Evaluation of the impact of a scanner prototype on proton CT and helium CT image quality and dose efficiency with Monte Carlo simulation.

Objective.The use of ion computed tomography (CT) promises to yield improved relative stopping power (RSP) estimation as input to particle therapy treatment planning. Recently, proton CT (pCT) has been shown to yield RSP accuracy on par with state-of-the-art x-ray dual energy CT. There are however concerns that the lower spatial resolution of pCT compared to x-ray CT may limit its potential, which has spurred interest in the use of helium ion CT (HeCT). The goal of this study was to investigate image quality of pCT and HeCT in terms of noise, spatial resolution, RSP accuracy and imaging dose using a detailed Monte Carlo (MC) model of an existing ion CT prototype.Approach.Three phantoms were used in simulated pCT and HeCT scans allowing estimation of noise, spatial resolution and the scoring of dose. An additional phantom was used to evaluate RSP accuracy. The imaging dose required to achieve the same image noise in a water and a head phantom was estimated at both native spatial resolution, and in a scenario where the HeCT spatial resolution was reduced and matched to that of pCT using Hann windowing of the reconstruction filter. A variance reconstruction formalism was adapted to account for Hann windowing.Main results.We confirmed that the scanner prototype would produce higher spatial resolution for HeCT than pCT by a factor 1.8 (0.86 lp mm-1versus 0.48 lp mm-1at the center of a 20 cm water phantom). At native resolution, HeCT required a factor 2.9 more dose than pCT to achieve the same noise, while at matched resolution, HeCT required only 38% of the pCT dose. Finally, RSP mean absolute percent error (MAPE) was found to be 0.59% for pCT and 0.67% for HeCT.Significance.This work compared the imaging performance of pCT and HeCT when using an existing scanner prototype, with the spatial resolution advantage of HeCT coming at the cost of increased dose. When matching spatial resolution via Hann windowing, HeCT had a substantial dose advantage. Both modalities provided state-of-the-art RSP MAPE. HeCT might therefore help reduce the dose exposure of patients with comparable image noise to pCT, enhanced spatial resolution and acceptable RSP accuracy at the same time.

Fluence-modulated proton CT optimized with patient-specific dose and variance objectives for proton dose calculation.

Particle therapy treatment planning requires accurate volumetric maps of the relative stopping power, which can directly be acquired using proton computed tomography (pCT). With fluence-modulated pCT (FMpCT) imaging fluence is concentrated in a region-of-interest (ROI), which can be the vicinity of the treatment beam path, and imaging dose is reduced elsewhere. In this work we present a novel optimization algorithm for FMpCT which, for the first time, calculates modulated imaging fluences for joint imaging dose and image variance objectives. Thereby, image quality is maintained in the ROI to ensure accurate calculations of the treatment dose, and imaging dose is minimized outside the ROI with stronger minimization penalties given to imaging organs-at-risk. The optimization requires an initial scan at uniform fluence or a previous x-ray CT scan. We simulated and optimized FMpCT images for three pediatric patients with tumors in the head region. We verified that the target image variance inside the ROI was achieved and demonstrated imaging dose reductions outside of the ROI of 74% on average, reducing the imaging dose from 1.2 to 0.3 mGy. Such dose savings are expected to be relevant compared to the therapeutic dose outside of the treatment field. Treatment doses were re-calculated on the FMpCT images and compared to treatment doses re-recalculated on uniform fluence pCT scans using a 1% criterion. Passing rates were above 98.3% for all patients. Passing rates comparing FMpCT treatment doses to the ground truth treatment dose were above 88.5% for all patients. Evaluation of the proton range with a 1 mm criterion resulted in passing rates above 97.5% (FMpCT/pCT) and 95.3% (FMpCT/ground truth). Jointly optimized fluence-modulated pCT images can be used for proton dose calculation maintaining the full dosimetric accuracy of pCT but reducing the required imaging dose considerably by three quarters. This may allow for daily imaging during particle therapy ensuring a safe and accurate delivery of the therapeutic dose and avoiding excess dose from imaging.

Experimental realization of dynamic fluence field optimization for proton computed tomography.

Proton computed tomography (pCT) has high accuracy and dose efficiency in producing spatial maps of the relative stopping power (RSP) required for treatment planning in proton therapy. With fluence-modulated pCT (FMpCT), prescribed noise distributions can be achieved, which allows to decrease imaging dose by employing object-specific dynamically modulated fluence during the acquisition. For FMpCT acquisitions we divide the image into region-of-interest (ROI) and non-ROI volumes. In proton therapy, the ROI volume would encompass all treatment beams. An optimization algorithm then calculates dynamically modulated fluence that achieves low prescribed noise inside the ROI and high prescribed noise elsewhere. It also produces a planned noise distribution, which is the expected noise map for that fluence, as calculated with a Monte Carlo simulation. The optimized fluence can be achieved by acquiring pCT images with grids of intensity modulated pencil beams. In this work, we interfaced the control system of a clinical proton beam line to deliver the optimized fluence. Using three phantoms we acquired images with uniform fluence, with a constant noise prescription, and with an FMpCT task. Image noise distributions as well as fluence maps were compared to the corresponding planned distributions as well as to the prescription. Furthermore, we propose a correction method that removes image artifacts stemming from the acquisition with pencil beams having a spatially varying energy distribution that is not seen in clinical operation. RSP accuracy of FMpCT scans was compared to uniform scans and was found to be comparable to standard pCT scans. While we identified technical improvements for future experimental acquisitions, in particular related to an unexpected pencil beam size reduction and a misalignment of the fluence pattern, agreement with the planned noise was satisfactory and we conclude that FMpCT optimized for specific image noise prescriptions is experimentally feasible.

An optimization algorithm for dose reduction with fluence-modulated proton CT.

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.

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

We present a method to accurately predict image noise in proton computed tomography (pCT) using data generated from a Monte Carlo simulation and a patient or object model that may be generated from a prior x-ray CT image. This enables noise prediction for arbitrary beam fluence settings and, therefore, the application of fluence-modulated pCT (FMpCT), which can achieve prescribed noise targets and may significantly reduce the integral patient dose. We extended an existing Monte Carlo simulation of a prototype pCT scanner to include effects of quenching in the energy detector scintillators and constructed a beam model from experimental tracking data. Simulated noise predictions were compared to experimental data both in the projection domain and in the reconstructed image. Noise prediction agreement between simulated and experimental data in terms of the root-mean-square (RMS) error was better than 7% for a homogeneous water phantom and a sensitometry phantom with tubular inserts. For an anthropomorphic head phantom, modeling the anatomy of a five-year-old child, the RMS error was better than 9% in three evaluated slices. We were able to reproduce subtle noise features near heterogeneities. To demonstrate the feasibility of Monte Carlo simulated noise maps for fluence modulation, we calculated a fluence profile that yields a homogeneous noise level in the image. Unlike for bow-tie filters in x-ray CT this does not require constant fluence at the detector and the shape of the fluence profile is fundamentally different. Using an improved Monte Carlo simulation, we demonstrated the feasibility of using simulated data for accurate image noise prediction for pCT. We believe that the agreement with experimental data is sufficient to enable the future optimization of FMpCT fluence plans to achieve prescribed noise targets in a fluence-modulated acquisition.

Application of fluence field modulation to proton computed tomography for proton therapy imaging.

This simulation study presents the application of fluence field modulated computed tomography, initially developed for x-ray CT, to proton computed tomography (pCT). By using pencil beam (PB) scanning, fluence modulated pCT (FMpCT) may achieve variable image quality in a pCT image and imaging dose reduction. Three virtual phantoms, a uniform cylinder and two patients, were studied using Monte Carlo simulations of an ideal list-mode pCT scanner. Regions of interest (ROI) were selected for high image quality and only PBs intercepting them preserved full fluence (FF). Image quality was investigated in terms of accuracy (mean) and noise (standard deviation) of the reconstructed proton relative stopping power compared to reference values. Dose calculation accuracy on FMpCT images was evaluated in terms of dose volume histograms (DVH), range difference (RD) for beam-eye-view (BEV) dose profiles and gamma evaluation. Pseudo FMpCT scans were created from broad beam experimental data acquired with a list-mode pCT prototype. FMpCT noise in ROIs was equivalent to FF images and accuracy better than -1.3%(-0.7%) by using 1% of FF for the cylinder (patients). Integral imaging dose reduction of 37% and 56% was achieved for the two patients for that level of modulation. Corresponding DVHs from proton dose calculation on FMpCT images agreed to those from reference images and 96% of BEV profiles had RD below 2 mm, compared to only 1% for uniform 1% of FF. Gamma pass rates (2%, 2 mm) were 98% for FMpCT while for uniform 1% of FF they were as low as 59%. Applying FMpCT to preliminary experimental data showed that low noise levels and accuracy could be preserved in a ROI, down to 30% modulation. We have shown, using both virtual and experimental pCT scans, that FMpCT is potentially feasible and may allow a means of imaging dose reduction for a pCT scanner operating in PB scanning mode. This may be of particular importance to proton therapy given the low integral dose found outside the target.

Quantification of the uncertainties of a biological model and their impact on variable RBE proton treatment plan optimization.

PURPOSE: In proton radiation therapy, a relative biological effectiveness (RBE) equal to 1.1 is currently assumed, although biological experiments show that it is not constant. The purpose of this study was to quantify the uncertainties of a published biological model and explore their impact on variable RBE treatment plan (TP) optimization. METHODS: Two patient cases with a high and a low (α/ß)x tumor were investigated. Firstly, intensity modulated proton therapy TPs assuming constant RBE were derived, and subsequently the variable RBE weighted dose (RWD), including the uncertainty originating in the fit to the experimental data and the uncertainty of the (α/ß)x, were calculated. Secondly, TPs optimized for uniform biological effect assuming a variable RBE were created using the worst case tissue specific (α/ß)x. RESULTS: For the nasopharyngeal cancer patient, the uncertainty of (α/ß)x corresponded to a CTV D98 confidence interval (CI) of (-2, +4)% while for the fit parameter CI was (-2,+1)%. For the standard fractionation prostate case the (α/ß)x CI was (-7,+5)% and the fit parameter CI was (-3,+3)%. For the hypofractionated case both CIs were (-1,+1)%. In both patient cases, the RBE in most organs at risk (OARs) was significantly underestimated by the constant RBE approximation, whereas the situation was not as definite in the target volumes. Overdosage of OARs was reduced by using the biological effect optimization. CONCLUSION: For the two patient cases, the RWD uncertainty from the fit parameter in the biological model contributed non-negligibly to the total uncertainty, depending on the patient case and the organ. The presented optimization strategy is a basic method for robust biological effect optimization to reduce potential consequences caused by the (α/ß)x uncertainty.

Monte Carlo study on the sensitivity of prompt gamma imaging to proton range variations due to interfractional changes in prostate cancer patients.

Proton range verification based on prompt gamma imaging is increasingly considered in proton therapy. Tissue heterogeneity normal to the beam direction or near the end of range may considerably degrade the ability of prompt gamma imaging to detect proton range shifts. The goal of this study was to systematically investigate the accuracy and precision of range detection from prompt gamma emission profiles for various fractions for intensity modulated proton therapy of prostate cancer, using a comprehensive clinical dataset of 15 different CT scans for 5 patients. Monte Carlo simulations using Geant4 were performed to generate spot-by-spot dose distributions and prompt gamma emission profiles for prostate treatment plans. The prompt gammas were scored at their point of emission. Three CT scans of the same patient were used to evaluate the impact of inter-fractional changes on proton range. The range shifts deduced from the comparison of prompt gamma emission profiles in the planning CT and subsequent CTs were then correlated to the corresponding range shifts deduced from the dose distributions for individual pencil beams. The distributions of range shift differences between prompt gamma and dose were evaluated in terms of precision (defined as half the 95% inter-percentile range IPR) and accuracy (median). In total about 1700 individual proton pencil beams were investigated. The IPR of the relative range shift differences between the dose profiles and the prompt gamma profiles varied between ±1.4 mm and ±2.9 mm when using the more robust profile shifting analysis. The median was found smaller than 1 mm. Methods to identify and reject unreliable spots for range verification due to range mixing were derived and resulted in an average 10% spot rejection, clearly improving the prompt gamma-dose correlation. This work supports that prompt gamma imaging can offer a reliable indicator of range changes due to anatomical variations and tissue heterogeneity in scanning proton treatment of prostate cancer patients when considering prompt gamma emission profiles.

Monte Carlo comparison of x-ray and proton CT for range calculations of proton therapy beams.

Proton computed tomography (CT) has been described as a solution for imaging the proton stopping power of patient tissues, therefore reducing the uncertainty of the conversion of x-ray CT images to relative stopping power (RSP) maps and its associated margins. This study aimed to investigate this assertion under the assumption of ideal detection systems. We have developed a Monte Carlo framework to assess proton CT performances for the main steps of a proton therapy treatment planning, i.e. proton or x-ray CT imaging, conversion to RSP maps based on the calibration of a tissue phantom, and proton dose simulations. Irradiations of a computational phantom with pencil beams were simulated on various anatomical sites and the proton range was assessed on the reference, the proton CT-based and the x-ray CT-based material maps. Errors on the tissue's RSP reconstructed from proton CT were found to be significantly smaller and less dependent on the tissue distribution. The imaging dose was also found to be much more uniform and conformal to the primary beam. The mean absolute deviation for range calculations based on x-ray CT varies from 0.18 to 2.01 mm depending on the localization, while it is smaller than 0.1 mm for proton CT. Under the assumption of a perfect detection system, proton range predictions based on proton CT are therefore both more accurate and more uniform than those based on x-ray CT.

Technical Note: Experimental carbon ion range verification in inhomogeneous phantoms using prompt gammas.

PURPOSE: The purpose of this study was to experimentally assess the possibility to monitor carbon ion range variations--due to tumor shift and/or elongation or shrinking--using prompt-gamma (PG) emission with inhomogeneous phantoms. Such a study is related to the development of PG monitoring techniques to be used in a carbon ion therapy context. METHODS: A 95 MeV/u carbon ion beam was used to irradiate phantoms with a variable density along the ion path to mimic the presence of bone and lung in homogeneous humanlike tissue. PG profiles were obtained after a longitudinal scan of the phantoms. A setup comprising a narrow single-slit collimator and two detectors placed at 90° with respect to the beam axis was used. The time of flight technique was applied to allow the selection between PG and background events. RESULTS: Using the positions at 50% entrance and 50% falloff of the PG profiles, a quantity called prompt-gamma profile length (PGPL) is defined. It is possible to observe shifts in the PGPL when there are absolute ion range shifts as small as 1-2 mm. Quantitatively, for an ion range shift of -1.33 ± 0.46 mm (insertion of a Teflon slab), a PGPL difference of -1.93 ± 0.58 mm and -1.84 ± 1.27 mm is obtained using a BaF2 and a NaI(Tl) detector, respectively. In turn, when an ion range shift of 4.59 ± 0.42 mm (insertion of a lung-equivalent material slab) is considered, the difference is of 4.10 ± 0.54 and 4.39 ± 0.80 mm for the same detectors. CONCLUSIONS: Herein, experimental evidence of the usefulness of employing PG to monitor carbon ion range using inhomogeneous phantoms is presented. Considering the homogeneous phantom as reference, the results show that the information provided by the PG emission allows for detecting ion range shifts as small as 1-2 mm. When considering the expected PG emission from an energy slice in a carbon ion therapy scenario, the experimental setup would allow to retrieve the same PGPL as the high statistics of the full experimental dataset in 58% of the times. However, this success rate increases to 93% when using a better optimized setup by means of Monte Carlo simulations.

Absolute prompt-gamma yield measurements for ion beam therapy monitoring.

Prompt-gamma emission detection is a promising technique for hadrontherapy monitoring purposes. In this regard, obtaining prompt-gamma yields that can be used to develop monitoring systems based on this principle is of utmost importance since any camera design must cope with the available signal. Herein, a comprehensive study of the data from ten single-slit experiments is presented, five consisting in the irradiation of either PMMA or water targets with lower and higher energy carbon ions, and another five experiments using PMMA targets and proton beams. Analysis techniques such as background subtraction methods, geometrical normalization, and systematic uncertainty estimation were applied to the data in order to obtain absolute prompt-gamma yields in units of prompt-gamma counts per incident ion, unit of field of view, and unit of solid angle. At the entrance of a PMMA target, where the contribution of secondary nuclear reactions is negligible, prompt-gamma counts per incident ion, per millimetre and per steradian equal to (124 ± 0.7stat ± 30sys) × 10(-6) for 95 MeV u(-1) carbon ions, (79 ± 2stat ± 23sys) × 10(-6) for 310 MeV u(-1) carbon ions, and (16 ± 0.07stat ± 1sys) × 10(-6) for 160 MeV protons were found for prompt gammas with energies higher than 1 MeV. This shows a factor 5 between the yields of two different ions species with the same range in water (160 MeV protons and 310 MeV u(-1) carbon ions). The target composition was also found to influence the prompt-gamma yield since, for 300/310 MeV u(-1) carbon ions, a 42% greater yield ((112 ± 1stat ± 22sys) × 10(-6) counts ion(-1) mm(-1) sr(-1)) was obtained with a water target compared to a PMMA one.

Factors influencing the accuracy of beam range estimation in proton therapy using prompt gamma emission.

In-vivo imaging is a strategy to monitor the range of protons inside the patient during radiation treatment. A possible method of in-vivo imaging is detection of secondary 'prompt' gamma (PG) photons outside the body, which are produced by inelastic proton-nuclear interactions inside the patient. In this paper, important parameters influencing the relationship between the PG profile and percentage depth dose (PDD) in a uniform cylindrical phantom are explored. Monte Carlo simulations are performed with the new Geant4 based code TOPAS for mono-energetic proton pencil beams (range: 100-250 MeV) and an idealized PG detector. PG depth profiles are evaluated using the inflection point on a sigmoid fit in the fall-off region of the profile. A strong correlation between the inflection point and the proton range determined from the PDD is found for all conditions. Variations between 1.5 mm and 2.7 mm in the distance between the proton range and the inflection point are found when either the mass density, phantom diameter, or detector acceptance angle is changed. A change in cut-off energy of the detector could induce a range difference of maximum 4 mm. Applying time-of-flight discrimination during detection, changing the primary energy of the beam or changing the elemental composition of the tissue affects the accuracy of the range prediction by less than 1 mm. The results indicate that the PG signal is rather robust to many parameter variations, but millimetre accurate range monitoring requires all medium and detector properties to be carefully taken into account.

Assessment and improvements of Geant4 hadronic models in the context of prompt-gamma hadrontherapy monitoring.

Monte Carlo simulations are nowadays essential tools for a wide range of research topics in the field of radiotherapy. They also play an important role in the effort to develop a real-time monitoring system for quality assurance in proton and carbon ion therapy, by means of prompt-gamma detection. The internal theoretical nuclear models of Monte Carlo simulation toolkits are of decisive importance for the accurate description of neutral or charged particle emission, produced by nuclear interactions between beam particles and target nuclei. We assess the performance of Geant4 nuclear models in the context of prompt-gamma emission, comparing them with experimental data from proton and carbon ion beams. As has been shown in the past and further indicated in our study, the prompt-gamma yields are consistently overestimated by Geant4 by a factor of about 100% to 200% over an energy range from 80 to 310 MeV/u for the case of (12)C, and to a lesser extent for 160 MeV protons. Furthermore, we focus on the quantum molecular dynamics (QMD) modeling of ion-ion collisions, in order to optimize its description of light nuclei, which are abundant in the human body and mainly anticipated in hadrontherapy applications. The optimization has been performed by benchmarking QMD free parameters with well established nuclear properties. In addition, we study the effect of this optimization on charged particle emission. With the usage of the proposed parameter values, discrepancies reduce to less than 70%, with the highest values being attributed to the nucleon-ion induced prompt-gammas. This conclusion, also confirmed by the disagreement we observe in the case of proton beams, indicates the need for further investigation on nuclear models which describe proton and neutron induced nuclear reactions.

Real-time proton beam range monitoring by means of prompt-gamma detection with a collimated camera.

Prompt-gamma profile was measured at WPE-Essen using 160 MeV protons impinging a movable PMMA target. A single collimated detector was used with time-of-flight (TOF) to reduce the background due to neutrons. The target entrance rise and the Bragg peak falloff retrieval precision was determined as a function of incident proton number by a fitting procedure using independent data sets. Assuming improved sensitivity of this camera design by using a greater number of detectors, retrieval precisions of 1 to 2 mm (rms) are expected for a clinical pencil beam. TOF improves the contrast-to-noise ratio and the performance of the method significantly.

Distributions of secondary particles in proton and carbon-ion therapy: a comparison between GATE/Geant4 and FLUKA Monte Carlo codes.

Monte Carlo simulations play a crucial role for in-vivo treatment monitoring based on PET and prompt gamma imaging in proton and carbon-ion therapies. The accuracy of the nuclear fragmentation models implemented in these codes might affect the quality of the treatment verification. In this paper, we investigate the nuclear models implemented in GATE/Geant4 and FLUKA by comparing the angular and energy distributions of secondary particles exiting a homogeneous target of PMMA. Comparison results were restricted to fragmentation of (16)O and (12)C. Despite the very simple target and set-up, substantial discrepancies were observed between the two codes. For instance, the number of high energy (>1 MeV) prompt gammas exiting the target was about twice as large with GATE/Geant4 than with FLUKA both for proton and carbon ion beams. Such differences were not observed for the predicted annihilation photon production yields, for which ratios of 1.09 and 1.20 were obtained between GATE and FLUKA for the proton beam and the carbon ion beam, respectively. For neutrons and protons, discrepancies from 14% (exiting protons-carbon ion beam) to 57% (exiting neutrons-proton beam) have been identified in production yields as well as in the energy spectra for neutrons.

Interaction vertex imaging (IVI) for carbon ion therapy monitoring: a feasibility study.

Proton imaging can be seen as a powerful technique for online monitoring of ion range during carbon ion therapy irradiations. Indeed, a large number of secondary protons are created during nuclear reactions, and many of these protons are likely to escape from the patient even for deep-seated tumors, carrying accurate information on the reaction vertex position. Two detection techniques have been considered: (i) double-proton detection by means of two forward-located trackers and (ii) single-proton detection in coincidence with the incoming carbon ion detected by means of a beam hodoscope. Geant4 simulations, validated by proton yield measurements performed at GANIL and GSI, show that ion-range monitoring is accessible on a pencil-beam basis with the single-proton imaging technique. Millimetric precision on the Bragg peak position is expected in the ideal case of homogeneous targets. The uncertainties in more realistic conditions should be investigated, in particular the influence of tissue heterogeneity in the very last part of the ion path (about 20 mm).