Radiation Treatment Planning With Robust Field Geometry
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Solution Overview
Problem
Existing radiation treatment plans often fail to discriminate between target volumes and adjacent tissues, leading to potential collateral damage due to uncertainties in patient positioning and anatomy, resulting in dosimetric inaccuracies.
Innovation Solution
A control circuit identifies field geometry parameter values and determines dosimetric robustness to optimize radiation treatment plans, ensuring stability against variations in patient positioning and anatomy by selecting robust field geometries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If radiation therapy is applied to treat target volumes, then therapeutic effect is improved, but collateral damage to adjacent tissues increases
Solution Approach 1:
The patent applies local quality by differentiating treatment parameters for different spatial regions. The system calculates dosimetric robustness for specific field geometry parameters (such as beam angle, position, and shape) and selects parameters that maximize therapeutic effect on the target volume while minimizing exposure to adjacent tissues. This localized optimization ensures that radiation delivery is tailored to specific anatomical regions rather than applying uniform treatment throughout.
Solution Approach 2:
The patent utilizes parameter changes by systematically varying field geometry parameters to optimize treatment outcomes. The system evaluates multiple parameter combinations (beam angles, positions, shapes) and selects those that achieve the desired dosimetric robustness. By changing these geometric parameters, the system can reshape the radiation distribution to better conform to the target volume while sparing surrounding healthy tissues.
2Reliability
If field geometry parameters are optimized manually based on planner experience, then treatment plan quality is improved, but treatment time and productivity are reduced
Solution Approach 1:
The patent implements self-service by enabling the treatment planning system to automatically evaluate and optimize field geometry parameters without requiring extensive manual intervention. The system autonomously calculates dosimetric robustness for different parameter combinations and selects optimal parameters based on predefined criteria, reducing the time planners need to manually adjust settings while maintaining high treatment plan quality.
Solution Approach 2:
The patent applies feedback by implementing an iterative optimization process where the system evaluates dosimetric robustness for candidate parameter sets and uses this feedback to refine subsequent iterations. The system automatically adjusts parameters based on the calculated robustness metrics, converging on optimal solutions more quickly than manual methods and thereby reducing overall treatment planning time.
3Ease of operation
If beam placement is determined using templated solutions, then ease of operation is improved, but manufacturing precision and treatment accuracy are reduced
Solution Approach 1:
The patent uses parameter changes by allowing the system to automatically adjust field geometry parameters based on patient-specific anatomical data and treatment objectives. Rather than relying on fixed templates, the system dynamically calculates optimal parameters (beam angles, positions, shapes) that achieve the desired dosimetric robustness for each individual patient, thereby improving treatment accuracy while maintaining ease of operation through automation.
Data Source
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AI summary
A control circuit identifies at least one field geometry parameter value 201 and then determines 203 dosimetric robustness for the at least one field geometry parameter value to produce a robustness assessment. The control circuit can then determine 205 whether the robustness assessment is satisfactory, and when true, optimize 206 a radiation treatment plan using the at least one field geometry parameter value.