Radiation Therapy Plan Optimization via Clinical Goal Interpolation

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Solution Overview

Problem

Current multi-criteria optimization methods for radiation therapy treatment plans require significant manual fine-tuning and operator skill to achieve clinical goals, as the indirect correlation between quality measures and clinical goals complicates precise navigation.

Innovation Solution

A method that involves defining an interpolation optimization problem based on clinical goals, using a set of input dose distributions to calculate interpolation weights for an optimized dose distribution, and automatically generating an updated treatment plan, reducing the need for manual adjustments and operator expertise.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Ease of operation

If multi-criteria optimization with manual slider adjustment is used, then treatment plan optimization is achievable, but significant manual fine-tuning and operator skill are required

Engineering Contradiction:
Improveease of treatment plan optimizationVSAvoidcomplexity of optimization process
Core Design Contradiction:
Ease of operationVSDevice complexity

Solution Approach 1:

The system performs automatic optimization by selecting treatment plans and adjusting parameters autonomously based on clinical goals, eliminating the need for manual slider adjustment by operators

Inventive Principle:
Principle #25Self-service

Solution Approach 2:

The manual mechanical slider adjustment system is replaced with an automated computer-based selection and optimization system that uses algorithms to determine optimal treatment plans

Inventive Principle:
Principle #28Mechanics substitution (Replace mechanical system)

2Manufacturing precision

If indirect quality measures are used for optimization, then mathematical optimization is enabled, but precise navigation to clinical goals becomes difficult

Engineering Contradiction:
Improveprecision of clinical goal achievementVSAvoiddifficulty of navigating to clinical goals
Core Design Contradiction:
Manufacturing precisionVSDifficulty of detecting and measuring

Solution Approach 1:

The system uses clinical goals as direct feedback criteria to evaluate and select treatment plans, creating a closed-loop optimization process that directly measures success against clinically relevant outcomes

Inventive Principle:
Principle #23Feedback

Solution Approach 2:

The optimization approach changes from using indirect mathematical quality measures to directly optimizing based on clinical goal parameters, transforming the measurement and control parameters of the system

Inventive Principle:
Principle #35Parameter changes

3Productivity

If multiple input treatment plans are precalculated, then real-time navigation is enabled, but time-consuming manual fine-tuning is required

Engineering Contradiction:
Improvespeed of treatment planningVSAvoidtime for manual adjustments
Core Design Contradiction:
ProductivityVSLoss of time

Solution Approach 1:

Multiple treatment plans are precalculated with different objective function weightings, and the system automatically selects and combines these preprepared plans based on clinical goals, eliminating the need for manual fine-tuning during the planning process

Inventive Principle:
Principle #10Preliminary action

Solution Approach 2:

The system autonomously performs the entire optimization process from plan selection to final parameter determination, requiring no manual intervention and significantly reducing planning time

Inventive Principle:
Principle #25Self-service

Data Source

PatentEP3581241B1A method, a user interface, a computer program product and a computer system for optimizing a radiation therapy treatment plan
Publication Date: 2022.09.28 RAYSEARCH LAB
  • EP3581241B1 patent drawingFigure 1a~1b
  • EP3581241B1 patent drawingFigure 2~4
  • EP3581241B1 patent drawing

AI summary

A method of obtaining an interpolated treatment plan is based on interpolating between associated dose distributions through optimization with respect to an optimization problem comprising optimization functions based on deviations from clinical goals. The method may suitably be used to improve navigated plans resulting from multi-criteria optimization.