An algorithm for coupling multibranch in vitro experiment to numerical physiology simulation for a hybrid...

Area of Science:

• Biomedical Engineering
• Computational Physiology
• Medical Device Testing

Background:

• Hybrid cardiovascular modeling integrates physical experiments with computational simulations.
• Accurate coupling between in vitro and computational domains is crucial for dynamic interaction analysis.
• Existing methods face challenges in integrating multi-branched in vitro setups with complex physiological models.

Purpose of the Study:

• To develop and validate an iterative algorithm for coupling multi-branched in vitro experiments with lumped-parameter cardiovascular simulations.
• To enable direct physical testing of medical devices within a closed-loop physiological context.
• To assess the accuracy and robustness of the developed coupling algorithm.

Main Methods:

• Developed an iterative algorithm using Broyden's approach to identify unique flow waveform solutions for each branch.
• Utilized mathematical surrogates of in vitro experiments for algorithm testing and validation against known "true solutions".
• Coupled surrogates to a lumped-parameter model of a Fontan patient's physiology across five distinct scenarios.
• Introduced random noise to surrogate models to emulate realistic experimental conditions and assess algorithm robustness.

Main Results:

• The algorithm successfully identified accurate flow waveforms in all tested scenarios, closely matching true solutions.
• Convergence was achieved in under 130 iterations across all test cases.
• The coupling algorithm maintained high accuracy even when noise was added to the surrogate models, with convergence tolerance below noise magnitude.
• Demonstrated real-world applicability by coupling a physical experiment to a computational model.

Conclusions:

• The developed iterative algorithm effectively couples multi-branched in vitro experiments with lumped-parameter cardiovascular models.
• This hybrid approach provides a validated and accurate method for testing medical devices in a simulated closed-loop physiological environment.
• The algorithm's robustness to noise and high accuracy demonstrate its potential for advancing cardiovascular research and medical device development.