Automatic Electroanatomical Map Shaving for Cardiac Ablation Visibility
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Solution Overview
Problem
Manual editing of electroanatomical maps for cardiac ablation is time-consuming and prone to errors, causing locations marked for treatment to be obscured by erroneous mapping, leading to inaccuracies and hidden icons in the map.
Innovation Solution
A processor-based method that updates the volume map by removing erroneous mapped locations, projecting treatment locations onto the surface, and generating an updated electroanatomical map to ensure that ablation sites are visible on the surface, using algorithms like 'ball rolling' to reconstruct the chamber surface and adjust the map during ablation procedures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual editing of electroanatomical maps is performed to correct erroneous mapped locations, then the accuracy of treatment locations is improved, but the time required for map preparation increases significantly
Solution Approach 1:
The system performs automatic identification and removal of erroneous mapped locations without requiring manual intervention. The processor autonomously analyzes the volume map, detects locations that should be on the surface but are incorrectly mapped inside the cavity, and corrects them automatically, making the system self-sufficient for error correction.
Solution Approach 2:
The patent replaces manual editing operations with automated computational algorithms. Instead of operators manually reviewing and correcting map errors, a processor executes automated logic to identify and correct erroneous locations, substituting mechanical human operations with computational processes.
2Loss of information
If the volume map includes all mapped locations, then the completeness of the map is maintained, but treatment locations may be hidden inside the cavity and not visible on the surface
Solution Approach 1:
The system extracts and removes erroneous mapped locations from the interior of the cavity volume that incorrectly obscure treatment locations. By identifying and eliminating these spurious internal points, the system reveals hidden treatment locations on the surface while preserving all valid map data.
Solution Approach 2:
The system uses visual differentiation through color coding to distinguish between valid surface locations and erroneous internal locations. Treatment locations are displayed with specific visual characteristics that make them distinguishable from erroneous mapped points, improving detectability.
3Productivity
If automated algorithms are used to remove erroneous mapped locations, then the productivity of map preparation is improved, but the complexity of the system increases
Solution Approach 1:
The automated system performs self-correction without requiring complex external intervention or manual oversight. The processor autonomously executes the complete workflow of identifying, selecting, and removing erroneous locations, making the system self-sufficient and reducing operational complexity despite the sophisticated algorithms involved.
Data Source
AI summary
A method includes receiving or generating (i) a volume map of at least a portion of a cavity of an organ of a body including a plurality of mapped locations, and (ii) ablation locations inside the cavity. The volume map is updated by removing a portion of the mapped locations, so that the ablation locations inside the cavity fall on a surface of the volume map. Using the updated volume map, a map of at least a portion of the cavity is generated, that includes the ablation locations located on a surface of the updated volume map. The map is displayed to a user.