Local Activation Time Mapping Sub-Map Segmentation
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Solution Overview
Problem
Current electrophysiology maps, particularly local activation time (LAT) maps, face challenges in visualizing certain arrhythmias such as supraventricular and ventricular extrasystoles due to limitations in quality, density, and rapidity of generation.
Innovation Solution
The method involves computing an LAT range, splitting it into sub-ranges, and generating sub-maps using different mapping conventions, allowing for increased granularity and visualization by scaling and outputting these sub-maps on a three-dimensional cardiac model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a single LAT map is generated using a uniform mapping convention, then the map covers the entire LAT range, but the visualization quality and detail of specific arrhythmia patterns are insufficient
Solution Approach 1:
The LAT map is divided into multiple sub-maps, each representing a specific time range subset. This segmentation allows each sub-map to be optimized for visualizing particular arrhythmia patterns with appropriate mapping conventions, thereby improving visualization quality without requiring a complete redesign of the entire mapping system.
Solution Approach 2:
Different mapping conventions (e.g., color scales, gradient types) are applied to different LAT sub-maps based on their specific time ranges and arrhythmia characteristics. This local optimization ensures that each region of the map has the most appropriate visualization style for its data, enhancing overall measurement precision.
2Loss of information
If the LAT map uses a single mapping convention for the entire LAT range, then the system is simple to operate, but the ability to distinguish and visualize different arrhythmia patterns is limited
Solution Approach 1:
The system dynamically selects and applies different mapping conventions based on the LAT time range being visualized. This dynamic adaptation allows the system to preserve detailed arrhythmia pattern information across different time periods while maintaining a unified interface that does not require manual reconfiguration, thus preserving information without significantly complicating operation.
3Productivity
If extant LAT mapping methods are used, then the system is easy to implement, but the rapidity and ease of generating high-quality maps are insufficient
Solution Approach 1:
The system pre-defines multiple mapping conventions and automatically selects the appropriate one based on the LAT time range. This preliminary preparation of mapping options eliminates the need for manual configuration during map generation, thereby improving productivity while ensuring that high-quality, appropriately-styled maps are generated automatically.
Data Source
AI summary
Local activation times (LATs) are mapped by computing an LAT range for a plurality of electrophysiology data points, splitting the LAT range into two or more LAT sub-ranges, splitting the LAT map into a corresponding number of LAT sub-maps, and associating a mapping sub-convention (e.g., a color spectrum, grayscale, and/or pattern density range) with each of the LAT sub-maps. The mapping sub-conventions can be scaled (e.g., linearly, logarithmically) to their respective LAT sub-ranges, allowing for an overall LAT map that offers increased granularity over LAT sub-ranges of particular interest to the practitioner. The LAT sub-maps can be updated in real time as additional electrophysiology data points are collected.