Dynamic Reference Library Extension for MRI Motion Compensation
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Solution Overview
Problem
Existing motion compensation methods in MRI-guided treatments, such as MRgFUS and MR-based thermometry, face challenges in real-time tracking due to patient movement, leading to potential beam-targeting inaccuracies and treatment interruptions, as they rely on pre-acquired reference libraries that may not cover all possible movements or changes in imaging conditions.
Innovation Solution
The method dynamically extends the reference library during treatment by incorporating new images and associated data when no matching reference is found, allowing continuous monitoring and adjustment of the treatment without interruption, by comparing treatment images with the existing library and adding new reference images as needed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If a pre-acquired reference library is used for motion compensation, then real-time tracking speed is improved, but tracking accuracy deteriorates when patient movement exceeds the library coverage
Solution Approach 1:
The reference library is made dynamic by automatically adding new reference images during treatment when patient movement exceeds the initial library coverage. This transforms the static pre-acquired library into an adaptive structure that evolves with patient movement, maintaining both real-time tracking speed and accuracy throughout the procedure.
Solution Approach 2:
The system changes the parameter of reference library content by incorporating new reference images with updated patient positioning data. This parameter change allows the library to adapt to exceeded movement ranges while maintaining the efficient reference-based matching approach for real-time tracking.
2Measurement precision
If the reference library is extended dynamically during treatment, then tracking accuracy is improved, but computational complexity increases
Solution Approach 1:
The system performs preliminary actions by acquiring an initial reference library before treatment begins. This pre-acquired library provides a foundation for real-time tracking, reducing the need for extensive computational operations during the actual treatment procedure.
Solution Approach 2:
The reference library performs self-service by automatically detecting when new reference images should be added based on patient movement detection. This self-managing approach minimizes the need for complex external control systems and manual interventions, reducing overall computational complexity while maintaining tracking accuracy.
3Productivity
If treatment interruptions are avoided by dynamic library extension, then productivity is improved, but system complexity increases
Solution Approach 1:
The system implements feedback by continuously monitoring patient movement and automatically determining when new reference images should be added to the library. This closed-loop feedback mechanism enables uninterrupted treatment by proactively adapting the reference library to patient movement, maintaining treatment continuity without requiring complex manual intervention systems.
Data Source
AI summary
Images acquired during an image-guided treatment procedure sometimes exceed the scope of a reference library previously acquired for the purpose of monitoring and/or adjusting the treatment. In this situation, the reference library may be extended dynamically and/or in real time based on the newly acquired treatment images and/or other available information.