Motion Model for Radiation Target Tracking
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Solution Overview
Problem
In radiation treatment procedures, accurately identifying and tracking the target region, such as a tumor, is challenging due to patient movement, especially during respiration, making it difficult to ensure that the radiation beam targets the correct area and avoids healthy tissue.
Innovation Solution
A system that generates a motion model using a sequence of x-ray images, allowing for dynamic adjustment of the radiation beam to compensate for patient movement by correlating external markers with internal features, and providing a graphical user interface to verify and modify the target region identification, ensuring accurate targeting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a sequence of x-ray images is acquired to track target motion, then measurement precision of target position is improved, but loss of time increases due to the need to process multiple images
Solution Approach 1:
A motion model is generated in advance from a sequence of x-ray images before treatment delivery begins. This preliminary motion model captures the temporal pattern of target motion, allowing the system to predict future target positions without processing new images in real-time during treatment, thus resolving the time-loss contradiction.
Solution Approach 2:
Instead of processing actual x-ray images continuously during treatment, the system creates a digital copy or representation of the motion pattern through the motion model. This model copy can be rapidly queried for predicted positions without the computational overhead of processing raw imaging data, maintaining precision while reducing time loss.
2Manufacturing precision
If dynamic tracking of target motion is performed using multiple images, then manufacturing precision of radiation delivery is improved, but device complexity increases
Solution Approach 1:
The patent extracts the essential motion characteristics from complex x-ray image sequences and isolates them into a simplified motion model. This extracted model contains only the necessary information for predicting target position, removing unnecessary complexity from the tracking system while maintaining delivery precision.
Solution Approach 2:
The system transforms the complex spatial-temporal data from multiple x-ray images into a parameterized motion model with defined variables for target position, velocity, and acceleration. This parameterization simplifies the device complexity by reducing the dimensionality of the data while preserving the precision needed for accurate radiation delivery.
3Measurement precision
If correlation parameters are modified to improve target identification, then measurement precision is improved, but loss of time increases due to re-correlation requirements
Solution Approach 1:
Correlation parameters are optimized and established during the preliminary motion model generation phase before treatment delivery. Once determined, these parameters are fixed and reused for all subsequent target position predictions, eliminating the need for time-consuming re-correlation while maintaining identification precision throughout the treatment process.
Data Source
AI summary
Images that are associated with an identification of a tracking target of a patient to receive radiation treatment may be received. The images may be sorted into a sequence based on a motion of the patient. The sorted images may be provided via a graphical user interface. The sequence of the sorted images that are based on the motion of the patient may be provided.