Voxel-Based Radiation Range Determination in Particle Therapy
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Solution Overview
Problem
In particle-beam therapy, accurately predicting the range of radiation in non-homogeneous target volumes is challenging due to the inverted dosage profile of particle radiation, which can lead to incorrect dosages and tissue sparing issues, as existing systems do not effectively account for varying tissue properties and boundary effects.
Innovation Solution
The method involves subdividing the target volume into voxels to determine radiation-attenuating properties using CT scans, deriving water-equivalent ranges, and employing adaptive calibration curves that consider surrounding voxel data to correct for partial volume effects and boundary face influences, ensuring precise radiation planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the target volume is divided into voxels to obtain local radiation-attenuating properties, then measurement precision of radiation range is improved, but device complexity increases due to the need for voxel-based processing and calibration
Solution Approach 1:
The target volume is divided into discrete voxels, with each voxel assigned radiation-attenuating properties based on CT data. This segmentation enables precise local characterization of tissue properties along the radiation path, improving range determination accuracy in non-homogeneous volumes.
Solution Approach 2:
A computation unit serves as an intermediary that processes CT data, determines voxel properties, and calculates water-equivalent ranges. This intermediary component bridges the gap between raw imaging data and therapeutic radiation planning, managing the complexity of voxel-based processing.
2Manufacturing precision
If adaptive calibration curves considering surrounding voxels are used to correct partial volume effects, then manufacturing precision of radiation plan is improved, but loss of time increases due to additional processing steps
Solution Approach 1:
Calibration curves are pre-determined for different tissue types and stored in the system. During radiation planning, these pre-computed calibration curves are retrieved and applied to voxels based on their tissue classification, avoiding the need to perform complex calibrations in real-time and reducing processing time.
Solution Approach 2:
The system adapts calibration parameters based on the tissue type identified in each voxel and its surrounding voxels. By changing calibration parameters according to local tissue characteristics and boundary conditions, the system achieves higher precision in water-equivalent range calculation without requiring uniform processing for all voxels.
3Device complexity
If conventional range determination methods are used without considering tissue heterogeneity, then device complexity is reduced, but reliability of radiation dosage prediction deteriorates
Solution Approach 1:
Each voxel is assigned specific radiation-attenuating properties based on its local tissue characteristics obtained from CT imaging. This local quality approach ensures that the radiation range prediction accounts for tissue heterogeneity, improving reliability in non-homogeneous target volumes compared to conventional uniform methods.
Solution Approach 2:
The system dynamically adjusts calibration parameters based on the tissue type and composition identified in each voxel. By adapting parameters to local conditions rather than using fixed values, the system achieves more reliable dosage predictions while maintaining reasonable system complexity through automated parameter selection.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enables high-precision particle therapy by accurately associating local radiation-attenuating properties with predicted water-equivalent ranges, preventing underdosage in the target volume and overdosage in surrounding tissues, thereby optimizing radiation delivery.
Implementation Method 1
The classification into volume elements is used first to obtain information with local resolution about radiation-attenuating properties of the target volume. The information is obtained, for example, by radiology, computed tomography... The range of values of the Hounsfield units (HU) is from −1000 (extremely slight attenuation of X-radiation) to +2000 (very strong attenuation of X-radiation)
Data Source
AI summary
A method for determining a range of radiation is provided. The method includes defining a target volume to be irradiated using a plurality of voxels; determining, without exposing the target volume to radiation, radiation-attenuating properties that are associated with individual voxels of the plurality of voxels; deriving a range datum from the radiation-attenuating properties; and changing the range datum of a first voxel if the range datum of the first voxel differs from the range datum of two adjacent voxels.