Radiation Dose Manipulation via Beamlet Intensity Control
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current radiation therapy systems are cumbersome and inefficient in evaluating trade-offs between delivering radiation dose to tumors while minimizing dose to healthy tissue, lacking direct manipulation and evaluation of achievable dose distributions.
Innovation Solution
A method and system for manipulating achievable dose distribution estimates in radiation therapy, allowing operators to directly modify dose values in specific voxels and update the dose distribution in real-time, using a radiation delivery apparatus that characterizes beams as two-dimensional arrays of beamlets and modifies their intensity values accordingly.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If current treatment plan optimization techniques are used, then radiation dose can be delivered to tumors while minimizing dose to healthy tissue, but the process is cumbersome and disconnects the operator from quick and direct manipulation and evaluation of achievable dose distributions
Solution Approach 1:
The radiation beam is segmented into multiple beamlets arranged in a two-dimensional array, allowing independent intensity control of each beamlet. This segmentation enables operators to directly manipulate dose distributions by adjusting individual beamlet intensities, providing fine-grained control over the dose delivered to different regions of the target and surrounding healthy tissue.
Solution Approach 2:
The system provides dynamic, real-time updating of the achievable dose distribution estimate as beamlet intensity values are modified. This dynamic feedback loop allows operators to immediately evaluate the effects of intensity changes on both tumor dose and healthy tissue dose, enabling interactive optimization without time-consuming iterative recalculations.
2Adaptability or versatility
If complex dose distributions are delivered, then trade-offs between tumor dose and healthy tissue dose can be evaluated, but the system lacks direct manipulation capability and requires cumbersome optimization techniques
Solution Approach 1:
The system pre-calculates and stores the geometric relationships between beamlets, voxels, and ray lines before treatment planning. This preliminary preparation creates a data structure that enables rapid querying and manipulation of dose distributions during interactive optimization, eliminating the need for complex real-time optimization algorithms.
Solution Approach 2:
The system creates a computational model (copy) of the achievable dose distribution that can be manipulated independently from the actual radiation delivery system. Operators can modify beamlet intensities and evaluate dose distributions in this virtual model without affecting the physical system, enabling safe and efficient exploration of different treatment scenarios.
3Manufacturing precision
If iterative optimization is used to achieve optimal dose distribution, then accurate dose delivery can be ensured, but the process is time-consuming and inefficient
Solution Approach 1:
The system implements immediate feedback by automatically updating the achievable dose distribution estimate whenever beamlet intensity values are modified. This real-time feedback provides operators with accurate information about the effects of their adjustments on both tumor coverage and healthy tissue sparing, enabling efficient interactive optimization without requiring multiple iterative cycles.
Solution Approach 2:
The system pre-establishes the mathematical relationships and data structures needed for dose calculation, including the mapping between beamlets, voxels, and ray lines. This preliminary preparation enables rapid dose estimation and updating during interactive optimization, maintaining accuracy while dramatically reducing computation time compared to traditional iterative methods.
Data Source
Figure 1
Figure 2
Figure 3
AI summary
Methods are provided for permitting manipulation of an achievable dose distribution estimate deliverable by a radiation delivery apparatus for proposed treatment of a subject. One such method comprises: determining a dose modification voxel for which it is desired to modify the dose value and a corresponding magnitude of desired dose modification; for each of a plurality of beams: (i) characterizing the beam as a two-dimensional array of beamlets, wherein each beamlet is associated with a corresponding intensity value and a ray line representing the projection of the beamlet into space; and (ii) identifying one or more dose-change beamlets which have associated ray lines that intersect the dose modification voxel; modifying the intensity values of at least one of the dose-change beamlets; and updating the achievable dose distribution estimate to account for the modified intensity values of the at least one of the dose-change beamlets.