Atrial Fibrillation Driver Detection via Activation Time Mapping
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Solution Overview
Problem
Current methods for characterizing and treating atrial fibrillation lack a clear understanding of its mechanisms, particularly in identifying atrial fibrillation drivers and the structural and functional changes associated with reentrant circuits, which hampers effective treatment strategies.
Innovation Solution
A novel polygon reentry model and detection algorithm that tracks the earliest and latest activation times to identify atrial fibrillation drivers, revealing unique line patterns with slow conduction zones at the edges, which are correlated with macroscopic fiber crossings and fibrosis/fat regions, providing a more accurate detection of reentrant activities and their stability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional methods are used to characterize atrial fibrillation, then the current understanding of AF mechanisms is limited, but the accuracy of driver detection and treatment effectiveness is insufficient
Solution Approach 1:
The patent segments the atrial tissue into distinct regions based on activation time maps, identifying specific zones of slow conduction and fiber crossings. This segmentation allows precise localization of reentrant circuit boundaries and driver sites, improving detection accuracy while enabling targeted treatment strategies that enhance treatment effectiveness.
Solution Approach 2:
The patent transitions from traditional two-dimensional surface mapping to three-dimensional activation time modeling by incorporating depth information from electroanatomical maps. This dimensional enhancement reveals spatial relationships between activation times, fiber orientations, and conduction delays, thereby improving driver detection accuracy and explaining treatment outcomes beyond immediate pulmonic vein isolation areas.
2Measurement precision
If reentry detection algorithms are improved, then the accuracy of detecting reentrant activities increases, but the complexity of the detection system increases
Solution Approach 1:
The patent introduces activation time maps as an intermediary representation that bridges raw electrogram data and reentry detection. By first computing activation times and visualizing them in maps, the system simplifies the detection process through intuitive spatial patterns while maintaining high accuracy in identifying reentrant activities and their stability.
Solution Approach 2:
The patent employs visual encoding where different colors represent varying activation times and conduction velocities in the activation time maps. This color-coding transformation converts complex numerical data into intuitive visual patterns, enabling accurate reentry detection while reducing algorithmic complexity through graphical representation rather than complex computational rules.
3Reliability
If treatment targets are expanded to include fiber crossings and fibro-fatty regions, then treatment success rates improve, but the scope of treatment areas increases
Solution Approach 1:
The patent identifies specific local regions characterized by slow conduction zones at fiber crossings and fibro-fatty infiltration, rather than treating the entire atrium uniformly. This localized approach concentrates treatment energy on precise driver sites and reentry boundaries, improving treatment success rates while limiting the effective treatment scope to only the most critical areas.
Data Source
AI summary
A method for characterizing atrial fibrillation includes determining, by a processor of a computing device and based on heart data, an earliest activation time of a heart being monitored. The method also includes determining, by the processor and based on the heart data, a latest activation time of the heart. The method also includes modeling, by the processor, the earliest activation time and the latest activation time within one or more activation time maps. The method further includes identifying, by the processor, an atrial fibrillation driver based at least in part on the one or more activation time maps.