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From raw data to data-analysis for magnetic resonance spectroscopy – the missing link: jMRUI2XML

BACKGROUND: Magnetic resonance spectroscopy provides metabolic information about living tissues in a non-invasive way. However, there are only few multi-centre clinical studies, mostly performed on a single scanner model or data format, as there is no flexible way of documenting and exchanging proce...

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Autores principales: Mocioiu, Victor, Ortega-Martorell, Sandra, Olier, Iván, Jablonski, Michal, Starcukova, Jana, Lisboa, Paulo, Arús, Carles, Julià-Sapé, Margarida
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4640235/
https://www.ncbi.nlm.nih.gov/pubmed/26552737
http://dx.doi.org/10.1186/s12859-015-0796-5
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author Mocioiu, Victor
Ortega-Martorell, Sandra
Olier, Iván
Jablonski, Michal
Starcukova, Jana
Lisboa, Paulo
Arús, Carles
Julià-Sapé, Margarida
author_facet Mocioiu, Victor
Ortega-Martorell, Sandra
Olier, Iván
Jablonski, Michal
Starcukova, Jana
Lisboa, Paulo
Arús, Carles
Julià-Sapé, Margarida
author_sort Mocioiu, Victor
collection PubMed
description BACKGROUND: Magnetic resonance spectroscopy provides metabolic information about living tissues in a non-invasive way. However, there are only few multi-centre clinical studies, mostly performed on a single scanner model or data format, as there is no flexible way of documenting and exchanging processed magnetic resonance spectroscopy data in digital format. This is because the DICOM standard for spectroscopy deals with unprocessed data. This paper proposes a plugin tool developed for jMRUI, namely jMRUI2XML, to tackle the latter limitation. jMRUI is a software tool for magnetic resonance spectroscopy data processing that is widely used in the magnetic resonance spectroscopy community and has evolved into a plugin platform allowing for implementation of novel features. RESULTS: jMRUI2XML is a Java solution that facilitates common preprocessing of magnetic resonance spectroscopy data across multiple scanners. Its main characteristics are: 1) it automates magnetic resonance spectroscopy preprocessing, and 2) it can be a platform for outputting exchangeable magnetic resonance spectroscopy data. The plugin works with any kind of data that can be opened by jMRUI and outputs in extensible markup language format. Data processing templates can be generated and saved for later use. The output format opens the way for easy data sharing- due to the documentation of the preprocessing parameters and the intrinsic anonymization - for example for performing pattern recognition analysis on multicentre/multi-manufacturer magnetic resonance spectroscopy data. CONCLUSIONS: jMRUI2XML provides a self-contained and self-descriptive format accounting for the most relevant information needed for exchanging magnetic resonance spectroscopy data in digital form, as well as for automating its processing. This allows for tracking the procedures the data has undergone, which makes the proposed tool especially useful when performing pattern recognition analysis. Moreover, this work constitutes a first proposal for a minimum amount of information that should accompany any magnetic resonance processed spectrum, towards the goal of achieving better transferability of magnetic resonance spectroscopy studies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0796-5) contains supplementary material, which is available to authorized users.
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spelling pubmed-46402352015-11-11 From raw data to data-analysis for magnetic resonance spectroscopy – the missing link: jMRUI2XML Mocioiu, Victor Ortega-Martorell, Sandra Olier, Iván Jablonski, Michal Starcukova, Jana Lisboa, Paulo Arús, Carles Julià-Sapé, Margarida BMC Bioinformatics Software BACKGROUND: Magnetic resonance spectroscopy provides metabolic information about living tissues in a non-invasive way. However, there are only few multi-centre clinical studies, mostly performed on a single scanner model or data format, as there is no flexible way of documenting and exchanging processed magnetic resonance spectroscopy data in digital format. This is because the DICOM standard for spectroscopy deals with unprocessed data. This paper proposes a plugin tool developed for jMRUI, namely jMRUI2XML, to tackle the latter limitation. jMRUI is a software tool for magnetic resonance spectroscopy data processing that is widely used in the magnetic resonance spectroscopy community and has evolved into a plugin platform allowing for implementation of novel features. RESULTS: jMRUI2XML is a Java solution that facilitates common preprocessing of magnetic resonance spectroscopy data across multiple scanners. Its main characteristics are: 1) it automates magnetic resonance spectroscopy preprocessing, and 2) it can be a platform for outputting exchangeable magnetic resonance spectroscopy data. The plugin works with any kind of data that can be opened by jMRUI and outputs in extensible markup language format. Data processing templates can be generated and saved for later use. The output format opens the way for easy data sharing- due to the documentation of the preprocessing parameters and the intrinsic anonymization - for example for performing pattern recognition analysis on multicentre/multi-manufacturer magnetic resonance spectroscopy data. CONCLUSIONS: jMRUI2XML provides a self-contained and self-descriptive format accounting for the most relevant information needed for exchanging magnetic resonance spectroscopy data in digital form, as well as for automating its processing. This allows for tracking the procedures the data has undergone, which makes the proposed tool especially useful when performing pattern recognition analysis. Moreover, this work constitutes a first proposal for a minimum amount of information that should accompany any magnetic resonance processed spectrum, towards the goal of achieving better transferability of magnetic resonance spectroscopy studies. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12859-015-0796-5) contains supplementary material, which is available to authorized users. BioMed Central 2015-11-09 /pmc/articles/PMC4640235/ /pubmed/26552737 http://dx.doi.org/10.1186/s12859-015-0796-5 Text en © Mocioiu et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Software
Mocioiu, Victor
Ortega-Martorell, Sandra
Olier, Iván
Jablonski, Michal
Starcukova, Jana
Lisboa, Paulo
Arús, Carles
Julià-Sapé, Margarida
From raw data to data-analysis for magnetic resonance spectroscopy – the missing link: jMRUI2XML
title From raw data to data-analysis for magnetic resonance spectroscopy – the missing link: jMRUI2XML
title_full From raw data to data-analysis for magnetic resonance spectroscopy – the missing link: jMRUI2XML
title_fullStr From raw data to data-analysis for magnetic resonance spectroscopy – the missing link: jMRUI2XML
title_full_unstemmed From raw data to data-analysis for magnetic resonance spectroscopy – the missing link: jMRUI2XML
title_short From raw data to data-analysis for magnetic resonance spectroscopy – the missing link: jMRUI2XML
title_sort from raw data to data-analysis for magnetic resonance spectroscopy – the missing link: jmrui2xml
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4640235/
https://www.ncbi.nlm.nih.gov/pubmed/26552737
http://dx.doi.org/10.1186/s12859-015-0796-5
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