Abstract
PURPOSE: Advanced MRS protocols improve data quality and reproducibility relative to vendor-provided protocols; however, they are challenging to incorporate into the clinical workflow and require local MRS expertise for successful implementation. Here, we developed an automated advanced MRS acquisition protocol at 3T to facilitate acquisition of high-quality spectroscopic data without local MRS expertise.
METHODS: First, a B 0 shimming protocol was selected for automation by comparing 3 widely used B 0 algorithms (2 vendor protocols and FAST(EST)MAP). Next, voxel-based B 0 and B 1 calibrations were incorporated into the consensus-recommended semi-LASER sequence and combined with an automated VOI prescription tool, a recently developed method for automated voxel prescription. The efficiency of collecting single-voxel data from a clinical cohort (N = 40) with the automated protocol (calibration time and fraction of usable datasets) was compared with the nonautomated semi-LASER protocol (N = 35) whereby all prescan calibrations were executed manually in the academic hospital setting with rotating MR technologists in the neuroradiology unit.
RESULTS: A multi-iteration FAST(EST)MAP protocol resulted in narrower water linewidths than vendor's B 0 shim protocols for data acquired from 6 brain locations (p < 1e-5) and was selected for automation. The automated B 0 and B 1 calibrations resulted in a time saving of ~4.5 minutes per voxel relative to the same advanced protocol executed manually. All spectra acquired with the automated protocol were usable, whereas only 86% of those collected with the manual protocol were usable and spectral quality was more variable.
CONCLUSION: The plug-and-play advanced MRS protocol allows automated acquisition of high-quality MRS data with high success rate and consistency on a clinical 3T platform.
Original language | English (US) |
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Pages (from-to) | 2613-2620 |
Number of pages | 8 |
Journal | Magnetic resonance in medicine |
Volume | 87 |
Issue number | 6 |
DOIs | |
State | Published - Jun 2022 |
Bibliographical note
Funding Information:Supported by funding from the National Institutes of Health (NIH) grants R01 NS080816, R01 EB030000, P41 EB027061, and P30 NS076408
Publisher Copyright:
© 2022 International Society for Magnetic Resonance in Medicine.
Keywords
- 3T
- FAST(EST)MAP
- automation
- brain
- semi-LASER
Center for Magnetic Resonance Research (CMRR) tags
- SMCT
- P41
PubMed: MeSH publication types
- Journal Article
- Research Support, N.I.H., Extramural