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The influence of radio-frequency transmit field inhomogeneities on the accuracy of g-ratio weighted imaging

MPG-Autoren
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Freund,  Patrick
Balgrist Spinal Cord Injury Center, Balgrist University Hospital, Zurich, Switzerland;
Department Neurophysics (Weiskopf), MPI for Human Cognitive and Brain Sciences, Max Planck Society;
Wellcome Trust Centre for Neuroimaging, Institute of Neurology, University College London, United Kingdom;

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Mohammadi,  Siawoosh
Department of Systems Neuroscience, University Medical Center Hamburg-Eppendorf, Germany;
Department Neurophysics (Weiskopf), MPI for Human Cognitive and Brain Sciences, Max Planck Society;

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Emmenegger_2021.pdf
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Zitation

Emmenegger, T. M., David, G., Ashtarayeh, M., Fritz, F. J., Ellerbrock, I., Helms, G., et al. (2021). The influence of radio-frequency transmit field inhomogeneities on the accuracy of g-ratio weighted imaging. Frontiers in Neuroscience, 15: 674719. doi:10.3389/fnins.2021.674719.


Zitierlink: https://hdl.handle.net/21.11116/0000-0009-24A2-7
Zusammenfassung
G-ratio weighted imaging is a non-invasive, in-vivo MRI-based technique that aims at estimating an aggregated measure of relative myelination of axons across the entire brain white matter. The MR g-ratio and its constituents (axonal and myelin volume fraction) are more specific to the tissue microstructure than conventional MRI metrics targeting either the myelin or axonal compartment. To calculate the MR g-ratio, an MRI-based myelin-mapping technique is combined with an axon-sensitive MR technique (such as diffusion MRI). Correction for radio-frequency transmit (B1+) field inhomogeneities is crucial for myelin mapping techniques such as magnetization transfer saturation. Here we assessed the effect of B1+ correction on g-ratio weighted imaging. To this end, the B1+ field was measured and the B1+ corrected MR g-ratio was used as the reference in a Bland-Altman analysis. We found a substantial bias (≈-89%) and error (≈37%) relative to the dynamic range of g-ratio values in the white matter if the B1+ correction was not applied. Moreover, we tested the efficiency of a data-driven B1+ correction approach that was applied retrospectively without additional reference measurements. We found that it reduced the bias and error in the MR g-ratio by a factor of three. The data-driven correction is readily available in the open-source hMRI toolbox (www.hmri.info) which is embedded in the statistical parameter mapping (SPM) framework.