Fast and Accurate Proton Computed Tomography Image Reconstruction for Applications in Proton Therapy

Penfold, Scott; Schulte, R.; Bashkirov, V.; Rosenfeld, Anatoly

doi:10.1007/978-3-642-03474-9_61

Cited by 8 publications

(9 citation statements)

References 10 publications

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“…The total number of proton histories generated for each projection was 12 × 10 6 . An iterative algebraic reconstruction algorithm [27] was used to calculate the 3D RSP map of the HIGH_RES_HEAD taking WEPL, position and direction of individual protons as input [17]. …”

Section: Methodsmentioning

confidence: 99%

Development of a high resolution voxelised head phantom for medical physics applications

et al. 2017

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Computational anthropomorphic phantoms have become an important investigation tool for medical imaging and dosimetry for radiotherapy and radiation protection. The development of computational phantoms with realistic anatomical features contribute significantly to the development of novel methods in medical physics. For many applications, it is desirable that such computational phantoms have a real-world physical counterpart in order to verify the obtained results. In this work, we report the development of a voxelised phantom, the HIGH_RES_HEAD, modelling a paediatric head based on the commercial phantom 715-HN (CIRS). HIGH_RES_HEAD is unique for its anatomical details and high spatial resolution (0.18 × 0.18 mm2 pixel size). The development of such a phantom was required to investigate the performance of a new proton computed tomography (pCT) system, in terms of detector technology and image reconstruction algorithms. The HIGH_RES_HEAD was used in an ad-hoc Geant4 simulation modelling the pCT system. The simulation application was previously validated with respect to experimental results. When compared to a standard spatial resolution voxelised phantom of the same paediatric head, it was shown that in pCT reconstruction studies, the use of the HIGH_RES_HEAD translates into a reduction from 2% to 0.7% of the average relative stopping power difference between experimental and simulated results thus improving the overall quality of the head phantom simulation. The HIGH_RES_HEAD can also be used for other medical physics applications such as treatment planning studies. A second version of the voxelised phantom was created that contains a prototypic base of skull tumour and surrounding organs at risk.

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Section: Methodsmentioning

confidence: 99%

Development of a high resolution voxelised head phantom for medical physics applications

et al. 2017

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“…In the current work a block-iterative algorithm known as DROP [31] was used. This algorithm has been compared with other projection algorithms and has demonstrated minor noise and convergence rate advantages with pCT data [34].…”

Section: Iterative Reconstruction With Tvsmentioning

confidence: 99%

Total variation superiorization in dual-energy CT reconstruction for proton therapy treatment planning

Zhu

Penfold

2017

Inverse Problems

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Proton therapy is a precise form of radiotherapy in which the range of an energetic beam of protons within a patient must be accurately known. The current approach based on single-energy computed tomography (SECT) can lead to uncertainties in the proton range of approximately 3%. This range of uncertainty may lead to under-dosing of the tumour or over-dosing of healthy tissues. Dual-energy CT (DECT) theoretically has the potential to reduce these range uncertainties by quantifying electron density and the effective atomic number. In practice, however, DECT images reconstructed with filtered backprojection (FBP) tend to suffer from high levels of noise. The objective of the current work was to examine the effect of total variation superiorization (TVS) on proton therapy planning accuracy when compared with FBP. A virtual CT scanner was created with the Monte Carlo toolkit Geant4. Tomographic images were reconstructed with FBP and TVS combined with diagonally relaxed orthogonal projections (TVS-DROP). A total variation minimization (TVM) filter was also applied to the image reconstructed with FBP (FBP-TVM). Quantitative accuracy and variance of proton relative stopping power (RSP) derived from each image set was assessed. Mean RSPs were comparable with each image; however, the standard deviation of pixel values with TVS-DROP was reduced by a factor of 0.44 compared with the FBP image and a factor of 0.66 when compared with the FBP-TVM image. Proton doses calculated with the TVS-DROP image set were also better able to predict a reference dose distribution when compared with the FBP and FBP-TVM image sets. The study demonstrated the potential advantages of TVS-DROP as an image reconstruction method for DECT applied to proton therapy treatment planning.

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“…We consider an approach that mixes ISM and string-averaging algorithms (SA algorithms). The general form of the SA algorithm was proposed initially in [13] and applied in solving convex feasibility problems with algorithms that use projection methods [13,14,44]. Strings are created so that ISM (more generally, any ò-ISM) can be processed in an independent form for each string (by step operators).…”

Section: Introductionmentioning

confidence: 99%

String-averaging incremental subgradients for constrained convex optimization with applications to reconstruction of tomographic images

Oliveira¹,

Helou²,

Costa³

2016

Inverse Problems

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We present a method for non-smooth convex minimization which is based on subgradient directions and string-averaging techniques. In this approach, the set of available data is split into sequences (strings) and a given iterate is processed independently along each string, possibly in parallel, by an incremental subgradient method (ISM). The end-points of all strings are averaged to form the next iterate. The method is useful to solve sparse and large-scale non-smooth convex optimization problems, such as those arising in tomographic imaging. A convergence analysis is provided under realistic, standard conditions. Numerical tests are performed in a tomographic image reconstruction application, showing good performance for the convergence speed when measured as the decrease ratio of the objective function, in comparison to classical ISM.

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Fast and Accurate Proton Computed Tomography Image Reconstruction for Applications in Proton Therapy

Cited by 8 publications

References 10 publications

Development of a high resolution voxelised head phantom for medical physics applications

Development of a high resolution voxelised head phantom for medical physics applications

Total variation superiorization in dual-energy CT reconstruction for proton therapy treatment planning

String-averaging incremental subgradients for constrained convex optimization with applications to reconstruction of tomographic images

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