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

Journal article

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 information. The FSL-MRS toolbox includes tools for preprocessing 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 optimization 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 data sets (257 single-voxel spectroscopy and 8 MRSI data sets) at 3 T and 7 T. Interactive HTML reports are automatically generated 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.

Authors: Clarke, WT; Stagg, CJ; Jbabdi, S

• Publication status: Published
• Peer review status: Peer reviewed
• Publisher: Wiley
• Journal: Magnetic Resonance in Medicine
• Volume: 85
• Issue: 6
• Pages: 2950-2964
• Publication date: 2020-12-06
• Acceptance date: 2020-11-11
• DOI: 10.1002/mrm.28630
• EISSN: 1522-2594
• ISSN: 0740-3194
• Pmid: 33280161
• Language: English
• Keywords: computer simulation; humans; 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: [email protected] 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,; phantoms, imaging; software; MRS; Bayesian fitting; neuroimaging; MRSI; magnetic resonance spectroscopy; open-source; FFR