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Radiomics-based aortic flow profile characterization with 4D phase-contrast MRI
4D PC MRI of the aorta has become a routinely available examination, and a multitude of single parameters have been suggested for the quantitative assessment of relevant flow features for clinical studies and diagnosis. However, clinically applicable assessment of complex flow patterns is still chal...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10106758/ https://www.ncbi.nlm.nih.gov/pubmed/37077748 http://dx.doi.org/10.3389/fcvm.2023.1102502 |
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author | Huellebrand, Markus Jarmatz, Lina Manini, Chiara Laube, Ann Ivantsits, Matthias Schulz-Menger, Jeanette Nordmeyer, Sarah Harloff, Andreas Hansmann, Jochen Kelle, Sebastian Hennemuth, Anja |
author_facet | Huellebrand, Markus Jarmatz, Lina Manini, Chiara Laube, Ann Ivantsits, Matthias Schulz-Menger, Jeanette Nordmeyer, Sarah Harloff, Andreas Hansmann, Jochen Kelle, Sebastian Hennemuth, Anja |
author_sort | Huellebrand, Markus |
collection | PubMed |
description | 4D PC MRI of the aorta has become a routinely available examination, and a multitude of single parameters have been suggested for the quantitative assessment of relevant flow features for clinical studies and diagnosis. However, clinically applicable assessment of complex flow patterns is still challenging. We present a concept for applying radiomics for the quantitative characterization of flow patterns in the aorta. To this end, we derive cross-sectional scalar parameter maps related to parameters suggested in literature such as throughflow, flow direction, vorticity, and normalized helicity. Derived radiomics features are selected with regard to their inter-scanner and inter-observer reproducibility, as well as their performance in the differentiation of sex-, age- and disease-related flow properties. The reproducible features were tested on user-selected examples with respect to their suitability for characterizing flow profile types. In future work, such signatures could be applied for quantitative flow assessment in clinical studies or disease phenotyping. |
format | Online Article Text |
id | pubmed-10106758 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-101067582023-04-18 Radiomics-based aortic flow profile characterization with 4D phase-contrast MRI Huellebrand, Markus Jarmatz, Lina Manini, Chiara Laube, Ann Ivantsits, Matthias Schulz-Menger, Jeanette Nordmeyer, Sarah Harloff, Andreas Hansmann, Jochen Kelle, Sebastian Hennemuth, Anja Front Cardiovasc Med Cardiovascular Medicine 4D PC MRI of the aorta has become a routinely available examination, and a multitude of single parameters have been suggested for the quantitative assessment of relevant flow features for clinical studies and diagnosis. However, clinically applicable assessment of complex flow patterns is still challenging. We present a concept for applying radiomics for the quantitative characterization of flow patterns in the aorta. To this end, we derive cross-sectional scalar parameter maps related to parameters suggested in literature such as throughflow, flow direction, vorticity, and normalized helicity. Derived radiomics features are selected with regard to their inter-scanner and inter-observer reproducibility, as well as their performance in the differentiation of sex-, age- and disease-related flow properties. The reproducible features were tested on user-selected examples with respect to their suitability for characterizing flow profile types. In future work, such signatures could be applied for quantitative flow assessment in clinical studies or disease phenotyping. Frontiers Media S.A. 2023-04-03 /pmc/articles/PMC10106758/ /pubmed/37077748 http://dx.doi.org/10.3389/fcvm.2023.1102502 Text en © 2023 Huellebrand, Jarmatz, Manini, Laube, Ivantsits, Schulz-Menger, Nordmeyer, Harloff, Hansmann, Kelle and Hennemuth. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cardiovascular Medicine Huellebrand, Markus Jarmatz, Lina Manini, Chiara Laube, Ann Ivantsits, Matthias Schulz-Menger, Jeanette Nordmeyer, Sarah Harloff, Andreas Hansmann, Jochen Kelle, Sebastian Hennemuth, Anja Radiomics-based aortic flow profile characterization with 4D phase-contrast MRI |
title | Radiomics-based aortic flow profile characterization with 4D phase-contrast MRI |
title_full | Radiomics-based aortic flow profile characterization with 4D phase-contrast MRI |
title_fullStr | Radiomics-based aortic flow profile characterization with 4D phase-contrast MRI |
title_full_unstemmed | Radiomics-based aortic flow profile characterization with 4D phase-contrast MRI |
title_short | Radiomics-based aortic flow profile characterization with 4D phase-contrast MRI |
title_sort | radiomics-based aortic flow profile characterization with 4d phase-contrast mri |
topic | Cardiovascular Medicine |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10106758/ https://www.ncbi.nlm.nih.gov/pubmed/37077748 http://dx.doi.org/10.3389/fcvm.2023.1102502 |
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