Velocity Vector Mapping for Precise Atrial Fibrillation Source Detection
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Solution Overview
Problem
Current diagnostic tools for cardiac rhythm disorders, such as atrial fibrillation, lack the precision to identify the source and type of AF drivers, leading to suboptimal RF ablation success rates and increased lesion load.
Innovation Solution
A system that processes electrogram signals to generate a velocity vector map, revealing the source of AF by determining spatial and temporal stability, classifying AF into types A, B, and C, and enabling precise cardiac ablation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If current diagnostic tools are used to identify AF drivers, then the diagnostic process is simple, but the measurement precision of AF driver location and type is insufficient
Solution Approach 1:
The diagnostic system segments the complex task of AF driver identification into multiple processing stages: electrogram signal acquisition from multiple electrodes, signal normalization and artifact removal, velocity vector map generation through sequential processing, and classification of AF driver types. This segmentation allows each stage to be optimized independently while maintaining overall system manageability.
Solution Approach 2:
The system transitions from traditional two-dimensional electrogram displays to three-dimensional velocity vector maps that incorporate temporal dimension. By processing electrogram signals through sequential time points and generating velocity vectors with directional information, the system adds spatial and temporal dimensions to the diagnostic data, enabling precise localization and characterization of AF drivers.
2Reliability
If RF ablation is performed without precise diagnostic tools, then the treatment can be applied broadly, but the success rate is limited and lesion load increases
Solution Approach 1:
The system performs preliminary diagnostic actions by generating velocity vector maps and classifying AF driver types (rotors, focal sources, wavebreak) before ablation treatment. This preliminary characterization enables clinicians to plan targeted ablation strategies, delivering lesions only at precisely identified driver locations rather than applying broad-area ablation, thereby improving success rates while reducing unnecessary lesion load.
Solution Approach 2:
The system provides real-time feedback during the ablation procedure by continuously monitoring electrogram signals and updating velocity vector maps. This feedback mechanism allows clinicians to verify that ablation lesions are effectively eliminating the identified AF drivers, enabling adaptive adjustment of the ablation strategy to maximize efficacy while minimizing excessive lesion creation.
Data Source
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AI summary
Disclosed are various examples and embodiments of systems, devices, components and methods configured to detect a location of a source of at least one cardiac rhythm disorder in a patient's heart, such as atrial fibrillation, and to classify same. Velocity vector maps reveal the location of the source of the at least one cardiac rhythm disorder in the patient's heart, which may be, by way of example, an active rotor in the patient's myocardium and atrium. The resulting velocity vector map may be further processed and/or analyzed to classify the nature of the patient's cardiac rhythm disorder, e.g., as Type A, B or C atrial fibrillation. The resulting cardiac rhythm classification then can be used to determine the optimal, most efficacious and/or most economic treatment or surgical procedure that should be provided to the individual patient. A simple and computationally efficient intra-cardiac catheter-based navigation system is also described. Also described and disclosed are various intra-cardiac catheter-based navigation systems.