Automated Arc Setup Optimization for Brain Metastasis Radiation
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Solution Overview
Problem
Current radiation treatment planning for multiple brain metastases relies on manual definitions of arc setups, limiting the optimization of treatment plans and requiring significant user intervention, which can lead to suboptimal dose distribution and increased treatment time.
Innovation Solution
A method to automatically optimize arc setups by comparing initial packed setups with predefined constraints, suggesting alternative setups, and iteratively refining them to minimize violations of constraints such as table angles and gantry spans, thereby improving treatment efficiency and dose distribution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual definition of arc setups is used, then user control over treatment parameters is maintained, but treatment planning efficiency decreases and optimization is limited
Solution Approach 1:
The system automatically optimizes arc setups by having the computer compare initial packed setups with predefined constraints and suggest alternative setups without requiring continuous manual intervention. The system serves itself by performing self-optimization through automated comparison and suggestion of improved arc configurations.
Solution Approach 2:
Predefined arc setup constraints are established in advance before the optimization process begins. These constraints include maximum number of arcs, maximum number of table angles, maximum gantry span, and other parameters that guide the automated optimization process to generate feasible treatment plans that meet clinical requirements.
2Manufacturing precision
If fixed arc setups are used, then treatment delivery is simplified, but dose distribution optimization is compromised
Solution Approach 1:
The system dynamically optimizes arc setups by automatically comparing initial configurations with predefined constraints and generating improved alternatives. The arc setup is not fixed but adaptable, allowing the system to adjust the number of arcs, table angles, and gantry spans to achieve optimal dose distribution while maintaining manageable complexity through automated management.
3Manufacturing precision
If multiple table angles and arcs are used, then target coverage is improved, but treatment time increases
Solution Approach 1:
The system optimizes treatment parameters including the number of arcs, table angles, and gantry spans to achieve the best balance between target coverage and treatment time. By automatically adjusting these parameters within predefined constraints, the system ensures sufficient target coverage while minimizing unnecessary treatment time through efficient arc configuration.
Data Source
AI summary
The present application provides an initial, or first, packed arc setup to be compared with predefined arc setup constraints. These predefined arc setup constraints constrain at least one or more of the number of patient table angles per target volume, the number of times the gantry moves along one arc per table angle, the sum of gantry span per metastasis over all arcs, and the minimum table span. Based on the result of the comparison between the packed first arc setup with the predefined arc setup constraints, a second arc setup is automatically suggested. The automatically suggested second arc setup may then be compared with the first arc setup by calculating a score for both setups. Several iterations of such a method can be carried out based on the comparison between an arc setup and the following, subsequent arc setup in the iteration.