Radiation Treatment Machine Selection for Moving Tumour Targets
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing radiation treatment methods for target regions subject to vital movement, such as breathing motion or heartbeat, face challenges in motion management, particularly with lung tumors, requiring sophisticated techniques like gating or tracking, which are time-consuming and dependent on patient compliance, and lack clear indicators for tracking or implanted markers.
Innovation Solution
A computer-implemented method that compares patient-specific conditions with treatment machine capabilities using look-up tables to determine a suitable radiation treatment strategy, selecting the most suitable machine based on weighted data analysis, and simulates the treatment plan, including imaging and beam activation modes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If gating or tracking techniques are used to treat lung tumors subject to respiratory motion, then treatment accuracy is improved, but treatment time increases significantly
Solution Approach 1:
The system performs preliminary simulation of the radiation treatment process before actual treatment delivery. By simulating the treatment plan in advance using the selected linear accelerator parameters and motion management technique, the system identifies potential issues and optimizes the treatment approach beforehand, reducing the time required during actual treatment while maintaining accuracy.
Solution Approach 2:
The system automatically selects the most appropriate motion management technique (gating, tracking, or ITV) and configures the linear accelerator parameters without requiring manual intervention. The automated selection process compares patient-specific motion characteristics with pre-defined technique criteria, enabling rapid determination of the optimal treatment approach and reducing treatment planning time.
2Manufacturing precision
If sophisticated motion management techniques like gating or tracking are implemented, then tumour treatment accuracy is improved, but device complexity increases
Solution Approach 1:
The system creates a unified selection framework that can handle multiple motion management techniques (gating, tracking, ITV) and different linear accelerator types through a single automated decision-making process. This universal approach allows the system to select from various techniques based on patient-specific needs without requiring separate complex workflows for each technique, thereby reducing overall system complexity while maintaining treatment accuracy.
Solution Approach 2:
The system uses simulated treatment plans as virtual models to evaluate and compare different motion management techniques before actual treatment. By creating and analyzing digital replicas of the treatment process, the system can determine the most appropriate technique without physically implementing and testing multiple complex hardware configurations, thus reducing device complexity requirements.
3Adaptability or versatility
If multiple treatment machines are evaluated to find the most suitable one, then treatment suitability is improved, but determination time increases
Solution Approach 1:
The system automatically evaluates multiple linear accelerators and selects the most suitable one based on pre-defined criteria and patient-specific requirements. The automated evaluation process compares machine capabilities (such as gating support, tracking accuracy, dose rate) with treatment requirements, enabling rapid determination of the optimal machine without manual assessment of each device, thus reducing selection time while maintaining high suitability.
Solution Approach 2:
The system varies and compares key parameters of different linear accelerators (dose rate, gating capabilities, tracking precision, beam energy) against treatment requirements to identify the most suitable machine. By systematically evaluating and comparing these parameters, the system可以快速确定最佳设备，在保证治疗适宜性的同时缩短选择时间。
Data Source
AI summary
Disclosed is a computer-implemented method which encompasses comparing the requirements for radiation therapy imposed by a patient's individual condition to the capabilities and requirements of different types of treatment machines to determine a suitable radiation treatment strategy including an identification of the treatment machine which shall be used and a treatment plan. Furthermore, a treatment plan is generated by simulating the envisaged radiation treatment. The type of treatment machine associated with a predetermined value for the sum of weights for all fields assigned to that treatment machine is determined as the treatment machine for treating the patient, and corresponding information is output detailing the treatment specifics such as radiation treatment parameters specifically suited for the patient target region tumor thereby reducing radiation exposure, efficient use of the machine and appropriate gating and tracking modes.