Radiation Therapy Cost Function for Multi-Target Coverage
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Solution Overview
Problem
Current radiation therapy techniques face challenges in achieving uniform target coverage for multiple treatment targets within a patient, leading to sub-optimal treatment plans due to differing target coverages, which cannot be corrected by a single scaling factor.
Innovation Solution
A cost function is constructed to guide optimization algorithms to achieve similar coverage for all targets, using max or soft-max terms to penalize deviations, and an iterative proportional integral (PI) controller-type approach is implemented to automate equal target coverage, eliminating the need for manual normalization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If traditional radiation treatment planning techniques are used for multiple targets, then treatment plans can be developed, but uniform target coverage cannot be achieved across all targets
Solution Approach 1:
The patent modifies the cost function parameters by adding a new term that specifically addresses target coverage uniformity. This parameter change transforms the optimization objective to simultaneously achieve both desired coverage levels and uniformity across multiple targets, resolving the contradiction between coverage precision and optimization complexity.
Solution Approach 2:
The patent implements a feedback mechanism where the optimization algorithm iteratively adjusts MLC leaf positions based on calculated target coverages. The cost function continuously evaluates coverage uniformity and feeds this information back to guide subsequent optimization iterations, enabling the system to converge on uniform multi-target coverage.
2Manufacturing precision
If separate normalization steps are performed for each target, then individual target coverage can be optimized, but treatment time increases and single scaling factor cannot correct all targets
Solution Approach 1:
The patent merges the normalization process for multiple targets into a single unified optimization step. By combining all target coverage requirements into one cost function with a uniformity term, the system achieves simultaneous optimization for all targets using a single scaling factor, eliminating the need for separate normalization steps and reducing planning time.
Solution Approach 2:
The cost function is designed to serve multiple functions simultaneously: it optimizes coverage for each individual target while also ensuring uniformity across all targets. This multi-functional approach allows a single optimization process to achieve what previously required multiple separate operations, reducing time loss.
3Object-affected harmful factors
If IMRT and VMAT techniques are used to provide conformal radiation, then ability to deliver radiation to target while avoiding healthy tissue is enhanced, but developing treatment plans becomes more difficult
Solution Approach 1:
The patent modifies the optimization parameters by incorporating a uniformity term into the cost function that specifically addresses multi-target coverage. This parameter enhancement maintains the conformal radiation delivery capabilities of IMRT and VMAT while simplifying the treatment planning process by enabling automatic uniform coverage optimization across multiple targets.
Solution Approach 2:
The optimization algorithm is enhanced to automatically adjust MLC leaf positions and radiation doses to achieve uniform target coverage without requiring manual intervention for each target. The system serves itself by autonomously optimizing the complex IMRT/VMAT parameters to simultaneously satisfy multiple coverage requirements, reducing the complexity burden on treatment planners.
Data Source
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AI summary
A cost function is constructed so as to guide an optimization process to achieve similar coverage for all targets simultaneously in a concurrent radiation treatment of multiple targets, so that a single scaling factor may be used in a plan normalization to achieve the desired coverage for all the targets. The cost function includes a component that favors a solution that attains similar target coverages for all targets, as well as a component that favors a solution that approaches the desired target coverage value for each individual target. The cost function includes a max term relating to deficiencies of actual target coverages with respect to a desired target coverage, or alternatively a soft-max term relating to deviations of actual target coverages with respect to an average target coverage, as well as to deficiencies of actual target coverages with respect to a desired target coverage.