Arrhythmia Source Localization Using Simulated Cardiac Electromagnetic Data
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Solution Overview
Problem
Current methods for identifying the source locations of heart disorders, such as arrhythmias, are complex, cumbersome, and expensive, and can lead to complications, while existing technologies like electrophysiology catheters and body surface vests are limited and ineffective in sensing certain areas of the heart.
Innovation Solution
A machine learning-based system (MLMO) generates a classifier using computational models and simulations to analyze electromagnetic data from the heart, such as ECG and VCG, to accurately identify arrhythmia sources, reducing the need for expensive and invasive procedures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If electrophysiology catheters are used to identify arrhythmia sources, then measurement precision is improved, but device complexity and cost increase, and harmful factors such as cardiac perforation and tamponade occur
Solution Approach 1:
The patent uses body surface electrodes as an intermediary device to indirectly measure cardiac electrical activity without invasive insertion into the heart. The electrodes placed on the skin surface capture electromagnetic signals that propagate through the body, providing arrhythmia source information without causing cardiac perforation or tamponade risks associated with intracardiac catheters
Solution Approach 2:
The patent replaces the mechanical intracardiac catheter system with a non-invasive body surface electrode system. Instead of physically inserting mechanical devices into the heart chamber, the system uses electromagnetic field detection through skin surface electrodes, eliminating the need for mechanical penetration of cardiac tissue
2Ease of operation
If body surface vests with electrodes are used to collect measurements, then ease of operation is improved, but measurement precision deteriorates due to inability to sense interventricular and interatrial septa
Solution Approach 1:
The patent enhances the body surface measurement approach by integrating computed tomography (CT) imaging data to add a spatial dimension to the electrode measurements. The CT images provide anatomical context and allow the system to localize arrhythmia sources in three-dimensional cardiac space, compensating for the limited sensing capability of surface electrodes in detecting septal activities
Solution Approach 2:
The patent introduces CT imaging as an intermediary modality that bridges the gap between body surface electrode measurements and intracardiac source localization. The CT images serve as a mediator to provide anatomical reference frames that enhance the precision of arrhythmia source identification without requiring direct intracardiac sensing
3Ease of operation
If body surface vests are used, then ease of operation is improved, but device complexity increases due to CT scan requirement and manufacturing difficulty
Solution Approach 1:
The patent performs CT scanning and anatomical modeling as preliminary actions before the actual arrhythmia detection procedure. The CT images are acquired and processed in advance to create patient-specific anatomical models, which are then used to guide the electrode placement and interpret the electrical measurements during the clinical procedure, separating the complex imaging task from the routine monitoring task
4Measurement precision
If electrophysiology catheters are used, then measurement precision is improved, but loss of time increases due to complex and cumbersome procedures
Solution Approach 1:
The patent performs anatomical modeling and electrode placement optimization as preliminary actions using pre-acquired CT images. This allows the system to pre-calculate optimal electrode positions and create patient-specific anatomical models before the clinical procedure, eliminating the need for time-consuming intracardiac catheter manipulation and real-time anatomical mapping during the actual arrhythmia detection procedure
Data Source
AI summary
Systems are provided for generating data representing electromagnetic states of a heart for medical, scientific, research, and/or engineering purposes. The systems generate the data based on source configurations such as dimensions of, and scar or fibrosis or pro-arrhythmic substrate location within, a heart and a computational model of the electromagnetic output of the heart. The systems may dynamically generate the source configurations to provide representative source configurations that may be found in a population. For each source configuration of the electromagnetic source, the systems run a simulation of the functioning of the heart to generate modeled electromagnetic output (e.g., an electromagnetic mesh for each simulation step with a voltage at each point of the electromagnetic mesh) for that source configuration. The systems may generate a cardiogram for each source configuration from the modeled electromagnetic output of that source configuration for use in predicting the source location of an arrhythmia.