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  Automated slice-specific z-shimming for functional magnetic resonance imaging of the human spinal cord

Kaptan, M., Vannesjo, S. J., Mildner, T., Horn, U., Hartley-Davies, R., Oliva, V., et al. (2022). Automated slice-specific z-shimming for functional magnetic resonance imaging of the human spinal cord. Human Brain Mapping. doi:10.1002/hbm.26018.

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Kaptan, Merve1, Author           
Vannesjo, S Johanna2, Author
Mildner, Toralf3, Author           
Horn, Ulrike1, Author                 
Hartley-Davies, Ronald4, Author
Oliva, Valeria5, Author
Brooks, Jonathan C. W.6, Author
Weiskopf, Nikolaus7, 8, Author           
Finsterbusch, Jürgen9, Author
Eippert, Falk1, Author           
1Max Planck Research Group Pain Perception, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_2497695              
2Department of Physics, Norwegian University of Science and Technology, Trondheim, Norway, ou_persistent22              
3Methods and Development Unit Nuclear Magnetic Resonance, MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_634558              
4Department of Medical Physics, University Hospitals Bristol and Weston, United Kingdom, ou_persistent22              
5School of Physiology, Pharmacology and Neuroscience, University of Bristol, United Kingdom, ou_persistent22              
6School of Psychology, University of East Anglia Wellcome Wolfson Brain Imaging Centre (UWWBIC), University of East Anglia, Norwich, United Kingdom, ou_persistent22              
7Department Neurophysics (Weiskopf), MPI for Human Cognitive and Brain Sciences, Max Planck Society, ou_2205649              
8Felix Bloch Institute for Solid State Physics, University of Leipzig, Germany, ou_persistent22              
9Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Germany, ou_persistent22              


Free keywords: Automated z-shim; Functional magnetic resonance imaging; Magnetic field inhomogeneities; Signal loss; Spinal cord; Temporal signal-to-noise ratio
 Abstract: Functional magnetic resonance imaging (fMRI) of the human spinal cord faces many challenges, such as signal loss due to local magnetic field inhomogeneities. This issue can be addressed with slice-specific z-shimming, which compensates for the dephasing effect of the inhomogeneities using a slice-specific gradient pulse. Here, we aim to address outstanding issues regarding this technique by evaluating its effects on several aspects that are directly relevant for spinal fMRI and by developing two automated procedures in order to improve upon the time-consuming and subjective nature of manual selection of z-shims: one procedure finds the z-shim that maximizes signal intensity in each slice of an EPI reference-scan and the other finds the through-slice field inhomogeneity for each EPI-slice in field map data and calculates the required compensation gradient moment. We demonstrate that the beneficial effects of z-shimming are apparent across different echo times, hold true for both the dorsal and ventral horn, and are also apparent in the temporal signal-to-noise ratio (tSNR) of EPI time-series data. Both of our automated approaches were faster than the manual approach, lead to significant improvements in gray matter tSNR compared to no z-shimming and resulted in beneficial effects that were stable across time. While the field-map-based approach performed slightly worse than the manual approach, the EPI-based approach performed as well as the manual one and was furthermore validated on an external corticospinal data-set (N > 100). Together, automated z-shimming may improve the data quality of future spinal fMRI studies and lead to increased reproducibility in longitudinal studies.


Language(s): eng - English
 Dates: 2022-06-212022-04-252022-06-242022-08-08
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1002/hbm.26018
Other: online ahead of print
PMID: 35938527
 Degree: -



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Project name : -
Grant ID : 01EW1711A & B
Funding program : -
Funding organization : Bundesministerium für Bildung und Forschung
Project name : -
Grant ID : 616905
Funding program : -
Funding organization : European Research Council
Project name : -
Grant ID : 681094, 758974
Funding program : Horizon 2020
Funding organization : European Research Council
Project name : -
Grant ID : MR/N026969/1
Funding program : -
Funding organization : Medical Research Council
Project name : -
Grant ID : 203963/Z/16/Z
Funding program : -
Funding organization : Wellcome Trust

Source 1

Title: Human Brain Mapping
Source Genre: Journal
Publ. Info: -
Pages: - Volume / Issue: - Sequence Number: - Start / End Page: - Identifier: ISSN: 1065-9471
CoNE: https://pure.mpg.de/cone/journals/resource/954925601686