Intravascular Mapping System for Cardiac Strain Calculation
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Solution Overview
Problem
Current cardiovascular navigation systems lack sufficient information about the behavior of heart wall tissue, particularly in characterizing the motion of the heart wall, which is crucial for optimal placement of left ventricular leads and understanding cardiac motion.
Innovation Solution
A method and system that utilize an intravascular mapping tool to collect point cloud data sets by maneuvering it to select locations on the heart surfaces, determining reference and instantaneous distances between map points, and calculating strain characteristics of the heart wall tissue based on these distances.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If qualitative techniques of characterizing motion are used, then the system can evaluate heart motion, but the system does not provide sufficient information about heart wall tissue behavior
Solution Approach 1:
The patent transforms qualitative motion characterization into quantitative strain measurements by changing the parameter being measured from general motion to specific tissue deformation. The system calculates strain using the formula ε = (L - L0) / L0, where L is the instantaneous distance and L0 is the reference distance, providing concrete numerical values that quantify heart wall tissue behavior rather than qualitative descriptions.
Solution Approach 2:
The patent replaces qualitative visual assessment with quantitative mechanical measurement. By using distance measurements between map points and calculating strain based on these measurements, the system substitutes subjective qualitative evaluation with objective mechanical parameters that directly characterize tissue behavior.
2Measurement precision
If more map points are collected to improve characterization accuracy, then the precision of motion characterization improves, but the time and complexity of data collection increases
Solution Approach 1:
The patent uses a sufficient number of map points (40-120 endocardial locations and up to 10 epicardial locations) rather than attempting to map every possible location. This partial action approach provides adequate precision for clinical decision-making without the excessive time investment required for complete comprehensive mapping of the entire heart surface.
Solution Approach 2:
The system performs preliminary selection of representative map points that capture the essential motion characteristics of different heart wall segments. By strategically placing map points at key locations rather than uniformly distributing them, the system achieves accurate motion characterization with fewer total measurements, reducing data collection time while maintaining precision.
Data Source
AI summary
A method and system is provided for calculating a strain from characterization motion data. 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 automatically assigning segment identifiers (IDs) to the map points based on a position of the map point within the point cloud data set. The method and system further select a first and second reference from a group of map points. Further, the method and system calculate a linear strain based on an instantaneous distance and a reference distance between the first and second references.