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Evaluation of Two Post-Processing Analysis Methods of Proton Magnetic Resonance Spectroscopy in Glioma Tumors

BACKGROUND: Magnetic resonance spectroscopy (MRS) is a non-invasive diagnostic and the neuroimaging method of choice for the noninvasive monitoring of brain metabolism in patients with glioma tumors. (1)H-MRS is a reliable and non-invasive tool used to study glioma. However, the metabolite spectra o...

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Autores principales: Saatchian, Erfan, Ehsani, Sina, Montazerabadi, Alireza
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Shiraz University of Medical Sciences 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9923243/
https://www.ncbi.nlm.nih.gov/pubmed/36818014
http://dx.doi.org/10.31661/jbpe.v0i0.2001-1055
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author Saatchian, Erfan
Ehsani, Sina
Montazerabadi, Alireza
author_facet Saatchian, Erfan
Ehsani, Sina
Montazerabadi, Alireza
author_sort Saatchian, Erfan
collection PubMed
description BACKGROUND: Magnetic resonance spectroscopy (MRS) is a non-invasive diagnostic and the neuroimaging method of choice for the noninvasive monitoring of brain metabolism in patients with glioma tumors. (1)H-MRS is a reliable and non-invasive tool used to study glioma. However, the metabolite spectra obtained by (1)H-MRS requires a specific quantification procedure for post-processing. According to our knowledge, no comparisons have yet been made between spectrum analysis software for quantification of gliomas metabolites. OBJECTIVE: Current study aims to evaluate the difference between this two common software in quantifying cerebral metabolites. MATERIAL AND METHODS: In this analytical study, we evaluate two post-processing software packages, java-based graphical for MR user interface packages (jMRUI) and totally automatic robust quantitation in NMR (TARQUIN) software. (1)H-MRS spectrum from the brain of patients with gliomas tumors was collected for post-processing. AMARES algorithms were conducted to metabolite qualification on jMRUI software, and TARQUIN software were implemented with automated quantification algorithms. The study included a total of 30 subjects. For quantification, subjects were divided into a normal group (n=15) and group of gliomas (n=15). RESULTS: When calculated by TARQUIN, the mean metabolites ratio was typically lower than by jMRUI. While, the mean ratio of metabolites varied when quantified by jMRUI vs. TARQUIN, both methods apparent clinical associations. CONCLUSION: TARQUIN and jMRUI are feasible choices for the post-processing of cerebral MRS data obtained from glioma tumors.
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spelling pubmed-99232432023-02-16 Evaluation of Two Post-Processing Analysis Methods of Proton Magnetic Resonance Spectroscopy in Glioma Tumors Saatchian, Erfan Ehsani, Sina Montazerabadi, Alireza J Biomed Phys Eng Original Article BACKGROUND: Magnetic resonance spectroscopy (MRS) is a non-invasive diagnostic and the neuroimaging method of choice for the noninvasive monitoring of brain metabolism in patients with glioma tumors. (1)H-MRS is a reliable and non-invasive tool used to study glioma. However, the metabolite spectra obtained by (1)H-MRS requires a specific quantification procedure for post-processing. According to our knowledge, no comparisons have yet been made between spectrum analysis software for quantification of gliomas metabolites. OBJECTIVE: Current study aims to evaluate the difference between this two common software in quantifying cerebral metabolites. MATERIAL AND METHODS: In this analytical study, we evaluate two post-processing software packages, java-based graphical for MR user interface packages (jMRUI) and totally automatic robust quantitation in NMR (TARQUIN) software. (1)H-MRS spectrum from the brain of patients with gliomas tumors was collected for post-processing. AMARES algorithms were conducted to metabolite qualification on jMRUI software, and TARQUIN software were implemented with automated quantification algorithms. The study included a total of 30 subjects. For quantification, subjects were divided into a normal group (n=15) and group of gliomas (n=15). RESULTS: When calculated by TARQUIN, the mean metabolites ratio was typically lower than by jMRUI. While, the mean ratio of metabolites varied when quantified by jMRUI vs. TARQUIN, both methods apparent clinical associations. CONCLUSION: TARQUIN and jMRUI are feasible choices for the post-processing of cerebral MRS data obtained from glioma tumors. Shiraz University of Medical Sciences 2023-02-01 /pmc/articles/PMC9923243/ /pubmed/36818014 http://dx.doi.org/10.31661/jbpe.v0i0.2001-1055 Text en Copyright: © Journal of Biomedical Physics and Engineering https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 Unported License, ( http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Article
Saatchian, Erfan
Ehsani, Sina
Montazerabadi, Alireza
Evaluation of Two Post-Processing Analysis Methods of Proton Magnetic Resonance Spectroscopy in Glioma Tumors
title Evaluation of Two Post-Processing Analysis Methods of Proton Magnetic Resonance Spectroscopy in Glioma Tumors
title_full Evaluation of Two Post-Processing Analysis Methods of Proton Magnetic Resonance Spectroscopy in Glioma Tumors
title_fullStr Evaluation of Two Post-Processing Analysis Methods of Proton Magnetic Resonance Spectroscopy in Glioma Tumors
title_full_unstemmed Evaluation of Two Post-Processing Analysis Methods of Proton Magnetic Resonance Spectroscopy in Glioma Tumors
title_short Evaluation of Two Post-Processing Analysis Methods of Proton Magnetic Resonance Spectroscopy in Glioma Tumors
title_sort evaluation of two post-processing analysis methods of proton magnetic resonance spectroscopy in glioma tumors
topic Original Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9923243/
https://www.ncbi.nlm.nih.gov/pubmed/36818014
http://dx.doi.org/10.31661/jbpe.v0i0.2001-1055
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