Nested Partitioning for Automated Beam Angle Selection
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Solution Overview
Problem
Current radiation treatment planning systems for cancer patients require expert judgment for beam angle selection and dose optimization, leading to inaccurate results due to interpretation and complexity, and lack automation in coupling these processes.
Innovation Solution
A medical treatment planning system utilizing a nested partitioning framework that automates beam angle selection and dose optimization through a CPU and memory storage device, employing algorithms and high-throughput computing to generate patient-specific radiation treatment plans by combining imaging data and initial dose information within an integer-programming optimization model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If expert judgment is used for beam angle selection, then the system can operate with current technology, but the results are inaccurate due to interpretation variability and subjectivity
Solution Approach 1:
The patent replaces the mechanical system of expert human judgment with an automated computational optimization system. The treatment planning system uses algorithms to automatically select beam angles and optimize dose distributions, eliminating the subjectivity and interpretational variability inherent in expert judgment while maintaining or improving accuracy through systematic computational methods.
Solution Approach 2:
The patent changes the parameters of the treatment planning process from manual expert selection to automated optimization. The system uses mathematical models and computational algorithms to systematically vary beam angle parameters and dose distribution parameters, optimizing them based on objective criteria such as tumor coverage and organ-at-risk constraints, thereby achieving higher precision without requiring human interpretation.
2Reliability
If manual beam angle selection and dose optimization are performed separately, then the process can be simplified, but the coupling between these processes is lost leading to suboptimal treatment plans
Solution Approach 1:
The patent merges the previously separate processes of beam angle selection and dose optimization into a single integrated optimization framework. The treatment planning system simultaneously optimizes both beam angle configurations and dose distributions using coupled mathematical models, ensuring that the interaction between these parameters is fully considered to achieve superior treatment plan quality.
Solution Approach 2:
The patent employs a nested optimization structure where inner optimization problems are embedded within outer optimization problems. The dose optimization is nested within the beam angle selection process, allowing the system to iteratively refine both levels of optimization. This nested approach enables comprehensive coupling of the two processes while managing complexity through hierarchical organization of the optimization algorithm.
3Manufacturing precision
If more beam angles are used to increase radiation effectiveness, then tumor treatment improves, but the exposure to healthy tissues increases
Solution Approach 1:
The patent applies local quality optimization by directing radiation beams with precise spatial and angular control to specific target regions. The treatment planning system optimizes the local dose distribution characteristics, concentrating radiation intensity on the tumor while minimizing exposure to surrounding healthy tissues. This is achieved through optimized beam angle selection and intensity modulation tailored to the specific anatomical and oncological requirements of each patient.
Data Source
AI summary
A novel approach to generating radiation treatment plans through a nested partitions framework provides an optimization of radiation delivery. The nested partitions approach couples beam angle selection and dose optimization to solve treatment planning problems. An optimal beam angle selection is provided to best treat tumors, while minimizing exposure to the surrounding healthy tissues.