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Journal article

FSL-MRS: an end-to-end spectroscopy analysis package

Abstract:

Purpose: We introduce FSL-MRS, an end-to-end, modular, open-source magnetic resonance spectroscopy analysis toolbox. FSL-MRS provides spectroscopic data conversion, pre-processing, spectral simulation, fitting, quantitation and visualisation.

Methods: FSL-MRS is modular. FSL-MRS programs operate on data in a standard format (NIfTI) capable of storing single voxel and multi-voxel spectroscopy, including spatial orientation information. FSL-MRS includes tools for pre-processing of raw spectroscopy data, including coil-combination, frequency and phase alignment, and filtering. A density matrix simulation program is supplied for generation of basis spectra from simple text-based descriptions of pulse sequences. Fitting is based on linear combination of basis spectra and implements Markov chain Monte Carlo optimisation for the estimation of the full posterior distribution of metabolite concentrations. Validation of the fitting is carried out on independently created simulated data, phantom data, and three in vivo human datasets (257 SVS and 8 MRSI datasets) at 3T and 7T. Interactive HTML reports are automatically generated by processing and fitting stages of the toolbox. FSL-MRS can be used on the command line or interactively in the Python language.

Results: Validation of the fitting shows low error in simulation (median error 11.9%) and in phantom (3.4%). Average correlation between a third-party toolbox (LCModel) and FSL-MRS was high (0.53-0.81) in all three in vivo datasets.

Conclusion: FSL-MRS is designed to be flexible and extensible to new forms of spectroscopic acquisitions. Custom fitting models can be specified within the framework for dynamic or multi-voxel spectroscopy. FSL-MRS is available as part of the FMRIB Software Library.

Publication status:
Published
Peer review status:
Peer reviewed

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Files:
Publisher copy:
10.1002/mrm.28630

Authors


More by this author
Institution:
University of Oxford
Division:
MSD
Sub department:
Clinical Neurosciences
Role:
Author
ORCID:
0000-0001-7159-7025
More by this author
Institution:
University of Oxford
Division:
MSD
Sub department:
Clinical Neurosciences
Role:
Author
ORCID:
0000-0002-5542-5036
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Clinical Neurosciences
Role:
Author


Publisher:
Wiley
Journal:
Magnetic Resonance in Medicine More from this journal
Volume:
85
Issue:
6
Pages:
2950-2964
Publication date:
2020-12-06
Acceptance date:
2020-11-11
DOI:
EISSN:
1522-2594
ISSN:
0740-3194


Language:
English
Keywords:
Pubs id:
1115959
Local pid:
pubs:1115959
Deposit date:
2020-11-16

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