Robust automated calcification meshing for biomechanical cardiac digital twins

TL;DR

This paper presents an automated meshing algorithm that efficiently incorporates calcification into heart models, significantly reducing manual effort and enabling large-scale, patient-specific cardiac simulations.

Contribution

The authors introduce a fully automated, robust meshing method for calcified hearts that outperforms existing template registration techniques in speed and accuracy.

Findings

Speed-up from hours to about 1 minute for meshing

Accurate modeling of patient-specific calcification effects

Validated through simulations of aortic stenosis and valve replacement

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.