Robust automated calcification meshing for biomechanical cardiac digital twins

• URL: http://arxiv.org/abs/2403.04998v1
• Date: Fri, 8 Mar 2024 02:25:44 GMT
• Title: Robust automated calcification meshing for biomechanical cardiac digital twins
• Authors: Daniel H. Pak, Minliang Liu, Theodore Kim, Caglar Ozturk, Raymond McKay, Ellen T. Roche, Rudolph Gleason, James S. Duncan
• Abstract summary: 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.
• Score: 7.253614989403737
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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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