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Validation and quantification of left ventricular function during exercise and free breathing from real-time cardiac magnetic resonance images
Exercise cardiovascular magnetic resonance (CMR) can unmask cardiac pathology not evident at rest. Real-time CMR in free breathing can be used, but respiratory motion may compromise quantification of left ventricular (LV) function. We aimed to develop and validate a post-processing algorithm that se...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8979972/ https://www.ncbi.nlm.nih.gov/pubmed/35379859 http://dx.doi.org/10.1038/s41598-022-09366-8 |
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author | Edlund, Jonathan Haris, Kostas Ostenfeld, Ellen Carlsson, Marcus Heiberg, Einar Johansson, Sebastian Östenson, Björn Jin, Ning Aletras, Anthony H. Steding-Ehrenborg, Katarina |
author_facet | Edlund, Jonathan Haris, Kostas Ostenfeld, Ellen Carlsson, Marcus Heiberg, Einar Johansson, Sebastian Östenson, Björn Jin, Ning Aletras, Anthony H. Steding-Ehrenborg, Katarina |
author_sort | Edlund, Jonathan |
collection | PubMed |
description | Exercise cardiovascular magnetic resonance (CMR) can unmask cardiac pathology not evident at rest. Real-time CMR in free breathing can be used, but respiratory motion may compromise quantification of left ventricular (LV) function. We aimed to develop and validate a post-processing algorithm that semi-automatically sorts real-time CMR images according to breathing to facilitate quantification of LV function in free breathing exercise. A semi-automatic algorithm utilizing manifold learning (Laplacian Eigenmaps) was developed for respiratory sorting. Feasibility was tested in eight healthy volunteers and eight patients who underwent ECG-gated and real-time CMR at rest. Additionally, volunteers performed exercise CMR at 60% of maximum heart rate. The algorithm was validated for exercise by comparing LV mass during exercise to rest. Respiratory sorting to end expiration and end inspiration (processing time 20 to 40 min) succeeded in all research participants. Bias ± SD for LV mass was 0 ± 5 g when comparing real-time CMR at rest, and 0 ± 7 g when comparing real-time CMR during exercise to ECG-gated at rest. This study presents a semi-automatic algorithm to retrospectively perform respiratory sorting in free breathing real-time CMR. This can facilitate implementation of exercise CMR with non-ECG-gated free breathing real-time imaging, without any additional physiological input. |
format | Online Article Text |
id | pubmed-8979972 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-89799722022-04-05 Validation and quantification of left ventricular function during exercise and free breathing from real-time cardiac magnetic resonance images Edlund, Jonathan Haris, Kostas Ostenfeld, Ellen Carlsson, Marcus Heiberg, Einar Johansson, Sebastian Östenson, Björn Jin, Ning Aletras, Anthony H. Steding-Ehrenborg, Katarina Sci Rep Article Exercise cardiovascular magnetic resonance (CMR) can unmask cardiac pathology not evident at rest. Real-time CMR in free breathing can be used, but respiratory motion may compromise quantification of left ventricular (LV) function. We aimed to develop and validate a post-processing algorithm that semi-automatically sorts real-time CMR images according to breathing to facilitate quantification of LV function in free breathing exercise. A semi-automatic algorithm utilizing manifold learning (Laplacian Eigenmaps) was developed for respiratory sorting. Feasibility was tested in eight healthy volunteers and eight patients who underwent ECG-gated and real-time CMR at rest. Additionally, volunteers performed exercise CMR at 60% of maximum heart rate. The algorithm was validated for exercise by comparing LV mass during exercise to rest. Respiratory sorting to end expiration and end inspiration (processing time 20 to 40 min) succeeded in all research participants. Bias ± SD for LV mass was 0 ± 5 g when comparing real-time CMR at rest, and 0 ± 7 g when comparing real-time CMR during exercise to ECG-gated at rest. This study presents a semi-automatic algorithm to retrospectively perform respiratory sorting in free breathing real-time CMR. This can facilitate implementation of exercise CMR with non-ECG-gated free breathing real-time imaging, without any additional physiological input. Nature Publishing Group UK 2022-04-04 /pmc/articles/PMC8979972/ /pubmed/35379859 http://dx.doi.org/10.1038/s41598-022-09366-8 Text en © The Author(s) 2022 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 Edlund, Jonathan Haris, Kostas Ostenfeld, Ellen Carlsson, Marcus Heiberg, Einar Johansson, Sebastian Östenson, Björn Jin, Ning Aletras, Anthony H. Steding-Ehrenborg, Katarina Validation and quantification of left ventricular function during exercise and free breathing from real-time cardiac magnetic resonance images |
title | Validation and quantification of left ventricular function during exercise and free breathing from real-time cardiac magnetic resonance images |
title_full | Validation and quantification of left ventricular function during exercise and free breathing from real-time cardiac magnetic resonance images |
title_fullStr | Validation and quantification of left ventricular function during exercise and free breathing from real-time cardiac magnetic resonance images |
title_full_unstemmed | Validation and quantification of left ventricular function during exercise and free breathing from real-time cardiac magnetic resonance images |
title_short | Validation and quantification of left ventricular function during exercise and free breathing from real-time cardiac magnetic resonance images |
title_sort | validation and quantification of left ventricular function during exercise and free breathing from real-time cardiac magnetic resonance images |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8979972/ https://www.ncbi.nlm.nih.gov/pubmed/35379859 http://dx.doi.org/10.1038/s41598-022-09366-8 |
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