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Assessing robustness of quantitative susceptibility-based MRI radiomic features in patients with multiple sclerosis

Multiple Sclerosis (MS) is an autoimmune demyelinating disease characterised by changes in iron and myelin content. These biomarkers are detectable by Quantitative Susceptibility Mapping (QSM), an advanced Magnetic Resonance Imaging technique detecting magnetic properties. When analysed with radiomi...

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Autores principales: Fiscone, Cristiana, Rundo, Leonardo, Lugaresi, Alessandra, Manners, David Neil, Allinson, Kieren, Baldin, Elisa, Vornetti, Gianfranco, Lodi, Raffaele, Tonon, Caterina, Testa, Claudia, Castelli, Mauro, Zaccagna, Fulvio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10533494/
https://www.ncbi.nlm.nih.gov/pubmed/37758804
http://dx.doi.org/10.1038/s41598-023-42914-4
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author Fiscone, Cristiana
Rundo, Leonardo
Lugaresi, Alessandra
Manners, David Neil
Allinson, Kieren
Baldin, Elisa
Vornetti, Gianfranco
Lodi, Raffaele
Tonon, Caterina
Testa, Claudia
Castelli, Mauro
Zaccagna, Fulvio
author_facet Fiscone, Cristiana
Rundo, Leonardo
Lugaresi, Alessandra
Manners, David Neil
Allinson, Kieren
Baldin, Elisa
Vornetti, Gianfranco
Lodi, Raffaele
Tonon, Caterina
Testa, Claudia
Castelli, Mauro
Zaccagna, Fulvio
author_sort Fiscone, Cristiana
collection PubMed
description Multiple Sclerosis (MS) is an autoimmune demyelinating disease characterised by changes in iron and myelin content. These biomarkers are detectable by Quantitative Susceptibility Mapping (QSM), an advanced Magnetic Resonance Imaging technique detecting magnetic properties. When analysed with radiomic techniques that exploit its intrinsic quantitative nature, QSM may furnish biomarkers to facilitate early diagnosis of MS and timely assessment of progression. In this work, we explore the robustness of QSM radiomic features by varying the number of grey levels (GLs) and echo times (TEs), in a sample of healthy controls and patients with MS. We analysed the white matter in total and within six clinically relevant tracts, including the cortico-spinal tract and the optic radiation. After optimising the number of GLs (n = 64), at least 65% of features were robust for each Volume of Interest (VOI), with no difference (p > .05) between left and right hemispheres. Different outcomes in feature robustness among the VOIs depend on their characteristics, such as volume and variance of susceptibility values. This study validated the processing pipeline for robustness analysis and established the reliability of QSM-based radiomics features against GLs and TEs. Our results provide important insights for future radiomics studies using QSM in clinical applications.
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spelling pubmed-105334942023-09-29 Assessing robustness of quantitative susceptibility-based MRI radiomic features in patients with multiple sclerosis Fiscone, Cristiana Rundo, Leonardo Lugaresi, Alessandra Manners, David Neil Allinson, Kieren Baldin, Elisa Vornetti, Gianfranco Lodi, Raffaele Tonon, Caterina Testa, Claudia Castelli, Mauro Zaccagna, Fulvio Sci Rep Article Multiple Sclerosis (MS) is an autoimmune demyelinating disease characterised by changes in iron and myelin content. These biomarkers are detectable by Quantitative Susceptibility Mapping (QSM), an advanced Magnetic Resonance Imaging technique detecting magnetic properties. When analysed with radiomic techniques that exploit its intrinsic quantitative nature, QSM may furnish biomarkers to facilitate early diagnosis of MS and timely assessment of progression. In this work, we explore the robustness of QSM radiomic features by varying the number of grey levels (GLs) and echo times (TEs), in a sample of healthy controls and patients with MS. We analysed the white matter in total and within six clinically relevant tracts, including the cortico-spinal tract and the optic radiation. After optimising the number of GLs (n = 64), at least 65% of features were robust for each Volume of Interest (VOI), with no difference (p > .05) between left and right hemispheres. Different outcomes in feature robustness among the VOIs depend on their characteristics, such as volume and variance of susceptibility values. This study validated the processing pipeline for robustness analysis and established the reliability of QSM-based radiomics features against GLs and TEs. Our results provide important insights for future radiomics studies using QSM in clinical applications. Nature Publishing Group UK 2023-09-27 /pmc/articles/PMC10533494/ /pubmed/37758804 http://dx.doi.org/10.1038/s41598-023-42914-4 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Fiscone, Cristiana
Rundo, Leonardo
Lugaresi, Alessandra
Manners, David Neil
Allinson, Kieren
Baldin, Elisa
Vornetti, Gianfranco
Lodi, Raffaele
Tonon, Caterina
Testa, Claudia
Castelli, Mauro
Zaccagna, Fulvio
Assessing robustness of quantitative susceptibility-based MRI radiomic features in patients with multiple sclerosis
title Assessing robustness of quantitative susceptibility-based MRI radiomic features in patients with multiple sclerosis
title_full Assessing robustness of quantitative susceptibility-based MRI radiomic features in patients with multiple sclerosis
title_fullStr Assessing robustness of quantitative susceptibility-based MRI radiomic features in patients with multiple sclerosis
title_full_unstemmed Assessing robustness of quantitative susceptibility-based MRI radiomic features in patients with multiple sclerosis
title_short Assessing robustness of quantitative susceptibility-based MRI radiomic features in patients with multiple sclerosis
title_sort assessing robustness of quantitative susceptibility-based mri radiomic features in patients with multiple sclerosis
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10533494/
https://www.ncbi.nlm.nih.gov/pubmed/37758804
http://dx.doi.org/10.1038/s41598-023-42914-4
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