Literature DB >> 32603810

Osprey: Open-source processing, reconstruction & estimation of magnetic resonance spectroscopy data.

Georg Oeltzschner1, Helge J Zöllner2, Steve C N Hui2, Mark Mikkelsen2, Muhammad G Saleh2, Sofie Tapper2, Richard A E Edden2.   

Abstract

BACKGROUND: Processing and quantitative analysis of magnetic resonance spectroscopy (MRS) data are far from standardized and require interfacing with third-party software. Here, we present Osprey, a fully integrated open-source data analysis pipeline for MRS data, with seamless integration of pre-processing, linear-combination modelling, quantification, and data visualization. NEW
METHOD: Osprey loads multiple common MRS data formats, performs phased-array coil combination, frequency-and phase-correction of individual transients, signal averaging and Fourier transformation. Linear combination modelling of the processed spectrum is carried out using simulated basis sets and a spline baseline. The MRS voxel is coregistered to an anatomical image, which is segmented for tissue correction and quantification is performed based upon modelling parameters and tissue segmentation. The results of each analysis step are visualized in the Osprey GUI. The analysis pipeline is demonstrated in 12 PRESS, 11 MEGA-PRESS, and 8 HERMES datasets acquired in healthy subjects.
RESULTS: Osprey successfully loads, processes, models, and quantifies MRS data acquired with a variety of conventional and spectral editing techniques. COMPARISON WITH EXISTING METHOD(S): Osprey is the first MRS software to combine uniform pre-processing, linear-combination modelling, tissue correction and quantification into a coherent ecosystem. Compared to existing compiled, often closed-source modelling software, Osprey's open-source code philosophy allows researchers to integrate state-of-the-art data processing and modelling routines, and potentially converge towards standardization of analysis.
CONCLUSIONS: Osprey combines robust, peer-reviewed data processing methods into a modular workflow that is easily augmented by community developers, allowing the rapid implementation of new methods.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Linear-combination modelling; Magnetic resonance spectroscopy; Pre-processing; Quantification; Tissue correction

Mesh:

Year:  2020        PMID: 32603810      PMCID: PMC7477913          DOI: 10.1016/j.jneumeth.2020.108827

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


  40 in total

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Journal:  Neuroimage       Date:  2017-07-14       Impact factor: 6.556

3.  1 H-MRS processing parameters affect metabolite quantification: The urgent need for uniform and transparent standardization.

Authors:  Alex A Bhogal; Remmelt R Schür; Lotte C Houtepen; Bart van de Bank; Vincent O Boer; Anouk Marsman; Peter B Barker; Tom W J Scheenen; Jannie P Wijnen; Christiaan H Vinkers; Dennis W J Klomp
Journal:  NMR Biomed       Date:  2017-09-15       Impact factor: 4.044

4.  Grey and white matter GABA level differences in the human brain using two-dimensional, J-resolved spectroscopic imaging.

Authors:  J Eric Jensen; Blaise de B Frederick; Perry F Renshaw
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5.  HERMES: Hadamard encoding and reconstruction of MEGA-edited spectroscopy.

Authors:  Kimberly L Chan; Nicolaas A J Puts; Michael Schär; Peter B Barker; Richard A E Edden
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6.  Fast computation of full density matrix of multispin systems for spatially localized in vivo magnetic resonance spectroscopy.

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7.  Gannet: A batch-processing tool for the quantitative analysis of gamma-aminobutyric acid–edited MR spectroscopy spectra.

Authors:  Richard A E Edden; Nicolaas A J Puts; Ashley D Harris; Peter B Barker; C John Evans
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Review 8.  Methodological consensus on clinical proton MRS of the brain: Review and recommendations.

Authors:  Martin Wilson; Ovidiu Andronesi; Peter B Barker; Robert Bartha; Alberto Bizzi; Patrick J Bolan; Kevin M Brindle; In-Young Choi; Cristina Cudalbu; Ulrike Dydak; Uzay E Emir; Ramon G Gonzalez; Stephan Gruber; Rolf Gruetter; Rakesh K Gupta; Arend Heerschap; Anke Henning; Hoby P Hetherington; Petra S Huppi; Ralph E Hurd; Kejal Kantarci; Risto A Kauppinen; Dennis W J Klomp; Roland Kreis; Marijn J Kruiskamp; Martin O Leach; Alexander P Lin; Peter R Luijten; Małgorzata Marjańska; Andrew A Maudsley; Dieter J Meyerhoff; Carolyn E Mountford; Paul G Mullins; James B Murdoch; Sarah J Nelson; Ralph Noeske; Gülin Öz; Julie W Pan; Andrew C Peet; Harish Poptani; Stefan Posse; Eva-Maria Ratai; Nouha Salibi; Tom W J Scheenen; Ian C P Smith; Brian J Soher; Ivan Tkáč; Daniel B Vigneron; Franklyn A Howe
Journal:  Magn Reson Med       Date:  2019-03-28       Impact factor: 4.668

Review 9.  FSL.

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10.  Across-vendor standardization of semi-LASER for single-voxel MRS at 3T.

Authors:  Dinesh K Deelchand; Adam Berrington; Ralph Noeske; James M Joers; Arvin Arani; Joseph Gillen; Michael Schär; Jon-Fredrik Nielsen; Scott Peltier; Navid Seraji-Bozorgzad; Karl Landheer; Christoph Juchem; Brian J Soher; Douglas C Noll; Kejal Kantarci; Eva M Ratai; Thomas H Mareci; Peter B Barker; Gülin Öz
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  13 in total

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Journal:  Magn Reson Med       Date:  2021-11-28       Impact factor: 4.668

2.  Comparison of linear combination modeling strategies for edited magnetic resonance spectroscopy at 3 T.

Authors:  Helge J Zöllner; Sofie Tapper; Steve C N Hui; Peter B Barker; Richard A E Edden; Georg Oeltzschner
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4.  MRSCloud: A cloud-based MRS tool for basis set simulation.

Authors:  Steve C N Hui; Muhammad G Saleh; Helge J Zöllner; Georg Oeltzschner; Hongli Fan; Yue Li; Yulu Song; Hangyi Jiang; Jamie Near; Hanzhang Lu; Susumu Mori; Richard A E Edden
Journal:  Magn Reson Med       Date:  2022-07-01       Impact factor: 3.737

5.  NIfTI-MRS: A standard data format for magnetic resonance spectroscopy.

Authors:  William T Clarke; Tiffany K Bell; Uzay E Emir; Mark Mikkelsen; Georg Oeltzschner; Amirmohammad Shamaei; Brian J Soher; Martin Wilson
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6.  Comparison of different linear-combination modeling algorithms for short-TE proton spectra.

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7.  PCA denoising and Wiener deconvolution of 31 P 3D CSI data to enhance effective SNR and improve point spread function.

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8.  Influence of editing pulse flip angle on J-difference MR spectroscopy.

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9.  Comparison of seven modelling algorithms for γ-aminobutyric acid-edited proton magnetic resonance spectroscopy.

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Authors:  Sofie Tapper; Mark Mikkelsen; Blake E Dewey; Helge J Zöllner; Steve C N Hui; Georg Oeltzschner; Richard A E Edden
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