Key result
Curvature-based RV morphing improves shape controllability over random point selection despite higher sensitivity to anomalies.
Why the study?
Segmenting the wetted surface for ventricular wall meshes in fluid dynamics simulations presents challenges, particularly in the right ventricle due to its significantly thinner parietal thickness compared to the left ventricle.
A curvature-based approach for selecting control points in RBF morphing improves the controllability of right ventricle 3D reconstructions, though at the cost of higher computational demands and sensitivity to vertex anomalies.
Curvature-based RBF morphing may refine RV computational models; leaves open clinical translation pending robustness validation.
In the realm of cardiac health research, accurate fluid dynamics simulations are vital for comprehending the heart function and diagnosing conditions. Central to these simulations is the precision of ventricular wall meshes used to model heart geometry. However, segmenting the wetted surface, particularly in the right ventricle (RV) with its significantly thinner parietal thickness compared to the left ventricle, presents challenges. This study focuses on qualitatively evaluating an automated reconstruction model for the RV’s outer wall using Radial Basis function (RBF) morphing. Two procedural criteria were compared, a random selection of control points and a curvature-based approach, which differ in terms of the identification of the control points of the RBF function. From these considerations, it emerges that a controlled use of the RBF function on the basis of the curvatures guarantees the greater controllability of the shape evolutions of the parietal structure of the RV, but it is more sensitive to any anomalies in the distribution of the vertices, as can be seen from the number of outliers, and its controllability is a function of the percentage of points chosen, exerting a greater impact on the required computational capacity. The definition of a strategic criterion for the selection of control points could represent a crucial aspect in the definition of an automatic reconstruction procedure of anatomical elements, which guarantees a morphological variability in line with the need to expand the pathological sample to be used for statistical formulations in the clinical field.
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Fontana et al. (2024) studied Right ventricle reconstruction. Curvature-based approach for RBF morphing vs. Random selection of control points was evaluated on Qualitative evaluation of shape evolutions and sensitivity to anomalies. A curvature-based approach for Radial Basis function morphing of the right ventricle provided greater shape controllability than random point selection, despite higher sensitivity to vertex anomalies.
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