Radiation Therapy Plan Alternatives Through Direct Metric Adjustment

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Solution Overview

Problem

Conventional automated treatment planners generate a single optimized treatment plan, requiring iterative clinician adjustments to improve specific metrics, leading to delays and unnecessary resource consumption.

Innovation Solution

Systems and methods that allow clinicians to update a treatment plan by adjusting metrics directly, enabling the generation of alternative plans that improve on one or more target metrics without reducing overall utility, using updated utility functions to identify optimized treatment plans.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If conventional automated treatment planners generate a single optimized treatment plan, then the treatment plan is optimized for one or more metrics based on a utility function, but the system cannot generate alternative treatment plans that improve on target metrics without reducing overall utility

Engineering Contradiction:

Improveability to generate alternative treatment plansVSAvoidcomplexity of treatment plan generation system

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The patent segments the treatment plan generation process by separating the utility function optimization from the metric-specific adjustments. It generates multiple alternative treatment plans by independently adjusting individual metrics (e.g., dose to PTV, dose to OAR) while maintaining the overall utility function framework, allowing clinicians to select plans optimized for specific metrics without regenerating the entire optimization system.

Inventive Principle:

Principle #1Segmentation

Solution Approach 2:

The system dynamically adjusts treatment plans by allowing iterative modification of individual metrics while maintaining the utility function. The automated treatment planner can regenerate alternative plans based on updated metric requirements without requiring complete redesign of the optimization framework, enabling flexible adaptation to different clinical scenarios.

Inventive Principle:

Principle #15Dynamics

2Manufacturing precision

If clinicians iteratively review and update the utility function to achieve target treatment objectives, then the desired treatment plan is generated, but the process causes delay and consumes computing resources

Engineering Contradiction:

Improveprecision of treatment plan meeting target objectivesVSAvoidtime for treatment plan generation

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The system performs preliminary generation of multiple alternative treatment plans based on the utility function before clinician review. By pre-generating plans with different metric optimizations, the system reduces the number of iterative cycles needed, as clinicians can directly select from pre-computed alternatives rather than undergoing repeated optimization cycles.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent creates copies of the treatment plan by generating alternative plans that optimize for different metrics while maintaining the base utility function. These copies allow clinicians to compare different metric priorities without regenerating the entire optimization, reducing time and computational resources required for iterative adjustments.

Inventive Principle:

Principle #26Copying

3Adaptability or versatility

If conventional automated treatment planners provide a single optimized treatment plan, then computing resources are consumed efficiently for one plan, but multiple alternative plans cannot be generated without additional computational burden

Engineering Contradiction:

Improveability to provide multiple treatment plan optionsVSAvoidcomputational resource consumption

Core Design Contradiction:

Adaptability or versatilityVSUse of energy by moving object

Solution Approach 1:

The system applies local quality optimization by allowing different treatment plans to be optimized for different local metrics (e.g., one plan optimized for PTV dose coverage, another for OAR sparing) while sharing the same overall utility function framework. This enables multiple plan options without requiring complete computational regeneration, as each plan is a localized optimization variant.

Inventive Principle:

Principle #3Local quality

Data Source

PatentUS20250387644A1Systems and methods for generating treatment plan alternatives for radiation therapy

Publication Date: 2025.12.25 SIEMENS HEALTHINEERS INTERNATIONAL AG

AI summary

Provided herein are system for generating radiation therapy treatment plan alternatives for radiation therapy. Systems can include one or more processors to determine a first treatment plan that satisfies an initial utility value, receive data associated with a request to determine a second treatment plan from among the plurality of treatment plans, the request specifying a desired first metric value that is different from the first metric value of the first treatment plan; and determine the second treatment plan from among the plurality of treatment plans, where the first metric value of the second treatment plan satisfies a first metric threshold when compared to first metric values of other treatment plans of the plurality of treatment plans. The one or more processors can provide data associated with the second treatment plan to cause a device to operate in accordance with the second treatment plan.