Automated Dose Falloff Constraints for Radiation Therapy Planning

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Solution Overview

Problem

Current radiation therapy techniques face challenges in efficiently controlling and shaping dose distribution outside treatment targets, particularly in stereotactic radiosurgery where targets are within normal brain tissue, requiring steep dose gradients to minimize healthy tissue irradiation.

Innovation Solution

The implementation of streamlined and partially automated methods for setting normal tissue objectives in radiation treatment planning, which impose target-specific dose falloff constraints based on geometric characteristics and planner preferences, reducing the need for contouring control structures and addressing dose bridging between targets.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If traditional radiation treatment planning methods are used, then treatment plans can be developed, but the process becomes increasingly difficult and time-consuming as more freedom is afforded to radiologists for shaping dose distribution

Engineering Contradiction:

Improvefreedom to shape dose distributionVSAvoidcomplexity of treatment plan development

Core Design Contradiction:

Adaptability or versatilityVSDevice complexity

Solution Approach 1:

The system automatically generates normal tissue objectives and dose falloff constraints without requiring manual contouring by radiologists. The algorithm self-adjusts parameters based on target geometry and treatment goals, eliminating the need for complex manual planning while preserving the freedom to shape dose distribution.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system dynamically adjusts dosimetric parameters such as dose falloff distances, gradient steepness, and constraint weights based on target characteristics and treatment objectives. This automated parameter optimization maintains versatility in dose shaping while simplifying the planning process.

Inventive Principle:

Principle #35Parameter changes

2Manufacturing precision

If manual contouring of control structures is performed around each target, then dose distribution can be controlled, but the process requires significant manual intervention and time

Engineering Contradiction:

Improveprecision of dose distribution controlVSAvoidtime for treatment plan development

Core Design Contradiction:

Manufacturing precisionVSLoss of time

Solution Approach 1:

The system pre-calculates optimal dose falloff constraints and normal tissue objectives based on target geometry before treatment planning begins. This preliminary automated setup eliminates the need for time-consuming manual contouring while maintaining precise dose control.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The manual mechanical process of contouring control structures is replaced with an automated computational algorithm that calculates dose constraints based on dosimetric parameters. This substitution maintains precision while dramatically reducing the time required.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Object-affected harmful factors

If steep dose gradients are required outside treatment targets to minimize healthy tissue irradiation, then healthy tissue exposure is reduced, but the planning complexity increases

Engineering Contradiction:

Improvehealthy tissue irradiationVSAvoidplanning complexity

Core Design Contradiction:

Object-affected harmful factorsVSDevice complexity

Solution Approach 1:

The system applies different dose falloff constraints and gradient steepness parameters to different regions surrounding each target based on local anatomical considerations. This localized approach minimizes healthy tissue exposure in critical areas while automating the complex planning process through region-specific dosimetric optimization.

Inventive Principle:

Principle #3Local quality

4Productivity

If automated methods are used to reduce manual intervention, then time is saved, but achieving precise dose distribution control becomes more challenging

Engineering Contradiction:

Improveefficiency of treatment planningVSAvoidprecision of dose distribution control

Core Design Contradiction:

ProductivityVSManufacturing precision

Solution Approach 1:

The system incorporates iterative optimization algorithms that automatically adjust dose constraints and MLC parameters based on calculated dose distributions. This feedback mechanism ensures precise dose control is achieved while maintaining high productivity through automation.

Inventive Principle:

Principle #23Feedback

Data Source

PatentUS10857384B2Controlling and shaping the dose distribution outside treatment targets in external-beam radiation treatments

Publication Date: 2020.12.08 SIEMENS HEALTHINEERS INTERNATIONAL AG

AI summary

Streamlined and partially automated methods of setting normal tissue objectives in radiation treatment planning are provided. These methods may be applied to multiple-target cases as well as single-target cases. The methods can impose one or more target-specific dose falloff constraints around each target, taking into account geometric characteristics of each target such as target volume and shape. In some embodiments, methods can also take into account a planner's preferences for target dose homogeneity. In some embodiments, methods can generate additional dose falloff constraints in locations between two targets where dose bridging is likely to occur.