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Simplified post processing of cine DENSE cardiovascular magnetic resonance for quantification of cardiac mechanics
BACKGROUND: Cardiovascular magnetic resonance using displacement encoding with stimulated echoes (DENSE) is capable of assessing advanced measures of cardiac mechanics such as strain and torsion. A potential hurdle to widespread clinical adoption of DENSE is the time required to manually segment the...
Autores principales: | , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4246464/ https://www.ncbi.nlm.nih.gov/pubmed/25430079 http://dx.doi.org/10.1186/s12968-014-0094-9 |
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author | Suever, Jonathan D Wehner, Gregory J Haggerty, Christopher M Jing, Linyuan Hamlet, Sean M Binkley, Cassi M Kramer, Sage P Mattingly, Andrea C Powell, David K Bilchick, Kenneth C Epstein, Frederick H Fornwalt, Brandon K |
author_facet | Suever, Jonathan D Wehner, Gregory J Haggerty, Christopher M Jing, Linyuan Hamlet, Sean M Binkley, Cassi M Kramer, Sage P Mattingly, Andrea C Powell, David K Bilchick, Kenneth C Epstein, Frederick H Fornwalt, Brandon K |
author_sort | Suever, Jonathan D |
collection | PubMed |
description | BACKGROUND: Cardiovascular magnetic resonance using displacement encoding with stimulated echoes (DENSE) is capable of assessing advanced measures of cardiac mechanics such as strain and torsion. A potential hurdle to widespread clinical adoption of DENSE is the time required to manually segment the myocardium during post-processing of the images. To overcome this hurdle, we proposed a radical approach in which only three contours per image slice are required for post-processing (instead of the typical 30–40 contours per image slice). We hypothesized that peak left ventricular circumferential, longitudinal and radial strains and torsion could be accurately quantified using this simplified analysis. METHODS AND RESULTS: We tested our hypothesis on a large multi-institutional dataset consisting of 541 DENSE image slices from 135 mice and 234 DENSE image slices from 62 humans. We compared measures of cardiac mechanics derived from the simplified post-processing to those derived from original post-processing utilizing the full set of 30–40 manually-defined contours per image slice. Accuracy was assessed with Bland-Altman limits of agreement and summarized with a modified coefficient of variation. The simplified technique showed high accuracy with all coefficients of variation less than 10% in humans and 6% in mice. The accuracy of the simplified technique was also superior to two previously published semi-automated analysis techniques for DENSE post-processing. CONCLUSIONS: Accurate measures of cardiac mechanics can be derived from DENSE cardiac magnetic resonance in both humans and mice using a simplified technique to reduce post-processing time by approximately 94%. These findings demonstrate that quantifying cardiac mechanics from DENSE data is simple enough to be integrated into the clinical workflow. |
format | Online Article Text |
id | pubmed-4246464 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-42464642014-12-02 Simplified post processing of cine DENSE cardiovascular magnetic resonance for quantification of cardiac mechanics Suever, Jonathan D Wehner, Gregory J Haggerty, Christopher M Jing, Linyuan Hamlet, Sean M Binkley, Cassi M Kramer, Sage P Mattingly, Andrea C Powell, David K Bilchick, Kenneth C Epstein, Frederick H Fornwalt, Brandon K J Cardiovasc Magn Reson Research BACKGROUND: Cardiovascular magnetic resonance using displacement encoding with stimulated echoes (DENSE) is capable of assessing advanced measures of cardiac mechanics such as strain and torsion. A potential hurdle to widespread clinical adoption of DENSE is the time required to manually segment the myocardium during post-processing of the images. To overcome this hurdle, we proposed a radical approach in which only three contours per image slice are required for post-processing (instead of the typical 30–40 contours per image slice). We hypothesized that peak left ventricular circumferential, longitudinal and radial strains and torsion could be accurately quantified using this simplified analysis. METHODS AND RESULTS: We tested our hypothesis on a large multi-institutional dataset consisting of 541 DENSE image slices from 135 mice and 234 DENSE image slices from 62 humans. We compared measures of cardiac mechanics derived from the simplified post-processing to those derived from original post-processing utilizing the full set of 30–40 manually-defined contours per image slice. Accuracy was assessed with Bland-Altman limits of agreement and summarized with a modified coefficient of variation. The simplified technique showed high accuracy with all coefficients of variation less than 10% in humans and 6% in mice. The accuracy of the simplified technique was also superior to two previously published semi-automated analysis techniques for DENSE post-processing. CONCLUSIONS: Accurate measures of cardiac mechanics can be derived from DENSE cardiac magnetic resonance in both humans and mice using a simplified technique to reduce post-processing time by approximately 94%. These findings demonstrate that quantifying cardiac mechanics from DENSE data is simple enough to be integrated into the clinical workflow. BioMed Central 2014-11-28 /pmc/articles/PMC4246464/ /pubmed/25430079 http://dx.doi.org/10.1186/s12968-014-0094-9 Text en © Suever et al.; licensee BioMed Central Ltd. 2014 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. 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 | Research Suever, Jonathan D Wehner, Gregory J Haggerty, Christopher M Jing, Linyuan Hamlet, Sean M Binkley, Cassi M Kramer, Sage P Mattingly, Andrea C Powell, David K Bilchick, Kenneth C Epstein, Frederick H Fornwalt, Brandon K Simplified post processing of cine DENSE cardiovascular magnetic resonance for quantification of cardiac mechanics |
title | Simplified post processing of cine DENSE cardiovascular magnetic resonance for quantification of cardiac mechanics |
title_full | Simplified post processing of cine DENSE cardiovascular magnetic resonance for quantification of cardiac mechanics |
title_fullStr | Simplified post processing of cine DENSE cardiovascular magnetic resonance for quantification of cardiac mechanics |
title_full_unstemmed | Simplified post processing of cine DENSE cardiovascular magnetic resonance for quantification of cardiac mechanics |
title_short | Simplified post processing of cine DENSE cardiovascular magnetic resonance for quantification of cardiac mechanics |
title_sort | simplified post processing of cine dense cardiovascular magnetic resonance for quantification of cardiac mechanics |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4246464/ https://www.ncbi.nlm.nih.gov/pubmed/25430079 http://dx.doi.org/10.1186/s12968-014-0094-9 |
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