Adaptive Radiation Therapy Plan Generation with Incompatible Goal Resolution
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Solution Overview
Problem
Current radiation therapy treatment planning systems struggle to automatically generate and optimize treatment plans efficiently, especially in adaptive workflows, due to the need for multiple clinical input data sources and the challenge of handling incompatible clinical goals.
Innovation Solution
The system automatically generates treatment plans using multiple sources of clinical input data, such as knowledge-based information and clinical goal templates, and automatically replaces incompatible goals with compatible ones, enabling efficient optimization of adapted treatment plans in adaptive workflows.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual treatment plan generation is used, then treatment plan accuracy can be optimized through expert judgment, but time consumption and workload increase significantly
Solution Approach 1:
The system enables automatic treatment plan generation where the computer system autonomously performs plan creation and optimization without requiring manual expert intervention. The system self-adjusts parameters, selects beam configurations, and optimizes dose distributions automatically, freeing clinicians from time-consuming manual tasks while maintaining plan quality through algorithmic optimization.
Solution Approach 2:
The patent replaces the manual mechanical process of treatment planning with an automated computational system. The computer-based automated planning system substitutes human manual operations with algorithmic processes, using software automation to generate and optimize treatment plans, thereby reducing time consumption while maintaining or improving plan accuracy through systematic optimization algorithms.
2Productivity
If automatic treatment plan generation is implemented, then time efficiency improves, but handling incompatible clinical goals becomes difficult
Solution Approach 1:
The system incorporates feedback mechanisms where the automated planning process continuously evaluates the compatibility of clinical goals during optimization. When conflicting goals are detected, the system provides feedback to adjust optimization parameters, re-evaluate goal priorities, or modify the treatment plan to resolve conflicts, enabling automatic handling of incompatible goals while maintaining time efficiency.
Solution Approach 2:
The automated planning system dynamically adapts to incompatible clinical goals by adjusting optimization parameters, goal weights, and treatment plan configurations in real-time. The system's dynamic capability allows it to respond to conflicting requirements by modifying the plan iteratively, balancing multiple competing objectives without requiring manual intervention to resolve the complexity.
3Manufacturing precision
If treatment plans are adapted during delivery phase, then accuracy of dose delivery improves, but optimization process becomes more complex
Solution Approach 1:
The system performs preliminary adaptation of treatment plans during the planning phase by anticipating potential anatomical changes and pre-optimizing multiple plan scenarios. This preliminary action prepares adapted plans in advance, reducing the complexity of real-time optimization during delivery while maintaining dose delivery accuracy through pre-computed adaptive strategies.
Solution Approach 2:
The automated planning system creates copied versions of the original treatment plan that are pre-adapted for potential anatomical variations. These copied plans are generated with modified parameters to account for expected changes, allowing the system to select the most appropriate pre-adapted plan during delivery without requiring complex real-time optimization, thereby simplifying the adaptation process while maintaining accuracy.
Data Source
AI summary
Systems and methods for the automatic generation and optimization of radiation therapy treatment plans, and systems and methods for the automatic generation and optimization of an adapted plan in an adaptive radiation therapy workflow.