Focal Arrhythmia Source Detection Using Directed EP Graphs
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Solution Overview
Problem
Existing cardiac electrophysiological mapping technologies face challenges in accurately identifying focal sources of arrhythmia due to complex patterns in EP behavior, particularly in scar-related atrial tachycardias, which are difficult to interpret visually and require significant computational resources.
Innovation Solution
A method using directed graphs to analyze EP conduction properties, identifying origin vectors and applying the divergence theorem to determine focal sources by fitting a vector field function, enhancing algorithm resilience to incomplete data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If visual inspection of EP velocity vectors map is used to detect focal source, then simplicity of method is maintained, but accuracy is reduced due to visual clutter of multiple velocity vectors
Solution Approach 1:
The patent introduces directed graphs as an intermediary computational structure between the raw velocity vectors and the focal source identification. The directed graphs organize velocity vectors into structured relationships with origins, paths, and destinations, enabling automated analysis that overcomes the visual clutter problem while maintaining algorithmic clarity.
Solution Approach 2:
The patent replaces the manual visual inspection process with an automated computational algorithm. By substituting human visual analysis with computer-based directed graph processing and divergence theorem application, the system eliminates visual clutter limitations while improving accuracy through systematic mathematical analysis.
2Measurement precision
If computer-assisted analysis of EP conduction properties in 3D space is performed, then measurement precision is improved, but device complexity and computational resources increase significantly
Solution Approach 1:
The patent segments the complex 3D analysis problem into manageable components: (1) constructing directed graphs from velocity vectors, (2) identifying origin vectors within regions, (3) grouping origins by spatial proximity, and (4) applying divergence theorem. This segmentation reduces computational complexity while maintaining analytical precision.
Solution Approach 2:
The patent transitions from direct 3D manifold analysis to a graph-theoretic representation that adds a topological dimension. By representing velocity vectors as directed graphs with nodes and edges, the system simplifies the computational geometry while preserving essential spatial relationships and enabling more efficient algorithms.
3Loss of information
If full analysis of manifold in 3D space is performed, then completeness of information is improved, but loss of time and computational resources increase due to requiring more information than available from measured EP values
Solution Approach 1:
The patent applies partial analysis by focusing computational effort on specific regions containing grouped origin vectors rather than performing exhaustive full-manifold analysis. By concentrating resources on high-probability areas identified through directed graph origins and spatial grouping, the system achieves practical completeness without the prohibitive cost of complete 3D space analysis.
Data Source
AI summary
A system includes a display and a processor. The processor is configured to (i) receive a cardiac electrophysiological (EP) velocity vectors map, (ii) compute a set of directed graphs from at least some of the velocity vectors, (iii) using the directed graphs, identify respective origin velocity vectors on the EP velocity vectors map, (iv) define one or more regions on the EP velocity vectors map, (v) determining based on origin velocity vectors in each of the one or more regions, whether the one or more regions contain a focal source of an arrhythmia, and (vi) visualize regions identified to contain a focal source on the EP map to a user, on the display.