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"Subject-specific optimization of background suppression for arterial spin labeling MRI using a real-time feedback loop on the scanner"
Kirsten Koolstra, Marius Staring, Paul de Bruin and Matthias J.P. van Osch
Abstract
Background suppression (BGS) in arterial spin labeling (ASL) leads to perfusion images with a higher temporal signal-to-noise ratio (tSNR) compared to ASL without BGS. The optimal inversion times (TIs), and therefore the quality of the BGS, depend on the T1 relaxation times of the underlying tissue and on inhomogeneities of the scanner's magnetic fields (B0, B1+). In this work, we designed and implemented a feedback mechanism that optimized the quality of background suppression in real time on the scanner. The results show an increased tSNR for the subject-specific optimization of BGS compared to standard BGS in 12 healthy volunteers.
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Copyright © 2022 by the authors.
Published version © 2022 by .
Personal use of this material is permitted. However, permission to reprint or republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works, must be obtained from the copyright holder.
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BibTeX entry
| @inproceedings{Koolstra:2022, |
| author |
= {Koolstra, Kirsten and Staring, Marius and de Bruin, Paul and van Osch, Matthias J.P.}, |
| title |
= {Subject-specific optimization of background suppression for arterial spin labeling MRI using a real-time feedback loop on the scanner}, |
| booktitle |
= {International Society for Magnetic Resonance in Medicine}, |
| address |
= {London, UK}, |
| month |
= {May}, |
| year |
= {2022}, |
| } |
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| last modified: 23-08-2023 |
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