Abstract
Introduction: Functional MRI methods have been used to study sensorimotor processing in the Spinal cord. However, these techniques confront unwanted contributions to the measured signal from the physiological fluctuations. For 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 Thoraco-lumbar regions. In this study, we investigated the effect of each source of physiological noise and contribution of them to the outcome of the analysis of the BOLD signal in human Thoraco-lumbar spinal cord.
Method: Fifteen young healthy male volunteers participated in the study, and pain stimuli was delivered on 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 GLM for quantification of the effect of each of them on the task-analyses 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 were comprised with ANOVA statistical test and ROC analysis.
Result: The results illustrated that cardiac noise correction had an effective role on increasing the active voxels (mean = 23.46±9.46) compared to other noise correction methods. Cardiac effects were higher than other physiological noise sources.
Conclusion: In summary, our results illustrated great respiration effects on the lumbar and thoraco-lumbar spinal cord fMRI, and its contribution with 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 Thoraco-lumbar and lumbar spinal cord fMRI results are significant and cannot be ignored.
Method: Fifteen young healthy male volunteers participated in the study, and pain stimuli was delivered on 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 GLM for quantification of the effect of each of them on the task-analyses 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 were comprised with ANOVA statistical test and ROC analysis.
Result: The results illustrated that cardiac noise correction had an effective role on increasing the active voxels (mean = 23.46±9.46) compared to other noise correction methods. Cardiac effects were higher than other physiological noise sources.
Conclusion: In summary, our results illustrated great respiration effects on the lumbar and thoraco-lumbar spinal cord fMRI, and its contribution with 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 Thoraco-lumbar and lumbar spinal cord fMRI results are significant and cannot be ignored.
Original language | English |
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Pages (from-to) | 2-2 |
Journal | Basic and Clinical Neuroscience |
Volume | 11 |
Issue number | 6 |
DOIs | |
Publication status | Published - 20 Nov 2020 |
Keywords
- fMRI
- spinal cord
- physiological noise
- imaging
- general linear model