Optimizing Study Designs for Cervical Spinal Cord fMRI During a Hand Motor Task
Poster No:
1056
Submission Type:
Abstract Submission
Authors:
Kiomars Sharifi1, Simon Schading-Sassenhausen1, Christian Kündig1, Jürgen Finsterbusch2, Patrick Freund1,3,4, Gergely David1
Institutions:
1Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich, Zurich, Switzerland, 2Institute of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Hamburg, Germany, 3Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany, 4Wellcome Trust Centre for Human Neuroimaging, Queen Square Institute of Neurology, University College London, London, United Kingdom
First Author:
Kiomars Sharifi
Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich
Zurich, Switzerland
Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich
Zurich, Switzerland
Co-Author(s):
Simon Schading-Sassenhausen
Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich
Zurich, Switzerland
Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich
Zurich, Switzerland
Christian Kündig
Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich
Zurich, Switzerland
Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich
Zurich, Switzerland
Jürgen Finsterbusch
Institute of Systems Neuroscience, University Medical Center Hamburg-Eppendorf
Hamburg, Germany
Institute of Systems Neuroscience, University Medical Center Hamburg-Eppendorf
Hamburg, Germany
Patrick Freund
Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich|Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences|Wellcome Trust Centre for Human Neuroimaging, Queen Square Institute of Neurology, University College London
Zurich, Switzerland|Leipzig, Germany|London, United Kingdom
Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich|Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences|Wellcome Trust Centre for Human Neuroimaging, Queen Square Institute of Neurology, University College London
Zurich, Switzerland|Leipzig, Germany|London, United Kingdom
Gergely David
Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich
Zurich, Switzerland
Spinal Cord Injury Center, Balgrist University Hospital, University of Zurich
Zurich, Switzerland
Introduction:
Blood-oxygen-level-dependent (BOLD) functional MRI (fMRI) has been increasingly used to study spinal cord sensorimotor functions (Kinany et al., 2023; Kündig et al., 2024; Landelle et al., 2021). Spinal cord fMRI can be conducted independently or simultaneously with brain fMRI, i.e., in a cortico-spinal protocol (Finsterbusch et al., 2012). While studies have detected motor- or sensory-related activity (Kinany et al., 2023; Landelle et al., 2021), considerable variability in study design-such as scan duration, number of runs, and sample size-complicates efforts to achieve consistent and comparable findings across studies. This study systematically examines the impact of scan duration, number of runs, and sample size on BOLD signal detectability in the cervical spinal cord during a hand motor task.
Methods:
MRI data were collected from 11 healthy participants (6 males, 5 females, age: 27.5 ± 4.8 years) using a 3T Siemens Prisma scanner. Four 10-min task runs were conducted, with a 13-min anatomical scan between the 2nd and 3rd runs. During task runs, participants squeezed a ball with their right hand following a block design with alternating 15-second motor activity and rest periods.
A cortico-spinal gradient-echo echo planar imaging protocol was used, with two field of views (FOV) covering the brain and lower cervical cord, optimized individually for frequency and shim settings (Finsterbusch et al., 2012). For this study, only the cervical FOV was analyzed. Spinal cord imaging parameters included: resolution=1×1×5 mm³, FOV=128×128×60 mm³, TR=2600 ms, TE=30 ms, flip angle=87°, and parallel imaging (GRAPPA 2x). The lower cervical cord structural scan parameters were: resolution=0.5×0.5×5 mm³, FOV=192×192×60 mm³, TR=586 ms, TEs (6.86, 10.86, 14.86, and 18.86 ms), flip angle=30°, and 4 repetitions.
fMRI data were motion-corrected with MCFLIRT and sct_fmri_moco (De Leener et al., 2017), segmented using sct_deepseg (Bédard et al., 2023), smoothed (1×1×5 mm³), and analyzed voxel-wise with a general linear model (FSL FEAT, Jenkinson et al., 2012). Nuisance regressors included slice-wise motion parameters, motion outliers, and five principal components from cerebrospinal fluid using the PhysIO toolbox (Kasper et al., 2017). Contrast of parameter estimates (COPE) maps for task vs. rest were generated in native space, and normalized to the PAM50 template (De Leener et al., 2018). Group analyses used permutation testing with FSL randomize, applying threshold-free cluster enhancement and family-wise error correction (pFWE<0.05). Statistical maps were computed for various combinations of run durations, number of runs, and sample sizes. For each combination, the mean t-value was computed within the right ventral and intermediate GM horn across C7-T1.
A cortico-spinal gradient-echo echo planar imaging protocol was used, with two field of views (FOV) covering the brain and lower cervical cord, optimized individually for frequency and shim settings (Finsterbusch et al., 2012). For this study, only the cervical FOV was analyzed. Spinal cord imaging parameters included: resolution=1×1×5 mm³, FOV=128×128×60 mm³, TR=2600 ms, TE=30 ms, flip angle=87°, and parallel imaging (GRAPPA 2x). The lower cervical cord structural scan parameters were: resolution=0.5×0.5×5 mm³, FOV=192×192×60 mm³, TR=586 ms, TEs (6.86, 10.86, 14.86, and 18.86 ms), flip angle=30°, and 4 repetitions.
fMRI data were motion-corrected with MCFLIRT and sct_fmri_moco (De Leener et al., 2017), segmented using sct_deepseg (Bédard et al., 2023), smoothed (1×1×5 mm³), and analyzed voxel-wise with a general linear model (FSL FEAT, Jenkinson et al., 2012). Nuisance regressors included slice-wise motion parameters, motion outliers, and five principal components from cerebrospinal fluid using the PhysIO toolbox (Kasper et al., 2017). Contrast of parameter estimates (COPE) maps for task vs. rest were generated in native space, and normalized to the PAM50 template (De Leener et al., 2018). Group analyses used permutation testing with FSL randomize, applying threshold-free cluster enhancement and family-wise error correction (pFWE<0.05). Statistical maps were computed for various combinations of run durations, number of runs, and sample sizes. For each combination, the mean t-value was computed within the right ventral and intermediate GM horn across C7-T1.
Results:
Significant task-related BOLD signal changes were observed in and around the ipsilateral (right) ventral and intermediate gray matter horn, across neurological levels C7 to T1 (Fig. 1). A comparison of group-level statistical maps showed an initial increase in t-value with longer duration, plateauing or slightly decreasing after ~7 minutes of acquisition per run (Fig. 2A). Increasing the number of runs increased the mean t-value for every run duration (Fig. 2A). Nevertheless, independent analysis of each run revealed lower t-values for the third and fourth runs (Fig. 2B). Increasing the sample size led to an increase in mean t-value, which approached a plateau toward 11 subjects (Fig. 2C).
Conclusions:
Our investigation revealed that increasing run duration beyond 7 minutes does not improve detection power, likely due to participant fatigue during a hand motor task. Furthermore, while increasing the sample size increases the number of significant voxels detected, the rate of improvement decreases with each additional participant. These findings provide guidance for optimizing spinal cord fMRI study designs with motor tasks, highlighting the importance of balancing scan duration, number of runs, and sample size.
Modeling and Analysis Methods:
Activation (eg. BOLD task-fMRI) 1
Methods Development 2
Univariate Modeling
Motor Behavior:
Motor Planning and Execution
Novel Imaging Acquisition Methods:
BOLD fMRI
Keywords:
Acquisition
Data analysis
Design and Analysis
FUNCTIONAL MRI
Motor
MRI
NORMAL HUMAN
1|2Indicates the priority used for review
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Please indicate below if your study was a "resting state" or "task-activation” study.
Healthy subjects only or patients (note that patient studies may also involve healthy subjects):
Was this research conducted in the United States?
Were any human subjects research approved by the relevant Institutional Review Board or ethics panel? NOTE: Any human subjects studies without IRB approval will be automatically rejected.
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Provide references using APA citation style.
De Leener, B., Fonov, V. S., Collins, D. L., Callot, V., Stikov, N. & Cohen-Adad, J. (2018). PAM50: Unbiased multimodal template of the brainstem and spinal cord aligned with the ICBM152 space. NeuroImage, 165, 170–179. https://doi.org/10.1016/j.neuroimage.2017.10.041
De Leener, B., Lévy, S., Dupont, S. M., Fonov, V. S., Stikov, N., Collins, D. L., Callot, V. & Cohen-Adad, J. (2017). SCT: Spinal Cord Toolbox, an open-source software for processing spinal cord MRI data. NeuroImage, 145, 24–43. https://doi.org/10.1016/j.neuroimage.2016.10.009
Finsterbusch, J., Eippert, F. & Büchel, C. (2012). Single, slice-specific z-shim gradient pulses improve T2*-weighted imaging of the spinal cord. NeuroImage, 59(3), 2307–2315. https://doi.org/10.1016/j.neuroimage.2011.09.038
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Kündig, C. W., Finsterbusch, J., Freund, P. & David, G. (2024). Functional magnetic resonance imaging of the lumbosacral cord during a lower extremity motor task. Imaging Neuroscience, 2, 1–19. https://doi.org/10.1162/imag_a_00227
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