Continuum Radiotherapy Planning in Infinite-Dimensional Space
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Solution Overview
Problem
Conventional radiation therapy planning methods restrict the search space by determining degrees of freedom first, leading to suboptimal treatment plans and sometimes requiring re-calculation due to the bounded optimization.
Innovation Solution
The approach involves treating radiation therapy planning as a continuum problem, allowing degrees of freedom to be represented by functions or fields in an infinite-dimensional space, rather than discrete variables, enabling optimization in a continuous computational space.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If degrees of freedom are determined prior to optimization in conventional treatment planning, then the optimization problem becomes computationally tractable, but the search space is restricted and the quality of treatment plans deteriorates
Solution Approach 1:
The patent transitions the optimization problem from a discrete finite-dimensional space to a continuous infinite-dimensional space by representing degrees of freedom as functions rather than discrete variables. This dimensional transformation allows the system to explore a vastly expanded search space while maintaining computational tractability through continuous optimization techniques, thereby resolving the contradiction between computational feasibility and treatment plan quality.
Solution Approach 2:
The patent fundamentally changes the parameter representation from discrete variables to continuous functions. By allowing degrees of freedom to vary continuously across the treatment space rather than being constrained to discrete values, the optimization can achieve superior treatment plans while using continuous mathematical methods that remain computationally manageable.
2Device complexity
If the search space is restricted by predetermined degrees of freedom, then the optimization problem is easier to solve, but the feasible set is bounded and may prevent finding acceptable plans
Solution Approach 1:
By moving from discrete to continuous representation, the patent dramatically expands the feasible set from a finite collection of discrete options to an infinite continuous space. This dimensional change allows the optimization to adapt to a much broader range of treatment scenarios and constraints while using continuous optimization algorithms that handle the increased complexity efficiently.
Solution Approach 2:
The continuous representation of degrees of freedom creates a universal framework that can accommodate various treatment modalities and constraints within a single optimization paradigm. This unified approach allows the same mathematical framework to handle diverse clinical scenarios, enhancing the versatility and adaptability of the treatment planning system.
Data Source
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AI summary
Systems and methods are disclosed for dynamic radiotherapy treatment planning in a continuous space of computation. Example operations for generating treatment plan data for a radiotherapy treatment include: obtaining data for a radiotherapy treatment of a human subject; generating a set of radiation controls from the data for the radiotherapy treatment, with at least one of the radiation controls being based on a mapping from a continuous (e.g., infinite dimensional) computational space; converting the generated set of radiation controls to a set of treatment delivery parameters, the set of treatment delivery parameters corresponding to capabilities of a radiotherapy treatment machine; and producing treatment plan data for the radiotherapy treatment based on the set of treatment delivery parameters.