Respiratory Model GUI for Tumor Tracking in Radiation Therapy
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Solution Overview
Problem
Current radiation treatment systems face challenges in accurately targeting tumors during respiratory motion, as the visibility of tumors in x-ray images can be difficult, making it hard to identify and correct errors in radiation delivery.
Innovation Solution
A graphical user interface (GUI) is provided to manage a respiratory model by allowing users to select, modify, and sort x-ray images based on respiratory order, enabling easier identification of tumors and adjustment of correlation parameters to ensure accurate targeting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If x-ray images are used to track tumor position during respiratory motion, then the ability to target the tumor is improved, but the visibility of the tumor in the images deteriorates
Solution Approach 1:
The patent introduces respiratory phase information as an intermediary parameter to organize and sort x-ray images. By sorting images according to respiratory phase, the system creates a structured representation that makes tumor position detectable across the respiratory cycle, even when individual images have poor visibility. This intermediary sorting mechanism transforms the unobservable tumor position into detectable image sequences.
Solution Approach 2:
The system performs preliminary sorting of x-ray images by respiratory phase before actual tumor detection and analysis. This preliminary organization of images according to respiratory position enables subsequent easier identification of tumor location patterns, as the images are pre-arranged in the order they represent the tumor's movement through the respiratory cycle.
2Measurement precision
If multiple x-ray images are collected to track respiratory motion, then the accuracy of tumor positioning is improved, but the complexity of managing and analyzing the images increases
Solution Approach 1:
The patent segments the large set of x-ray images into smaller groups based on respiratory phase. Instead of managing all images as a single complex dataset, the system divides them into respiratory-phase-specific subsets, making the data more manageable and easier to analyze. This segmentation reduces the apparent complexity by organizing images into meaningful, smaller units.
Solution Approach 2:
The system performs preliminary sorting and organization of multiple x-ray images by respiratory phase before analysis. This pre-processing step automatically arranges the complex dataset into an ordered structure, reducing the manual effort and complexity required for subsequent image management and analysis tasks.
3Reliability
If the respiratory model is updated in real-time to correct targeting errors, then the reliability of radiation delivery is improved, but the time required for correction increases
Solution Approach 1:
The patent implements a feedback mechanism where the respiratory model is continuously updated based on real-time analysis of sorted x-ray images. The system monitors tumor position through the sorted image sequences and automatically adjusts the radiation targeting parameters in response to detected positional deviations, creating a closed-loop control system that maintains accuracy throughout treatment.
Solution Approach 2:
The system performs preliminary sorting and analysis of x-ray images by respiratory phase during the treatment setup and monitoring phases. By having the images pre-sorted and the respiratory model pre-established, the system can quickly detect and correct targeting errors without requiring time-consuming analysis during actual radiation delivery, thus minimizing correction time while maintaining reliability.
Data Source
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AI summary
Imaging data including images associated with a patient may be received. A subset of the images that are used with a model that is associated with the position and motion of a targeted region of the patient to receive radiation treatment may be identified. The subset of images may be sorted. A graphical user interface (GUI) that identifies two or more of the images of the sorted subset may be provided. A selection associated with one of the images of the sorted subset may be received by the GUI. Furthermore, a new model to identify the targeted region based on the selection that is associated with one of the two or more images may be generated.