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<jats:title>Abstract</jats:title><jats:sec><jats:title>Purpose</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Methods</jats:title><jats:p>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.</jats:p><jats:p>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.</jats:p><jats:p>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.</jats:p><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Results</jats:title><jats:p>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.</jats:p></jats:sec><jats:sec><jats:title>Conclusion</jats:title><jats:p>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.</jats:p></jats:sec>

Original publication

DOI

10.1101/2020.06.16.155291

Type

Journal article

Publisher

Cold Spring Harbor Laboratory

Publication Date

18/06/2020