Dynamic Vessel Roadmapping for Motion-Compensated Fluoroscopy
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Solution Overview
Problem
During fluoroscopy-based medical interventions, the alignment between vessel images obtained during a preceding medical imaging method and real-time fluoroscopy images is often misaligned due to patient movement, leading to the need for excessive contrast medium and radiation exposure.
Innovation Solution
A dynamic vessel roadmapping method that generates a vessel roadmap library with alignment data, allowing real-time alignment of vessel images with fluoroscopy images using cardiac and respiratory information to compensate for vessel shifts caused by cardiac and breathing motions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If vessel images from a preceding medical imaging method are used during fluoroscopy-based intervention, then the amount of contrast medium and radiation exposure can be reduced, but misalignment between the overlaid vessel tree and the actual position of the vessel tree occurs due to patient movement
Solution Approach 1:
The system performs preliminary actions by acquiring vessel images and extracting alignment information before the actual fluoroscopy intervention. The alignment information is pre-computed and stored, allowing the system to prepare the necessary data for accurate overlay during the intervention without requiring real-time contrast medium injection or extended fluoroscopy exposure.
Solution Approach 2:
The system addresses the dynamic nature of patient movement by continuously updating the vessel roadmap based on real-time fluoroscopy images. The alignment information is dynamically adjusted during the intervention to compensate for changes in patient position and vessel location, maintaining accurate alignment throughout the procedure.
2Productivity
If vessel images are overlaid on real-time fluoroscopy images without alignment adjustment, then the intervention can proceed with reduced contrast medium and radiation, but the alignment accuracy deteriorates due to vessel movement from cardiac and respiratory motions
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring real-time fluoroscopy images and comparing them with the overlaid vessel roadmap. Based on this feedback, the alignment information is dynamically adjusted to compensate for vessel movement caused by cardiac and respiratory motions, maintaining accurate alignment throughout the intervention.
Solution Approach 2:
The system changes alignment parameters dynamically during the intervention. The alignment information is updated based on real-time fluoroscopy images, adjusting position, orientation, and scaling parameters to account for vessel movement. This allows the vessel roadmap to remain accurately aligned with the actual vessel tree despite physiological motions.
Data Source
AI summary
The present application relates to a computer-implemented dynamic vessel roadmapping method. The method comprises generating a vessel roadmap library, the vessel roadmap library including a plurality of vessel roadmaps, wherein each vessel roadmap comprises vessel roadmap image and first and second alignment data, obtaining a real-time fluoroscopy image and corresponding real-time first and second fluoroscopy information, overlaying a vessel roadmap image of the vessel roadmap library with the real-time fluoroscopy image based on the first alignment data, the second alignment data, and the real time first and second fluoroscopy information and aligning the vessel roadmap image and the real-time fluoroscopy image based on the second alignment data and the real time second fluoroscopy information, wherein the second alignment data is derived from the corresponding vessel roadmap image.