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...

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Bibliographic Details
Published in:PloS one 2022-09, Vol.17 (9), p.e0274491-e0274491
Main Authors: Romero R., William A, Viallon, Magalie, Spaltenstein, Joël, Petrusca, Lorena, Bernard, Olivier, Belle, Loïc, Clarysse, Patrick, Croisille, Pierre
Format: Article
Language:English
Subjects:
Algorithms
Biology and Life Sciences
Clinical trials
Collaboration
Computer and Information Sciences
Computer Science
Diagnosis
Engineering and Technology
Evaluation
Heart
Heart attack
Image processing
Image segmentation
Interoperability
Itk protein
Keywords
Lesions
Machine learning
Magnetic resonance
Magnetic resonance imaging
Medical imaging
Medicine and Health Sciences
Microvasculature
Myocardial infarction
Open source software
Plugs
Programming languages
Public domain
Public software
R&D
Reperfusion
Research & development
Research and Analysis Methods
Science Policy
Software
Source code
Statistical analysis
Statistical methods
User interface
Ventricle
Visualization
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Summary: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.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0274491