Voxel-wise dose rate calculation in clinical pencil beam scanning proton therapy.

OBJECTIVE: Clinical outcomes after proton therapy have shown some variability that is not fully understood. Different approaches have been suggested to explain the biological outcome, but none has yet provided a comprehensive and satisfactory rationale for observed toxicities. The relatively recent transition from passive scattering (PS) to pencil beam scanning (PBS) treatments has significantly increased the voxel-wise dose rate in proton therapy. In addition, the dose rate distribution is no longer uniform along the cross section of the target but rather highly heterogeneous, following the spot placement. We suggest investigating dose rate as potential contributor to a more complex proton RBE model. Approach. Due to the time structure of the PBS beam delivery the instantaneous dose rate is highly variable voxel by voxel. Several possible parameters to represent voxel-wise dose rate for a given clinical PBS treatment plan are detailed. These quantities were implemented in the scripting environment of our treatment planning system, and computations experimentally verified. Sample applications to treated patient plans are shown. Main Results. Computed dose rates we experimentally confirmed. Dose rate maps vary depending on which method is used to represent them. Mainly, the underlying time and dose intervals chosen determine the topography of the resultant distributions. The maximum dose rates experienced by any target voxel in a given PBS treatment plan in our system range from ~100 to ~450 Gy(RBE)/min, a factor of 10 - 100 increase compared to PS. These dose rate distributions are very heterogeneous, with distinct hot spots. Significance. Voxel-wise dose rates for current clinical PBS treatment plans vary greatly from clinically established practice with PS. The exploration of different dose rate measures to evaluate potential correlations with observed clinical outcomes is suggested, potentially adding a missing component in the understanding of proton RBE.

Modernization of safety environment for a dedicated beamline for proton ocular therapy.

BACKGROUND: Proton therapy is an effective treatment for ocular melanoma, and other tumors of the eye. The fixed horizontal beamline dedicated to ocular treatments at Massachusetts General Hospital was originally commissioned in 2002, with much of the equipment, safety features, and practices dating back to an earlier implementation at Harvard Cyclotron in the 1970s. PURPOSE: To describe the experience of reevaluation and enhancement of the safety environment for one of the longest continuously operating proton therapy programs. METHODS: Several enhancements in quality control had been introduced throughout the years of operation, as described in this manuscript, to better align the practice with the evolving standards of proton therapy and the demands of a modern hospital. We spotlight the design and results of the failure mode and effect analysis (FMEA), and subsequent actions introduced to mitigate the modes associated with elevated risk. The findings of the FMEA informed the specifications for the new software application, which facilitated the improved management of the treatment workflow and the image-guidance aspects of ocular treatments. RESULTS: Eleven failure modes identified as having the highest risk are described. Six of these were mitigated with the clinical roll-out of a new application for image-guided radiation therapy (IGRT). Others were addressed through task automation, the broader introduction of checklists, and enhancements in pre-treatment staff-led time-out. CONCLUSIONS: Throughout the task of modernizing the safety system of our dedicated ocular beamline, FMEA proved to be an effective instrument in soliciting inputs from the staff about safety and workflow concerns, helping to identify steps associated with elevated failure risks. Risks were reduced with the clinical introduction of a new IGRT application, which integrates quality management tools widely recognized for their role in risk mitigation: automation of the data transfer and workflow steps, and with the introduction of checklists and redundancy cross-checks.

Validation of an MR-based multimodal method for molecular composition and proton stopping power ratio determination using ex vivo animal tissues and tissue-mimicking phantoms.

Objective. Range uncertainty in proton therapy is an important factor limiting clinical effectiveness. Magnetic resonance imaging (MRI) can measure voxel-wise molecular composition and, when combined with kilovoltage CT (kVCT), accurately determine mean ionization potential (Im), electron density, and stopping power ratio (SPR). We aimed to develop a novel MR-based multimodal method to accurately determine SPR and molecular compositions. This method was evaluated in tissue-mimicking andex vivoporcine phantoms, and in a brain radiotherapy patient.Approach. Four tissue-mimicking phantoms with known compositions, two porcine tissue phantoms, and a brain cancer patient were imaged with kVCT and MRI. Three imaging-based values were determined: SPRCM(CT-based Multimodal), SPRMM(MR-based Multimodal), and SPRstoich(stoichiometric calibration). MRI was used to determine two tissue-specific quantities of the Bethe Bloch equation (Im, electron density) to compute SPRCMand SPRMM. Imaging-based SPRs were compared to measurements for phantoms in a proton beam using a multilayer ionization chamber (SPRMLIC).Main results. Root mean square errors relative to SPRMLICwere 0.0104(0.86%), 0.0046(0.45%), and 0.0142(1.31%) for SPRCM, SPRMM, and SPRstoich, respectively. The largest errors were in bony phantoms, while soft tissue and porcine tissue phantoms had <1% errors across all SPR values. Relative to known physical molecular compositions, imaging-determined compositions differed by approximately ≤10%. In the brain case, the largest differences between SPRstoichand SPRMMwere in bone and high lipids/fat tissue. The magnitudes and trends of these differences matched phantom results.Significance. Our MR-based multimodal method determined molecular compositions and SPR in various tissue-mimicking phantoms with high accuracy, as confirmed with proton beam measurements. This method also revealed significant SPR differences compared to stoichiometric kVCT-only calculation in a clinical case, with the largest differences in bone. These findings support that including MRI in proton therapy treatment planning can improve the accuracy of calculated SPR values and reduce range uncertainties.

Large anatomical changes in head-and-neck cancers - A dosimetric comparison of online and offline adaptive proton therapy.

Purpose: This work evaluates an online adaptive (OA) workflow for head-and-neck (H&N) intensity-modulated proton therapy (IMPT) and compares it with full offline replanning (FOR) in patients with large anatomical changes. Methods: IMPT treatment plans are created retrospectively for a cohort of eight H&N cancer patients that previously required replanning during the course of treatment due to large anatomical changes. Daily cone-beam CTs (CBCT) are acquired and corrected for scatter, resulting in 253 analyzed fractions. To simulate the FOR workflow, nominal plans are created on the planning-CT and delivered until a repeated-CT is acquired; at this point, a new plan is created on the repeated-CT. To simulate the OA workflow, nominal plans are created on the planning-CT and adapted at each fraction using a simple beamlet weight-tuning technique. Dose distributions are calculated on the CBCTs with Monte Carlo for both delivery methods. The total treatment dose is accumulated on the planning-CT. Results: Daily OA improved target coverage compared to FOR despite using smaller target margins. In the high-risk CTV, the median D98 degradation was 1.1 % and 2.1 % for OA and FOR, respectively. In the low-risk CTV, the same metrics yield 1.3 % and 5.2 % for OA and FOR, respectively. Smaller setup margins of OA reduced the dose to all OARs, which was most relevant for the parotid glands. Conclusion: Daily OA can maintain prescription doses and constraints over the course of fractionated treatment, even in cases of large anatomical changes, reducing the necessity for manual replanning in H&N IMPT.

Validation of prompt gamma-ray spectroscopy for proton range verification in tissue-mimicking and porcine samples.

Objective. Proton therapy of cancer improves dose conformality to the target and sparing of surrounding healthy tissues compared to conventional photon treatments. However, proton therapy's advantage could be even larger if proton range uncertainties were reduced. Sources of range uncertainties include computed tomography treatment planning images and variations in patient anatomy and setup. To reduce range uncertainties, we have developed a system for real-timein vivorange monitoring. The system is based on spectroscopy of prompt gamma-rays emitted through proton-nuclear interactions during irradiation. We validated the performance of our prompt gamma-ray spectroscopy detector prototype using tissue-mimicking and porcine samples.Approach. Measurements were performed in water, four tissue-mimicking samples (spongiosa, muscle, adipose tissue, and cortical bone), and two porcine samples (liver and brain). A dose of 0.9 Gy was delivered to a target at a depth of 12.5-17.5 cm. Multi-layer ionization chamber measurements were performed to determine stopping power ratios relative to water and ground truth proton ranges. Ground truth elemental compositions were determined using combustion analysis. Proton ranges and elemental compositions measured using prompt gamma-ray spectroscopy were compared to the ground truth.Main results. For all samples, the mean measured range over all pencil-beam spots differed from the ground truth by less than 1.2 mm. The mean standard deviation was 0.9 mm (range: 0.4-1.6 mm). The mean difference between ground truth and measured elemental compositions was 0.06gcm3(range: 0.00gcm3to 0.12gcm3).Significance. We verified the performance of our prompt gamma-ray spectroscopy detector prototype for proton range verification using tissue-mimicking and porcine samples. Measured proton ranges and elemental sample compositions were in good agreement with the ground truth. These measurements confirm the system's reliability for a variety of tissues and bridge the gap between previously-reported experiments and ongoingin vivopatient measurements.

MOQUI: an open-source GPU-based Monte Carlo code for proton dose calculation with efficient data structure.

Objective.Monte Carlo (MC) codes are increasingly used for accurate radiotherapy dose calculation. In proton therapy, the accuracy of the dose calculation algorithm is expected to have a more significant impact than in photon therapy due to the depth-dose characteristics of proton beams. However, MC simulations come at a considerable computational cost to achieve statistically sufficient accuracy. There have been efforts to improve computational efficiency while maintaining sufficient accuracy. Among those, parallelizing particle transportation using graphic processing units (GPU) achieved significant improvements. Contrary to the central processing unit, a GPU has limited memory capacity and is not expandable. It is therefore challenging to score quantities with large dimensions requiring extensive memory. The objective of this study is to develop an open-source GPU-based MC package capable of scoring those quantities.Approach.We employed a hash-table, one of the key-value pair data structures, to efficiently utilize the limited memory of the GPU and score the quantities requiring a large amount of memory. With the hash table, only voxels interacting with particles will occupy memory, and we can search the data efficiently to determine their address. The hash-table was integrated with a novel GPU-based MC code, moqui.Main results.The developed code was validated against an MC code widely used in proton therapy, TOPAS, with homogeneous and heterogeneous phantoms. We also compared the dose calculation results of clinical treatment plans. The developed code agreed with TOPAS within 2%, except for the fall-off and regions, and the gamma pass rates of the results were >99% for all cases with a 2 mm/2% criteria.Significance.We can score dose-influence matrix and dose-rate on a GPU for a 3-field H&N case with 10 GB of memory using moqui, which would require more than 100 GB of memory with the conventionally used array data structure.

Range uncertainty reductions in proton therapy may lead to the feasibility of novel beam arrangements which improve organ-at-risk sparing.

PURPOSE: In proton therapy, dose distributions are currently often conformed to organs at risk (OARs) using the less sharp dose fall-off at the lateral beam edge to reduce the effects of uncertainties in the in vivo proton range. However, range uncertainty reductions may make greater use of the sharper dose fall-off at the distal beam edge feasible, potentially improving OAR sparing. We quantified the benefits of such novel beam arrangements. METHODS: For each of 10 brain or skull base cases, five treatment plans robust to 2 mm setup and 0%-4% range uncertainty were created for the traditional clinical beam arrangement and a novel beam arrangement making greater use of the distal beam edge to conform the dose distribution to the brainstem. Metrics including the brainstem normal tissue complication probability (NTCP) with the endpoint of necrosis were determined for all plans and all setup and range uncertainty scenarios. RESULTS: For the traditional beam arrangement, reducing the range uncertainty from the current level of approximately 4% to a potentially achievable level of 1% reduced the brainstem NTCP by up to 0.9 percentage points in the nominal and up to 1.5 percentage points in the worst-case scenario. Switching to the novel beam arrangement at 1% range uncertainty improved these values by a factor of 2, that is, to 1.8 percentage points and 3.2 percentage points, respectively. The novel beam arrangement achieved a lower brainstem NTCP in all cases starting at a range uncertainty of 2%. CONCLUSION: The benefits of novel beam arrangements may be of the same magnitude or even exceed the direct benefits of range uncertainty reductions. Indirect effects may therefore contribute markedly to the benefits of reducing proton range uncertainties.

Proton range uncertainty reduction benefits for skull base tumors in terms of normal tissue complication probability (NTCP) and healthy tissue doses.

PURPOSE: Proton therapy allows for more conformal dose distributions and lower organ at risk and healthy tissue doses than conventional photon-based radiotherapy, but uncertainties in the proton range currently prevent proton therapy from making full use of these advantages. Numerous developments therefore aim to reduce such range uncertainties. In this work, we quantify the benefits of reductions in range uncertainty for treatments of skull base tumors. METHODS: The study encompassed 10 skull base patients with clival tumors. For every patient, six treatment plans robust to setup errors of 2 mm and range errors from 0% to 5% were created. The determined metrics included the brainstem and optic chiasm normal tissue complication probability (NTCP) with the endpoints of necrosis and blindness, respectively, as well as the healthy tissue volume receiving at least 70% of the prescription dose. RESULTS: A range uncertainty reduction from the current level of 4% to a potentially achievable level of 1% reduced the probability of brainstem necrosis by up to 1.3 percentage points in the nominal scenario in which neither setup nor range errors occur and by up to 2.9 percentage points in the worst-case scenario. Such a range uncertainty reduction also reduced the optic chiasm NTCP with the endpoint of blindness by up to 0.9 percentage points in the nominal scenario and by up to 2.2 percentage points in the worst-case scenario. The decrease in the healthy tissue volume receiving at least 70% of the prescription dose ranged from -7.8 to 24.1 cc in the nominal scenario and from -3.4 to 38.4 cc in the worst-case scenario. CONCLUSION: The benefits quantified as part of this study serve as a guideline of the OAR and healthy tissue dose benefits that range monitoring techniques may be able to achieve. Benefits were observed between all levels of range uncertainty. Even smaller range uncertainty reductions may therefore be beneficial.

Anatomic changes in head and neck intensity-modulated proton therapy: Comparison between robust optimization and online adaptation.

BACKGROUND/PURPOSE: Setup variations and anatomical changes can severely affect the quality of head and neck intensity-modulated proton therapy (IMPT) treatments. The impact of these changes can be alleviated by increasing the plan's robustness a priori, or by adapting the plan online. This work compares these approaches in the context of head and neck IMPT. MATERIALS/METHODS: A representative cohort of 10 head and neck squamous cell carcinoma (HNSCC) patients with daily cone-beam computed tomography (CBCT) was evaluated. For each patient, three IMPT plans were created: 1- a classical robust optimization (cRO) plan optimized on the planning CT, 2- an anatomical robust optimization (aRO) plan additionally including the two first daily CBCTs and 3- a plan optimized without robustness constraints, but online-adapted (OA) daily, using a constrained spot intensity re-optimization technique only. RESULTS: The cumulative dose following OA fulfilled the clinical objective of both the high-risk and low-risk clinical target volumes (CTV) coverage in all 10 patients, compared to 8 for aRO and 4 for cRO. aRO did not significantly increase the dose to most organs at risk compared to cRO, although the integral dose was higher. OA significantly reduced the integral dose to healthy tissues compared to both robust methods, while providing equivalent or superior target coverage. CONCLUSION: Using a simple spot intensity re-optimization, daily OA can achieve superior target coverage and lower dose to organs at risk than robust optimization methods.

Comparison of weekly and daily online adaptation for head and neck intensity-modulated proton therapy.

The high conformality of intensity-modulated proton therapy (IMPT) dose distributions causes treatment plans to be sensitive to geometrical changes during the course of a fractionated treatment. This can be addressed using adaptive proton therapy (APT). One important question in APT is the frequency of adaptations performed during a fractionated treatment, which is related to the question whether plan adaptation has to be done online or offline. The purpose of this work is to investigate the impact of weekly and daily online IMPT plan adaptation on the treatment quality for head and neck patients. A cohort of ten head and neck patients with daily acquired cone-beam CT (CBCT) images was evaluated retrospectively. Dose tracking of the IMPT treatment was performed for three scenarios: base plan with no adaptation (BP), weekly online adaptation (OAW), and daily online adaptation (OAD). Both adaptation schemes used an in-house developed online APT workflow, performing Monte Carlo dose calculations on scatter-corrected CBCTs. IMPT plan adaptation was achieved by only tuning the weights of a subset of beamlets, based on deformable image registration from the planning CT to each CBCT. Although OADmitigated random delivery errors more effectively than OAWon a fraction per fraction basis, both OAWand OADachieved the clinical goals for all ten patients, while BP failed for six cases. In the high-risk CTV, accumulated values ofD98%ranged between 97.15% and 99.73% of the prescription dose for OAD, with a median of 98.07%. For OAW, values between 95.02% and 99.26% were obtained, with a median of 97.61% of the prescription dose. Otherwise, the dose to most organs at risk was similar for all three scenarios. Globally, our results suggest that OAWcould be used as an alternative approach to OADfor most patients in order to reduce the clinical workload.

Evaluation of CBCT scatter correction using deep convolutional neural networks for head and neck adaptive proton therapy.

Adaptive proton therapy (APT) is a promising approach for the treatment of head and neck cancers. One crucial element of APT is daily volumetric imaging of the patient in the treatment position. Such data can be acquired with cone-beam computed tomography (CBCT), although scatter artifacts make uncorrected CBCT images unsuitable for proton therapy dose calculation. The purpose of this work is to evaluate the performance of a U-shape deep convolutive neural network (U-Net) to perform projection-based scatter correction and enable fast and accurate dose calculation on CBCT images in the context of head and neck APT. CBCT projections are simulated for a cohort of 48 head and neck patients using a GPU accelerated Monte Carlo (MC) code . A U-Net is trained to reproduce MC projection-based scatter correction from raw projections. The accuracy of the scatter correction is experimentally evaluated using CT and CBCT images of an anthropomorphic head phantom. The potential of the method for head and neck APT is assessed by comparing proton therapy dose distributions calculated on scatter-free, uncorrected and scatter-corrected CBCT images. Finally, dose calculation accuracy is estimated in experimental patient images using a previously validated empirical scatter correction as reference. The mean and mean absolute HU differences between scatter-free and scatter-corrected images are -0.8 and 13.4 HU, compared to -28.6 and 69.6 HU for the uncorrected images. In the head phantom, the root-mean square difference of proton ranges calculated in the reference CT and corrected CBCT is 0.73 mm. The average 2%/2 mm gamma pass rate for proton therapy plans optimized in the scatter free images and re-calculated in the scatter-corrected ones is 98.89%. In experimental CBCT patient images, a 3%/3 mm passing rate of 98.72% is achieved between the proposed method and the reference one. All CBCT projection volume could be corrected in less than 5 seconds.

A full-scale clinical prototype for proton range verification using prompt gamma-ray spectroscopy.

We present a full-scale clinical prototype system for in vivo range verification of proton pencil-beams using the prompt gamma-ray spectroscopy method. The detection system consists of eight LaBr3 scintillators and a tungsten collimator, mounted on a rotating frame. Custom electronics and calibration algorithms have been developed for the measurement of energy- and time-resolved gamma-ray spectra during proton irradiation at a clinical dose rate. Using experimentally determined nuclear reaction cross sections and a GPU-accelerated Monte Carlo simulation, a detailed model of the expected gamma-ray emissions is created for each individual pencil-beam. The absolute range of the proton pencil-beams is determined by minimizing the discrepancy between the measurement and this model, leaving the absolute range of the beam and the elemental concentrations of the irradiated matter as free parameters. The system was characterized in a clinical-like situation by irradiating different phantoms with a scanning pencil-beam. A dose of 0.9 Gy was delivered to a [Formula: see text] cm3 target with a beam current of 2 nA incident on the phantom. Different range shifters and materials were used to test the robustness of the verification method and to calculate the accuracy of the detected range. The absolute proton range was determined for each spot of the distal energy layer with a mean statistical precision of 1.1 mm at a 95% confidence level and a mean systematic deviation of 0.5 mm, when aggregating pencil-beam spots within a cylindrical region of 10 mm radius and 10 mm depth. Small range errors that we introduced were successfully detected and even large differences in the elemental composition do not affect the range verification accuracy. These results show that our system is suitable for range verification during patient treatments in our upcoming clinical study.

Metal artifacts in computed tomography for radiation therapy planning: dosimetric effects and impact of metal artifact reduction.

A significant and increasing number of patients receiving radiation therapy present with metal objects close to, or even within, the treatment area, resulting in artifacts in computed tomography (CT) imaging, which is the most commonly used imaging method for treatment planning in radiation therapy. In the presence of metal implants, such as dental fillings in treatment of head-and-neck tumors, spinal stabilization implants in spinal or paraspinal treatment or hip replacements in prostate cancer treatments, the extreme photon absorption by the metal object leads to prominent image artifacts. Although current CT scanners include a series of correction steps for beam hardening, scattered radiation and noisy measurements, when metal implants exist within or close to the treatment area, these corrections do not suffice. CT metal artifacts affect negatively the treatment planning of radiation therapy either by causing difficulties to delineate the target volume or by reducing the dose calculation accuracy. Various metal artifact reduction (MAR) methods have been explored in terms of improvement of organ delineation and dose calculation in radiation therapy treatment planning, depending on the type of radiation treatment and location of the metal implant and treatment site. Including a brief description of the available CT MAR methods that have been applied in radiation therapy, this article attempts to provide a comprehensive review on the dosimetric effect of the presence of CT metal artifacts in treatment planning, as reported in the literature, and the potential improvement suggested by different MAR approaches. The impact of artifacts on the treatment planning and delivery accuracy is discussed in the context of different modalities, such as photon external beam, brachytherapy and particle therapy, as well as by type and location of metal implants.

Automated Monte Carlo Simulation of Proton Therapy Treatment Plans.

Simulations of clinical proton radiotherapy treatment plans using general purpose Monte Carlo codes have been proven to be a valuable tool for basic research and clinical studies. They have been used to benchmark dose calculation methods, to study radiobiological effects, and to develop new technologies such as in vivo range verification methods. Advancements in the availability of computational power have made it feasible to perform such simulations on large sets of patient data, resulting in a need for automated and consistent simulations. A framework called MCAUTO was developed for this purpose. Both passive scattering and pencil beam scanning delivery are supported. The code handles the data exchange between the treatment planning system and the Monte Carlo system, which requires not only transfer of plan and imaging information but also translation of institutional procedures, such as output factor definitions. Simulations are performed on a high-performance computing infrastructure. The simulation methods were designed to use the full capabilities of Monte Carlo physics models, while also ensuring consistency in the approximations that are common to both pencil beam and Monte Carlo dose calculations. Although some methods need to be tailored to institutional planning systems and procedures, the described procedures show a general road map that can be easily translated to other systems.

Range verification of passively scattered proton beams using prompt gamma-ray detection.

We performed an experimental study to verify the range of passively scattered proton beams by detecting prompt gamma-rays emitted from proton-nuclear interactions. A method is proposed using a single scintillation detector positioned near the distal end of the irradiated target. Lead shielding was used to attenuate gamma-rays emitted along most of the entrance path of the beam. By synchronizing the prompt gamma-ray detector to the rotation of the range modulation wheel, the relation between the gamma emission from the distal part of the target and the range of the incident proton beam was determined. In experiments with a water phantom and an anthropomorphic head phantom, this relation was found to be sensitive to range shifts that were introduced. The wide opening angle of the detector enabled a sufficient signal-to-background ratio to be achieved in the presence of neutron-induced background from the scattering and collimating devices. Uniform range shifts were detected with a standard deviation of 0.1 mm to 0.2 mm at a dose level of 30 cGy to 50 cGy (RBE). The detectable magnitude of a range shift limited to a part of the treatment field area was approximately proportional to the ratio between the field area and the area affected by the range shift. We conclude that it is feasible to detect changes in the range of passively scattered proton beams using a relatively simple prompt gamma-ray detection system. The method can be employed for in vivo verification of the consistency of the delivered range in fractionated treatments.

Proton range verification through prompt gamma-ray spectroscopy.

We present an experimental study of a novel method to verify the range of proton therapy beams. Differential cross sections were measured for 15 prompt gamma-ray lines from proton-nuclear interactions with (12)C and (16)O at proton energies up to 150 MeV. These cross sections were used to model discrete prompt gamma-ray emissions along proton pencil-beams. By fitting detected prompt gamma-ray counts to these models, we simultaneously determined the beam range and the oxygen and carbon concentration of the irradiated matter. The performance of the method was assessed in two phantoms with different elemental concentrations, using a small scale prototype detector. Based on five pencil-beams with different ranges delivering 5 × 10(8) protons and without prior knowledge of the elemental composition at the measurement point, the absolute range was determined with a standard deviation of 1.0-1.4 mm. Relative range shifts at the same dose level were detected with a standard deviation of 0.3-0.5 mm. The determined oxygen and carbon concentrations also agreed well with the actual values. These results show that quantitative prompt gamma-ray measurements enable knowledge of nuclear reaction cross sections to be used for precise proton range verification in the presence of tissue with an unknown composition.

Range verification of passively scattered proton beams based on prompt gamma time patterns.

We propose a proton range verification technique for passive scattering proton therapy systems where spread out Bragg peak (SOBP) fields are produced with rotating range modulator wheels. The technique is based on the correlation of time patterns of the prompt gamma ray emission with the range of protons delivering the SOBP. The main feature of the technique is the ability to verify the proton range with a single point of measurement and a simple detector configuration. We performed four-dimensional (time-dependent) Monte Carlo simulations using TOPAS to show the validity and accuracy of the technique. First, we validated the hadronic models used in TOPAS by comparing simulations and prompt gamma spectrometry measurements published in the literature. Second, prompt gamma simulations for proton range verification were performed for the case of a water phantom and a prostate cancer patient. In the water phantom, the proton range was determined with 2 mm accuracy with a full ring detector configuration for a dose of ~2.5 cGy. For the prostate cancer patient, 4 mm accuracy on range determination was achieved for a dose of ~15 cGy. The results presented in this paper are encouraging in view of a potential clinical application of the technique.

The impact of low-Z and high-Z metal implants in IMRT: a Monte Carlo study of dose inaccuracies in commercial dose algorithms.

PURPOSE: The aim of the study was to evaluate the dosimetric impact of low-Z and high-Z metallic implants on IMRT plans. METHODS: Computed tomography (CT) scans of three patients were analyzed to study effects due to the presence of Titanium (low-Z), Platinum and Gold (high-Z) inserts. To eliminate artifacts in CT images, a sinogram-based metal artifact reduction algorithm was applied. IMRT dose calculations were performed on both the uncorrected and corrected images using a commercial planning system (convolution/superposition algorithm) and an in-house Monte Carlo platform. Dose differences between uncorrected and corrected datasets were computed and analyzed using gamma index (Pγ<1) and setting 2 mm and 2% as distance to agreement and dose difference criteria, respectively. Beam specific depth dose profiles across the metal were also examined. RESULTS: Dose discrepancies between corrected and uncorrected datasets were not significant for low-Z material. High-Z materials caused under-dosage of 20%-25% in the region surrounding the metal and over dosage of 10%-15% downstream of the hardware. Gamma index test yielded Pγ<1>99% for all low-Z cases; while for high-Z cases it returned 91% < Pγ<1< 99%. Analysis of the depth dose curve of a single beam for low-Z cases revealed that, although the dose attenuation is altered inside the metal, it does not differ downstream of the insert. However, for high-Z metal implants the dose is increased up to 10%-12% around the insert. In addition, Monte Carlo method was more sensitive to the presence of metal inserts than superposition/convolution algorithm. CONCLUSIONS: The reduction in terms of dose of metal artifacts in CT images is relevant for high-Z implants. In this case, dose distribution should be calculated using Monte Carlo algorithms, given their superior accuracy in dose modeling in and around the metal. In addition, the knowledge of the composition of metal inserts improves the accuracy of the Monte Carlo dose calculation significantly.

Proton radiography and proton computed tomography based on time-resolved dose measurements.

We present a proof of principle study of proton radiography and proton computed tomography (pCT) based on time-resolved dose measurements. We used a prototype, two-dimensional, diode-array detector capable of fast dose rate measurements, to acquire proton radiographic images expressed directly in water equivalent path length (WEPL). The technique is based on the time dependence of the dose distribution delivered by a proton beam traversing a range modulator wheel in passive scattering proton therapy systems. The dose rate produced in the medium by such a system is periodic and has a unique pattern in time at each point along the beam path and thus encodes the WEPL. By measuring the time dose pattern at the point of interest, the WEPL to this point can be decoded. If one measures the time­dose patterns at points on a plane behind the patient for a beam with sufficient energy to penetrate the patient, the obtained 2D distribution of the WEPL forms an image. The technique requires only a 2D dosimeter array and it uses only the clinical beam for a fraction of second with negligible dose to patient. We first evaluated the accuracy of the technique in determining the WEPL for static phantoms aiming at beam range verification of the brain fields of medulloblastoma patients. Accurate beam ranges for these fields can significantly reduce the dose to the cranial skin of the patient and thus the risk of permanent alopecia. Second, we investigated the potential features of the technique for real-time imaging of a moving phantom. Real-time tumor tracking by proton radiography could provide more accurate validations of tumor motion models due to the more sensitive dependence of proton beam on tissue density compared to x-rays. Our radiographic technique is rapid (~100 ms) and simultaneous over the whole field, it can image mobile tumors without the problem of interplay effect inherently challenging for methods based on pencil beams. Third, we present the reconstructed pCT images of a cylindrical phantom containing inserts of different materials. As for all conventional pCT systems, the method illustrated in this work produces tomographic images that are potentially more accurate than x-ray CT in providing maps of proton relative stopping power (RSP) in the patient without the need for converting x-ray Hounsfield units to proton RSP. All phantom tests produced reasonable results, given the currently limited spatial and time resolution of the prototype detector. The dose required to produce one radiographic image, with the current settings, is ~0.7 cGy. Finally, we discuss a series of techniques to improve the resolution and accuracy of radiographic and tomographic images for the future development of a full-scale detector.