Robust automated calcification meshing for biomechanical cardiac digital twins
This addresses the problem of slow and manual meshing for researchers and clinicians in cardiovascular disease modeling, representing an incremental improvement over existing template-based methods.
The researchers tackled the bottleneck of manual reconstruction of calcified heart meshes for biomechanical simulations by developing an automated meshing algorithm, achieving a speed-up from several hours to about 1 minute and enabling accurate modeling of patient-specific aortic stenosis and Transcatheter Aortic Valve Replacement.
Calcification has significant influence over cardiovascular diseases and interventions. Detailed characterization of calcification is thus desired for predictive modeling, but calcified heart meshes for physics-driven simulations are still often reconstructed using manual operations. This poses a major bottleneck for large-scale adoption of computational simulations for research or clinical use. To address this, we propose an end-to-end automated meshing algorithm that enables robust incorporation of patient-specific calcification onto a given heart mesh. The algorithm provides a substantial speed-up from several hours of manual meshing to $\sim$1 minute of automated computation, and it solves an important problem that cannot be addressed with recent template registration-based heart meshing techniques. We validated our final calcified heart meshes with extensive simulations, demonstrating our ability to accurately model patient-specific aortic stenosis and Transcatheter Aortic Valve Replacement. Our method may serve as an important tool for accelerating the development and usage of physics-driven simulations for cardiac digital twins.