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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 MRS analysis toolbox. It provides spectroscopic data conversion, preprocessing, spectral simulation, fitting, quantitation, and visualization.
Methods
The FSL-MRS package is modular. Its programs operate on data in a standard format (Neuroimaging Informatics Technology Initiative [NIfTI]) capable of storing single-voxel and multivoxel spectroscopy, including spatial orientation... Expand abstract
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1002/mrm.28630

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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
Sub department:
Clinical Neurosciences
Oxford college:
Linacre College
Role:
Author
ORCID:
0000-0003-3234-5639
Medical Research Council More from this funder
Publisher:
Wiley Publisher's website
Journal:
Magnetic Resonance in Medicine Journal website
Volume:
85
Issue:
6
Pages:
2950-2964
Publication date:
2020-12-06
Acceptance date:
2020-11-11
DOI:
EISSN:
1522-2594
ISSN:
0740-3194
Pmid:
33280161
Language:
English
Keywords:
2950 | Magn Reson Med. 2021;85:2950–2964.wileyonlinelibrary.com/journal/mrmReceived: 19 June 2020 | Revised: 11 October 2020 | Accepted: 11 November 2020DOI: 10.1002/mrm.28630 FULL PAPERFSL-MRS: An end-to-end spectroscopy analysis packageWilliam T.Clarke1,2 | Charlotte J.Stagg1,2 | SaadJbabdi11Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom2MRC Brain Network Dynamics Unit, University of Oxford, Oxford, United KingdomThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.© 2020 The Authors. Magnetic Resonance in Medicine published by Wiley Periodicals LLC on behalf of International Society for Magnetic Resonance in MedicineCorrespondenceWilliam T. Clarke, Wellcome Centre for Integrative Neuroimaging, FMRIB, University of Oxford, Level 0, John Radcliffe Hospital, Oxford, OX3 9DU, United Kingdom.Email: william.clarke@ndcn.ox.ac.ukFunding informationWellcome Trust Collaborative Award (215573/Z/19/Z); Wellcome Trust and the Royal Society (102584/Z/13/Z and 203139/Z/16/Z); Medical Research Council (MR/K022202/1, G1001354, and MR/K014382/1); EU Horizon 2020 (732592); HDH Wills 1965 Charitable Trust (1117747); and National Institute for Health Research (CA-CDRF-2016-02-002)Purpose: We introduce FSL-MRS, an end-to-end, modular, open-source MRS anal-ysis toolbox. It provides spectroscopic data conversion, preprocessing, spectral simu-lation, fitting, quantitation, and visualization.Methods: The FSL-MRS package is modular. Its programs operate on data in a standard format (Neuroimaging Informatics Technology Initiative [NIfTI]) capable of storing single-voxel and multivoxel spectroscopy, including spatial orientation information. The FSL-MRS toolbox includes tools for preprocessing of raw spec-troscopy data, including coil combination, frequency and phase alignment, and filter-ing. 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 optimiza-tion for the estimation of the full posterior distribution of metabolite concentrations. Validation of the fitting is carried out on independently created simulated data, phan-tom data, and three in vivo human data sets (257 single-voxel spectroscopy and 8 MRSI data sets) at 3 T and 7 T. Interactive HTML reports are automatically gener-ated by processing and fitting stages of the toolbox. The FSL-MRS package 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 of 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 data sets.Conclusion: The FSL-MRS toolbox 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 multivoxel spectroscopy. It is available as part of the FMRIB Software Library.KEYWORDSBayesian fitting, MRS, MRSI, open-source,
Pubs id:
1148355
Local pid:
pubs:1148355
Deposit date:
2021-10-06

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