Cargando…

CMRSegTools: An open-source software enabling reproducible research in segmentation of acute myocardial infarct in CMR images

In the last decade, a large number of clinical trials have been deployed using Cardiac Magnetic Resonance (CMR) to evaluate cardioprotective strategies aiming at reducing the irreversible myocardial damage at the time of reperfusion. In these studies, segmentation and quantification of myocardial in...

Descripción completa

Detalles Bibliográficos
Autores principales: Romero R., William A., Viallon, Magalie, Spaltenstein, Joël, Petrusca, Lorena, Bernard, Olivier, Belle, Loïc, Clarysse, Patrick, Croisille, Pierre
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9469999/
https://www.ncbi.nlm.nih.gov/pubmed/36099286
http://dx.doi.org/10.1371/journal.pone.0274491
_version_ 1784788755526189056
author Romero R., William A.
Viallon, Magalie
Spaltenstein, Joël
Petrusca, Lorena
Bernard, Olivier
Belle, Loïc
Clarysse, Patrick
Croisille, Pierre
author_facet Romero R., William A.
Viallon, Magalie
Spaltenstein, Joël
Petrusca, Lorena
Bernard, Olivier
Belle, Loïc
Clarysse, Patrick
Croisille, Pierre
author_sort Romero R., William A.
collection PubMed
description In the last decade, a large number of clinical trials have been deployed using Cardiac Magnetic Resonance (CMR) to evaluate cardioprotective strategies aiming at reducing the irreversible myocardial damage at the time of reperfusion. In these studies, segmentation and quantification of myocardial infarct lesion are often performed with a commercial software or an in-house closed-source code development thus creating a barrier for reproducible research. This paper introduces CMRSegTools: an open-source application software designed for the segmentation and quantification of myocardial infarct lesion enabling full access to state-of-the-art segmentation methods and parameters, easy integration of new algorithms and standardised results sharing. This post-processing tool has been implemented as a plug-in for the OsiriX/Horos DICOM viewer leveraging its database management functionalities and user interaction features to provide a bespoke tool for the analysis of cardiac MR images on large clinical cohorts. CMRSegTools includes, among others, user-assisted segmentation of the left-ventricle, semi- and automatic lesion segmentation methods, advanced statistical analysis and visualisation based on the American Heart Association 17-segment model. New segmentation methods can be integrated into the plug-in by developing components based on image processing and visualisation libraries such as ITK and VTK in C++ programming language. CMRSegTools allows the creation of training and testing data sets (labeled features such as lesion, microvascular obstruction and remote ROI) for supervised Machine Learning methods, and enables the comparative assessment of lesion segmentation methods via a single and integrated platform. The plug-in has been successfully used by several CMR imaging studies.
format Online
Article
Text
id pubmed-9469999
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-94699992022-09-14 CMRSegTools: An open-source software enabling reproducible research in segmentation of acute myocardial infarct in CMR images Romero R., William A. Viallon, Magalie Spaltenstein, Joël Petrusca, Lorena Bernard, Olivier Belle, Loïc Clarysse, Patrick Croisille, Pierre PLoS One Research Article In the last decade, a large number of clinical trials have been deployed using Cardiac Magnetic Resonance (CMR) to evaluate cardioprotective strategies aiming at reducing the irreversible myocardial damage at the time of reperfusion. In these studies, segmentation and quantification of myocardial infarct lesion are often performed with a commercial software or an in-house closed-source code development thus creating a barrier for reproducible research. This paper introduces CMRSegTools: an open-source application software designed for the segmentation and quantification of myocardial infarct lesion enabling full access to state-of-the-art segmentation methods and parameters, easy integration of new algorithms and standardised results sharing. This post-processing tool has been implemented as a plug-in for the OsiriX/Horos DICOM viewer leveraging its database management functionalities and user interaction features to provide a bespoke tool for the analysis of cardiac MR images on large clinical cohorts. CMRSegTools includes, among others, user-assisted segmentation of the left-ventricle, semi- and automatic lesion segmentation methods, advanced statistical analysis and visualisation based on the American Heart Association 17-segment model. New segmentation methods can be integrated into the plug-in by developing components based on image processing and visualisation libraries such as ITK and VTK in C++ programming language. CMRSegTools allows the creation of training and testing data sets (labeled features such as lesion, microvascular obstruction and remote ROI) for supervised Machine Learning methods, and enables the comparative assessment of lesion segmentation methods via a single and integrated platform. The plug-in has been successfully used by several CMR imaging studies. Public Library of Science 2022-09-13 /pmc/articles/PMC9469999/ /pubmed/36099286 http://dx.doi.org/10.1371/journal.pone.0274491 Text en © 2022 Romero R. et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Romero R., William A.
Viallon, Magalie
Spaltenstein, Joël
Petrusca, Lorena
Bernard, Olivier
Belle, Loïc
Clarysse, Patrick
Croisille, Pierre
CMRSegTools: An open-source software enabling reproducible research in segmentation of acute myocardial infarct in CMR images
title CMRSegTools: An open-source software enabling reproducible research in segmentation of acute myocardial infarct in CMR images
title_full CMRSegTools: An open-source software enabling reproducible research in segmentation of acute myocardial infarct in CMR images
title_fullStr CMRSegTools: An open-source software enabling reproducible research in segmentation of acute myocardial infarct in CMR images
title_full_unstemmed CMRSegTools: An open-source software enabling reproducible research in segmentation of acute myocardial infarct in CMR images
title_short CMRSegTools: An open-source software enabling reproducible research in segmentation of acute myocardial infarct in CMR images
title_sort cmrsegtools: an open-source software enabling reproducible research in segmentation of acute myocardial infarct in cmr images
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9469999/
https://www.ncbi.nlm.nih.gov/pubmed/36099286
http://dx.doi.org/10.1371/journal.pone.0274491
work_keys_str_mv AT romerorwilliama cmrsegtoolsanopensourcesoftwareenablingreproducibleresearchinsegmentationofacutemyocardialinfarctincmrimages
AT viallonmagalie cmrsegtoolsanopensourcesoftwareenablingreproducibleresearchinsegmentationofacutemyocardialinfarctincmrimages
AT spaltensteinjoel cmrsegtoolsanopensourcesoftwareenablingreproducibleresearchinsegmentationofacutemyocardialinfarctincmrimages
AT petruscalorena cmrsegtoolsanopensourcesoftwareenablingreproducibleresearchinsegmentationofacutemyocardialinfarctincmrimages
AT bernardolivier cmrsegtoolsanopensourcesoftwareenablingreproducibleresearchinsegmentationofacutemyocardialinfarctincmrimages
AT belleloic cmrsegtoolsanopensourcesoftwareenablingreproducibleresearchinsegmentationofacutemyocardialinfarctincmrimages
AT claryssepatrick cmrsegtoolsanopensourcesoftwareenablingreproducibleresearchinsegmentationofacutemyocardialinfarctincmrimages
AT croisillepierre cmrsegtoolsanopensourcesoftwareenablingreproducibleresearchinsegmentationofacutemyocardialinfarctincmrimages