Cargando…

Comparison of left ventricular strains and torsion derived from feature tracking and DENSE CMR

BACKGROUND: Cardiovascular magnetic resonance (CMR) feature tracking is increasingly used to quantify cardiac mechanics from cine CMR imaging, although validation against reference standard techniques has been limited. Furthermore, studies have suggested that commonly-derived metrics, such as peak g...

Descripción completa

Detalles Bibliográficos
Autores principales: Wehner, Gregory J., Jing, Linyuan, Haggerty, Christopher M., Suever, Jonathan D., Chen, Jing, Hamlet, Sean M., Feindt, Jared A., Dimitri Mojsejenko, W., Fogel, Mark A., Fornwalt, Brandon K.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6136226/
https://www.ncbi.nlm.nih.gov/pubmed/30208894
http://dx.doi.org/10.1186/s12968-018-0485-4
_version_ 1783354957642072064
author Wehner, Gregory J.
Jing, Linyuan
Haggerty, Christopher M.
Suever, Jonathan D.
Chen, Jing
Hamlet, Sean M.
Feindt, Jared A.
Dimitri Mojsejenko, W.
Fogel, Mark A.
Fornwalt, Brandon K.
author_facet Wehner, Gregory J.
Jing, Linyuan
Haggerty, Christopher M.
Suever, Jonathan D.
Chen, Jing
Hamlet, Sean M.
Feindt, Jared A.
Dimitri Mojsejenko, W.
Fogel, Mark A.
Fornwalt, Brandon K.
author_sort Wehner, Gregory J.
collection PubMed
description BACKGROUND: Cardiovascular magnetic resonance (CMR) feature tracking is increasingly used to quantify cardiac mechanics from cine CMR imaging, although validation against reference standard techniques has been limited. Furthermore, studies have suggested that commonly-derived metrics, such as peak global strain (reported in 63% of feature tracking studies), can be quantified using contours from just two frames – end-diastole (ED) and end-systole (ES) – without requiring tracking software. We hypothesized that mechanics derived from feature tracking would not agree with those derived from a reference standard (displacement-encoding with stimulated echoes (DENSE) imaging), and that peak strain from feature tracking would agree with that derived using simple processing of only ED and ES contours. METHODS: We retrospectively identified 88 participants with 186 pairs of DENSE and balanced steady state free precession (bSSFP) image slices acquired at the same locations across two institutions. Left ventricular (LV) strains, torsion, and dyssynchrony were quantified from both feature tracking (TomTec Imaging Systems, Circle Cardiovascular Imaging) and DENSE. Contour-based strains from bSSFP images were derived from ED and ES contours. Agreement was assessed with Bland-Altman analyses and coefficients of variation (CoV). All biases are reported in absolute percentage. RESULTS: Comparison results were similar for both vendor packages (TomTec and Circle), and thus only TomTec Imaging System data are reported in the abstract for simplicity. Compared to DENSE, mid-ventricular circumferential strain (Ecc) from feature tracking had acceptable agreement (bias: − 0.4%, p = 0.36, CoV: 11%). However, feature tracking significantly overestimated the magnitude of Ecc at the base (bias: − 4.0% absolute, p < 0.001, CoV: 18%) and apex (bias: − 2.4% absolute, p = 0.01, CoV: 15%), underestimated torsion (bias: − 1.4 deg/cm, p < 0.001, CoV: 41%), and overestimated dyssynchrony (bias: 26 ms, p < 0.001, CoV: 76%). Longitudinal strain (Ell) had borderline-acceptable agreement (bias: − 0.2%, p = 0.77, CoV: 19%). Contour-based strains had excellent agreement with feature tracking (biases: − 1.3–0.2%, CoVs: 3–7%). CONCLUSION: Compared to DENSE as a reference standard, feature tracking was inaccurate for quantification of apical and basal LV circumferential strains, longitudinal strain, torsion, and dyssynchrony. Feature tracking was only accurate for quantification of mid LV circumferential strain. Moreover, feature tracking is unnecessary for quantification of whole-slice strains (e.g. base, apex), since simplified processing of only ED and ES contours yields very similar results to those derived from feature tracking. Current feature tracking technology therefore has limited utility for quantification of cardiac mechanics. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12968-018-0485-4) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-6136226
institution National Center for Biotechnology Information
language English
publishDate 2018
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-61362262018-09-15 Comparison of left ventricular strains and torsion derived from feature tracking and DENSE CMR Wehner, Gregory J. Jing, Linyuan Haggerty, Christopher M. Suever, Jonathan D. Chen, Jing Hamlet, Sean M. Feindt, Jared A. Dimitri Mojsejenko, W. Fogel, Mark A. Fornwalt, Brandon K. J Cardiovasc Magn Reson Research BACKGROUND: Cardiovascular magnetic resonance (CMR) feature tracking is increasingly used to quantify cardiac mechanics from cine CMR imaging, although validation against reference standard techniques has been limited. Furthermore, studies have suggested that commonly-derived metrics, such as peak global strain (reported in 63% of feature tracking studies), can be quantified using contours from just two frames – end-diastole (ED) and end-systole (ES) – without requiring tracking software. We hypothesized that mechanics derived from feature tracking would not agree with those derived from a reference standard (displacement-encoding with stimulated echoes (DENSE) imaging), and that peak strain from feature tracking would agree with that derived using simple processing of only ED and ES contours. METHODS: We retrospectively identified 88 participants with 186 pairs of DENSE and balanced steady state free precession (bSSFP) image slices acquired at the same locations across two institutions. Left ventricular (LV) strains, torsion, and dyssynchrony were quantified from both feature tracking (TomTec Imaging Systems, Circle Cardiovascular Imaging) and DENSE. Contour-based strains from bSSFP images were derived from ED and ES contours. Agreement was assessed with Bland-Altman analyses and coefficients of variation (CoV). All biases are reported in absolute percentage. RESULTS: Comparison results were similar for both vendor packages (TomTec and Circle), and thus only TomTec Imaging System data are reported in the abstract for simplicity. Compared to DENSE, mid-ventricular circumferential strain (Ecc) from feature tracking had acceptable agreement (bias: − 0.4%, p = 0.36, CoV: 11%). However, feature tracking significantly overestimated the magnitude of Ecc at the base (bias: − 4.0% absolute, p < 0.001, CoV: 18%) and apex (bias: − 2.4% absolute, p = 0.01, CoV: 15%), underestimated torsion (bias: − 1.4 deg/cm, p < 0.001, CoV: 41%), and overestimated dyssynchrony (bias: 26 ms, p < 0.001, CoV: 76%). Longitudinal strain (Ell) had borderline-acceptable agreement (bias: − 0.2%, p = 0.77, CoV: 19%). Contour-based strains had excellent agreement with feature tracking (biases: − 1.3–0.2%, CoVs: 3–7%). CONCLUSION: Compared to DENSE as a reference standard, feature tracking was inaccurate for quantification of apical and basal LV circumferential strains, longitudinal strain, torsion, and dyssynchrony. Feature tracking was only accurate for quantification of mid LV circumferential strain. Moreover, feature tracking is unnecessary for quantification of whole-slice strains (e.g. base, apex), since simplified processing of only ED and ES contours yields very similar results to those derived from feature tracking. Current feature tracking technology therefore has limited utility for quantification of cardiac mechanics. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12968-018-0485-4) contains supplementary material, which is available to authorized users. BioMed Central 2018-09-13 /pmc/articles/PMC6136226/ /pubmed/30208894 http://dx.doi.org/10.1186/s12968-018-0485-4 Text en © The Author(s). 2018 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
Wehner, Gregory J.
Jing, Linyuan
Haggerty, Christopher M.
Suever, Jonathan D.
Chen, Jing
Hamlet, Sean M.
Feindt, Jared A.
Dimitri Mojsejenko, W.
Fogel, Mark A.
Fornwalt, Brandon K.
Comparison of left ventricular strains and torsion derived from feature tracking and DENSE CMR
title Comparison of left ventricular strains and torsion derived from feature tracking and DENSE CMR
title_full Comparison of left ventricular strains and torsion derived from feature tracking and DENSE CMR
title_fullStr Comparison of left ventricular strains and torsion derived from feature tracking and DENSE CMR
title_full_unstemmed Comparison of left ventricular strains and torsion derived from feature tracking and DENSE CMR
title_short Comparison of left ventricular strains and torsion derived from feature tracking and DENSE CMR
title_sort comparison of left ventricular strains and torsion derived from feature tracking and dense cmr
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6136226/
https://www.ncbi.nlm.nih.gov/pubmed/30208894
http://dx.doi.org/10.1186/s12968-018-0485-4
work_keys_str_mv AT wehnergregoryj comparisonofleftventricularstrainsandtorsionderivedfromfeaturetrackinganddensecmr
AT jinglinyuan comparisonofleftventricularstrainsandtorsionderivedfromfeaturetrackinganddensecmr
AT haggertychristopherm comparisonofleftventricularstrainsandtorsionderivedfromfeaturetrackinganddensecmr
AT sueverjonathand comparisonofleftventricularstrainsandtorsionderivedfromfeaturetrackinganddensecmr
AT chenjing comparisonofleftventricularstrainsandtorsionderivedfromfeaturetrackinganddensecmr
AT hamletseanm comparisonofleftventricularstrainsandtorsionderivedfromfeaturetrackinganddensecmr
AT feindtjareda comparisonofleftventricularstrainsandtorsionderivedfromfeaturetrackinganddensecmr
AT dimitrimojsejenkow comparisonofleftventricularstrainsandtorsionderivedfromfeaturetrackinganddensecmr
AT fogelmarka comparisonofleftventricularstrainsandtorsionderivedfromfeaturetrackinganddensecmr
AT fornwaltbrandonk comparisonofleftventricularstrainsandtorsionderivedfromfeaturetrackinganddensecmr