Robust automated calcification meshing for biomechanical cardiac digital twins (2403.04998v1)
Abstract: 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.
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- Daniel H. Pak (6 papers)
- Minliang Liu (4 papers)
- Theodore Kim (7 papers)
- Caglar Ozturk (2 papers)
- Raymond McKay (2 papers)
- Ellen T. Roche (2 papers)
- Rudolph Gleason (1 paper)
- James S. Duncan (67 papers)