Effect of Physiological Noise on Thoracolumbar Spinal Cord Functional Magnetic Resonance Imaging in 3T Magnetic Field

Abstract

Introduction: Functional Magnetic Resonance Imaging (fMRI) methods have been used to study sensorimotor processing in the spinal cord. However, these techniques confront unwanted noises to the measured signal from the physiological fluctuations. In the spinal cord imaging, most of the challenges are consequences of cardiac and respiratory movement artifacts that are considered as significant sources of noise, especially in the thoracolumbar region. In this study, we investigated the effect of each source of physiological noise and their contribution to the outcome of the analysis of the blood-oxygen-level-dependent signal in the human thoracolumbar spinal cord.

Methods: Fifteen young healthy male volunteers participated in the study, and pain stimuli were delivered on the L5 dermatome between the two malleoli. Respiratory and cardiac signals were recorded during the imaging session, and the generated respiration and cardiac regressors were included in the general linear model for quantification of the effect of each of them on the task-analysis results. The sum of active voxels of the clusters was calculated in the spinal cord in three correction states (respiration correction only, cardiac correction only, and respiration and cardiac noise corrections) and analyzed with analysis of variance statistical test and receiver operating characteristic curve.

Results: The results illustrated that cardiac noise correction had an effective role in increasing the active voxels (Mean±SD = 23.46±9.46) compared to other noise correction methods. Cardiac effects were higher than other physiological noise sources.

Conclusion: In summary, our results indicate great respiration effects on the lumbar and thoracolumbar spinal cord fMRI, and its contribution to the heartbeat effect can be a significant variable in the individual fMRI data analysis. Displacement of the spinal cord and the effects of this noise in the thoracolumbar and lumbar spinal cord fMRI results are significant and cannot be ignored.

Keywords: Functional Magnetic Resonance Imaging (fMRI); General linear model; Imaging; Physiological noise; Spinal cord.

Figure 1.

Example of our GRE-EPI images A: Coronal; and B: Sagittal views of the spine, with the yellow box illustrating the field of view of imaging; part c of the image shows the axial view of three sample slices GRE-EPI: Gradient Recall Echo-Echo Planar Imaging.

Figure 2.

Sample cardiac and respiration physiological records A: A sample record of cardiac; and B: respiration pulsations, along with their three harmonics

Figure 3.

The influence of correction steps on the number of active voxels The graphs show how the type of correction step influences the number of active voxels in the spinal cord areas

Figure 4.

The influence of correction steps on the number of active voxels The graphs show how the type of correction step influences the number of active voxels in the CSF areas

Figure 5.

The Receiver Operating Characteristic (ROC) curves for different noise correction methods in CSF areas Plots are the mean ROC curves of the 15^th thoracolumbar spinal cord fMRI data-sets in the CSF areas. For respiration noise correction, the area under the ROC curve (AUC) is 0.864, and for the cardiac noise correction it is 0.751, showing the superiority of the respiration noise correction method

Figure 6.

The Receiver Operating Characteristic (ROC) curves for different noise correction methods in spinal cord areas Plots are the mean ROC curves of the 15^th thoracolumbar spinal cord fMRI data-sets in the spinal cord areas. For respiration noise correction, the area under the ROC curve (AUC) is 0.936, and for the cardiac noise correction, it is 0.856, showing the superiority of the respiration noise correction method.

Figure 7.

The influence of noise correction methods on the activation maps A–D: The activation maps with no noise correction; E–H: The activations map after cardiac and respiration noise correction; This figure illustrates that physiological noise correction decreases the active voxels in the CSF (false positives) and increases active voxels in the spinal cord.