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Comparison and calibration of a real-time virtual stenting algorithm using Finite Element Analysis and Genetic
K Spranger1, C Capelli2, G M Bosi2
1Department of Engineering Science, University of Oxford, Parks Road, Oxford OX1 3PJ, UK ; Department of Mechanical Engineering, University College London, UK.
Computer Methods in Applied Mechanics and Engineering
|December 15, 2015
Summary
This study compares a fast virtual stenting method with finite element analysis. Optimization using a genetic algorithm significantly improved accuracy, validating the fast method for computational simulations.
Area of Science:
- Biomedical Engineering
- Computational Mechanics
- Medical Device Simulation
Background:
- Accurate virtual stent deployment is crucial for pre-procedural planning.
- Detailed finite element analysis (FEA) is computationally intensive.
- A faster, reliable method for virtual stenting is needed.
Purpose of the Study:
- To compare a novel fast virtual stenting method with FEA.
- To optimize the fast method using a genetic algorithm.
- To validate the optimized fast method for clinical applications.
Main Methods:
- Comparative analysis of a spring-mass model-based fast stenting method against FEA.
- Optimization of the fast method's parameters via a genetic algorithm, using FEA results as a reference.
- Validation through assessment of force discrepancies and final device configurations.
Main Results:
- The genetic algorithm successfully calibrated parameters for the fast stenting method.
- Substantial reduction in force measure discrepancy between the fast and FEA methods was achieved.
- The optimized fast method demonstrated comparable final device configurations to FEA.
Conclusions:
- The optimized fast virtual stenting method offers a computationally efficient alternative to FEA.
- This validated method can aid in pre-procedural planning and medical device design.
- Further research can explore its application in diverse clinical scenarios.
