Effects of transverse heterogeneities on the most likely path of protons

Khellaf, Feriel; Krah, Nils; Rinaldi, I.; Létang, Jean Michel; Rit, Simon

doi:10.1088/1361-6560/ab02a8

Cited by 9 publications

(14 citation statements)

References 27 publications

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“…Collins-Fekete et al [72] , Brooke and Penfold [73] proposed a method to account for inhomogeneous material composition along the MLP based on an a priori image. Khellaf et al [74] investigated the impact of material inhomogeneities normal to the path direction. As a conclusion of these three works, approximating patient geometries by homogeneous water volumes is sufficiently accurate for MLP estimation.…”

Section: Simulations With Ideal Detection and Analytical Studiesmentioning

confidence: 99%

The role of Monte Carlo simulation in understanding the performance of proton computed tomography

Dedes

Dickmann

Giacometti

et al. 2022

Zeitschrift für Medizinische Physik

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Proton computed tomography (pCT) is a promising tomographic imaging modality allowing direct reconstruction of proton relative stopping power (RSP) required for proton therapy dose calculation. In this review article, we aim at highlighting the role of Monte Carlo (MC) simulation in pCT studies. After describing the requirements for performing proton computed tomography and the various pCT scanners actively used in recent research projects, we present an overview of available MC simulation platforms. The use of MC simulations in the scope of investigations of image reconstruction, and for the evaluation of optimal RSP accuracy, precision and spatial resolution omitting detector effects is then described. In the final sections of the review article, we present specific applications of realistic Monte Carlo simulations of an existing pCT scanner prototype, which we describe in detail.

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Section: Simulations With Ideal Detection and Analytical Studiesmentioning

confidence: 99%

The role of Monte Carlo simulation in understanding the performance of proton computed tomography

Dedes

Dickmann

Giacometti

et al. 2022

Zeitschrift für Medizinische Physik

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“…If variation of material properties in depth are considered by appropriately adjusting the β 2 p 2 -term in T (u) and the radiation length X 0 (u), the polynomial degree M will likely depend on the degree of heterogeneity. The impact of material heterogeneities on the MLP has been studied elsewhere (Wong et al, 2009;Khellaf et al, 2019) and was not the subject of this work.…”

Section: Resultsmentioning

confidence: 99%

Polynomial modelling of proton trajectories in homogeneous media for fast most likely path estimation and trajectory simulation

2019

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Protons undergo many small angle deflections when traversing a medium, such as a patient. This effect, known as multiple Coulomb scattering (MCS), leads to degraded image resolution in proton radiography and computed tomography (CT) and to lateral spreading of the dose distribution in proton therapy. To optimally account for MCS in proton imaging, the most likely path (MLP) of a proton is estimated based on its position and propagation angle measured in front of and behind the object. In this work, we propose a functional which quantifies the likelihood of a proton trajectory and study how it can be used to model proton trajectories in a homogeneous medium. We focus on two aspects: first, we present an analytical method to quickly generate proton trajectories in a homogeneous medium based on the likelihood functional and validate it through Monte Carlo simulations. It could be used for fast generation of proton CT images without a full Monte Carlo simulation, or potentially to complement the components in a treatment planning Monte Carlo which simulate MCS. Second, by maximising the likelihood functional, we derive an expression for the MLP which is equivalent to the conventional ones reported in the literature yet computationally more convenient. Moreover, we show that the MLP is strictly a polynomial function if the protons' energy loss in the medium is approximated as a polynomial and that the orders of both are linked. We validate our MLP through Monte Carlo simulations and compare proton CT images reconstructed with our expression and with the conventional one. We find that an MLP polynomial of orders larger than five do not lead to increased spatial resolution compared to lower order expressions.

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“…The increased bin size does reduce the overall noise in the phantom, but not to the point where it is equal to the Prior Filter. Additionally, this phantom is mostly uniform which reduces the negative impacts of increasing the bin size such as splitting the distribution as described in Khellaf et al 10 . Some of the effect can be seen in the negative side of the x axis, where the noise increases sharply, due to the higher density inserts on this side.…”

Section: Acknowledgmentmentioning

confidence: 99%

“…INTRODUCTION theory, any cut off value can be used. It may, however, perform poorly in a heterogeneous medium, where the distribution of all particles is a poor surrogate for the state of an individual particle 10 .…”

Section: Introductionmentioning

confidence: 99%

“…with a threshold of

\sigma _t = 2\sigma

, but in theory, any cut off value can be used. It may, however, perform poorly in a heterogeneous medium, where the distribution of all particles is a poor surrogate for the state of an individual particle 10 . Despite being the filter approach used most often in literature, there is no agreed‐upon standard of how to perform the 3σ filtering.…”

Section: Introductionmentioning

confidence: 99%

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A likelihood‐based particle imaging filter using prior information

et al. 2023

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Background: Particle imaging can increase precision in proton and ion therapy. Interactions with nuclei in the imaged object increase image noise and reduce image quality, especially for multi-nucleon ions that can fragment, such as helium.Purpose: This work proposes a particle imaging filter, referred to as the Prior Filter, based on using prior information in the form of an estimated relative stopping power (RSP) map and the principles of electromagnetic interaction, to identify particles that have undergone nuclear interaction. The particles identified as having undergone nuclear interactions are then excluded from the image reconstruction, reducing the image noise. Methods:The Prior Filter uses Fermi-Eyges scattering and Tschalär straggling theories to determine the likelihood that a particle only interacts electromagnetically. A threshold is then set to reject those particles with a low likelihood. The filter was evaluated and compared with a filter that estimates this likelihood based on the measured distribution of energy and scattering angle within pixels, commonly implemented as the 3σ filter. Reconstructed radiographs from simulated data of a 20 cm water cylinder and an anthropomorphic chest phantom were generated with both protons and helium ions to assess the effect of the filters on noise reduction.The simulation also allowed assessment of secondary particle removal through the particle histories. Experimental data were acquired of the Catphan CTP 404 Sensitometry phantom using i the U.S. proton CT (pCT) collaboration prototype scanner. The proton and helium images were filtered with both the prior filtering method and a state-of-the-art method including an implementation of the 3σ filter. For both cases a dE-E telescope filter, designed for this type of detector, was also applied. Results:The proton radiographs showed a small reduction in noise (1 mm of water equivalent thickness) but a larger reduction in helium radiographs (up to 5-6 mm of water equivalent thickness) due to better secondary filtering. The proton and helium CT images reflected this, with similar noise at the center of the phantom (0.02 RSP) for the proton images and an RSP noise of 0.03 for the proposed filter and 0.06 for the 3σ filter in the helium images. Images reconstructed from data with a dose reduction, up to a factor of 9, maintained a lower noise level using the Prior Filter over the state-of-the-art filtering method. Conclusions:The proposed filter results in images with equal or reduced noise compared to those that have undergone a filtering method typical of current particle imaging studies. This work also demonstrates that the proposed filter maintains better performance against the state of the art with up to a nine-fold dose reduction.

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Effects of transverse heterogeneities on the most likely path of protons

Cited by 9 publications

References 27 publications

The role of Monte Carlo simulation in understanding the performance of proton computed tomography

The role of Monte Carlo simulation in understanding the performance of proton computed tomography

Polynomial modelling of proton trajectories in homogeneous media for fast most likely path estimation and trajectory simulation

A likelihood‐based particle imaging filter using prior information

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