Key result
A novel volumetric parcellation method for the right ventricle based on geodesic distances demonstrated intra- and inter-observer reproducibility errors of 7-12% and 10-23%, respectively.
Why the study?
Regional quantification of right ventricular geometry and function by 3D echocardiography is limited by lower spatial and temporal resolution and scarce identifiable intracavity anatomical landmarks.
A novel volumetric parcellation method for the right ventricle using 3D echocardiography demonstrates acceptable reproducibility and can capture clinically relevant regional remodeling.
Acceptable reproducibility supports regional RV analysis by 3D echo; leaves open larger validation before clinical adoption.
3D echocardiography is an increasingly popular tool for assessing cardiac remodelling in the right ventricle (RV). It allows quantification of the cardiac chambers without any geometric assumptions, which is the main weakness of 2D echocardiography. However, regional quantification of geometry and function is limited by the lower spatial and temporal resolution and the scarcity of identifiable anatomical landmarks, especially within the ventricular cavity. We developed a technique for regionally assessing the volume of 3 relevant RV volumetric regions: apical, inlet and outflow. The proposed parcellation method is based on the geodesic distances to anatomical landmarks that are easily identifiable in the images: the apex and the tricuspid and pulmonary valves, each associated to a region. Based on these distances, we define a partition in the endocardium at end-diastole (ED). This partition is then interpolated to the blood cavity using the Laplace equation, which allows to compute regional volumes. For obtaining an end-systole (ES) partition, the endocardial partition is transported from ED to ES using a commercial image-based tracking software, and then the interpolation process is repeated. We assessed the intra- and inter-observer reproducibility using a 10-subjects dataset containing repeated quantifications of the same images, obtaining intra- and inter- observer errors (7-12% and 10-23% respectively). Finally, we propose a novel synthetic mesh generation algorithm that deforms a template mesh imposing a user-defined strain to a template mesh. We used this method to create a new dataset for involving distinct types of remodelling that were used to assess the sensitivity of the parcellation method to identify volume changes affecting different parts. We show that the parcellation method is adequate for capturing local circumferential and global circumferential and longitudinal RV remodelling, which are the most clinically relevant cases.
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Bernardino et al. (2021) studied Healthy (n=11). Volumetric parcellation method based on geodesic distances was evaluated on Intra- and inter-observer reproducibility errors. A novel volumetric parcellation method for the right ventricle based on geodesic distances demonstrated intra- and inter-observer reproducibility errors of 7-12% and 10-23%, respectively.
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