Proton CT Image Reconstruction via Scattering-Aware Cost Functions
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Solution Overview
Problem
Current image reconstruction techniques for proton Computed Tomography (pCT) face challenges due to proton beams' nonlinear paths and interactions with body tissues, leading to inaccurate radiation dose calculations and limited accuracy in proton therapy, as they rely on X-ray computed tomography methods that do not account for proton deflection and scattering.
Innovation Solution
An image reconstruction method that records projection path and energy loss information of protons traversing an object, using cost functions like Adaptive-weighted Total Variation, Penalized Weighted Least-Squares, and Alpha-Divergence to iteratively update images, accounting for Multiple Coulomb Scattering and energy deposition, resulting in more accurate 3D imaging and treatment planning.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional X-ray computed tomography methods are used for proton treatment planning, then the imaging process is simple and well-established, but the accuracy of radiation dose calculations deteriorates due to proton deflection and scattering not being accounted for
Solution Approach 1:
The patent changes the fundamental parameters of the imaging approach by switching from X-ray photons to proton particles, and from straight-line path assumptions to curved trajectory modeling. This involves changing the particle type, energy loss mechanisms considered, and path geometry parameters to accurately reflect proton behavior in tissue.
Solution Approach 2:
The patent introduces an intermediary transformation process that converts measured proton energy loss data into quantitative images of electron density distribution. This intermediary step involves sophisticated image reconstruction algorithms that account for proton scattering and energy deposition patterns to bridge the gap between raw measurements and clinically useful images.
2Reliability
If proton beams are used for therapy, then radiation energy is delivered precisely to targeted tissue with minimal harm to surrounding tissues, but image reconstruction becomes difficult due to nonlinear proton paths
Solution Approach 1:
The patent explicitly accounts for the curved trajectories of protons as they traverse through tissue, replacing the straight-line path assumption with models that incorporate multiple Coulomb scattering effects. This involves using curved path geometry in the image reconstruction algorithms to match the actual nonlinear proton tracks.
Solution Approach 2:
The patent employs iterative image reconstruction methods where the reconstructed images are used to update the proton transport model, which in turn refines the image reconstruction. This feedback loop continuously improves the accuracy of both the proton path modeling and the resulting images.
3Adaptability or versatility
If xCT attenuation maps are used for treatment planning, then the process is conventional and widely available, but uncertainty is introduced into proton therapy due to differences in physical interactions between X-rays and protons
Solution Approach 1:
The patent creates a dual-purpose system where the proton imaging apparatus can serve both diagnostic imaging functions and treatment planning functions. The same proton beam and detection system used for therapy can generate accurate attenuation maps specific to proton interactions, eliminating the need for separate X-ray imaging while providing more accurate proton-specific data.
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 method provides improved accuracy and efficiency in proton beam dose distribution and patient positioning, overcoming limitations of conventional X-ray-based methods by directly reconstructing proton paths and interactions, enhancing the precision of proton therapy.
Implementation Method 1
a proton loses energy through elastic and inelastic collisions with atomic electrons and nuclei, resulting in a nonlinear path of traversal
Implementation Method 2
a proton loses energy through elastic and inelastic collisions with atomic electrons and nuclei
Implementation Method 3
This mode of interaction also results in an energy deposition phenomenon known as the Bragg peak in which the proton releases a burst of energy around the end of its trajectory
Data Source
AI summary
Provided herein is a computerized image reconstruction apparatus and method that includes recording projection path information and energy loss information of a plurality of particles traversing an object being imaged and determining an estimated image of the object based on the projection path information and the energy loss information sampled into a projection format. The estimated image includes an active volume defined by an enclosure border. Cost function minimization uses an Adaptive-weighted Total Variation cost function, a Penalized Weighted Least-Squares cost function, or an Alpha-Divergence cost function to update the estimated image. An iterative updating algorithm corresponding to the cost function updates the estimated image and produces a final image based on the estimated image according to a predetermined threshold.