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Cardiovascular magnetic resonance myocardial feature tracking using a non-rigid, elastic image registration algorithm: assessment of variability in a real-life clinical setting

BACKGROUND: Cardiovascular magnetic resonance myocardial feature tracking (CMR-FT) is a promising technique for quantification of myocardial strain from steady-state free precession (SSFP) cine images. We sought to determine the variability of CMR-FT using a non-rigid elastic registration algorithm...

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Autores principales: Morais, Pedro, Marchi, Alberto, Bogaert, Julie A., Dresselaers, Tom, Heyde, Brecht, D’hooge, Jan, Bogaert, Jan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5314711/
https://www.ncbi.nlm.nih.gov/pubmed/28209163
http://dx.doi.org/10.1186/s12968-017-0333-y
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author Morais, Pedro
Marchi, Alberto
Bogaert, Julie A.
Dresselaers, Tom
Heyde, Brecht
D’hooge, Jan
Bogaert, Jan
author_facet Morais, Pedro
Marchi, Alberto
Bogaert, Julie A.
Dresselaers, Tom
Heyde, Brecht
D’hooge, Jan
Bogaert, Jan
author_sort Morais, Pedro
collection PubMed
description BACKGROUND: Cardiovascular magnetic resonance myocardial feature tracking (CMR-FT) is a promising technique for quantification of myocardial strain from steady-state free precession (SSFP) cine images. We sought to determine the variability of CMR-FT using a non-rigid elastic registration algorithm recently available in a commercial software package (Segment, Medviso) in a real-life clinical setting. METHODS: Firstly, we studied the variability in a healthy volunteer who underwent 10 CMR studies over five consecutive days. Secondly, 10 patients were selected from our CMR database yielding normal findings (normal group). Finally, we prospectively studied 10 patients with known or suspected myocardial pathology referred for further investigation to CMR (patient group). In the patient group a second study was performed respecting an interval of 30 min between studies. All studies were manually segmented at the end-diastolic phase by three observers. In all subjects left ventricular (LV) circumferential and radial strain were calculated in the short-axis direction (Ecc(SAX) and Err(SAX,) respectively) and longitudinal strain in the long-axis direction (Ell(LAX)). The level of CMR experience of the observers was 2 weeks, 6 months and >20 years. RESULTS: Mean contouring time was 7 ± 1 min, mean FT calculation time 13 ± 2 min. Intra- and inter-observer variability was good to excellent with an coefficient of reproducibility (CR) ranging 1.6% to 11.5%, and 1.7% to 16.0%, respectively and an intraclass correlation coefficient (ICC) ranging 0.89 to 1.00 and 0.74 to 0.99, respectively. Variability considerably increased in the test-retest setting with a CR ranging 4.2% to 29.1% and an ICC ranging 0.66 to 0.95 in the patient group. Variability was not influenced by level of expertise of the observers. Neither did the presence of myocardial pathology at CMR negatively impact variability. However, compared to global myocardial strain, segmental myocardial strain variability increased with a factor 2–3, in particular for the basal and apical short-axis slices. CONCLUSIONS: CMR-FT using non-rigid, elastic registration is a reproducible approach for strain analysis in patients routinely scheduled for CMR, and is not influenced by the level of training. However, further improvement is needed to reliably depict small variations in segmental myocardial strain. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12968-017-0333-y) contains supplementary material, which is available to authorized users.
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spelling pubmed-53147112017-02-24 Cardiovascular magnetic resonance myocardial feature tracking using a non-rigid, elastic image registration algorithm: assessment of variability in a real-life clinical setting Morais, Pedro Marchi, Alberto Bogaert, Julie A. Dresselaers, Tom Heyde, Brecht D’hooge, Jan Bogaert, Jan J Cardiovasc Magn Reson Research BACKGROUND: Cardiovascular magnetic resonance myocardial feature tracking (CMR-FT) is a promising technique for quantification of myocardial strain from steady-state free precession (SSFP) cine images. We sought to determine the variability of CMR-FT using a non-rigid elastic registration algorithm recently available in a commercial software package (Segment, Medviso) in a real-life clinical setting. METHODS: Firstly, we studied the variability in a healthy volunteer who underwent 10 CMR studies over five consecutive days. Secondly, 10 patients were selected from our CMR database yielding normal findings (normal group). Finally, we prospectively studied 10 patients with known or suspected myocardial pathology referred for further investigation to CMR (patient group). In the patient group a second study was performed respecting an interval of 30 min between studies. All studies were manually segmented at the end-diastolic phase by three observers. In all subjects left ventricular (LV) circumferential and radial strain were calculated in the short-axis direction (Ecc(SAX) and Err(SAX,) respectively) and longitudinal strain in the long-axis direction (Ell(LAX)). The level of CMR experience of the observers was 2 weeks, 6 months and >20 years. RESULTS: Mean contouring time was 7 ± 1 min, mean FT calculation time 13 ± 2 min. Intra- and inter-observer variability was good to excellent with an coefficient of reproducibility (CR) ranging 1.6% to 11.5%, and 1.7% to 16.0%, respectively and an intraclass correlation coefficient (ICC) ranging 0.89 to 1.00 and 0.74 to 0.99, respectively. Variability considerably increased in the test-retest setting with a CR ranging 4.2% to 29.1% and an ICC ranging 0.66 to 0.95 in the patient group. Variability was not influenced by level of expertise of the observers. Neither did the presence of myocardial pathology at CMR negatively impact variability. However, compared to global myocardial strain, segmental myocardial strain variability increased with a factor 2–3, in particular for the basal and apical short-axis slices. CONCLUSIONS: CMR-FT using non-rigid, elastic registration is a reproducible approach for strain analysis in patients routinely scheduled for CMR, and is not influenced by the level of training. However, further improvement is needed to reliably depict small variations in segmental myocardial strain. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12968-017-0333-y) contains supplementary material, which is available to authorized users. BioMed Central 2017-02-17 /pmc/articles/PMC5314711/ /pubmed/28209163 http://dx.doi.org/10.1186/s12968-017-0333-y Text en © The Author(s). 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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
Morais, Pedro
Marchi, Alberto
Bogaert, Julie A.
Dresselaers, Tom
Heyde, Brecht
D’hooge, Jan
Bogaert, Jan
Cardiovascular magnetic resonance myocardial feature tracking using a non-rigid, elastic image registration algorithm: assessment of variability in a real-life clinical setting
title Cardiovascular magnetic resonance myocardial feature tracking using a non-rigid, elastic image registration algorithm: assessment of variability in a real-life clinical setting
title_full Cardiovascular magnetic resonance myocardial feature tracking using a non-rigid, elastic image registration algorithm: assessment of variability in a real-life clinical setting
title_fullStr Cardiovascular magnetic resonance myocardial feature tracking using a non-rigid, elastic image registration algorithm: assessment of variability in a real-life clinical setting
title_full_unstemmed Cardiovascular magnetic resonance myocardial feature tracking using a non-rigid, elastic image registration algorithm: assessment of variability in a real-life clinical setting
title_short Cardiovascular magnetic resonance myocardial feature tracking using a non-rigid, elastic image registration algorithm: assessment of variability in a real-life clinical setting
title_sort cardiovascular magnetic resonance myocardial feature tracking using a non-rigid, elastic image registration algorithm: assessment of variability in a real-life clinical setting
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5314711/
https://www.ncbi.nlm.nih.gov/pubmed/28209163
http://dx.doi.org/10.1186/s12968-017-0333-y
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