Radiation Therapy Planning System Using Objective Function Feedback
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Solution Overview
Problem
Current radiation therapy treatment planning systems, particularly those using AI algorithms, often generate dose distributions that are not feasible due to physical or technical constraints, necessitating manual modifications to ensure optimal delivery and adherence to treatment goals.
Innovation Solution
A system that allows planners to control the generation of treatment plans by modifying objective functions based on initial dose distributions, using a combination of AI-generated dose distributions and physical models to ensure feasibility and adherence to treatment goals, incorporating user input to adjust weights and objectives for optimal dose delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If AI algorithms are used to generate dose distributions, then treatment planning efficiency is improved, but the generated dose distributions may not be feasible due to physical or technical constraints
Solution Approach 1:
The patent introduces an intermediary optimization process between AI-generated dose distributions and final treatment plans. This intermediary step uses objective functions to adjust and refine the AI-generated distributions, ensuring they meet physical and technical constraints while maintaining the efficiency benefits of AI generation.
Solution Approach 2:
The system implements feedback mechanisms where the feasibility of AI-generated dose distributions is evaluated against physical and technical constraints, and the generated distributions are iteratively adjusted through optimization processes that use objective functions to guide improvements until feasibility requirements are met.
2Reliability
If manual modifications are made to AI-generated dose distributions to ensure feasibility, then reliability is improved, but treatment planning time increases
Solution Approach 1:
The patent replaces manual mechanical adjustment processes with automated computational optimization processes. Instead of planners manually modifying dose distributions, the system uses computer-implemented optimization algorithms with objective functions to automatically adjust and refine AI-generated distributions, maintaining reliability while reducing time loss.
3Manufacturing precision
If treatment plans are generated individually for each patient using inverse planning, then treatment precision is improved, but the complexity of the planning process increases
Solution Approach 1:
The patent applies preliminary action by using AI algorithms to generate initial dose distributions before the formal inverse planning process. This preliminary step provides a starting point that is already close to feasible solutions, reducing the complexity and computational burden of the subsequent individualized optimization processes for each patient.
Data Source
AI summary
The invention relates a system for assisting in planning a radiation therapy treatment provided using a treatment plan comprising irradiation parameters for controlling a delivery of radiation. The system is configured to (i) receive a first dose distribution, (ii) obtain a first objective function, which depends upon at least one parameter and a dose distribution, (iii) determine a first value of the parameter such that the first objective function fulfills a predefined criterion when being evaluated for the first value of the parameter and for a second dose distribution derived from the first dose distribution, (iii) provide the first objective function in connection with the first value of the at least one parameter to a user for modifying the first objective function to generate a second objective function, and (v) determine the treatment plan using the second objective function. Further, the invention relates to a corresponding method and computer program.