Deformable 2D-3D Registration for Respiratory Motion Compensation
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Solution Overview
Problem
Current radiation therapy techniques face challenges in accurately reproducing patient position due to respiratory motion, leading to discrepancies between planned and delivered treatment positions, which degrades the therapeutic ratio.
Innovation Solution
A deformable 2D-3D registration system and method that determines a vector field from simulated 2D images and actual 2D images, using control points to parameterize deformation profiles, allowing for non-rigid registration and updating control point configurations to map 2D images to 3D volumes, incorporating 4D CT data and free-form deformation techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If rigid body transformation is used to compute patient setup, then the computation is simple and fast, but the accuracy deteriorates due to respiratory motion causing non-rigid deformations
Solution Approach 1:
The patent applies dynamics by transitioning from rigid body transformation to deformable registration that accounts for respiratory motion. The system uses 4D CT data (3D spatial + temporal dimension) to model the dynamic deformation of anatomical structures during breathing cycles, allowing the registration method to adapt to changing patient anatomy rather than assuming static rigid transformations.
Solution Approach 2:
The patent changes the transformation parameters from rigid body (6 parameters: 3 translations + 3 rotations) to deformable transformation fields that include spatially varying displacement vectors. The deformable registration uses control points and basis functions to parameterize complex non-rigid deformations, significantly increasing the number of parameters but capturing the true nature of respiratory-induced anatomical changes.
2Measurement precision
If deformable registration is implemented to account for respiratory motion, then patient setup accuracy is improved, but the computational complexity and processing time increase
Solution Approach 1:
The patent applies preliminary action by pre-computing deformable registration transformations using 4D CT data acquired during the planning phase. The deformable registration is performed offline to create pre-computed transformation fields and control point configurations, which can then be applied rapidly during daily treatment sessions without requiring time-consuming real-time computations.
Solution Approach 2:
The patent segments the deformable registration process into distinct phases: (1) 4D CT data acquisition and reconstruction, (2) deformable registration computation using control points and basis functions, (3) transformation field generation, and (4) application to treatment planning. This segmentation allows computationally intensive steps to be performed when time is available (planning phase) while enabling faster application during treatment delivery.
3Reliability
If 4D CT data and deformable registration are used, then the therapeutic ratio is improved through precise beam alignment, but the device complexity and data processing requirements increase
Solution Approach 1:
The patent introduces intermediary elements including control points, basis functions, and transformation fields that mediate between the 4D CT data and the final treatment plan. These intermediaries serve as computational bridges that translate complex 4D anatomical variations into manageable deformation models, enabling accurate beam alignment without requiring direct manipulation of raw 4D CT data during treatment delivery.
Data Source
AI summary
A method for deformable registration including determining a vector field from a two-dimensional matching of a volume of an object of interest and a two-dimensional image of the object of interest, providing a deformation profile, and finding a volume deformation that maps to a state of the two-dimensional image, wherein the deformation is parameterized by the vector field and control points of the deformation profile to find a control point configuration of the volume deformation.