Validation of cardiac diffusion tensor imaging sequences: A multicentre test-retest phantom study.

Cardiac diffusion tensor imaging (DTI) is an emerging technique for the in vivo characterisation of myocardial microstructure, and there is a growing need for its validation and standardisation. We sought to establish the accuracy, precision, repeatability and reproducibility of state-of-the-art pulse sequences for cardiac DTI among 10 centres internationally. Phantoms comprising 0%-20% polyvinylpyrrolidone (PVP) were scanned with DTI using a product pulsed gradient spin echo (PGSE; N = 10 sites) sequence, and a custom motion-compensated spin echo (SE; N = 5) or stimulated echo acquisition mode (STEAM; N = 5) sequence suitable for cardiac DTI in vivo. A second identical scan was performed 1-9 days later, and the data were analysed centrally. The average mean diffusivities (MDs) in 0% PVP were (1.124, 1.130, 1.113) x 10-3  mm2 /s for PGSE, SE and STEAM, respectively, and accurate to within 1.5% of reference data from the literature. The coefficients of variation in MDs across sites were 2.6%, 3.1% and 2.1% for PGSE, SE and STEAM, respectively, and were similar to previous studies using only PGSE. Reproducibility in MD was excellent, with mean differences in PGSE, SE and STEAM of (0.3 ± 2.3, 0.24 ± 0.95, 0.52 ± 0.58) x 10-5  mm2 /s (mean ± 1.96 SD). We show that custom sequences for cardiac DTI provide accurate, precise, repeatable and reproducible measurements. Further work in anisotropic and/or deforming phantoms is warranted.

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 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.