Beam Angle Optimization Algorithm for Radiation Therapy
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Solution Overview
Problem
Current beam angle optimization methods for radiation therapy lack a convenient strategy to select noncolliding beam angles, particularly for large body sizes and immobilization equipment, which increases mechanical collision risk and dosimetric challenges.
Innovation Solution
A voxel-based method that converts DICOM files into Euclidean coordinate locations, calculates optimal beam angles by segmenting patient images into polygons and cubes, and adjusts secondary beam block fields to minimize collisions, using a user-defined goal for hit frequencies and ranking arcs for optimal radiation delivery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If noncoplanar RT techniques are used to achieve dosimetric advantages, then radiation dose distribution is improved, but mechanical collision risk increases
Solution Approach 1:
The system performs preliminary collision detection and beam angle optimization before treatment delivery. By pre-calculating optimal beam angles that avoid mechanical collisions using voxel-based patient anatomy models, the system eliminates collision risks during actual treatment while maintaining dosimetric precision.
Solution Approach 2:
The invention introduces a voxel-based three-dimensional modeling approach to represent patient anatomy and equipment geometry. This dimensional transformation enables comprehensive spatial analysis of beam paths and equipment trajectories, allowing the system to identify and eliminate collision-prone configurations while optimizing dose distribution.
2Reliability
If beam angle optimization is performed to avoid mechanical collisions, then equipment reliability is improved, but computational complexity increases
Solution Approach 1:
The system segments the treatment planning process into distinct computational stages: voxel model generation from DICOM images, collision detection algorithm execution, beam angle optimization calculation, and treatment plan generation. This segmentation allows each computational task to be optimized independently and processed efficiently.
Solution Approach 2:
The invention creates simplified voxel-based digital models that replicate patient anatomy and equipment geometry. These computational models serve as accurate but computationally manageable representations, enabling complex collision detection and optimization calculations without requiring processing of full-resolution medical images.
3Manufacturing precision
If voxel-based modeling is used to improve beam angle calculation accuracy, then dosimetric precision is improved, but data processing time increases
Solution Approach 1:
The system performs preliminary conversion of DICOM image data into voxel models before the optimization calculation phase. This pre-processing step organizes anatomical data into a computational format that enables efficient collision detection and beam angle optimization, reducing processing time during the actual treatment planning stage.
Solution Approach 2:
The invention transforms medical image data into a discrete voxel representation with optimized spatial parameters. By changing the data structure from continuous medical images to discrete volumetric pixels with standardized dimensions, the system enables faster computational processing while maintaining sufficient anatomical detail for accurate beam angle calculation.
Data Source
AI summary
A newly developed algorithm and software can effectively and accurately predict the collisions for the accelerator, phantom, and patient setups, and can help physicians to choose the noncolliding and optimized beam sets efficiently via offering the ideal hits of planning target volume (PTV) and constraints of organ at risks (OARs).