Intravascular Mapping Tool Triangulation for Cardiac Strain Analysis
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Solution Overview
Problem
Current cardiovascular navigation systems lack sufficient information to prepare characterization data for strain analysis, particularly in evaluating the motion of the heart for optimal placement of left ventricular leads.
Innovation Solution
A method involving an intravascular mapping tool that collects point cloud data sets by maneuvering sensors along the heart's surfaces, selecting regions of interest, and applying triangulation techniques to generate triangles from map points within these regions, facilitating strain analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If qualitative characterization techniques are used to evaluate heart motion, then the evaluation process is simplified, but sufficient information for strain analysis is not obtained
Solution Approach 1:
The heart surface is segmented into multiple discrete map points that are systematically sampled during the mapping procedure. This segmentation allows the collection of sufficient data points to perform strain analysis while maintaining a structured and manageable evaluation process. Each map point contributes to the overall strain calculation, enabling both simplicity and information completeness.
2Reliability
If map points are collected at multiple endocardial and epicardial locations, then comprehensive heart motion data is obtained, but the complexity of data processing increases
Solution Approach 1:
The patent transitions from two-dimensional map point coordinates to three-dimensional spatial reconstruction of the heart surface. By incorporating depth information and creating a 3D point cloud representation, the system can process multiple map points more efficiently while maintaining comprehensive coverage of endocardial and epicardial locations. This dimensional enhancement allows for more reliable heart motion data without proportionally increasing processing complexity.
3Measurement precision
If a triangulation technique is applied to generate triangles from map points, then strain analysis capability is enabled, but the computational complexity increases
Solution Approach 1:
The triangulation process segments the heart surface into discrete triangular elements formed by connecting adjacent map points. This segmentation enables strain analysis by creating a mesh structure that can be processed computationally. The method balances measurement precision by using enough triangles to capture surface geometry accurately while avoiding excessive computational complexity through efficient triangulation algorithms that process map points systematically.
Data Source
AI summary
A method and system are provided for subdividing a region of interest. The method and system utilize an intravascular mapping tool configured to be inserted into at least one of the endocardial or epicardial space. The mapping tool is maneuvered to select locations proximate to surfaces of the heart, while collecting map points at the select locations to form a point cloud data set during at least one cardiac cycle. The method and system further include selecting a region of interest from the point cloud data set, and forming a triangulation area that include a set of map points from the point cloud data set corresponding to the region of interest. Further, the method and system use a triangulation technique algorithm to generate at least one triangle within the triangulation area formed from at least a portion of the set of map points.