Computational Model for Pediatric ICD Placement Optimization
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Solution Overview
Problem
There is no reliable method to predict the optimal placement of cardiac defibrillator devices in pediatric and congenital heart disease patients, particularly when transvenous lead ICD configurations are not feasible, leading to higher defibrillation and cardioversion thresholds that can cause cardiac damage and trauma.
Innovation Solution
A computational method using three-dimensional imaging and modeling to determine the placement of cardiac defibrillators, incorporating active properties in the ventricular mesh and simulating defibrillation to identify the lowest defibrillation and cardioversion thresholds, which involves obtaining images, generating a mesh, and testing various ICD configurations to find the most favorable placement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If non-standard ICD configurations are used in pediatric and congenital heart defect patients, then the defibrillator can be implanted when transvenous lead ICD is not feasible, but the defibrillation threshold and cardioversion threshold increase leading to cardiac damage and trauma
Solution Approach 1:
The computational model predicts optimal ICD lead and can placement sites before actual implantation by simulating defibrillation shocks on patient-specific 3D heart models. This preliminary virtual testing identifies configurations with lowest defibrillation and cardioversion thresholds, preventing harmful high-threshold shocks before they occur.
Solution Approach 2:
The invention creates virtual copies of the patient's heart anatomy through 3D imaging and computational modeling. These digital twins allow testing of multiple ICD configurations in silico, selecting the optimal placement that minimizes shock thresholds without requiring trial-and-error physical implantation.
2Reliability
If multiple ICD configurations are tested to find optimal placement, then the defibrillation threshold can be minimized, but the time and computational resources required increase
Solution Approach 1:
The computational model performs preliminary virtual testing of multiple ICD configurations before actual implantation. By simulating defibrillation shocks on patient-specific 3D models, the system identifies optimal placement sites that minimize thresholds, eliminating the need for time-consuming trial-and-error adjustments after surgery.
Solution Approach 2:
The invention replaces physical trial-and-error ICD placement with computational simulations. Instead of implanting and testing multiple physical configurations, the system uses electrical field simulations on digital heart models to predict optimal placement, significantly reducing time and resource requirements.
Data Source
AI summary
The present invention includes a method for determining optimal placement sites for internal defibrillators in pediatric and congenital heart defect patients. The method is executed by creating a personalized active heart-torso model. The model is created using imaging scans (e.g., low resolution clinical scans) and advanced image processing techniques. The image processing results in a heart-torso mesh model. The ventricular portion of the mesh incorporates cell membrane dynamics. The combined torso-active ventricular defibrillation model can be used for patient specific modeling of the defibrillation process and optimal defibrillator placement can be determined. This method could also be used to decrease the energy needed for a defibrillation shock, because of the optimized defibrillator placement.