Radiotherapy Treatment Planning with Prioritized Scripted Optimization
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Solution Overview
Problem
Conventional radiotherapy treatment planning methods require significant trial-and-error and user interaction to achieve clinical goals, often leading to unacceptable delays and errors due to complex manual changes and trade-offs between optimization parameters.
Innovation Solution
A computer-implemented method that automatically determines a treatment plan by prioritizing clinical goals, selecting scripts, and executing them in a specific order to adapt optimization structures, weightings, and objectives, reducing the need for manual intervention and avoiding undesirable trade-offs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual changes and trial-and-error are used to achieve clinical goals, then the treatment plan can be customized to meet specific clinical requirements, but the process becomes cumbersome, error-prone, and time-consuming
Solution Approach 1:
The system performs automatic optimization of dose distribution without requiring manual intervention. The computer automatically adjusts optimization structures, weightings, and objectives to achieve clinical goals, eliminating the need for planner intervention and significantly reducing planning time while maintaining precision
Solution Approach 2:
The system automatically modifies optimization parameters such as weightings and constraints based on clinical goals. By programmatically changing these parameters, the system achieves precise dose distribution optimization without manual trial-and-error, resolving the contradiction between precision and time
2Reliability
If complex manual changes are made to optimization parameters, then the optimization algorithm can be steered to achieve specific clinical goals, but the method becomes error-prone and requires significant user interaction
Solution Approach 1:
The computer system autonomously performs the optimization process by automatically selecting and executing appropriate scripts based on clinical goals. This eliminates the need for user interaction during optimization, removing errors associated with manual parameter changes while maintaining reliable clinical goal fulfillment
Solution Approach 2:
The system replaces manual mechanical adjustment of optimization parameters with automated computational processes. Scripts programmatically modify optimization structures, weightings, and objectives, substituting human operation with reliable automated algorithms that eliminate manual errors
3Adaptability or versatility
If conventional optimization algorithms are used with trade-offs between parameters, then some clinical goals can be achieved, but higher-priority goals may be compromised due to interference from lower-priority goals
Solution Approach 1:
The optimization process is divided into separate scripts, each dedicated to achieving a specific clinical goal. By segmenting the optimization into discrete, prioritized tasks, the system can systematically address higher-priority goals first without interference from lower-priority objectives, maintaining dose distribution accuracy while achieving adaptability
Solution Approach 2:
The system executes optimization scripts in a predetermined order based on clinical goal priorities. Higher-priority goals are addressed first with their optimization parameters set before lower-priority goals are considered, preventing trade-offs that would compromise critical clinical requirements
Data Source
AI summary
Disclosed is a computer-implemented method for determining a treatment plan for a radiotherapy treatment including a dose distribution, the method comprising the steps of (a) determining a plurality of clinical goals, the plurality of clinical goals associated with a dose distribution, (b) determining, based at least in part on a user input, a priority for each of the clinical goals, (c) automatically determining a subset and order of scripts among a plurality of scripts, based on the plurality of clinical goals and their respective priority, each script configured to, when executed, adapt one or more optimization objectives and/or adapt weightings for optimization and/or provide and/or adapt an optimization structure, (d) generating a dose distribution, wherein the generating of the dose distribution comprises executing the subset of scripts in the determined order, wherein executing the subset of scripts comprises, for each of the scripts, obtaining at least one of an optimization structure, optimization objectives, and weightings for optimization,