Radiotherapy Image Comparison System for Treatment Re-planning
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Solution Overview
Problem
Current medical radiation therapy systems fail to effectively re-plan and refine treatment processes based on subsequent 3D X-Ray images, leading to potentially ineffective treatments due to anatomical changes and misidentification of patient images.
Innovation Solution
A system that compares aligned 3D X-Ray images taken at different treatment stages to determine anatomical changes and verify patient identity, using image alignment and comparison techniques to generate alerts for re-planning and patient verification, thereby ensuring accurate treatment targeting and patient association.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If subsequent 3D X-Ray images are taken during radiotherapy treatment, then anatomical changes can be detected, but the images are not effectively used to re-plan and refine treatment processes
Solution Approach 1:
The system implements automated feedback by comparing subsequent X-ray images with the original treatment plan images, detecting anatomical changes, and automatically triggering treatment plan updates when changes exceed predefined thresholds. This closed-loop feedback mechanism ensures that image data is effectively utilized to maintain treatment accuracy throughout the radiotherapy process.
Solution Approach 2:
The system performs preliminary comparison and analysis of subsequent images against the treatment plan before actual treatment delivery. By pre-detecting anatomical changes and flagging cases requiring re-planning, the system prepares treatment adjustments in advance, preventing ineffective treatment delivery and ensuring that updated plans are ready when needed.
2Measurement precision
If manual image verification is performed, then patient identity can be confirmed, but the process is time-consuming and prone to human error
Solution Approach 1:
The system performs automated self-verification by comparing patient anatomical features in subsequent images with those in the treatment plan images. The automated comparison algorithm independently verifies patient identity and detects anatomical changes without requiring manual intervention, thereby eliminating human error and significantly reducing verification time while maintaining high accuracy.
3Reliability
If comprehensive image comparison is performed on all subsequent images, then treatment accuracy is improved, but system complexity and processing time increase
Solution Approach 1:
The system applies local quality analysis by focusing comparison efforts on specific anatomical regions and features that are most relevant to treatment accuracy. Rather than uniformly processing all image data, the system identifies and prioritizes critical anatomical structures for comparison, reducing overall system complexity while maintaining high treatment plan accuracy through targeted local analysis.
Solution Approach 2:
The system dynamically adjusts comparison parameters and thresholds based on treatment stage, anatomical region, and detected change magnitude. By adaptively modifying analysis parameters rather than using fixed comprehensive processing, the system optimizes the balance between treatment accuracy and processing complexity, applying more rigorous analysis only where and when necessary.
Data Source
AI summary
A system automatically compares radiotherapy 3D X-Ray images and subsequent images for update and re-planning of treatment and for verification of correct patient and image association. A medical radiation therapy system and workflow includes a task processor for providing task management data for initiating image comparison tasks prior to performing a session of radiotherapy. An image comparator, coupled to the task processor, in response to the task management data, compares a first image of an anatomical portion of a particular patient used for planning radiotherapy for the particular patient, with a second image of the anatomical portion of the particular patient obtained on a subsequent date, by image alignment and comparison of image element representative data of aligned first and second images to determine an image difference representative remainder value and determines whether the image difference representative remainder value exceeds a first predetermined threshold. An output processor, coupled to the image comparator, initiates generation of an alert message indicating a need to review planned radiotherapy treatment for communication to a user in response to a determination the image difference representative remainder value exceeds a predetermined threshold.