Expert-Guided Volumetric Contouring in Radiation Therapy
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Solution Overview
Problem
Current methods for contouring target volumes and normal tissues in radiation therapy treatment planning are time-consuming and labor-intensive, relying heavily on manual drawing and 3D reconstructions, which limits efficiency and quality, especially with the increasing complexity of image slices and anatomical areas of interest.
Innovation Solution
A system and method that utilize an expert case as an interactive tutorial reference for guiding the contouring of target volumes, allowing users to select and modify contours slice-by-slice and side-by-side, using aligned imaging data sets from both the patient and an expert case, with options for manual or computer-assisted alignment and overlay, to improve contour accuracy and efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual drawing and 3D reconstructions are used for contouring target volumes, then contour accuracy can be achieved, but the process becomes time-consuming and labor-intensive
Solution Approach 1:
The system performs preliminary automated contour generation based on expert cases before manual refinement. Contours are pre-computed using image registration and automated algorithms, providing a starting point that reduces the time required for manual drawing while maintaining accuracy through subsequent expert-guided adjustments.
Solution Approach 2:
The system creates copies of expert-verified contours from reference cases and applies them to new patient data through image registration. These copied contours serve as templates that can be rapidly adapted to new cases, significantly reducing the time required to generate accurate contours from scratch while maintaining quality through expert guidance.
2Reliability
If more image slices and anatomical areas are contoured, then comprehensive treatment planning is improved, but the complexity and labor required increase
Solution Approach 1:
The system uses a universal expert case database that can be applied across multiple anatomical regions and disease types. The same automated contouring algorithms and expert guidance framework work across different imaging modalities and anatomical areas, reducing the complexity burden that would otherwise increase with each additional anatomical region contoured.
Solution Approach 2:
The contouring process is segmented into automated steps (image registration, initial contour generation) and manual refinement steps. This segmentation allows comprehensive contouring of multiple anatomical areas to be handled systematically, with the automated portion managing routine tasks across all regions and expert intervention focused only on critical areas, thereby managing complexity while maintaining comprehensiveness.
3Manufacturing precision
If expert guidance is integrated into the contouring process, then contouring quality is enhanced, but system complexity increases
Solution Approach 1:
The system introduces an intermediary automated algorithm layer that bridges expert knowledge and the contouring process. Instead of requiring direct expert intervention for every contouring task, the system uses automated algorithms trained on expert cases to generate initial contours, with experts providing guidance only when needed. This intermediary layer enhances quality while limiting the complexity increase to the algorithmic layer rather than the entire system.
4Productivity
If automated algorithms are used for contouring, then efficiency is improved, but adaptability to specific patient anatomy may be reduced
Solution Approach 1:
The system implements a dynamic contouring approach where the level of automation adapts based on patient-specific factors. For cases with anatomy similar to expert reference cases, the system operates in fully automated mode for maximum efficiency. For cases with unique or complex anatomy, the system dynamically shifts to interactive mode where experts can guide the contouring process, thereby maintaining both efficiency and anatomical adaptability.
Data Source
AI summary
An efficient method and system of contouring target volumes and normal tissues at risk using an expert case as interactive tutorial reference for radiation therapy treatment plan is disclosed. Target volume contours based on guidance from a disease-matched expert case is selected by the user. The second imaging data set of a new patient is then displayed and linked with expert's case in a the slice-by-slice and side-by-side fashion and at comparable field-of-view angles. Users can generate the target volume contours on the new patient using expert case as tutorial guidance or overlaying the expert contours onto the new patient's imaging data set followed by reforming the target volume contours to fit the anatomical terrain of the patient. Users can then modify the target volume contours of their patient using expert case as tutorial guidance linked in a the slice-by-slice and side-by-side fashion and at comparable field-of-view angles.