Two-dimensional noise reconstruction in proton computed tomography using distance-driven filtered back-projection of simulated projections

Rädler, Martin; Landry, Guillaume; Rit, Simon; Schulte, R.; Parodi, Katia; Dedes, G.

doi:10.1088/1361-6560/aae5c9

Cited by 22 publications

(58 citation statements)

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“…The algorithm extends ideas from literature for x-ray CT 21,22 to requirements of pCT such as the 3D projections due to distance-driven binning 39 and a more complex noise model. 33,34 It is, to our knowledge, not equivalent to any existing approach as it is performed in projection domain and computationally feasible without simplification to a parallelbeam geometry.…”

Section: E Proposed Algorithm For Fluence Field Optimizationmentioning

confidence: 99%

“…Given a variance projection stack V a unit ðu; v; dÞ, the corresponding image variance V unit ðx; y; zÞ can be calculated analytically as reconstruction was performed using filtered backprojection. Please refer to previous publications 33,34 for details about variance calculations for pCT and for variance reconstruction in general. 42…”

Section: E1 Step 1: Variance At Unit Fluence Predictionmentioning

confidence: 99%

“…30 A challenge for FMpCT is that simple Poisson noise modeling is not sufficient, as image variance for pCT depends on the object's heterogeneity, and several contributions, including multiple Coulomb scattering, have to be taken into account for fluence-modulation. 33,34 In this work, we present a method for fluence-field optimization in pCT using pencil beam scanning. We employ a pCT scanner-specific Monte Carlo simulation, 35 which was shown to reproduce experimental variance levels for a typical fluence field.…”

Section: Introductionmentioning

confidence: 99%

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An optimization algorithm for dose reduction with fluence‐modulated proton CT

et al. 2020

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Purpose: Fluence-modulated proton computed tomography (FMpCT) using pencil beam scanning aims at achieving task-specific image noise distributions by modulating the imaging proton fluence spot-by-spot based on an object-specific noise model. In this work, we present a method for fluence field optimization and investigate its performance in dose reduction for various phantoms and image variance targets. Methods: The proposed method uses Monte Carlo simulations of a proton CT (pCT) prototype scanner to estimate expected variance levels at uniform fluence. Using an iterative approach, we calculate a stack of target variance projections that are required to achieve the prescribed image variance, assuming a reconstruction using filtered backprojection. By fitting a pencil beam model to the ratio of uniform fluence variance and target variance, relative weights for each pencil beam can be calculated. The quality of the resulting fluence modulations is evaluated by scoring imaging doses and comparing them to those at uniform fluence, as well as evaluating conformity of the achieved variance with the prescription. For three different phantoms, we prescribed constant image variance as well as two regions-of-interest (ROI) imaging tasks with inhomogeneous image variance. The shape of the ROIs followed typical beam profiles for proton therapy. Results: Prescription of constant image variance resulted in a dose reduction of 8.9% for a homogeneous water phantom compared to a uniform fluence scan at equal peak variance level. For a more heterogeneous head phantom, dose reduction increased to 16.0% for the same task. Prescribing two different ROIs resulted in dose reductions between 25.7% and 40.5% outside of the ROI at equal peak variance levels inside the ROI. Imaging doses inside the ROI were increased by 9.2% to 19.2% compared to the uniform fluence scan, but can be neglected assuming that the ROI agrees with the therapeutic dose region. Agreement of resulting variance maps with the prescriptions was satisfactory. Conclusions: We developed a method for fluence field optimization based on a noise model for a real scanner used in pCT. We demonstrated that it can achieve prescribed image variance targets. A uniform fluence field was shown not to be dose optimal and dose reductions achievable with the proposed method for FMpCT were considerable, opening an interesting perspective for image guidance and adaptive therapy.

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Section: E Proposed Algorithm For Fluence Field Optimizationmentioning

confidence: 99%

Section: E1 Step 1: Variance At Unit Fluence Predictionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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An optimization algorithm for dose reduction with fluence‐modulated proton CT

et al. 2020

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“…However, energy straggling as well as nuclear interactions inside the object to be imaged result in events with an unusually large energy loss and the production of secondary protons that consequently increase the image noise and compromise the RSP accuracy if included in the image reconstruction procedure (Schulte et al 2005) -see also (Rädler et al 2018) for a comprehensive analysis of image 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 A c c e p t e d M a n u s c r i p t noise in proton imaging. In order to ensure high quality pCT images, data filters have to be implemented that accurately identify and remove such events from the recorded particle histories.…”

Section: Introductionmentioning

confidence: 99%

Improving single-event proton CT by removing nuclear interaction events within the energy/range detector

Volz¹,

Piersimoni²,

Johnson³

et al. 2019

Phys. Med. Biol.

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Improving single-event proton CT by removing nuclear interaction events within the energy/range detector. Permalink https://escholarship.org/uc/item/5rg9r6rw Journal Physics in medicine and biology, 64 (15) Abstract. Data filtering is crucial for accurate relative stopping power (RSP) reconstruction in proton CT (pCT). In this work, we assess different filters and their performance for the US pCT collaboration prototype pCT system in Monte Carlo (MC) simulations. The potential of using the recently proposed ∆E-E filter for removing nuclear interactions that occurred in the energy/range detector of the pCT system is investigated.Full pCT scans were acquired with the TOPAS MC simulated version of the prototype scanner that comprises two tracking detectors and a 5 stage energy/range detector. An ideal water cylinder and a water cylinder with 5 tissue inserts were investigated. Before image reconstruction, a 3 σ WEPL filter was applied as the only filter, or in addition to filters acting on the energy deposit in each of the energy detector stages, as done currently with the prototype. The potential of the ∆E-E filter that was recently proposed for helium imaging was assessed. The results were compared to simulations for which nuclear interactions were disabled representing ground truth.The 3 σ WEPL filter alone was not sufficient to filter out all nuclear interaction events and systematic fluctuations in the form of ring artifacts were present in the pCT reconstructed images. Applying energy filters currently used with the device prior to the 3 σ WEPL filter only slightly improved the image quality. A 2 σ WEPL filter improved the mean RSP accuracy, but could not

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“…Specifically, we introduced the relative scattering power in analogy to the relative stopping power in energy-loss proton CT and adapted a distance-driven filtered backprojection algorithm to scattering proton CT. It is worth mentioning that there is some resemblance between our algorithm and the noise reconstruction in Rädler et al (2018).…”

Section: Discussionmentioning

confidence: 82%

Scattering proton CT

et al. 2020

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Proton computed tomography (CT) is an imaging modality investigated mainly in the context of proton therapy as a complement to x-ray CT. It uses protons with high enough energy to fully traverse the imaged object. Common prototype systems measure each proton's position and direction upstream and downstream of the object as well as the energy loss which can be converted into the water equivalent thickness. A reconstruction algorithm then produces a map of the relative stopping power in the object. As an alternative to energy-loss proton CT, it has been proposed to reconstruct a map of the object's scattering power based on the protons' angular dispersion which can be estimated from the measured directions. As in energy-loss proton CT, reconstruction should best be performed considering the non-linear shape of proton trajectories due to multiple Coulomb scattering, but no algorithm to achieve this is so far available in the literature. In this work, we propose a filtered backprojection algorithm with distance-driven binning to account for the protons' most likely path. Furthermore, we present a systematic study of scattering proton CT in terms of inherent noise and spatial resolution and study the artefacts which arise from the physics of multiple Coulomb scattering. Our analysis is partly based on analytical models and partly on Monte Carlo simulations. Our results show that the proposed algorithm performs well in reconstructing relative scattering power maps, i.e. scattering power relative to that of water. Spatial resolution is improved by almost a factor of three compared to straight line projection and is comparable to energy-loss proton CT. Image noise, on the other hand, is inherently much higher. For example, in a water cylinder of 20 cm diameter, representative of a human head, noise in the central image pixel is about 40 times higher in scattering proton CT than in energy-loss proton CT. Relative scattering power in dense regions such as bone inserts is systematically underestimated by a few percent, depending on beam energy and phantom geometry.

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Two-dimensional noise reconstruction in proton computed tomography using distance-driven filtered back-projection of simulated projections

Cited by 22 publications

References 50 publications

An optimization algorithm for dose reduction with fluence‐modulated proton CT

An optimization algorithm for dose reduction with fluence‐modulated proton CT

Improving single-event proton CT by removing nuclear interaction events within the energy/range detector

Scattering proton CT

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