Microbead Size-Driven Vessel Visualization for Embolization Planning
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Solution Overview
Problem
Current embolization procedures lack a method to determine the relationship between target vessel sizes and microbead sizes, leading to imprecise planning and differentiation between affected and unaffected vessels during microbead injection.
Innovation Solution
A method involving high-resolution imaging and machine learning models to correlate vessel diameters with microbead sizes, providing adaptive vessel visualization and recommending suitable microbeads for embolization procedures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual measurement of vessel diameters is performed, then some vessel diameters can be obtained, but complete understanding of all target vessels is not achieved and differentiation between affected and unaffected vessels is not possible
Solution Approach 1:
The patent replaces manual mechanical measurement with automated image processing and machine learning algorithms. The system uses digital image analysis to automatically segment vessels, measure diameters, and classify affected versus unaffected vessels, eliminating the limitations of manual measurement while assessing all target vessels comprehensively
Solution Approach 2:
The patent creates a digital representation (copy) of the vessel tree from medical imaging data. This digital model allows for complete measurement and analysis of all vessels without physical intervention, enabling differentiation between affected and unaffected vessels through automated processing of the entire vascular network
2Ease of operation
If microbeads are injected without vessel size correlation, then embolization procedure can be performed, but precision of targeting affected vessels is reduced
Solution Approach 1:
The patent performs preliminary analysis of vessel diameters and microbead size correlations before the actual embolization procedure. By pre-classifying vessels as affected or unaffected based on size matching criteria, the system enables precise targeting during injection while maintaining procedural ease
Solution Approach 2:
The patent changes the approach from generic microbead injection to parameter-driven injection by correlating microbead size parameters with measured vessel diameter parameters. This allows optimization of microbead selection for each specific vessel based on quantitative size matching, improving targeting precision
Data Source
AI summary
A method of planning an embolization procedure for a patient includes capturing a 3D digital image of a vessel at a target site after a contrast agent has been administered to the vessel; determining diameters of the vessel based on the digital image; and outputting a digital representation of the vessel where different colors indicate different diameters of the vessel.


