Background: Functional Magnetic Resonance Imaging (fMRI) is based on the Blood Oxygenation Level Dependent contrast and has been exploited f
Background: Functional Magnetic Resonance Imaging (fMRI) is based on the Blood Oxygenation Level Dependent contrast and has been exploited for the indirect study of the neuronal activity within both the brain and the spinal cord. However, the interpretation of spinal cord fMRI (scfMRI) is still controversial and its adoption is rather restricted because of technical limitations. Overcoming these limitations would have a beneficial effect for the assessment and follow-up of spinal injuries and neurodegenerative diseases. Purpose: This study was aimed at systematically verifying whether sagittal scanning in scfMRI using EPI readout is a viable alternative to the more common axial scanning, and at optimizing a pipeline for EPI-based scfMRI data analysis, based on Spinal Cord Toolbox (SCT). Methods: Forty-five healthy subjects underwent MRI acquisition in a Philips Achieva 3T MRI scanner. T2*-weighted fMRI data were acquired using a GE-EPI sequence along sagittal and axial planes during an isometric motor task. Differences on benchmarks were assessed via paired two-sample t-test at p < 0.05. Results: We investigated the impact of the acquisition strategy by means of various metrics such as Temporal Signal to Noise Ratio (tSNR), Dice Coefficient to assess geometric distortions, Reproducibility and BOLD signal sensitivity to the stimulus. tSNR was higher in axial than in sagittal scans, as well as reproducibility within the whole cord mask (t = 7.4, p < 0.01) and within the GM mask (t = 4.2, p < 0.01). The other benchmarks, associated with distortion and functional response, showed no difference between images obtained along the axial and sagittal planes. Conclusions: Quantitative metrics of data quality suggest that axial scanning would be the optimal choice. We conclude that axial acquisition is advantageous specially to mitigate the effects of physiological noise and to minimize inter-subject variance. [ABSTRACT FROM AUTHOR]
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