Quasi-real-time range monitoring by in-beam PET: a case for 15O.

A fast and reliable range monitoring method is required to take full advantage of the high linear energy transfer provided by therapeutic ion beams like carbon and oxygen while minimizing damage to healthy tissue due to range uncertainties. Quasi-real-time range monitoring using in-beam positron emission tomography (PET) with therapeutic beams of positron-emitters of carbon and oxygen is a promising approach. The number of implanted ions and the time required for an unambiguous range verification are decisive factors for choosing a candidate isotope. An experimental study was performed at the FRS fragment-separator of GSI Helmholtzzentrum für Schwerionenforschung GmbH, Germany, to investigate the evolution of positron annihilation activity profiles during the implantation of [Formula: see text]O and [Formula: see text]O ion beams in a PMMA phantom. The positron activity profile was imaged by a dual-panel version of a Siemens Biograph mCT PET scanner. Results from a similar experiment using ion beams of carbon positron-emitters [Formula: see text]C and [Formula: see text]C performed at the same experimental setup were used for comparison. Owing to their shorter half-lives, the number of implanted ions required for a precise positron annihilation activity peak determination is lower for [Formula: see text]C compared to [Formula: see text]C and likewise for [Formula: see text]O compared to [Formula: see text]O, but their lower production cross-sections make it difficult to produce them at therapeutically relevant intensities. With a similar production cross-section and a 10 times shorter half-life than [Formula: see text]C, [Formula: see text]O provides a faster conclusive positron annihilation activity peak position determination for a lower number of implanted ions compared to [Formula: see text]C. A figure of merit formulation was developed for the quantitative comparison of therapy-relevant positron-emitting beams in the context of quasi-real-time beam monitoring. In conclusion, this study demonstrates that among the positron emitters of carbon and oxygen, [Formula: see text]O is the most feasible candidate for quasi-real-time range monitoring by in-beam PET that can be produced at therapeutically relevant intensities. Additionally, this study demonstrated that the in-flight production and separation method can produce beams of therapeutic quality, in terms of purity, energy, and energy spread.

Production and separation of positron emitters for hadron therapy at FRS-Cave M.

The FRagment Separator FRS at GSI is a versatile spectrometer and separator for experiments with relativistic in-flight separated short-lived exotic beams. One branch of the FRS is connected to the target hall where the bio-medical cave (Cave M) is located. Recently a joint activity between the experimental groups of the FRS and the biophysics at the GSI and Department of physics at LMU was started to perform biomedical experiments relevant for hadron therapy with positron emitting carbon and oxygen beams. This paper presents the new ion-optical mode and commissioning results of the FRS-Cave M branch where positron emitting 15O-ions were provided to the medical cave for the first time. An overall conversion efficiency of 2.9±0.2×10-4 15O fragments per primary 16O ion accelerated in the synchrotron SIS18 was reached.

Feasibility of CycleGAN enhanced low dose CBCT imaging for prostate radiotherapy dose calculation.

Daily cone beam computed tomography (CBCT) imaging during the course of fractionated radiotherapy treatment can enable online adaptive radiotherapy but also expose patients to a non-negligible amount of radiation dose. This work investigates the feasibility of low dose CBCT imaging capable of enabling accurate prostate radiotherapy dose calculation with only 25% projections by overcoming under-sampling artifacts and correcting CT numbers by employing cycle-consistent generative adversarial networks (cycleGAN). Uncorrected CBCTs of 41 prostate cancer patients, acquired with ∼350 projections (CBCTorg), were retrospectively under-sampled to 25% dose images (CBCTLD) with only ∼90 projections and reconstructed using Feldkamp-Davis-Kress. We adapted a cycleGAN including shape loss to translate CBCTLDinto planning CT (pCT) equivalent images (CBCTLD_GAN). An alternative cycleGAN with a generator residual connection was implemented to improve anatomical fidelity (CBCTLD_ResGAN). Unpaired 4-fold cross-validation (33 patients) was performed to allow using the median of 4 models as output. Deformable image registration was used to generate virtual CTs (vCT) for Hounsfield units (HU) accuracy evaluation on 8 additional test patients. Volumetric modulated arc therapy plans were optimized on vCT, and recalculated on CBCTLD_GANand CBCTLD_ResGANto determine dose calculation accuracy. CBCTLD_GAN, CBCTLD_ResGANand CBCTorgwere registered to pCT and residual shifts were analyzed. Bladder and rectum were manually contoured on CBCTLD_GAN, CBCTLD_ResGANand CBCTorgand compared in terms of Dice similarity coefficient (DSC), average and 95th percentile Hausdorff distance (HDavg, HD95). The mean absolute error decreased from 126 HU for CBCTLDto 55 HU for CBCTLD_GANand 44 HU for CBCTLD_ResGAN. For PTV, the median differences ofD98%,D50%andD2%comparing both CBCTLD_GANto vCT were 0.3%, 0.3%, 0.3%, and comparing CBCTLD_ResGANto vCT were 0.4%, 0.3% and 0.4%. Dose accuracy was high with both 2% dose difference pass rates of 99% (10% dose threshold). Compared to the CBCTorg-to-pCT registration, the majority of mean absolute differences of rigid transformation parameters were less than 0.20 mm/0.20°. For bladder and rectum, the DSC were 0.88 and 0.77 for CBCTLD_GANand 0.92 and 0.87 for CBCTLD_ResGANcompared to CBCTorg, and HDavgwere 1.34 mm and 1.93 mm for CBCTLD_GAN, and 0.90 mm and 1.05 mm for CBCTLD_ResGAN. The computational time was ∼2 s per patient. This study investigated the feasibility of adapting two cycleGAN models to simultaneously remove under-sampling artifacts and correct image intensities of 25% dose CBCT images. High accuracy on dose calculation, HU and patient alignment were achieved. CBCTLD_ResGANachieved better anatomical fidelity.

Precision of the PET activity range during irradiation with10C,11C, and12C beams.

Objective. Beams of stable ions have been a well-established tool for radiotherapy for many decades. In the case of ion beam therapy with stable12C ions, the positron emitters10,11C are produced via projectile and target fragmentation, and their decays enable visualization of the beam via positron emission tomography (PET). However, the PET activity peak matches the Bragg peak only roughly and PET counting statistics is low. These issues can be mitigated by using a short-lived positron emitter as a therapeutic beam.Approach.An experiment studying the precision of the measurement of ranges of positron-emitting carbon isotopes by means of PET has been performed at the FRS fragment-separator facility of GSI Helmholtzzentrum für Schwerionenforschung GmbH, Germany. The PET scanner used in the experiment is a dual-panel version of a Siemens Biograph mCT PET scanner.Main results.High-quality in-beam PET images and activity distributions have been measured from the in-flight produced positron emitting isotopes11C and10C implanted into homogeneous PMMA phantoms. Taking advantage of the high statistics obtained in this experiment, we investigated the time evolution of the uncertainty of the range determined by means of PET during the course of irradiation, and show that the uncertainty improves with the inverse square root of the number of PET counts. The uncertainty is thus fully determined by the PET counting statistics. During the delivery of 1.6 × 107ions in 4 spills for a total duration of 19.2 s, the PET activity range uncertainty for10C,11C and12C is 0.04 mm, 0.7 mm and 1.3 mm, respectively. The gain in precision related to the PET counting statistics is thus much larger when going from11C to10C than when going from12C to11C. The much better precision for10C is due to its much shorter half-life, which, contrary to the case of11C, also enables to include the in-spill data in the image formation.Significance. Our results can be used to estimate the contribution from PET counting statistics to the precision of range determination in a particular carbon therapy situation, taking into account the irradiation scenario, the required dose and the PET scanner characteristics.

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.

Experimental demonstration of accurate Bragg peak localization with ionoacoustic tandem phase detection (iTPD).

Accurate knowledge of the exact stopping location of ions inside the patient would allow full exploitation of their ballistic properties for patient treatment. The localized energy deposition of a pulsed particle beam induces a rapid temperature increase of the irradiated volume and leads to the emission of ionoacoustic (IA) waves. Detecting the time-of-flight (ToF) of the IA wave allows inferring information on the Bragg peak location and can henceforth be used forin-vivorange verification. A challenge for IA is the poor signal-to-noise ratio at clinically relevant doses and viable machines. We present a frequency-based measurement technique, labeled as ionoacoustic tandem phase detection (iTPD) utilizing lock-in amplifiers. The phase shift of the IA signal to a reference signal is measured to derive theToF. Experimental IA measurements with a 3.5 MHz lead zirconate titanate (PZT) transducer and lock-in amplifiers were performed in water using 22 MeV proton bursts. A digital iTPD was performedin-silicoat clinical dose levels on experimental data obtained from a clinical facility and secondly, on simulations emulating a heterogeneous geometry. For the experimental setup using 22 MeV protons, a localization accuracy and precision obtained through iTPD deviates from a time-based reference analysis by less than 15µm. Several methodological aspects were investigated experimentally in systematic manner. Lastly, iTPD was evaluatedin-silicofor clinical beam energies indicating that iTPD is in reach of sub-mm accuracy for fractionated doses < 5 Gy. iTPD can be used to accurately measure theToFof IA signals online via its phase shift in frequency domain. An application of iTPD to the clinical scenario using a single pulsed beam is feasible but requires further development to reach <1 Gy detection capabilities.

Sub-millimeter precise photon interaction position determination in large monolithic scintillators via convolutional neural network algorithms.

In this work, we present the development and application of a convolutional neural network (CNN)-based algorithm to precisely determine the interaction position ofγ-quanta in large monolithic scintillators. Those are used as an absorber component of a Compton camera (CC) system under development for ion beam range verification via prompt-gamma imaging. We examined two scintillation crystals: LaBr3:Ce and CeBr3. Each crystal had dimensions of 50.8 mm × 50.8 mm × 30 mm and was coupled to a 64-fold segmented multi-anode photomultiplier tube (PMT) with an 8 × 8 pixel arrangement. We determined the spatial resolution for three photon energies of 662, 1.17 and 1.33 MeV obtained from 2D detector scans with tightly collimated137Cs and60Co photon sources. With the new algorithm we achieved a spatial resolution for the CeBr3 crystal below 1.11(8) mm and below 0.98(7) mm for the LaBr3:Ce detector for all investigated energies between 662 keV and 1.33 MeV. We thereby improved the performance by more than a factor of 2.5 compared to the previously used categorical average pattern algorithm, which is a variation of the well-established k-nearest neighbor algorithm. The trained CNN has a low memory footprint and enables the reconstruction of up to 104events per second with only one GPU. Those improvements are crucial on the way to future clinicalin vivoapplicability of the CC for ion beam range verification.

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.

Integration of spatial distortion effects in a 4D computational phantom for simulation studies in extra-cranial MRI-guided radiation therapy: Initial results.

PURPOSE: Spatial distortions in magnetic resonance imaging (MRI) are mainly caused by inhomogeneities of the static magnetic field, nonlinearities in the applied gradients, and tissue-specific magnetic susceptibility variations. These factors may significantly alter the geometrical accuracy of the reconstructed MR image, thus questioning the reliability of MRI for guidance in image-guided radiation therapy. In this work, we quantified MRI spatial distortions and created a quantitative model where different sources of distortions can be separated. The generated model was then integrated into a four-dimensional (4D) computational phantom for simulation studies in MRI-guided radiation therapy at extra-cranial sites. METHODS: A geometrical spatial distortion phantom was designed in four modules embedding laser-cut PMMA grids, providing 3520 landmarks in a field of view of (345 × 260 × 480) mm3 . The construction accuracy of the phantom was verified experimentally. Two fast MRI sequences for extra-cranial imaging at 1.5 T were investigated, considering axial slices acquired with online distortion correction, in order to mimic practical use in MRI-guided radiotherapy. Distortions were separated into their sources by acquisition of images with gradient polarity reversal and dedicated susceptibility calculations. Such a separation yielded a quantitative spatial distortion model to be used for MR imaging simulations. Finally, the obtained spatial distortion model was embedded into an anthropomorphic 4D computational phantom, providing registered virtual CT/MR images where spatial distortions in MRI acquisition can be simulated. RESULTS: The manufacturing accuracy of the geometrical distortion phantom was quantified to be within 0.2 mm in the grid planes and 0.5 mm in depth, including thickness variations and bending effects of individual grids. Residual spatial distortions after MRI distortion correction were strongly influenced by the applied correction mode, with larger effects in the trans-axial direction. In the axial plane, gradient nonlinearities caused the main distortions, with values up to 3 mm in a 1.5 T magnet, whereas static field and susceptibility effects were below 1 mm. The integration in the 4D anthropomorphic computational phantom highlighted that deformations can be severe in the region of the thoracic diaphragm, especially when using axial imaging with 2D distortion correction. Adaptation of the phantom based on patient-specific measurements was also verified, aiming at increased realism in the simulation. CONCLUSIONS: The implemented framework provides an integrated approach for MRI spatial distortion modeling, where different sources of distortion can be quantified in time-dependent geometries. The computational phantom represents a valuable platform to study motion management strategies in extra-cranial MRI-guided radiotherapy, where the effects of spatial distortions can be modeled on synthetic images in a virtual environment.

Animal tissue-based quantitative comparison of dual-energy CT to SPR conversion methods using high-resolution gel dosimetry.

Dual-energy computed tomography (DECT) has been shown to allow for more accurate ion therapy treatment planning by improving the estimation of tissue stopping power ratio (SPR) relative to water, among other tissue properties. In this study, we measured and compared the accuracy of SPR values derived using both dual- and single-energy CT (SECT) based on different published conversion algorithms. For this purpose, a phantom setup containing either fresh animal soft tissue samples (beef, pork) and a water reference or tissue equivalent plastic materials was designed and irradiated in a clinical proton therapy facility. Dosimetric polymer gel was positioned downstream of the samples to obtain a three-dimensional proton range distribution with high spatial resolution. The mean proton range in gel for each tissue relative to the water sample was converted to a SPR value. Additionally, the homogeneous samples were probed with a variable water column encompassed by two ionization chambers to benchmark the SPR accuracy of the gel dosimetry. The SPR values measured with both methods were consistent with a mean deviation of 0.2%, but the gel dosimetry captured range variations up to 5 mm within individual samples.Across all fresh tissue samples the SECT approach yielded significantly greater mean absolute deviations from the SPR deduced using gel range measurements, with an average difference of 1.2%, compared to just 0.3% for the most accurate DECT-based algorithm. These results show a significant advantage of DECT over SECT for stopping power prediction in a realistic setting, and for the first time allow to compare a large set of methods under the same conditions.

Laser-driven x-ray and proton micro-source and application to simultaneous single-shot bi-modal radiographic imaging.

Radiographic imaging with x-rays and protons is an omnipresent tool in basic research and applications in industry, material science and medical diagnostics. The information contained in both modalities can often be valuable in principle, but difficult to access simultaneously. Laser-driven solid-density plasma-sources deliver both kinds of radiation, but mostly single modalities have been explored for applications. Their potential for bi-modal radiographic imaging has never been fully realized, due to problems in generating appropriate sources and separating image modalities. Here, we report on the generation of proton and x-ray micro-sources in laser-plasma interactions of the focused Texas Petawatt laser with solid-density, micrometer-sized tungsten needles. We apply them for bi-modal radiographic imaging of biological and technological objects in a single laser shot. Thereby, advantages of laser-driven sources could be enriched beyond their small footprint by embracing their additional unique properties, including the spectral bandwidth, small source size and multi-mode emission.

Beam characterization and feasibility study for a small animal irradiation platform at clinical proton therapy facilities.

A deeper understanding of biological mechanisms to promote more efficient treatment strategies in proton therapy demands advances in preclinical radiation research. However this is often limited by insufficient availability of adequate infrastructures for precision image guided small animal proton irradiation. The project SIRMIO aims at filling this gap by developing a portable image-guided research platform for small animal irradiation, to be used at clinical facilities and allowing for a precision similar to a clinical treatment, when scaled down to the small animal size. This work investigates the achievable dosimetric properties of different lowest energy clinical proton therapy beams, manipulated by a dedicated portable beamline including active focusing after initial beam energy degradation and collimation. By measuring the lateral beam size in air close to the beam nozzle exit and the laterally integrated depth dose in water, an analytical beam model based on the beam parameters of the clinical beam at the Rinecker Proton Therapy Center was created for the lowest available clinical beam energy. The same approach was then applied to estimate the lowest energy beam model of different proton therapy facilities, Paul Scherrer Institute, Centre Antoine Lacassagne, Trento Proton Therapy Centre and the Danish Centre for Particle Therapy, based on their available beam commissioning data. This comparison indicated similar beam properties for all investigated sites, with emittance values of a few tens of mm·mrad. Finally, starting from these beam models, we simulated propagation through a novel beamline designed to manipulate the beam energy and size for precise small animal irradiation, and evaluated the resulting dosimetric properties in water. For all investigated initial clinical beams, similar dosimetric results suitable for small animal irradiation were found. This work supports the feasibility of the proposed SIRMIO beamline, promising suitable beam characteristics to allow for precise preclinical irradiation at clinical treatment facilities.

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.

Assessment of range uncertainty in lung-like tissue using a porcine lung phantom and proton radiography.

Thoracic tumours are increasingly considered indications for pencil beam scanned proton therapy (PBS-PT) treatments. Conservative robustness settings have been suggested due to potential range straggling effects caused by the lung micro-structure. Using proton radiography (PR) and a 4D porcine lung phantom, we experimentally assess range errors to be considered in robust treatment planning for thoracic indications. A human-chest-size 4D phantom hosting inflatable porcine lungs and corresponding 4D computed tomography (4DCT) were used. Five PR frames were planned to intersect the phantom at various positions. Integral depth-dose curves (IDDs) per proton spot were measured using a multi-layer ionisation chamber (MLIC). Each PR frame consisted of 81 spots with an assigned energy of 210 MeV (full width at half maximum (FWHM) 8.2 mm). Each frame was delivered five times while simultaneously acquiring the breathing signal of the 4D phantom, using an ANZAI load cell. The synchronised ANZAI and delivery log file information was used to retrospectively sort spots into their corresponding breathing phase. Based on this information, IDDs were simulated by the treatment planning system (TPS) Monte Carlo dose engine on a dose grid of 1 mm. In addition to the time-resolved TPS calculations on the 4DCT phases, IDDs were calculated on the average CT. Measured IDDs were compared with simulated ones, calculating the range error for each individual spot. In total, 2025 proton spots were individually measured and analysed. The range error of a specific spot is reported relative to its water equivalent path length (WEPL). The mean relative range error was 1.2% (1.5 SD 2.3 %) for the comparison with the time-resolved TPS calculations, and 1.0% (1.5 SD 2.2 %) when comparing to TPS calculations on the average CT. The determined mean relative range errors justify the use of 3% range uncertainty for robust treatment planning in a clinical setting for thoracic indications.

A filtering approach for PET and PG predictions in a proton treatment planning system.

Positron emission tomography (PET) and prompt gamma (PG) detection are promising proton therapy monitoring modalities. Fast calculation of the expected distributions is desirable for comparison to measurements and to develop/train algorithms for automatic treatment error detection. A filtering formalism was used for positron-emitter predictions and adapted to allow for its use for the beamline of any proton therapy centre. A novel approach based on a filtering formalism was developed for the prediction of energy-resolved PG distributions for arbitrary tissues. The method estimates PG yields and their energy spectra in the entire treatment field. Both approaches were implemented in a research version of the RayStation treatment planning system. The method was validated against PET monitoring data and Monte Carlo simulations for four patients treated with scanned proton beams. Longitudinal shifts between profiles from analytical and Monte Carlo calculations were within -1.7 and 0.9 mm, with maximum standard deviation of 0.9 mm and 1.1 mm, for positron-emitters and PG shifts, respectively. Normalized mean absolute errors were within 1.2 and 5.3%. When comparing measured and predicted PET data, the same more complex case yielded an average shift of 3 mm, while all other cases were below absolute average shifts of 1.1 mm. Normalized mean absolute errors were below 7.2% for all cases. A novel solution to predict positron-emitter and PG distributions in a treatment planning system is proposed, enabling calculation times of only a few seconds to minutes for entire patient cases, which is suitable for integration in daily clinical routine.

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.

Offline imaging of positron emitters induced by therapeutic helium, carbon and oxygen ion beams with a full-ring PET/CT scanner: experiments in reference targets.

In vivo verification of light ion therapy based on positron-emission tomography (PET) imaging of irradiation induced patient activation relies on activity predictions from Monte-Carlo (MC) or analytical computational engines for comparison to the measurements. In order to achieve the necessary accuracy, experimental data are indispensable for the validation of the calculation models. For this we irradiated thick reference targets with mono-energetic helium, carbon and oxygen ion beams and measured the resulting material activation offline with a commercial full-ring PET/CT scanner located nearby the treatment room. Acquired PET data were analysed over time to separate the activity contribution of different radionuclides. Determined production yields were compared to published findings obtained from in-beam activation measurements with a limited-angle double-head PET camera. In addition, we investigated the time-dependence of the measured radionuclide-specific contributions and of the distal activity range, as well as the lateral spread of the activity signal as a function of beam penetration depth. We present radionuclide-specific depth-resolved activity distributions and production yields for the radionuclides [Formula: see text], [Formula: see text] and [Formula: see text], dominating irradiation-induced patient activation. We observe systematically lower production yields with a ratio between the dual-head and our full-ring PET measurements of, on average, 1.7 and 1.3 for the oxygen and carbon beam irradiations, and 1.7 (2.1) for the high (low) energy helium beam irradiations. Findings on the temporal development of the activity range confirm the expectation, with the oxygen beam induced signal being the most sensitive scenario. The experimental data reported in this work, acquired with a state-of-the-art full ring PET scanner, provide a comprehensive and consistent basis for the benchmarking of PET signal calculation engines. In particular, they can support a fine-tuning of the underlying physics models used by the respective implementation and therefore improve the accuracy of PET-based therapy verifications at current and future treatment facilities.

Improving the modelling of susceptibility-induced spatial distortions in MRI-guided extra-cranial radiotherapy.

Magnetic-resonance linear-accelerator (MR-LINAC) systems integrating in-room magnetic-resonance-imaging (MRI) guidance are a currently emerging technology. Such systems address the need to provide frequent imaging at optimal soft-tissue contrast for treatment guidance. However, the use of MRI-guidance in radiotherapy should address imaging-related spatial distortions, which may hinder accurate geometrical characterization of the treatment site. Since spatial encoding relies on well-defined magnetic fields, accurate modeling of the magnetic field alterations due to [Formula: see text]-inhomogeneities, gradient nonlinearities, and susceptibilities is needed. In this work, the modeling of susceptibility induced distortions is considered. Dedicated susceptibility measurements are reported, aiming at extending the characterization of different tissues for MRI-guided extra-cranial radiotherapy applications. A digital 4D anthropomorphic phantom, providing time-resolved anatomical changes due to breathing, is exploited as reference anatomy to quantify spatial distortions due to variations in tissue susceptibility. Sub-millimeter values can be attributed to susceptibility-induced distortions, with maximum values up to 2.3 mm at a gradient strength of 5 mT m-1. Improvements in susceptibility simulation for extra-cranial sites are shown when including specifically the contributions from lung, liver and muscular tissues.

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.