Purpose: The spinal cord contains sensorimotor neural circuits of scientific and clinical interest. However, spinal cord functional MRI (fMRI) is significantly more technically demanding than brain fMRI, due primarily to its proximity to the lungs. Accelerated echo-planar imaging (EPI) at 7 T is particularly vulnerable to k-space phase inconsistencies induced by motion or B0 fluctuation, during either autocalibration signal (ACS) or time-series acquisition. For 7 T brain fMRI, sensitivity to motion and B0 fluctuation can be reduced using a re-ordered segmented EPI ACS based on the fast low-angle excitation echo-planar technique (FLEET). However, respiration-induced B0 fluctuations (exceeding 100 Hz at C7) are greater, and fewer k-space lines per slice are required for cervical spinal cord fMRI at 7 T, necessitating a separate evaluation of ACS methods. Methods: We compared 24-line single-shot EPI with 48-line two-shot segmented EPI, two-shot FLEET, and gradient echo (GRE)–based ACS acquisition methods, performed under various physiological conditions, in terms of temporal signal-to-noise ratio and prevalence of artifacts in generalized autocalibrating partially parallel acquisition (GRAPPA)-accelerated EPI of the cervical spinal cord at 7 T. Results: Segmented EPI and FLEET ACS produce images with nearly identical patterns of severe image artifacts. GRE and single-shot EPI ACS consistently produce images free from significant artifacts, and temporal signal-to-noise ratio is significantly greater for GRE ACS, particularly in lower slices where through-slice dephasing is most severe. Conclusions: GRE and single-shot EPI-ACS acquisition methods, which are robust to respiration-induced phase errors between k-space segments, produce images with fewer and less severe artifacts than either FLEET or conventionally segmented EPI for accelerated EPI of the cervical spinal cord at 7 T.

Original languageEnglish
Pages (from-to)2583-2591
Number of pages9
JournalMagnetic Resonance in Medicine
Issue number6
StatePublished - Dec 2022


  • autocalibration signal
  • functional MRI
  • spinal cord
  • temporal SNR
  • ultrahigh-field MRI


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