Key result
The distance regularization level set function performed better than the Gaussian-based function in improving computational complexity and surface tracking behaviors during thrombus growth simulation.
Why the study?
Computational models of thrombosis are of great importance in determining simulation performance.
A novel level set method using a distance regularization function improves the computational complexity and surface tracking of thrombus growth simulations.
May streamline thrombus simulations; leaves open clinical validation before research translation.
The computational model of thrombosis is of great importance that decides the simulation performance. In the present study, a hybrid particle-continuum model with plasma, vascular wall, and thrombus being continuum material and platelets being discrete particles, was developed to simulate the thrombus growth. In the computational model, the thrombus growth was reformulated as a novel continuum surface expansion problem implemented by a level set function due to its capability of effectively handling the topological changes comprising splitting and merging, rather than a traditional particle accumulation problem. Additionally, a Gaussian-based function and distance regularization function, served as speed functions to drive the thrombus growth, were proposed and compared in our study. Experiments demonstrated that the growing thrombus could retain the particle texture of platelets by both level set speed functions, while the distance regularization function performed better in improving computational complexity and surface tracking behaviors. Both simulations demonstrated better visuality in the progress of thrombosis, and the geometry shape of the virtual primary thrombi were similar to the realistic counterpart.
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Ma et al. (2021) studied Thrombosis. Distance regularization level set function vs. Gaussian-based function was evaluated on Computational complexity and surface tracking behaviors. The distance regularization level set function performed better than the Gaussian-based function in improving computational complexity and surface tracking behaviors during thrombus growth simulation.
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