Robust automated calcification meshing for biomechanical cardiac digital
  twins
Daniel H. Pak Minliang Liu Theodore Kim Caglar Ozturk Raymond McKay Ellen T. Roche Rudolph Gleason James S. Duncan
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.