FSL‐MRS: An end‐to‐end spectroscopy analysis package
William T. Clarke, Charlotte J. Stagg, Saad Jbabdi
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 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.