rendered on two-dimensional and three-dimensional images. Seed-based analysis was performed for cross validation with ICA networks by using Pearson correlation. Results Reproducibility analysis of resting-state functional MR imaging maps from four repeated trials in a single participant yielded a mean z score of 6 ± 1 (P < .0001). The centroid coordinates across the four trials deviated by 2 in-plane voxels ± 2 mm (standard deviation) and up to one adjacent image section ± 3 mm. ICA of group resting-state functional MR imaging data revealed prominent functional connectivity patterns within the spinal cord gray matter. There were statistically significant (z score > 3, P < .001) bilateral, unilateral, and intersegmental correlations in the ventral horns, dorsal horns, and central spinal cord gray matter. Three-dimensional surface rendering provided visualization of these components along the length of the spinal cord. Seed-based analysis showed that many ICA components exhibited strong and significant (P < .05) correlations, corroborating the ICA results. Resting-state functional MR imaging connectivity networks are qualitatively consistent with known neuroanatomic and functional structures in the spinal cord. Conclusion Resting-state functional MR imaging of the human cervical spinal cord with a 3.0-T clinical MR imaging unit and standard MR imaging protocols and hardware reveals prominent functional connectivity patterns within the spinal cord gray matter, consistent with known functional and anatomic layouts of the spinal cord.

Denoising spinal cord fMRI data: Approaches to acquisition and analysis

“…Once the components are identified, these can then be removed from the data (for task-based data, this should be done by including their time-courses as covariates in the design matrix). Such an approach has been taken in a recent resting-state spinal fMRI study (San Emeterio Nateras et al, 2016), as well as in a task-based study on motor-learning where the authors also explicitly listed their criteria for designating a component as noise (Vahdat et al, 2015). It is furthermore possible to combine ICAbased denoising with the model-based approaches described earlier; such an approach has recently been shown beneficial for brainstem data (Faull et al, 2016) and might hold potential for spinal fMRI as well.…”

Amplitude of Low Frequency Fluctuation (ALFF) in the Cervical Spinal Cord with Stenosis: A Resting State fMRI Study

“…Through the Statistical Parametric Mapping 8 (SPM8, http://www.fil.ion.ucl.ac.uk/spm/) and Resting-State fMRI Data Analysis Toolkit (REST, http://restfmri.net/forum/index.php) toolboxes in MATLAB 7.11.0 (Mathworks, Natick, MA, USA), the raw EPI images were processed for slice timing, motion correction, nuisance regression, detrend, and band-pass filtering (0.01–0.08 Hz). Regressors included: 1) cerebrospinal fluid (CSF) pulsation signal and tissue motion signal that was extracted through independent component analysis (ICA) through gift (http://mialab.mrn.org/software/gift/) toolbox; 2) motion correction parameters (x and y translation)[12]. The first 10 volumes were discarded to exclude the initial transient effects.…”

“…RsfMRI focused on low-frequency blood oxygen level-dependent (BOLD) fluctuations which are considered to reflect intrinsic neural activity. In recent years, rsfMRI has already been introduced in spinal cord studies and revealed that the spinal cord is intrinsically organized [10–12]. …”

Robust spinal cord resting‐state fMRI using independent component analysis‐based nuisance regression noise reduction

“…Spinal cord Resting‐State functional magnetic resonance imaging (rsfMRI) is a promising technique that offers a new way to investigate intrinsic spinal cord function in health and disease . However, several technical challenges still hamper its clinical application.…”

“…However, several technical challenges still hamper its clinical application. Recent studies have adopted adjustments to rsfMRI image acquisition to successfully overcome challenges such as the small size of the spinal cord and susceptibility artifacts . One key problem that remains is non‐ignorable physiological noise …”