Radiation Dose Computation Using Heterogeneity Compensation
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Solution Overview
Problem
Current radiation therapy systems face limitations in computational performance for dose computation, particularly when dealing with heterogeneous density distributions, leading to inefficiencies in treatment planning and the inability to perform real-time radiation therapy due to serial algorithms that do not effectively utilize multi-core processing architectures.
Innovation Solution
A radiation planning system that includes a data processor capable of receiving information about an intended treatment region, computing radiation doses with contributions from scattering at multiple locations, and determining therapy parameters, utilizing a back-projected ray tracing algorithm to avoid read-write conflicts and improve performance on graphics processing units (GPUs).
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If superposition/convolution algorithm is used for dose computation, then manufacturing precision is improved, but productivity deteriorates
Solution Approach 1:
The patent segments the dose computation process into two distinct phases: (1) a fast pre-computation phase that calculates dose in homogeneous media using efficient algorithms, and (2) a correction phase that adds heterogeneity corrections for density variations. This segmentation allows the majority of computations to use fast algorithms while applying accurate corrections only where needed, resolving the contradiction between speed and accuracy.
Solution Approach 2:
The patent performs preliminary computation of dose distribution in homogeneous media before applying heterogeneity corrections. By pre-computing the base dose distribution using fast algorithms and then adding correction terms for density variations, the system achieves both computational efficiency and dosimetric accuracy without requiring full superposition/convolution calculations.
2Manufacturing precision
If intensity modulation is implemented, then manufacturing precision is improved, but productivity deteriorates
Solution Approach 1:
The patent segments the optimization process by using the fast approximate dose computation method during iterative optimization to quickly evaluate different treatment plans, and then applies more accurate superposition/convolution calculations for final dose verification. This allows multiple optimization iterations to be performed rapidly without sacrificing final plan quality.
Solution Approach 2:
The patent uses a computationally inexpensive approximate dose calculation method during the optimization process that can be rapidly evaluated multiple times, accepting that this approximation is not fully accurate. The more accurate but computationally expensive superposition/convolution method is then used only for final verification, similar to using a disposable sketch before creating a final artwork.
3Manufacturing precision
If serial algorithms are used for dose computation, then manufacturing precision is maintained, but productivity deteriorates
Solution Approach 1:
The patent replaces the traditional serial computation mechanism with a parallel computation approach using Graphics Processing Units (GPUs). By formulating the dose computation problem in terms of parallelizable operations and utilizing GPU architecture, the system maintains dosimetric accuracy while achieving significant speedups through parallel processing of multiple dose calculation points simultaneously.
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 significantly enhances computational efficiency, reducing artifacts from discretization and achieving a multiple-order-of-magnitude performance improvement, enabling faster and more accurate radiation therapy planning, including real-time capabilities and improved handling of heterogeneous tissue densities.
Implementation Method 1
The Compton effect is the most important photon-tissue interaction for the treatment of cancer. In this case, a photon collides with a 'free electron,' i.e, one that is not tightly bound to the atom.
Implementation Method 2
In the photoelectric effect, an incoming photon transfers energy to a tightly bound electron. The photon transfers practically all of its energy to the electron and ceases to exist.
Data Source
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AI summary
A system for radiation therapy includes a radiation planning system. The radiation planning system includes a data processor that is adapted to receive information concerning an intended radiation treatment region of a body, receive a calculated initial energy released per unit mass for a plurality of locations within the body, compute a radiation dose at a plurality of locations within the radiation treatment region based on the calculated initial energy released per unit mass and including radiation dose contributions due to scattering from other locations within the body, and determine radiation therapy parameters for providing radiation treatment to the intended radiation treatment region based on the radiation dose computed at the plurality of locations within the radiation treatment region. Including radiation dose contributions due to scattering from other locations within the body take into account density discontinuities in the body.