Defibrillator Tech: How New Models Improve Heart Treatment
"Researchers are using computer models to improve defibrillator placement and performance, making them safer and more effective for patients of all ages."
Implantable cardioverter-defibrillators (ICDs) are essential for preventing life-threatening arrhythmias, with approximately 100,000 implantations performed each year. However, finding the optimal placement for these devices can be challenging, especially in children and individuals with unique anatomies. This has led to the exploration of alternative configurations, such as placing the ICD generator in the abdomen or eliminating leads in the subclavian vein, to improve device efficiency and safety.
Unnecessary or overly strong shocks from ICDs can have negative consequences, potentially altering calcium dynamics in cardiac tissue and inhibiting normal cell contraction. This has motivated the development of new implantation strategies, including subcutaneous ICDs and wearable external defibrillation devices. However, each new approach requires optimization and testing, which can be a slow process that involves animal and human experiments.
To speed up this process, researchers have developed computational models and computer simulations to optimize and test ICDs. These models can predict the potential field throughout the torso during defibrillation and estimate the defibrillation threshold (DFT), which is the lowest level of energy needed for successful defibrillation. While previous studies have shown the accuracy of these simulation pipelines in predicting threshold energy, more detailed validation is needed to assess how well the models predict the actual distribution of potential over the heart and thorax.
How Computer Models are Validating Defibrillator Performance
To validate the defibrillation simulation pipeline, researchers measured body-surface potentials during ICD shocks and the DFTs of patients undergoing ICD implantation. These data were then compared to the values predicted by the simulation. The validation process involved three main steps: adapting a limited lead selection and body surface estimation algorithm for use with ICD potential maps, recording ICD potential maps and DFTs for each patient, and generating patient-specific models to predict the potential field and DFT for comparison with recorded values.
- Limited Lead Selection: Identifying the best spots for leads to capture unique electrical signals.
- Body Surface Estimation: Using statistical models to predict the full potential map from limited data.
- Simulation Training: Training the algorithm with thousands of simulated potential maps to ensure accuracy.
The Future of Defibrillator Technology
This study demonstrates the effectiveness of using computer simulations to predict defibrillation potentials in humans. The high agreement between simulated and measured potential maps and DFTs suggests that predictive simulations can generate realistic potential values and accurately predict DFTs in patients. These validation results pave the way for using this model in optimization studies before device implantation, potentially leading to improved ICD placement and reduced unnecessary shocks for patients.