Automated slice-specific z-shimming for functional magnetic resonance imaging of the human spinal cord
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Automated slice-specific z-shimming for functional magnetic resonance imaging of the human spinal cord. / Kaptan, Merve; Vannesjo, S Johanna; Mildner, Toralf; Horn, Ulrike; Hartley-Davies, Ronald; Oliva, Valeria; Brooks, Jonathan C W; Weiskopf, Nikolaus; Finsterbusch, Jürgen; Eippert, Falk.
In: HUM BRAIN MAPP, Vol. 43, No. 18, 15.12.2022, p. 5389-5407.Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review
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TY - JOUR
T1 - Automated slice-specific z-shimming for functional magnetic resonance imaging of the human spinal cord
AU - Kaptan, Merve
AU - Vannesjo, S Johanna
AU - Mildner, Toralf
AU - Horn, Ulrike
AU - Hartley-Davies, Ronald
AU - Oliva, Valeria
AU - Brooks, Jonathan C W
AU - Weiskopf, Nikolaus
AU - Finsterbusch, Jürgen
AU - Eippert, Falk
N1 - © 2022 The Authors. Human Brain Mapping published by Wiley Periodicals LLC.
PY - 2022/12/15
Y1 - 2022/12/15
N2 - 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.
AB - 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.
KW - Humans
KW - Echo-Planar Imaging/methods
KW - Artifacts
KW - Image Processing, Computer-Assisted/methods
KW - Reproducibility of Results
KW - Magnetic Resonance Imaging/methods
KW - Spinal Cord/diagnostic imaging
KW - Brain/diagnostic imaging
U2 - 10.1002/hbm.26018
DO - 10.1002/hbm.26018
M3 - SCORING: Journal article
C2 - 35938527
VL - 43
SP - 5389
EP - 5407
JO - HUM BRAIN MAPP
JF - HUM BRAIN MAPP
SN - 1065-9471
IS - 18
ER -