Towards real-time EPID-based 3D in vivo dosimetry for IMRT with Deep Neural Networks: A feasibility study.

We investigate the potential of the Deep Dose Estimate (DDE) neural network to predict 3D dose distributions inside patients with Monte Carlo (MC) accuracy, based on transmitted EPID signals and patient CTs. The network was trained using as input patient CTs and first-order dose approximations (FOD). Accurate dose distributions (ADD) simulated with MC were given as training targets. 83 pelvic CTs were used to simulate ADDs and respective EPID signals for subfields of prostate IMRT plans (gantry at 0∘). FODs were produced as backprojections from the EPID signals. 581 ADD-FOD sets were produced and divided into training and test sets. An additional dataset simulated with gantry at 90∘ (lateral set) was used for evaluating the performance of the DDE at different beam directions. The quality of the FODs and DDE-predicted dose distributions (DDEP) with respect to ADDs, from the test and lateral sets, was evaluated with gamma analysis (3%,2 mm). The passing rates between FODs and ADDs were as low as 46%, while for DDEPs the passing rates were above 97% for the test set. Meaningful improvements were also observed for the lateral set. The high passing rates for DDEPs indicate that the DDE is able to convert FODs into ADDs. Moreover, the trained DDE predicts the dose inside a patient CT within 0.6 s/subfield (GPU), in contrast to 14 h needed for MC (CPU-cluster). 3D in vivo dose distributions due to clinical patient irradiation can be obtained within seconds, with MC-like accuracy, potentially paving the way towards real-time EPID-based in vivo dosimetry.

Comparison of reconstructed prompt gamma emissions using maximum likelihood estimation and origin ensemble algorithms for a Compton camera system tailored to proton range monitoring.

Compton-based prompt gamma (PG) imaging is being investigated by several groups as a potential solution for in vivo range monitoring in proton therapy. The performance of this technique depends on the detector system as well as the ability of the reconstruction method to obtain good spatial resolution to establish a quantitative correlation between the PG emission and the proton beam range in the patient. To evaluate the feasibility of PG imaging for range monitoring, we quantitatively evaluated the emission distributions reconstructed by a Maximum Likelihood Expectation Maximization (MLEM) and a Stochastic Origin Ensemble (SOE) algorithm. To this end, we exploit experimental and Monte Carlo (MC) simulation data acquired with the Polaris-J Compton Camera (CC) prototype. The differences between the proton beam range (RD) defined as the 80% distal dose fall-off and the PG range (RPG), obtained by fitting the distal end of the reconstructed profile with a sigmoid function, were quantified. A comparable performance of both reconstruction algorithms was found. For both experimental and simulated irradiation scenarios, the correlation between RD and RPG was within 5 mm. These values were consistent with the ground truth distance (RD-RPGg≈ 3 mm) calculated by using the expected PG emission available from MC simulation. Furthermore, shifts of 3 mm in the proton beam range were resolved with the MLEM algorithm by calculating the relative difference between the RPG for each reconstructed profile. In non-homogeneous targets, the spatial changes in the PG emission due to the different materials could not be fully resolved from the reconstructed profiles; however, the fall-off region still resembled the ground truth emission. For this scenario, the PG correlation (RD-RPG) varied from 0.1 mm to 4 mm, which is close to the ground truth correlation (3 mm). This work provides a framework for the evaluation of the range monitoring capabilities of a CC device for PG imaging. The two investigated image reconstruction algorithms showed a comparable and consistent performance for homogeneous and heterogeneous targets.

Applications of a patient-specific whole-body CT-mesh hybrid computational phantom in second cancer risk prediction.

Objective.CT-mesh hybrid phantoms (or 'hybrid(s)') made from integrated patient CT data and mesh-type reference computational phantoms (MRCPs) can be beneficial for patient-specific whole-body dose evaluation, but this benefit has yet to be evaluated for second cancer risk prediction. The purpose of this study is to compare the hybrid's ability to predict risk throughout the body with a patient-scaled MRCP against ground truth whole-body CTs (WBCTs).Approach.Head and neck active scanning proton treatment plans were created for and simulated on seven hybrids and the corresponding scaled MRCPs and WBCTs. Equivalent dose throughout the body was calculated and input into five second cancer risk models for both excess absolute and excess relative risk (EAR and ERR). The hybrid phantom was evaluated by comparing equivalent dose and risk predictions against the WBCT.Main results.The hybrid most frequently provides whole-body second cancer risk predictions which are closer to the ground truth when compared to a scaled MRCP alone. The performance of the hybrid relative to the scaled MRCP was consistent across ERR, EAR, and all risk models. For all in-field organs, where the hybrid shares the WBCT anatomy, the hybrid was better than or equal to the scaled MRCP for both equivalent dose and risk prediction. For out-of-field organs across all patients, the hybrid's equivalent dose prediction was superior than the scaled MRCP in 48% of all comparisons, equivalent for 34%, and inferior for 18%. For risk assessment in the same organs, the hybrid's prediction was superior than the scaled MRCP in 51.8% of all comparisons, equivalent in 28.6%, and inferior in 19.6%.Significance.Whole-body risk predictions from the CT-mesh hybrid have shown to be more accurate than those from a reference phantom alone. These hybrids could aid in risk-optimized treatment planning and individual risk assessment to minimize second cancer incidence.

Comparative accuracy and resolution assessment of two prototype proton computed tomography scanners.

BACKGROUND: Improving the accuracy of relative stopping power (RSP) in proton therapy may allow reducing range margins. Proton computed tomography (pCT) has been shown to provide state-of-the-art RSP accuracy estimation, and various scanner prototypes have recently been built. The different approaches used in scanner design are expected to impact spatial resolution and RSP accuracy. PURPOSE: The goal of this study was to perform the first direct comparison, in terms of spatial resolution and RSP accuracy, of two pCT prototype scanners installed at the same facility and by using the same image reconstruction algorithm. METHODS: A phantom containing cylindrical inserts of known RSP was scanned at the phase-II pCT prototype of the U.S. pCT collaboration and at the commercially oriented ProtonVDA scanner. Following distance-driven binning filtered backprojection reconstruction, the radial edge spread function of high-density inserts was used to estimate the spatial resolution. RSP accuracy was evaluated by the mean absolute percent error (MAPE) over the inserts. No direct imaging dose estimation was possible, which prevented a comparison of the two scanners in terms of RSP noise. RESULTS: In terms of RSP accuracy, both scanners achieved the same MAPE of 0.72% when excluding the porous sinus insert from the evaluation. The ProtonVDA scanner reached a better overall MAPE when all inserts and the body of the phantom were accounted for (0.81%), compared to the phase-II scanner (1.14%). The spatial resolution with the phase-II scanner was found to be 0.61 lp/mm, while for the ProtonVDA scanner somewhat lower at 0.46 lp/mm. CONCLUSIONS: The comparison between two prototype pCT scanners operated in the same clinical facility showed that they both fulfill the requirement of an RSP accuracy of about 1%. Their spatial resolution performance reflects the different design choices of either a scanner with full tracking capabilities (phase-II) or of a more compact tracker system, which only provides the positions of protons but not their directions (ProtonVDA).

A patient-specific hybrid phantom for calculating radiation dose and equivalent dose to the whole body.

Objective. As cancer survivorship increases, there is growing interest in minimizing the late effects of radiation therapy such as radiogenic second cancer, which may occur anywhere in the body. Assessing the risk of late effects requires knowledge of the dose distribution throughout the whole body, including regions far from the treatment field, beyond the typical anatomical extent of clinical computed tomography (CT) scans.Approach. A hybrid phantom was developed which consists of in-field patient CT images extracted from ground truth whole-body CT scans, out-of-field mesh phantoms scaled to basic patient measurements, and a blended transition region. Four of these hybrid phantoms were created, representing male and female patients receiving proton therapy treatment in pelvic and cranial sites. To assess the performance of the hybrid approach, we simulated treatments using the hybrid phantoms, the scaled and unscaled mesh phantoms, and the ground truth whole-body CTs. We calculated absorbed dose and equivalent dose in and outside of the treatment field, with a focus on neutrons induced in the patient by proton therapy. Proton and neutron dose was calculated using a general purpose Monte Carlo code.Main results. The hybrid phantom provided equal or superior accuracy in calculated organ dose and equivalent dose values relative to those obtained using the mesh phantoms in 78% in all selected organs and calculated dose quantities. Comparatively the default mesh and scaled mesh were equal or superior to the other phantoms in 21% and 28% of cases respectively.Significance. The proposed methodology for hybrid synthesis provides a tool for whole-body organ dose estimation for individual patients without requiring CT scans of their entire body. Such a capability would be useful for personalized assessment of late effects and risk-optimization of treatment plans.

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

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 MC simulations of an existing pCT scanner prototype, which we describe in detail.

Combining inter-observer variability, range and setup uncertainty in a variance-based sensitivity analysis for proton therapy.

Margin concepts in proton therapy aim to ensure full dose coverage of the clinical target volume (CTV) in presence of setup and range uncertainty. Due to inter-observer variability (IOV), the CTV itself is uncertain. We present a framework to evaluate the combined impact of IOV, setup and range uncertainty in a variance-based sensitivity analysis (SA). For ten patients with skull base meningioma, the mean calculation time to perform the SA including 1.6 × 104 dose recalculations was 59 min. For two patients in this dataset, IOV had a relevant impact on the estimated CTV D95% uncertainty.

An empirical artifact correction for proton computed tomography.

PURPOSE: To reduce image artifacts of proton computed tomography (pCT) from a preclinical scanner, for imaging of the relative stopping power (RSP) needed for particle therapy treatment planning using a simple empirical artifact correction method. METHODS: We adapted and employed a correction method previously used for beam-hardening correction in x-ray CT which makes use of a single scan of a custom-built homogeneous phantom with known RSP. Exploiting the linearity of the filtered backprojection operation, a function was found which corrects water-equivalent path lengths (RSP line integrals) in experimental scans using a prototype pCT scanner. The correction function was applied to projection values of subsequent scans of a homogeneous water phantom, a sensitometric phantom with various inserts and an anthropomorphic head phantom. Data were acquired at two different incident proton energies to test the robustness of the method. RESULTS: Inaccuracies in the detection process caused an offset and known ring artifacts in the water phantom which were considerably reduced using the proposed method. The mean absolute percentage error (MAPE) of mean RSP values of all inserts of the sensitometric phantom and the water phantom was reduced from 0.87% to 0.44% and from 0.86% to 0.48% for the two incident energies respectively. In the head phantom a clear reduction of artifacts was observed. CONCLUSIONS: Image artifacts of experimental pCT scans with a prototype scanner could substantially be reduced both in homogeneous, heterogeneous and anthropomorphic phantoms. RSP accuracy was also improved.

Proof of concept image artifact reduction by energy-modulated proton computed tomography (EMpCT).

PURPOSE: To reduce imaging artifacts and improve image quality of a specific proton computed tomography (pCT) prototype scanner by combining pCT data acquired at two different incident proton energies to avoid protons stopping in sub-optimal detector sections. METHODS: Image artifacts of a prototype pCT scanner are linked to protons stopping close to internal structures of the scanner's multi-stage energy detector. We aimed at avoiding such protons by acquiring pCT data at two different incident energies and combining the data in post-processing from which artifact-reduced images of the relative stopping power (RSP) were calculated. Energy-modulated pCT (EMpCT) images were assessed visually and quantitatively and compared to the original mono-energetic images in terms of RSP accuracy and noise. Data were acquired for a homogeneous water phantom. RESULTS: RSP images reconstructed from the mono-energetic datasets displayed local image artifacts which were ring-shaped due to the homogeneity of the phantom. The merged EMpCT dataset achieved a superior visual image quality with reduced artifacts and only minor remaining rings. The inter-quartile range (25/75) of RSP values was reduced from 0.7% with the current standard acquisition to 0.2% with EMpCT due to the reduction of ring artifacts. In this study, dose was doubled compared to a standard scan, but we discuss strategies to reduce excess dose. CONCLUSIONS: EMpCT allows to effectively avoid regions of the energy detector that cause image artifacts. Thereby, image quality is improved.

Variance-based sensitivity analysis for uncertainties in proton therapy: A framework to assess the effect of simultaneous uncertainties in range, positioning, and RBE model predictions on RBE-weighted dose distributions.

PURPOSE: Treatment plans in proton therapy are more sensitive to uncertainties than in conventional photon therapy. In addition to setup uncertainties, proton therapy is affected by uncertainties in proton range and relative biological effectiveness (RBE). While to date a constant RBE of 1.1 is commonly assumed, the actual RBE is known to increase toward the distal end of the spread-out Bragg peak. Several models for variable RBE predictions exist. We present a framework to evaluate the combined impact and interactions of setup, range, and RBE uncertainties in a comprehensive, variance-based sensitivity analysis (SA). MATERIAL AND METHODS: The variance-based SA requires a large number (104 -105 ) of RBE-weighted dose (RWD) calculations. Based on a particle therapy extension of the research treatment planning system CERR we implemented a fast, graphics processing unit (GPU) accelerated pencil beam modeling of patient and range shifts. For RBE predictions, two biological models were included: The mechanistic repair-misrepair-fixation (RMF) model and the phenomenological Wedenberg model. All input parameters (patient position, proton range, RBE model parameters) are sampled simultaneously within their assumed probability distributions. Statistical formalisms rank the input parameters according to their influence on the overall uncertainty of RBE-weighted dose-volume histogram (RW-DVH) quantiles and the RWD in every voxel, resulting in relative, normalized sensitivity indices (S = 0: noninfluential input, S = 1: only influential input). Results are visualized as RW-DVHs with error bars and sensitivity maps. RESULTS AND CONCLUSIONS: The approach is demonstrated for two representative brain tumor cases and a prostate case. The full SA including ∼ 3 × 10 4 RWD calculations took 39, 11, and 55 min, respectively. Range uncertainty was an important contribution to overall uncertainty at the distal end of the target, while the relatively smaller uncertainty inside the target was governed by biological uncertainties. Consequently, the uncertainty of the RW-DVH quantile D98 for the target was governed by range uncertainty while the uncertainty of the mean target dose was dominated by the biological parameters. The SA framework is a powerful and flexible tool to evaluate uncertainty in RWD distributions and DVH quantiles, taking into account physical and RBE uncertainties and their interactions. The additional information might help to prioritize research efforts to reduce physical and RBE uncertainties and could also have implications for future approaches to biologically robust planning and optimization.

Accounting for prompt gamma emission and detection for range verification in proton therapy treatment planning.

Prompt gamma (PG) imaging is widely investigated as one of the most promising methods for proton range verification in proton therapy. The performance of this technique is affected by several factors like tissue heterogeneity, number of protons in the considered pencil beam and the detection device. Our previous work proposed a new treatment planning concept which boosts the number of protons of a few PG monitoring-friendly pencil beams (PBs), selected on the basis of two proposed indicators quantifying the conformity between the dose and PG at the emission level, above the desired detectability threshold. To further explore this method at the detection level, in this work we investigated the response of a knife-edge slit PG camera which was deployed in the first clinical application of PG to proton therapy monitoring. The REGistration Graphical User Interface (REGGUI) is employed to simulate the PG emission, PG detection as well as the corresponding dose distribution. As the PG signal detected by this kind of PG camera is sensitive to the relative position of the camera and PG signal falloff, we optimized our PB selection method for this camera by introducing a new camera position indicator identifying whether the expected falloff of the PG signal is centered in the field of view of the camera or not. Our camera-adapted PB selection method is investigated using computed tomography (CT) scans at two different treatment time points of a head and neck, and a prostate cancer patient under scenarios considering different statistics level. The results show that a precision of 0.8 mm for PG falloff identification can be achieved when a PB has more than 2 × 108 primary protons. Except for one case due to unpredictable and comparably large anatomical changes, the PG signals of most of the PBs recommended by all our indicators are observed to be reliable for proton range verification with deviations between the inter-fractional shift of proton range (as deduced from the PB dose distribution) and the detected PG signal within 2.0 mm. In contrast, a shift difference up to 9.6 mm has been observed for the rejected PBs. The magnitude of the proton range shift due to the inter-fractional anatomical changes is observed to be up to 23 mm. The proposed indicators are shown to be valuable for identifying and recommending reliable PBs to create new PG monitoring-friendly TPs. Comparison between our PB boosting method and the alternative PB aggregation, which combines the signal of nearby PBs to reach the desired counting statistics, is also discussed.

Radiation protection modelling for 2.5 Petawatt-laser production of ultrashort x-ray, proton and ion bunches: Monte Carlo model of the Munich CALA facility.

The 'Centre for Advanced Laser Applications' (CALA) is a new research institute for laser-based acceleration of electron beams for brilliant x-ray generation, laser-driven sub-nanosecond bunches of protons and heavy ions for biomedical applications like imaging and tumour therapy as well as for nuclear and high-field physics.The radiation sources emerging from experiments using the up to 2.5 petawatt laser pulses with 25 femtosecond duration will be mixed particle-species of high intensity, high energy and pulsed, thus posing new challenges compared to conventional radiation protection. Such worldwide pioneering laser experiments result in source characteristics that require careful a-priori radiation safety simulations.The FLUKA Monte-Carlo code was used to model the five CALA experimental caves, including the corridors, halls and air spaces surrounding the caves. Beams of electrons (<5 GeV), protons (<200 MeV),12C (<400MeV/u) and197Au (<10MeV/u) ions were simulated using spectra, divergences and bunch-charges based on expectations from recent scientific progress.Simulated dose rates locally can exceed 1.5 kSv h-1inside beam dumps. Vacuum pipes in the cave walls for laser transport and extraction channels for the generated x-rays result in small dose leakage to neighboring areas. Secondary neutrons contribute to most of the prompt dose rate outside caves into which the beam is delivered. This secondary radiation component causes non-negligible dose rates to occur behind walls to which large fluences of secondary particles are directed.By employing adequate beam dumps matched to beam-divergence, magnets, passive shielding and laser pulse repetition limits, average dose rates in- and outside the experimental building stay below design specifications (<0.5µSv h-1) for unclassified areas,<2.5µSv h-1for supervised areas,<7.5µSv h-1maximum local dose rate) and regulatory limits (<1mSv a-1for unclassified areas).

A new treatment planning approach accounting for prompt gamma range verification and interfractional anatomical changes.

Prompt gamma (PG) imaging is widely investigated for spot-by-spot in vivo range verification for proton therapy. Previous studies pointed out that the accuracy of prompt gamma imaging is affected by the statistics (number of protons delivered per pencil beam) of the proton beams and the conformity between prompt gamma and dose distribution (PG-dose correlation). Recently a novel approach to re-optimize conventional treatment plans by boosting a few pencil beams with good PG-dose correlation above the statistics limit for reliable PG detectability was proposed. However, up to now, only PG-dose correlation on the planning computed tomography (CT) was considered, not accounting for the fact that the robustness of the PG-dose correlation is not guaranteed in the cases of interfractional anatomical changes. In this work, this approach is further explored with respect to the robustness of the PG-dose correlation of each pencil beam in the case of interfractional anatomical changes. A research computational platform, combining Monte Carlo pre-calculated pencil beams with the analytical Matlab-based treatment planning system (TPS) CERR, is used for treatment planning. Geant4 is used for realistic simulation of the dose delivery and PG generation for all individual pencil beams in the heterogeneous patient anatomy using multiple CT images for representative patient cases (in this work, CTs of one prostate and one head and neck cancer patient are used). First, a Monte Carlo treatment plan is created using CERR. Thereby the PG emission and dose distribution for each individual spot is obtained. Second, PG-dose correlation is quantified using the originally proposed approach as well as a new indicator, which accounts for the sensitivity of individual spots to heterogeneities in the 3D dose distribution. This is accomplished by using a 2D distal surface (dose surface) derived from the 3D dose distribution for each spot. A few pencil beams are selected for each treatment field, based on their PG-dose correlation and dose surface, and then boosted in the new re-optimized treatment plan. All treatment plans are then fully re-calculated with Monte Carlo on the CT scans of the corresponding patient at three different time points. The result shows that all treatment plans are comparable in terms of dose distribution and dose averaged LET distributions. The spots recommended by our indicators maintain good PG-dose correlation in the cases of interfractional anatomical changes, thus ensuring that the proton range shift due to anatomical changes can be monitored. Compared to another proposed spots aggregation approach, our approach shows advantages in terms of the detectability and reliability of PG, especially in presence of heterogeneities.

Towards a novel small animal proton irradiation platform: the SIRMIO project.

Background: Precision small animal radiotherapy research is a young emerging field aiming to provide new experimental insights into tumor and normal tissue models in different microenvironments, to unravel complex mechanisms of radiation damage in target and non-target tissues and assess efficacy of novel therapeutic strategies. For photon therapy, modern small animal radiotherapy research platforms have been developed over the last years and are meanwhile commercially available. Conversely, for proton therapy, which holds potential for an even superior outcome than photon therapy, no commercial system exists yet. Material and methods: The project SIRMIO (Small Animal Proton Irradiator for Research in Molecular Image-guided Radiation-Oncology) aims at realizing and demonstrating an innovative portable prototype system for precision image-guided small animal proton irradiation, suitable for installation at existing clinical treatment facilities. The proposed design combines precise dose application with in situ multi-modal anatomical image guidance and in vivo verification of the actual treatment delivery. Results and conclusions: This manuscript describes the status of the different components under development, featuring a dedicated beamline for degradation and focusing of clinical proton beams, along with novel detector systems for in situimaging and range verification. The foreseen workflow includes pre-treatment proton transmission imaging, complemented by ultrasonic tumor localization, for treatment planning and position verification, followed by image-guided delivery with on site range verification by means of ionoacoustics (for pulsed beams) and positron-emission-tomography (PET, for continuous beams). The proposed compact and cost-effective system promises to open a new era in small animal proton therapy research, contributing to the basic understanding of in vivo radiation action to identify areas of potential breakthroughs for future translation into innovative clinical strategies.

Experimental comparison of proton CT and dual energy x-ray CT for relative stopping power estimation in proton therapy.

Proton computed tomography (pCT) has been proposed as an alternative to x-ray computed tomography (CT) for acquiring relative to water stopping power (RSP) maps used for proton treatment planning dose calculations. In parallel, it has been shown that dual energy x-ray CT (DECT) improves RSP accuracy when compared to conventional single energy x-ray CT. This study aimed at directly comparing the RSP accuracy of both modalities using phantoms scanned at an advanced prototype pCT scanner and a state-of-the-art DECT scanner. Two phantoms containing 13 tissue-mimicking inserts of known RSP were scanned at the pCT phase II prototype and a latest generation dual-source DECT scanner (Siemens SOMATOM Definition FORCE). RSP accuracy was compared by mean absolute percent error (MAPE) over all inserts. A highly realistic Monte Carlo (MC) simulation was used to gain insight on pCT image artifacts which degraded MAPE. MAPE was 0.55% for pCT and 0.67% for DECT. The realistic MC simulation agreed well with pCT measurements ([Formula: see text]). Both simulation and experimental results showed ring artifacts in pCT images which degraded the MAPE compared to an ideal pCT simulation ([Formula: see text]). Using the realistic simulation, we could identify sources of artifacts, which are attributed to the interfaces in the five-stage plastic scintillator energy detector and calibration curve interpolation regions. Secondary artifacts stemming from the proton tracker geometry were also identified. The pCT prototype scanner outperformed a state-of-the-art DECT scanner in terms of RSP accuracy (MAPE) for plastic tissue mimicking inserts. Since artifacts tended to concentrate in the inserts, their mitigation may lead to further improvements in the reported pCT accuracy.

Gel dosimetry for three dimensional proton range measurements in anthropomorphic geometries.

Proton beams used for radiotherapy have potential for superior sparing of normal tissue, although range uncertainties are among the main limiting factors in the accuracy of dose delivery. The aim of this study was to benchmark an N-vinylpyrrolidone based polymer gel to perform three-dimensional measurement of geometric proton beam characteristics and especially to test its suitability as a range probe in combination with an anthropomorphic phantom. For single proton pencil beams as well as for 3×3cm2 mono-energy layers depth dose profiles, lateral dose distribution at different depths and proton range were evaluated in simple cubic gel phantoms at different energies from 75 to 115MeV and different dose levels. In addition, a 90MeV mono-energetic beam was delivered to an anthropomorphic 3D printed head phantom, which was filled with gel. Subsequently, all phantoms underwent magnetic resonance imaging using an axial pixel size of 0.68-0.98mm and with slice thicknesses of 2 or 3mm to derive a 3-dimensional distribution of the T2 relaxation time, which correlates with radiation dose. Indices describing lateral dose distribution and proton range were compared against predictions from a treatment planning system (TPS, for cubic and head phantoms) and Monte Carlo simulations (MC, for the head phantom) after manual rigid co-registration with the T2 relaxation time datasets. For all pencil beams, the FWHM agreement with TPS was better than 1mm or 7%. For the mono-energetic layer, the agreement with TPS in this respect was even better than 0.3mm in each case. With respect to range, results from gel measurements differed no more than 0.9mm (1.6%) from values predicted by TPS. In case of the anthropomorphic phantom, deviations with respect to a nominal range of about 61mm as well as in FWHM were slightly higher, namely within 1.0mm and 1.1mm respectively. Average deviations between gel and TPS/MC were similar (-0.3mm±0.4mm/-0.2±0.5mm). In conclusion, polymer gel dosimetry was found to be a valuable tool to determine geometric proton beam properties three-dimensionally and with high spatial resolution in simple cubic as well as in a more complex anthropomorphic phantom. Post registration range errors of the order of 1mm could be achieved. The additional registration uncertainty (95%) was 1mm.

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

We present a formalism for two-dimensional (2D) noise reconstruction in proton computed tomography (pCT). This is necessary for the application of fluence modulated pCT (FMpCT) since it permits image noise prescription and the corresponding proton fuence optimization. We aimed at extending previously published formalisms to account for the impact of multiple Coulomb scattering (MCS) on projection noise, and the use of filtered back projection (FBP) reconstruction along curved paths with distance driven binning (DDB). 2D noise reconstruction for a beam of protons with parallel initial momentum vectors, and for projections binned both at the rear tracker and with DDB, was established. Monte Carlo (MC) simulations of pCT scans of a water cylinder were employed to generate pCT projections and to calculate their noise for use in 2D noise reconstruction. These were compared to results from an analytical model accounting for MCS for rear tracker binning as well as against the previously published central pixel model which ignores MCS. Image noise reconstructed with the formalism for rear tracker binning and DDB were compared to MC results using annular regions of interest (ROIs). Agreement better than 8% was obtained between the noise of projections calculated with MC simulation and our model. Noise from annular ROIs agreed with our noise reconstructions for rear tracker binning and DDB. The central pixel model ignoring MCS underestimated projection and thus image noise by up to 40% towards the object's edge. The use of DDB decreased the image noise towards the object's edge when compared to rear tracker binning and yielded more uniform noise throughout the image. MCS should not be neglected when predicting image noise for pixels away from the center of an object in a pCT scan due to the increasing influence of the gradient of the object's hull closer to the edges.

Experimental fluence-modulated proton computed tomography by pencil beam scanning.

PURPOSE: This experimental study is aimed at demonstrating, using a simple cylindrical water phantom, the feasibility of fluence-modulated proton computed tomography (FMpCT) by pencil beam scanning (PBS) proton computed tomography (pCT). METHODS: The phase II pCT prototype of the Loma Linda U. and U. C. Santa Cruz was operated using the PBS beam line of the Northwestern Medicine Chicago Proton Center. A 20 × 10 grid of 1.37 cm full width half maximum pencil beams (PB) equally spaced by 1 cm was used to acquire 45 projections in step and shoot mode. The PB pattern's fluence was modified to allow FMpCT scans with fluence modulation factors (FMF) of 50% and 20%. A central FMpCT region of interest (FMpCT-ROI) was used to define a high image quality region. Reconstructed images were evaluated in terms of relative stopping power (RSP) accuracy and noise using annular ROIs. The FMpCT dose savings were estimated by Monte Carlo (MC) simulation of the pCT acquisitions using beam phase space distributions. PBS pCT results with homogeneous fluence were additionally compared to broad beam results in terms of RSP accuracy and noise. RESULTS: PBS pCT scans with acceptable pileup were possible, and images were comparable to previously acquired broad beam pCT images in terms of both noise and accuracy. In the FMpCT-ROI, the noise and accuracy from full fluence (FF) scans were preserved. Dose savings of up to 60% were achieved at the object's edge when using FMF of 20%. CONCLUSION: In this study, we have demonstrated that PBS pCT scans can achieve equivalent accuracy as those obtained from broad beams. The feasibility of FMpCT scans was demonstrated; image accuracy and noise were successfully preserved in the central FMpCT-ROI chosen for this study, and dose reduction of up to 60% at the object's edge was realized.

Monte Carlo proton dose calculations using a radiotherapy specific dual-energy CT scanner for tissue segmentation and range assessment.

Proton beam ranges derived from dual-energy computed tomography (DECT) images from a dual-spiral radiotherapy (RT)-specific CT scanner were assessed using Monte Carlo (MC) dose calculations. Images from a dual-source and a twin-beam DECT scanner were also used to establish a comparison to the RT-specific scanner. Proton ranges extracted from conventional single-energy CT (SECT) were additionally performed to benchmark against literature values. Using two phantoms, a DECT methodology was tested as input for Geant4 MC proton dose calculations. Proton ranges were calculated for different mono-energetic proton beams irradiating both phantoms; the results were compared to the ground truth based on the phantom compositions. The same methodology was applied in a head-and-neck cancer patient using both SECT and dual-spiral DECT scans from the RT-specific scanner. A pencil-beam-scanning plan was designed, which was subsequently optimized by MC dose calculations, and differences in proton range for the different image-based simulations were assessed. For phantoms, the DECT method yielded overall better material segmentation with >86% of the voxel correctly assigned for the dual-spiral and dual-source scanners, but only 64% for a twin-beam scanner. For the calibration phantom, the dual-spiral scanner yielded range errors below 1.2 mm (0.6% of range), like the errors yielded by the dual-source scanner (<1.1 mm, <0.5%). With the validation phantom, the dual-spiral scanner yielded errors below 0.8 mm (0.9%), whereas SECT yielded errors up to 1.6 mm (2%). For the patient case, where the absolute truth was missing, proton range differences between DECT and SECT were on average in -1.2 ± 1.2 mm (-0.5% ± 0.5%). MC dose calculations were successfully performed on DECT images, where the dual-spiral scanner resulted in media segmentation and range accuracy as good as the dual-source CT. In the patient, the various methods showed relevant range differences.

A Monte-Carlo study to assess the effect of 1.5 T magnetic fields on the overall robustness of pencil-beam scanning proton radiotherapy plans for prostate cancer.

Combining magnetic-resonance imaging (MRI) and proton therapy (PT) using pencil-beam scanning (PBS) may improve image-guided radiotherapy. We aimed at assessing the impact of a magnetic field on PBS-PT plan quality and robustness. Specifically, the robustness against anatomical changes and positioning errors in an MRI-guided scenario with a 30 cm radius 1.5 T magnetic field was studied for prostate PT. Five prostate cancer patients with three consecutive CT images (CT1-3) were considered. Single-field uniform dose PBS-PT plans were generated on the segmented CT1 with Monte-Carlo-based treatment planning software for inverse optimization. Plans were optimized at 90° gantry angle without B-field (no B), with ±1.5 T B-field (B and minus B), as well as at 81° gantry angle and +1.5 T (B G81). Plans were re-calculated on aligned CT2 and CT3 to study the impact of anatomical changes. Dose distributions were compared in terms of changes in DVH parameters, proton range and gamma-index pass-rates. To assess the impact of positioning errors, DVH parameters were compared for ±5 mm CT1 patient shifts in anterior-posterior (AP) and left-right (LR) direction. Proton beam deflection considerably reduced robustness against inter-fractional changes for the B scenario. Range agreement, gamma-index pass-rates and PTV V95% were significantly lower compared to no B. Improved robustness was obtained for minus B and B G81, the latter showing only minor differences to no B. The magnetic field introduced slight dosimetric changes under LR shifts. The impact of AP shifts was considerably larger, and equivalent for scenarios with and without B-field. Results suggest that robustness equivalent to PT without magnetic field can be achieved by adaptation of the treatment parameters, such as B-field orientation (minus B) with respect to the patient and/or gantry angle (B G81). MRI-guided PT for prostate cancer might thus be implemented without compromising robustness compared to state-of-the-art CT-guided PT.