Evidence map›Paper›PMID 33280161›Full record

ArticleMagnetic resonance in medicine2021

FSL-MRS: An end-to-end spectroscopy analysis package.

William T Clarke, Charlotte J Stagg, Saad Jbabdi

Abstract read
In one paragraph

Article in Magnetic resonance in medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

58 citing papers in PubMed.

  1. Article
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  6. A Digital Phantom for MR Spectroscopy Data Simulation.Magnetic resonance in medicine · 2026
    Article
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  15. Review
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  20. Simultaneous Concentration and TNMR in biomedicine · 2025
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

William T ClarkeWellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.ORCID 0000-0001-7159-7025
Charlotte J StaggWellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.ORCID 0000-0002-5542-5036
Saad JbabdiWellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom.ORCID 0000-0003-3234-5639

Funding

Department of Health CA-CDRF-2016-02-002Medical Research Council G1001354Medical Research Council MR/K014382/1Medical Research Council MR/K022202/1Medical Research Council MR/L009013/1Wellcome Trust 102584Wellcome Trust 203139Wellcome Trust 215573
6 · The paper itself

Abstract

purposeWe 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.

methodsThe 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.

resultsValidation 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.

conclusionThe 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.

Indexed as

NeuroimagingSoftwareComputer SimulationHumansMagnetic Resonance SpectroscopyPhantoms, ImagingBayesian fittingMRSMRSIopen-sourcespectroscopy

Identifiers

PMID33280161
PMCPMC7116822

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.