An integrated RF-receive/B0-shim array coil boosts performance of whole-brain MR spectroscopic imaging at 7 T
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s41598-020-71623-5.pdf
Description
Published version
Size
12.86 MB
Format
Adobe PDF
Checksum (MD5)
022e5b35c639525e68fda32d0f5cf686
Author(s)
Esmaeili, Morteza
Stockmann, Jason
Strasser, Bernhard
Arango, Nicolas
Thapa, Bijaya
Wang, Zhe
van der Kouwe, Andre
Dietrich, Jorg
Cahill, Daniel P
Batchelor, Tracy T
Date Issued
2020
Journal
Scientific Reports
Publisher
Springer Science and Business Media LLC
Version
Final published version
Abstract
© 2020, The Author(s). Metabolic imaging of the human brain by in-vivo magnetic resonance spectroscopic imaging (MRSI) can non-invasively probe neurochemistry in healthy and disease conditions. MRSI at ultra-high field (≥ 7 T) provides increased sensitivity for fast high-resolution metabolic imaging, but comes with technical challenges due to non-uniform B0 field. Here, we show that an integrated RF-receive/B0-shim (AC/DC) array coil can be used to mitigate 7 T B0 inhomogeneity, which improves spectral quality and metabolite quantification over a whole-brain slab. Our results from simulations, phantoms, healthy and brain tumor human subjects indicate improvements of global B0 homogeneity by 55%, narrower spectral linewidth by 29%, higher signal-to-noise ratio by 31%, more precise metabolite quantification by 22%, and an increase by 21% of the brain volume that can be reliably analyzed. AC/DC shimming provide the highest correlation (R2 = 0.98, P = 0.001) with ground-truth values for metabolite concentration. Clinical translation of AC/DC and MRSI is demonstrated in a patient with mutant-IDH1 glioma where it enables imaging of D-2-hydroxyglutarate oncometabolite with a 2.8-fold increase in contrast-to-noise ratio at higher resolution and more brain coverage compared to previous 7 T studies. Hence, AC/DC technology may help ultra-high field MRSI become more feasible to take advantage of higher signal/contrast-to-noise in clinical applications.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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Creative Commons Attribution 4.0 International license
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DOI of Published Version
https://doi.org/10.1038/s41598-020-71623-5
