Guided Adaptive Radiation Therapy Workflow for Faster On-Couch Planning
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Solution Overview
Problem
Current adaptive radiation therapy workflows require significant time and expertise due to manual or semi-automatic contouring and plan selection, leading to errors and inefficiencies, especially in on-couch adaptive therapy.
Innovation Solution
A guided, automated workflow system that uses adaptive directives to generate a session patient model and select a treatment plan, minimizing the need for expert intervention by employing automated contouring, deformable registration, and optimized plan generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual or semi-automatic contouring and plan selection are used in adaptive radiation therapy, then treatment accuracy can be maintained, but significant time and expertise are required leading to errors and inefficiencies
Solution Approach 1:
The adaptive radiation therapy workflow is divided into distinct automated modules: image registration module, contour propagation module, dose calculation module, and plan selection module. Each module handles specific tasks automatically, eliminating the need for manual intervention while maintaining treatment accuracy through systematic processing of anatomical changes and dose distributions.
Solution Approach 2:
The system performs self-service by automatically generating session patient models, propagating contours, calculating doses, and selecting treatment plans without requiring expert intervention. The automated workflow uses pre-established algorithms and criteria to make decisions that previously required manual expert analysis, significantly reducing time while maintaining accuracy.
2Productivity
If expert intervention is minimized in automated workflows, then efficiency increases, but reliability and accuracy may deteriorate
Solution Approach 1:
The system incorporates feedback mechanisms where treatment outcomes and anatomical changes are continuously monitored and fed back into the planning system. This closed-loop approach allows the automated system to learn from and adjust to actual treatment responses, maintaining high reliability without requiring continuous expert intervention. The feedback loop ensures that automated decisions are validated and refined based on real-world outcomes.
Solution Approach 2:
Expert knowledge is encoded into pre-established algorithms, decision rules, and optimization criteria before the automated workflow begins. These preliminary configurations capture expert judgment in the form of automated logic that guides contour propagation, dose calculation, and plan selection, ensuring reliability is built into the system architecture rather than requiring ongoing expert oversight.
3Adaptability or versatility
If on-couch adaptive therapy is implemented, then real-time treatment adaptation is achieved, but the complexity of the procedure increases significantly
Solution Approach 1:
The system employs a multi-functional automated workflow that handles image registration, contour propagation, dose recalculation, and plan selection within a single integrated platform. This universal system performs multiple functions that would otherwise require separate procedures and equipment, reducing overall complexity while enabling real-time adaptive therapy. The unified approach allows the system to adapt to various anatomical changes and treatment scenarios without increasing procedural complexity.
Data Source
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AI summary
Systems and methods for implementing an adaptive therapy workflow that minimizes time needed to create a session patient model, select an appropriate plan for the treatment session, and treat the patient.