Univ Lyon, INSA-Lyon, Université Claude Bernard Lyon 1, UJM-Saint Etienne, CNRS, Inserm, CREATIS UMR 5220, U1294, Saint Etienne, France.
Spaltenstein Natural Image, Geneva, Switzerland.
PLoS One. 2022 Sep 13;17(9):e0274491. doi: 10.1371/journal.pone.0274491. eCollection 2022.
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.
在过去的十年中,已经部署了大量的临床试验,使用心脏磁共振(CMR)来评估旨在减少再灌注时不可逆心肌损伤的心脏保护策略。在这些研究中,心肌梗死病变的分割和定量通常使用商业软件或内部闭源代码开发来完成,从而为可重复性研究造成了障碍。本文介绍了 CMRSegTools:一个用于心肌梗死病变分割和定量的开源应用软件,它可以完全访问最新的分割方法和参数,轻松集成新的算法,并实现标准化的结果共享。这个后处理工具已作为 OsiriX/Horos DICOM 查看器的插件实现,利用其数据库管理功能和用户交互功能,为大型临床队列的心脏磁共振图像分析提供了专用工具。CMRSegTools 包括用户辅助的左心室分割、半自动和自动病变分割方法、基于美国心脏协会 17 节段模型的高级统计分析和可视化等功能。新的分割方法可以通过基于图像处理和可视化库(如 ITK 和 VTK)的 C++编程语言开发组件来集成到插件中。CMRSegTools 允许为监督机器学习方法创建训练和测试数据集(例如病变、微血管阻塞和远程 ROI 等标记特征),并通过单个集成平台来比较评估病变分割方法。该插件已成功用于多个 CMR 成像研究。