Adaptive Feedback Loop for Radiation Dose Verification
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Solution Overview
Problem
In radiation therapy, uncertainties such as patient setup variations, physiological changes, and motion can lead to inaccuracies in delivering the intended radiation dose, with existing quality assurance methods often failing to detect errors in treatment planning due to focusing on machine functionality rather than input data correctness.
Innovation Solution
Implementing an adaptive feedback loop for quality assurance that involves image-guided patient positioning, online image acquisition during treatment, and automatic recalculations of the radiation dose to ensure accurate delivery, using software to process data and adjust treatment plans based on real-time patient anatomy and position.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional quality assurance methods focusing on machine functionality are used, then machine operation can be verified, but errors in treatment planning and input data cannot be detected
Solution Approach 1:
The patent implements a feedback mechanism where daily images acquired during treatment are automatically processed and compared against the treatment plan. The system recalculates the delivered dose based on actual patient anatomy and position, then feeds this information back to verify whether the planned dose was accurately delivered. This closed-loop feedback system detects discrepancies between planned and actual treatment, identifying errors in planning or execution that traditional QA methods would miss.
2Manufacturing precision
If adaptive feedback loop with online image acquisition and automatic recalculation is implemented, then treatment accuracy is improved, but system complexity and processing time increase
Solution Approach 1:
The system performs automatic processing of daily images and dose recalculation without requiring manual intervention. The software autonomously acquires images, processes them through the treatment planning algorithm, recalculates the delivered dose, and compares results against the plan. This self-service automation reduces the need for complex manual QA procedures while maintaining high accuracy in dose delivery verification.
3Reliability
If margins are increased to account for target location uncertainties, then target coverage is improved, but radiation exposure to healthy tissue increases
Solution Approach 1:
The patent transitions from static margin planning to dynamic verification. Instead of relying on fixed margins calculated during planning, the system dynamically verifies actual target location and dose delivery using daily images acquired during treatment. By continuously monitoring the actual position and recalculating the delivered dose, the system can identify when margins are sufficient or when adjustments are needed, allowing for more precise dose delivery that reduces unnecessary exposure to healthy tissues while ensuring adequate target coverage.
Data Source
AI summary
A system and method of automatically processing data relating to a radiation therapy treatment plan. The method includes the acts of acquiring image data of a patient, generating a treatment plan for the patient based at least in part on the image data, the treatment plan including a calculated radiation dose to be delivered to the patient, acquiring an on-line image of the patient in substantially a treatment position, delivering at least a portion of the calculated radiation dose to the patient, and automatically recalculating the radiation dose received by the patient.