Prediction of image noise contributions in proton computed tomography and comparison to measurements

Dickmann, Jannis; Wesp, Philipp; Rädler, Martin; Rit, Simon; Pankuch, Mark; Johnson, R. P.; Bashkirov, V.; Schulte, R.; Parodi, Katia; Landry, Guillaume; Dedes, Georgios

doi:10.1088/1361-6560/ab2474

Cited by 22 publications

(77 citation statements)

References 55 publications

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“…The proton's initial energy was set to 200.00 AE 0.66 MeV, which is the standard mean energy used experimentally. The energy spread was determined in a previous study 34 and agrees with experimental data acquired at the beamline at the Northwestern Medicine Chicago Proton Center, albeit with a wider spot size setting.…”

Section: D1 Simulation Of Pencil Beamssupporting

confidence: 72%

“…The point d 0 is just before the front tracker and was chosen in agreement to previous investigations. 34 Protons were assumed to have an initial direction vector of ðu 0 d u ; v 0 d v ; 1Þ. The beam centers ðu 0 ; v 0 Þ were chosen according to the pencil beam grid defined above.…”

Section: D1 Simulation Of Pencil Beamsmentioning

confidence: 99%

“…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%

“…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%

“…We employ a pCT scanner-specific Monte Carlo simulation, 35 which was shown to reproduce experimental variance levels for a typical fluence field. 34 The problem of finding relative modulation factors for each pencil beam such that the summed fluence pattern results in a prescribed image variance map is a computationally expensive optimization problem which generally requires alternating between the reconstructed image domain (where the variance prescription is defined) and the projection domain (the detector data at each projection angle from which the image is reconstructed, and where the fluence modulation is defined). Therefore, we separated the problem into first solving for the projection domain variance yielding a given prescribed variance in the image domain and subsequently optimizing pencil beam weights leading to this projection domain variance.…”

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: D1 Simulation Of Pencil Beamssupporting

confidence: 72%

Section: D1 Simulation Of Pencil Beamsmentioning

confidence: 99%

Section: E Proposed Algorithm For Fluence Field Optimizationmentioning

confidence: 99%

Section: Introductionmentioning

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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A technique for spatial resolution improvement in helium‐beam radiography

2020

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Purpose: Ion-beam radiography exhibits a significantly lower spatial resolution (SR) compared to xray radiography. This is mostly due the multiple Coulomb scattering (MCS) that the ions undergo in the imaged object. In this work, a novel technique to improve the spatial resolution in helium-beam radiography was developed. Increasing helium-beam energies were exploited in order to decrease the MCS, and therefore increase the SR. Methods: The experimental investigation was carried out with a dedicated ion-tracking imaging system fully composed of thin, pixelated silicon detectors (Timepix). Four helium beams with increasing energies (from 168.8 to 220.5 MeV/u) were used to image a homogeneous 160 mm PMMA phantom with a 2 mm air gap at middle depth. An energy degrader (ED) was placed between the rear tracking system and the energy-deposition detector to compensate for the longer range associated with more energetic ions. The SR was measured for each beam energy. To take into account the overall impact on the image quality, the contrast-to-noise ratio (CNR), the single-ion water equivalent thickness (WET) precision and the absorbed dose in the phantom were also evaluated as a function of the initial beam energy. FLUKA Monte Carlo simulations were used to support the conceptual design of the experimental setup and for dose estimation. Results: In the investigated energy interval, a total SR increase by around 30% was measured with increasing beam energy, reaching a maximum value of 0.69 lp/mm. For radiographs generated with 350 lGy of absorbed dose and 220 lm pixel size, a CNR decrease of 32% was found as the beam energy increases. For 1 mm pixel size, the CNR decreases only by 22%. The CNR of the images was always above 6. The single-ion WET precision was found to be in a range between 1.2% and 1.5%. Conclusions: We have experimentally shown and quantified the possibility of improving SR in helium-beam radiography by using increasing beam energies in combination with an ED. A significant SR increase was measured with an acceptable decrease of CNR. Furthermore, we have shown that an ED can be a valuable tool to exploit increasing beam energies to generate energy-deposition radiographs.

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Experimental helium‐beam radiography with a high‐energy beam: Water‐equivalent thickness calibration and first image‐quality results

et al. 2022

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A clinical implementation of ion-beam radiography (iRAD) is envisaged to provide a method for on-couch verification of ion-beam treatment plans. The aim of this work is to introduce and evaluate a method for quantitative waterequivalent thickness (WET) measurements for a specific helium-ion imaging system for WETs that are relevant for imaging thicker body parts in the future. Methods: Helium-beam radiographs (𝛼Rads) are measured at the Heidelberg Ion-beam Therapy Center with an initial beam energy of 239.5 MeV/u. An imaging system based on three pairs of thin silicon pixel detectors is used for ion path reconstruction and measuring the energy deposition (dE) of each particle behind the object to be imaged. The dE behind homogeneous plastic blocks is related to their well-known WETs between 280.6 and 312.6 mm with a calibration curve that is created by a fit to measured data points. The quality of the quantitative WET measurements is determined by the uncertainty of the measured WET of a single ion (single-ion WET precision) and the deviation of a measured WET value to the well-known WET (WET accuracy). Subsequently, the fitted calibration curve is applied to an energy deposition radiograph of a phantom with a complex geometry. The spatial resolution (modulation transfer function at 10 % -MTF 10% ) and WET accuracy (mean absolute percentage difference-MAPD) of the WET map are determined. Results: In the optimal imaging WET-range from ∼280 to 300 mm, the fitted calibration curve reached a mean single-ion WET precision of 1.55 ± 0.00%. Applying the calibration to an ion radiograph (iRad) of a more complex WET distribution, the spatial resolution was determined to be MTF 10% = 0.49 ± 0.03 lp/mm and the WET accuracy was assessed as MAPD to 0.21 %. Conclusions: Using a beam energy of 239.5 MeV/u and the proposed calibration procedure, quantitative 𝛼Rads of WETs between ∼280 and 300 mm can be measured and show high potential for clinical use. The proposed approach with the resulting image qualities encourages further investigation toward the clinical application of helium-beam radiography.

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Prediction of image noise contributions in proton computed tomography and comparison to measurements

Cited by 22 publications

References 55 publications

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

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

A technique for spatial resolution improvement in helium‐beam radiography

Experimental helium‐beam radiography with a high‐energy beam: Water‐equivalent thickness calibration and first image‐quality results

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