Automated IMRT Planning System for Breast Treatment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current intensity modulated radiation therapy (IMRT) planning for breast treatment requires extensive user interaction and iterative trial-and-error, making it resource-intensive and less reproducible, especially in automating steps like gantry angle and collimator angle determination, and regions of interest segmentation.
Innovation Solution
An automated treatment planning system that uses empirical and historical data to determine optimization parameters, such as segment number and lung distance, to generate IMRT plans with minimal user input, incorporating clinical requirements like target tissue coverage and non-target tissue avoidance, using a processor-based system with user interfaces for inputting clinical needs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If automated planning is implemented for IMRT, then planning time is reduced and reproducibility is improved, but device complexity and resource requirements increase
Solution Approach 1:
The automated IMRT planning system segments the treatment planning process into distinct modular components: image import and preprocessing, automatic contouring/segmentation of anatomical structures, treatment plan generation with multiple parameter options, and dose calculation. Each module can be independently configured and executed, reducing overall system complexity while enabling automation.
Solution Approach 2:
The system performs preliminary actions by pre-defining anatomical contours, segmentation parameters, and treatment constraints based on historical data and clinical guidelines before the actual treatment planning. This preliminary setup automates routine decisions and reduces the complexity of real-time planning interactions.
2Manufacturing precision
If extensive user interaction and iterative trial-and-error are used in IMRT planning, then treatment plan quality can be improved, but productivity and efficiency decrease
Solution Approach 1:
The automated planning system incorporates feedback mechanisms that evaluate treatment plan quality metrics (dose distribution, target coverage, organ-at-risk constraints) and automatically adjust planning parameters. This closed-loop feedback enables high-quality plan generation without requiring multiple manual iteration cycles, thereby improving efficiency while maintaining precision.
Solution Approach 2:
The system enables self-service automated planning where the software independently performs contouring, parameter optimization, and plan generation based on pre-configured clinical protocols. This reduces the need for extensive user interaction and iterative manual adjustments, significantly improving productivity while maintaining treatment plan quality through algorithmic optimization.
3Manufacturing precision
If more resources and expertise are allocated to IMRT planning, then treatment plan quality and modulation capability improve, but cost and accessibility worsen
Solution Approach 1:
The system replaces the mechanical dependency on highly skilled manual planners with an automated computational engine that uses algorithms and optimization techniques to generate treatment plans. This substitution maintains high modulation capability and plan quality while reducing the need for extensive expert intervention, thereby lowering operational costs and improving accessibility.
Solution Approach 2:
The automated system dynamically adjusts planning parameters (beam angles, segmentations, dose constraints) based on patient-specific anatomy and treatment goals rather than relying on fixed expert knowledge. This parameter-driven approach achieves high modulation capability through computational optimization, reducing the need for expensive specialized expertise and making IMRT more accessible.
4Device complexity
If manual treatment planning is used, then resource requirements are lower, but planning time increases and reproducibility decreases
Solution Approach 1:
The system segments the planning workflow into automated and manual components, allowing low-resource environments to utilize the automated portions (contouring, parameter selection) while maintaining the option for manual review. This partial automation reduces planning time without requiring full system deployment, balancing resource requirements with efficiency gains.
Solution Approach 2:
The system enables copying and reuse of standardized treatment plans, anatomical contours, and planning parameters across multiple patients with similar conditions. This template-based approach significantly reduces planning time and improves reproducibility while requiring minimal additional resources, as the same plan templates can be replicated and adapted rather than created from scratch for each patient.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Methods and systems for automated treatment planning for radiation therapy are disclosed. Such methods and systems may be useful for treatment planning for intensity-modulate radiotherapy (IMRT). Also provided are user interfaces for automated radiation therapy treatment planning.