Motion Management System Using Uncertainty Convolution
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Solution Overview
Problem
Conventional radiation therapy methods face challenges in accurately targeting moving tumors due to normal physiological movements, such as respiration or heart movement, leading to unnecessary exposure of healthy tissue and difficulty in comparing the effectiveness of different motion management strategies.
Innovation Solution
A method and system that combine multiple uncertainties using convolution to predict the accuracy of treatment, allowing for comparison of treatment delivery scenarios and determination of the best strategy, such as gating or tracking, by processing probability density functions related to various sources of uncertainty, including target motion and patient positioning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the field aperture is opened up to ensure the radiation volume covers the entire extent of tumor motion, then the tumor coverage is improved, but the volume of healthy tissue exposed to radiation increases
Solution Approach 1:
The patent implements dynamic aperture adjustment where the radiation field aperture changes in real-time to follow tumor motion. The multi-leaf collimator dynamically reconfigures the radiation field shape and position during treatment, allowing the aperture to track the moving tumor while maintaining precise boundaries that exclude healthy tissue.
Solution Approach 2:
The system uses real-time feedback from tumor position sensors (such as optical trackers or implanted fiducials) to continuously adjust the radiation field aperture. The control system receives position data, calculates the optimal aperture configuration, and actuates the multi-leaf collimator accordingly, creating a closed-loop system that adapts to tumor motion.
2Object-affected harmful factors
If physiological gating of the radiation beam is performed to reduce healthy tissue exposure, then the healthy tissue exposure is reduced, but the treatment session duration is extended
Solution Approach 1:
The system employs periodic gating based on the patient's respiratory cycle, delivering radiation only during specific phases (such as end-exhale) when the tumor is in the desired position. The radiation beam is periodically interrupted to allow the tumor to return to the target position, creating a rhythmic on-off pattern that aligns with physiological motion.
Solution Approach 2:
Instead of static gating windows, the system dynamically adjusts the gating criteria and aperture configuration in real-time based on actual tumor position feedback. This allows optimization of the balance between delivery time and healthy tissue protection by adapting to variations in respiratory pattern and tumor motion characteristics.
3Object-affected harmful factors
If the radiation beam is shaped to conform the treatment volume to the exact dimensions of a tumor, then the healthy tissue exposure is reduced, but the tumor coverage becomes insufficient when the tumor moves
Solution Approach 1:
The patent implements a dynamic conformal approach where the radiation field aperture continuously adapts its shape and position to match the tumor's real-time position. The multi-leaf collimator adjusts the field boundaries dynamically, maintaining precise conformity to the tumor volume throughout its motion range rather than using a static enlarged field.
Solution Approach 2:
The system pre-calculates the aperture configuration for multiple anticipated tumor positions based on the motion trajectory. By preparing and quickly switching between pre-computed aperture settings, the system maintains precise tumor conformity during motion without requiring continuous real-time calculation and adjustment.
Data Source
AI summary
A medical method includes: determining a first probability density function related to a first uncertainty in hitting a target in a treatment of the target; determining a second probability density function related to a second uncertainty, wherein the first uncertainty is attributable to a first source of uncertainty, and the second uncertainty is attributable to a second source of uncertainty that is different from the first source of uncertainty; processing at least the first probability density function and the second probability density function using a processing unit; and outputting a result of the processing.