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. 2017 Sep 22;12(9):e0185356.
doi: 10.1371/journal.pone.0185356. eCollection 2017.

OXSA: An open-source magnetic resonance spectroscopy analysis toolbox in MATLAB

Lucian A B Purvis  1 , William T Clarke  1 , Luca Biasiolli  1 , Ladislav Valkovič  1   2 , Matthew D Robson  1 , Christopher T Rodgers  1
Affiliations

OXSA: An open-source magnetic resonance spectroscopy analysis toolbox in MATLAB

Lucian A B Purvis et al. PLoS One. .

Abstract

In vivo magnetic resonance spectroscopy provides insight into metabolism in the human body. New acquisition protocols are often proposed to improve the quality or efficiency of data collection. Processing pipelines must also be developed to use these data optimally. Current fitting software is either targeted at general spectroscopy fitting, or for specific protocols. We therefore introduce the MATLAB-based OXford Spectroscopy Analysis (OXSA) toolbox to allow researchers to rapidly develop their own customised processing pipelines. The toolbox aims to simplify development by: being easy to install and use; seamlessly importing Siemens Digital Imaging and Communications in Medicine (DICOM) standard data; allowing visualisation of spectroscopy data; offering a robust fitting routine; flexibly specifying prior knowledge when fitting; and allowing batch processing of spectra. This article demonstrates how each of these criteria have been fulfilled, and gives technical details about the implementation in MATLAB. The code is freely available to download from https://github.com/oxsatoolbox/oxsa.

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Conflict of interest statement

Competing Interests: The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. The OXSA Siemens DICOM loading GUI.
A Spectro.FileOpenGui object showing a Spectro.dicomUiTree (left) together with a DICOM image preview (right). The contrast can be adjusted in the top right, and individual pixels can be examined using the data cursor.
Fig 2
Fig 2. Spectroscopy visualisation tool.
The red lines mark the nominal voxel size. The selected voxel is highlighted in red. Saturation bands are highlighted in yellow. The sliders on the right hand side can be used to select CSI slice or voxel. The buttons can be used to run various functions to e.g. fit or inspect the data from a single voxel.
Fig 3
Fig 3. OXSA fitting flow diagram.
Flow diagram of the functions used for fitting spectroscopy data that has been loaded into MATLAB.
Fig 4
Fig 4. amaresPlot output.
The default output figure from amaresPlot showing the fit of the example cardiac 31P data. Individual peaks are truncated in the frequency domain to 2.5× the full width at half maximum for display purposes only, i.e. to allow easier identification of peaks in cases where one peak has a much smaller amplitude than the others.
See this image and copyright information in PMC

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