Spatially-Variant Normal Tissue Constraint Optimization
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Solution Overview
Problem
Current radiation treatment plans often create hotspots in healthy tissues due to the inability to accurately discriminate between target and adjacent tissues, leading to inadequate dose distribution and exposure constraints.
Innovation Solution
A control circuit determines a spatially-variant normal tissue constraint based on dose distribution, allowing for flexible and nuanced optimization of radiation treatment plans by penalizing excessive dose levels at specific distances from the target volume, using a free-form function to minimize collateral exposure to healthy tissues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If a constraint is imposed on specifically-identified healthy tissues to minimize hotspots, then the radiation dose to healthy tissue is reduced, but the treatment plan becomes more complex and may not adequately account for spatial variations in dose distribution
Solution Approach 1:
The patent applies local quality by imposing different constraint values on different portions of healthy tissue based on their spatial relationship to the target volume. Specifically, healthy tissue closer to the target volume is imposed with a higher constraint value while healthy tissue further away is imposed with a lower constraint value, creating a spatially-variant constraint structure that accounts for local dose distribution characteristics
Solution Approach 2:
The patent implements dynamics by using an exponential fall-off curve to dynamically adjust constraint values based on distance from the target volume. The constraint value varies continuously as a function of distance, allowing the treatment plan to adapt to spatial variations in dose distribution rather than applying static uniform constraints
2Ease of operation
If a same constraint value is applied to all portions of healthy tissue, then the treatment plan is simpler to implement, but hotspots are created in healthy tissue closer to the target volume
Solution Approach 1:
The patent resolves this contradiction by applying different constraint values to different portions of healthy tissue based on their local characteristics. The constraint value is not uniform but varies spatially, with higher values assigned to healthy tissue closer to the target volume where hotspots are more likely to occur, and lower values assigned to healthy tissue further away
3Measurement precision
If an exponential fall-off curve is used to vary constraints spatially, then dose distribution accuracy is improved, but the treatment plan optimization becomes more computationally intensive
Solution Approach 1:
The patent applies parameter changes by using an exponential fall-off curve to vary the constraint parameter spatially based on distance from the target volume. This mathematical relationship provides a systematic way to adjust constraint values to achieve more accurate dose distribution while maintaining a manageable optimization process through the use of a well-defined functional form
Data Source
AI summary
A control circuit optimizes a radiation-treatment plan (as regards treating at least one target volume for a given patient) by automatically determining a spatially-variant normal tissue constraint as a function, at least in part, of dose distribution for normal tissue that is proximal to the target volume. If desired, the control circuit can repeatedly determine spatially-variant normal tissue constraints while optimizing the radiation-treatment plan. This automatic determination can comprise evaluating dose distributions at specific different distances from the target volume. So configured, the control circuit can effect such evaluation by penalizing, during the optimization of the radiation-treatment plan, dose distribution levels that exceed a predetermined distribution property (such as an aggregation value for the dose values including, but not limited to, an average value of dose values for each of the given specific different distances) at a given one of the specific different distances.