3D Heart Ablation Planning From Electrical Mapping Clusters
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Solution Overview
Problem
Current heart surgery procedures for treating atrial fibrillation and cardiac arrhythmias lack detailed guidance for creating ablation lines, leading to variability and time-consuming manual planning based on physician expertise, without a step-by-step automatic plan.
Innovation Solution
A computer-implemented method that receives procedure images forming a three-dimensional map of the heart, determines ablation-candidate points and cluster boundaries, and outputs ablation lines to assist in designing efficient ablation strategies by regrouping points less than 4mm apart, using spatiotemporal dispersion or voltage values from electrical measurements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If physicians manually determine ablation zones based on pre-procedure imaging or in-surgery determination, then the ablation strategy can be customized to patient anatomy, but the procedure becomes tedious and time-consuming
Solution Approach 1:
The system performs preliminary automatic planning of ablation lines by receiving pre-procedure imaging data, generating a three-dimensional map, determining ablation-candidate points, and proposing ablation lines before the actual surgery. This preliminary automatic planning reduces in-surgery determination time while maintaining anatomical customization.
Solution Approach 2:
The system acts as an intermediary between pre-procedure imaging data and the physician's decision-making by automatically generating ablation line proposals based on anatomical features and electrical measurements, bridging the gap between raw data and clinical decision.
2Adaptability or versatility
If physicians manually plan ablation strategies based on individual expertise, then the strategy can be tailored to specific cases, but significant variability arises between different physicians
Solution Approach 1:
The system creates a standardized three-dimensional map and ablation line proposal that can be consistently generated for each patient based on their specific anatomy and electrical measurements. This standardized approach reduces variability between different physicians while maintaining case-specific customization through the automated analysis of patient-specific data.
3Manufacturing precision
If detailed step-by-step guidance for creating ablation lines is provided, then procedural consistency improves, but the system complexity increases
Solution Approach 1:
The system performs self-service by automatically receiving procedure images, generating three-dimensional maps, determining ablation-candidate points, and proposing ablation lines without requiring manual intervention at each step. This automation provides detailed step-by-step guidance while managing system complexity through integrated computational processing.
4Productivity
If automatic planning methods are implemented, then procedure time is reduced, but the absence of detailed guidance on ablation line construction and connection remains
Solution Approach 1:
The system provides feedback by outputting the three-dimensional map with superimposed ablation line proposals, cluster boundaries, and ablation-candidate points, giving the physician detailed guidance on ablation line construction and connection while maintaining procedural efficiency through automated generation.
Data Source
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AI summary
A computer implemented heart surgery assistance method comprises: a) receiving (300) one or more procedure images representing the heart a patient, said one or more procedure images forming a three-dimensional map associating heart-condition values derived from electrical measurements of said heart a patient to the location at which those electrical measurements were obtained, b) determining or receiving (310) ablation-candidate points derived from said heart-condition values in said at least one or more procedure images based on said electrical measurements, c) determining (320) cluster boundaries within said at least one or more procedure images by regrouping ablation-candidate points which are less than 4mm apart within said three-dimensional map, d) determining (330-380) ablation lines joining neighboring cluster boundaries and/or ablation-candidate points which are less than 4mm apart within said three-dimensional map, e) outputting (390) to a display said three-dimensional map along with data representing said cluster boundaries, said ablation lines, and at least said ablation-candidate points which are neither contained with a cluster boundary or within an ablation line.