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

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.

[1]  Wolfgang Bogner,et al.  Dynamic 31P–MRSI using spiral spectroscopic imaging can map mitochondrial capacity in muscles of the human calf during plantar flexion exercise at 7 T , 2016, NMR in biomedicine.

[2]  S. Van Huffel,et al.  MRS signal quantitation: a review of time- and frequency-domain methods. , 2008, Journal of magnetic resonance.

[3]  Zenon Starčuk,et al.  Quantitation of magnetic resonance spectroscopy signals: the jMRUI software package , 2009 .

[4]  Matthew D. Robson,et al.  Phosphodiester content measured in human liver by in vivo 31P MR spectroscopy at 7 tesla , 2017, Magnetic resonance in medicine.

[5]  S. Provencher Automatic quantitation of localized in vivo 1H spectra with LCModel , 2001, NMR in biomedicine.

[6]  Theodoros N. Arvanitis,et al.  A constrained least‐squares approach to the automated quantitation of in vivo 1H magnetic resonance spectroscopy data , 2011, Magnetic resonance in medicine.

[7]  Stefan Neubauer,et al.  Human cardiac 31P magnetic resonance spectroscopy at 7 tesla , 2013, Magnetic resonance in medicine.

[8]  Matthew D Robson,et al.  Bloch‐Siegert B1+‐mapping for human cardiac 31P‐MRS at 7 Tesla , 2015, Magnetic resonance in medicine.

[9]  Thomas F. Coleman,et al.  An Interior Trust Region Approach for Nonlinear Minimization Subject to Bounds , 1993, SIAM J. Optim..

[10]  Rolf Gruetter,et al.  Which prior knowledge? Quantification of in vivo brain 13C MR spectra following 13C glucose infusion using AMARES , 2013, Magnetic resonance in medicine.

[11]  Peter Boesiger,et al.  ProFit: two‐dimensional prior‐knowledge fitting of J‐resolved spectra , 2006, NMR in biomedicine.

[12]  Ernest B. Cady,et al.  A reappraisal of the absolute concentrations of phosphorylated metabolites in the human neonatal cerebral cortex obtained by fitting Lorentzian curves to the 31P NMR spectrum , 1991 .

[13]  Wolfgang Bogner,et al.  One‐dimensional image‐selected in vivo spectroscopy localized phosphorus saturation transfer at 7T , 2014, Magnetic resonance in medicine.

[14]  Stefan Neubauer,et al.  Creatine kinase rate constant in the human heart measured with 3D‐localization at 7 tesla , 2016, Magnetic resonance in medicine.

[15]  Wolfgang Bogner,et al.  In vivo 31P magnetic resonance spectroscopy of the human liver at 7 T: an initial experience , 2014, NMR in biomedicine.

[16]  Stefan Neubauer,et al.  Dilated Cardiomyopathy: Phosphorus 31 MR Spectroscopy at 7 T , 2016, Radiology.

[17]  Robin A. de Graaf,et al.  In Vivo NMR Spectroscopy , 2019 .

[18]  Vanhamme,et al.  Improved method for accurate and efficient quantification of MRS data with use of prior knowledge , 1997, Journal of magnetic resonance.

[19]  Matthew D. Robson,et al.  Adiabatic excitation for 31P MR spectroscopy in the human heart at 7 T: A feasibility study , 2016, Magnetic resonance in medicine.

[20]  Michael Schär,et al.  Triple repetition time saturation transfer (TRiST) 31P spectroscopy for measuring human creatine kinase reaction kinetics , 2010, Magnetic resonance in medicine.

[21]  D van Ormondt,et al.  Cramér–Rao bounds: an evaluation tool for quantitation , 2001, NMR in biomedicine.

[22]  Johannes Bernarding,et al.  Quantitation of simulated short echo time 1H human brain spectra by LCModel and AMARES , 2004, Magnetic resonance in medicine.