Towards standardized postprocessing of global longitudinal strain by feature tracking - OptiStrain CMR-FT study.


Journal

BMC cardiovascular disorders
ISSN: 1471-2261
Titre abrégé: BMC Cardiovasc Disord
Pays: England
ID NLM: 100968539

Informations de publication

Date de publication:
27 11 2019
Historique:
received: 22 02 2019
accepted: 12 11 2019
entrez: 29 11 2019
pubmed: 30 11 2019
medline: 27 5 2020
Statut: epublish

Résumé

Left ventricular global longitudinal strain (GLS) with cardiovascular magnetic resonance (CMR) is an important prognostic biomarker. Its everyday clinical use is limited due to methodological and postprocessing diversity among the users and vendors. Standardization of postprocessing approaches may reduce the random operator-dependent variability, allowing for comparability of measurements despite the systematic vendor-related differences. We investigated the random component of variability in GLS measurements by optimization steps which incrementally improved observer reproducibility and agreement. Cine images in two-, three- and four-chamber-views were serially analysed by two independent observers using two different CMR-FT softwares. The disparity of outcomes after each series was systematically assessed after a number of stepwise adjustments which were shown to significantly reduce the inter-observer and intervendor bias, resulting standardized postprocessing approach. The final analysis was performed in 44 subjects (ischaemic heart disease n = 15, non-ischaemic dilated cardiomyopathy, n = 19, healthy controls, n = 10). All measurements were performed blind to the underlying group allocation and previous measurements. Inter- and intra-observer variability were tested using Bland-Altman analyses, intra-class correlation coefficients (ICCs) and coefficients of variation (CVs). Compared to controls, mean GLS was significantly lower in patients, as well as between the two subgroups (p < 0.01). These differences were accentuated by standardization procedures, with significant increase in Cohen's D and AUCs. The benefit of standardization was also evident through improved CV and ICC agreements between observers and the two vendors. Initial intra-observer variability CVs for GLS parameters were 7.6 and 4.6%, inter-observer variability CVs were 11 and 4.7%, for the two vendors, respectively. After standardization, intra- and interobserver variability CVs were 3.1 and 4.3%, and 5.2 and 4.4%, respectively. Standardization of GLS postprocessing helps to reduce the random component of variability, introduced by inconsistencies of and between observers, and also intervendor variability, but not the systematic inter-vendor bias due to differences in image processing algorithms. Standardization of GLS measurements is an essential step in ensuring the reliable quantification of myocardial deformation, and implementation of CMR-FT in clinical routine.

Sections du résumé

BACKGROUND
Left ventricular global longitudinal strain (GLS) with cardiovascular magnetic resonance (CMR) is an important prognostic biomarker. Its everyday clinical use is limited due to methodological and postprocessing diversity among the users and vendors. Standardization of postprocessing approaches may reduce the random operator-dependent variability, allowing for comparability of measurements despite the systematic vendor-related differences.
METHODS
We investigated the random component of variability in GLS measurements by optimization steps which incrementally improved observer reproducibility and agreement. Cine images in two-, three- and four-chamber-views were serially analysed by two independent observers using two different CMR-FT softwares. The disparity of outcomes after each series was systematically assessed after a number of stepwise adjustments which were shown to significantly reduce the inter-observer and intervendor bias, resulting standardized postprocessing approach. The final analysis was performed in 44 subjects (ischaemic heart disease n = 15, non-ischaemic dilated cardiomyopathy, n = 19, healthy controls, n = 10). All measurements were performed blind to the underlying group allocation and previous measurements. Inter- and intra-observer variability were tested using Bland-Altman analyses, intra-class correlation coefficients (ICCs) and coefficients of variation (CVs).
RESULTS
Compared to controls, mean GLS was significantly lower in patients, as well as between the two subgroups (p < 0.01). These differences were accentuated by standardization procedures, with significant increase in Cohen's D and AUCs. The benefit of standardization was also evident through improved CV and ICC agreements between observers and the two vendors. Initial intra-observer variability CVs for GLS parameters were 7.6 and 4.6%, inter-observer variability CVs were 11 and 4.7%, for the two vendors, respectively. After standardization, intra- and interobserver variability CVs were 3.1 and 4.3%, and 5.2 and 4.4%, respectively.
CONCLUSION
Standardization of GLS postprocessing helps to reduce the random component of variability, introduced by inconsistencies of and between observers, and also intervendor variability, but not the systematic inter-vendor bias due to differences in image processing algorithms. Standardization of GLS measurements is an essential step in ensuring the reliable quantification of myocardial deformation, and implementation of CMR-FT in clinical routine.

Identifiants

pubmed: 31775656
doi: 10.1186/s12872-019-1255-4
pii: 10.1186/s12872-019-1255-4
pmc: PMC6882184
doi:

Types de publication

Journal Article Multicenter Study Observational Study Video-Audio Media

Langues

eng

Sous-ensembles de citation

IM

Pagination

267

Subventions

Organisme : DZHK
ID : none
Pays : International

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Auteurs

Robert Heinke (R)

Institute of Experimental and Translational Cardiac Imaging DZHK Centre for Cardiovascular Imaging Goethe University Hospital Frankfurt, Theodor-Stern Kai 7, 60590, Frankfurt am Main, Germany.

Faraz Pathan (F)

Institute of Experimental and Translational Cardiac Imaging DZHK Centre for Cardiovascular Imaging Goethe University Hospital Frankfurt, Theodor-Stern Kai 7, 60590, Frankfurt am Main, Germany.
Department of Cardiovascular Imaging, Menzies Institute for Medical Research, Hobart, Tasmania, Australia.

Melanie Le (M)

Institute of Experimental and Translational Cardiac Imaging DZHK Centre for Cardiovascular Imaging Goethe University Hospital Frankfurt, Theodor-Stern Kai 7, 60590, Frankfurt am Main, Germany.

Tommaso D'Angelo (T)

Institute of Experimental and Translational Cardiac Imaging DZHK Centre for Cardiovascular Imaging Goethe University Hospital Frankfurt, Theodor-Stern Kai 7, 60590, Frankfurt am Main, Germany.
Department of Biomedical Sciences and Morphological and Functional Imaging, G. Martino University Hospital Messina, Messina, Italy.

Lea Winau (L)

Institute of Experimental and Translational Cardiac Imaging DZHK Centre for Cardiovascular Imaging Goethe University Hospital Frankfurt, Theodor-Stern Kai 7, 60590, Frankfurt am Main, Germany.

Christophe Arendt (C)

Department of Radiology, Goethe University Hospital Frankfurt, Frankfurt-am Main, Germany.

Thomas J Vogl (TJ)

Department of Radiology, Goethe University Hospital Frankfurt, Frankfurt-am Main, Germany.

Andreas Zeiher (A)

Department of Cardiology, Goethe University Hospital Frankfurt, Frankfurt-am Main, Germany.

Eike Nagel (E)

Institute of Experimental and Translational Cardiac Imaging DZHK Centre for Cardiovascular Imaging Goethe University Hospital Frankfurt, Theodor-Stern Kai 7, 60590, Frankfurt am Main, Germany.

Valentina O Puntmann (VO)

Institute of Experimental and Translational Cardiac Imaging DZHK Centre for Cardiovascular Imaging Goethe University Hospital Frankfurt, Theodor-Stern Kai 7, 60590, Frankfurt am Main, Germany. valentina.puntmann@icloud.com.
Department of Cardiology, Goethe University Hospital Frankfurt, Frankfurt-am Main, Germany. valentina.puntmann@icloud.com.

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Classifications MeSH