Investigation of dosimetric effect of beam current fluctuations in synchrotron-based proton PBS continuous scanning.

Objective.In proton pencil beam scanning (PBS) continuous delivery, the beam is continuously delivered without interruptions between spots. For synchrotron-based systems, the extracted beam current exhibits a spill structure, and recent publications on beam current measurements have demonstrated significant fluctuations around the nominal values. These fluctuations potentially lead to dose deviations from those calculated assuming a stable beam current. This study investigated the dosimetric implications of such beam current fluctuations during proton PBS continuous scanning.Approach.Using representative clinical proton PBS plans, we performed simulations to mimic a worst-case clinical delivery environment with beam current varies from 50% to 250% of the nominal values. The simulations used the beam delivery parameters optimized for the best beam delivery efficiency of the upcoming particle therapy system at Mayo Clinic Florida. We reconstructed the simulated delivered dose distributions and evaluated the dosimetric impact of beam current fluctuations.Main results.Despite significant beam current fluctuations resulting in deviations at each spot level, the overall dose distributions were nearly identical to those assuming a stable beam current. The 1 mm/1% Gamma passing rate was 100% for all plans. Less than 0.2% root mean square error was observed in the planning target volume dose-volume histogram. Minimal differences were observed in all dosimetric evaluation metrics.Significance.Our findings demonstrate that with our beam delivery system and clinical planning practice, while significant beam current fluctuations may result in large local move monitor unit deviations at each spot level, the overall impact on the dose distribution is minimal.

Performance assessment of variant UNet-based deep-learning dose engines for MR-Linac-based prostate IMRT plans.

Objective. UNet-based deep-learning (DL) architectures are promising dose engines for traditional linear accelerator (Linac) models. Current UNet-based engines, however, were designed differently with various strategies, making it challenging to fairly compare the results from different studies. The objective of this study is to thoroughly evaluate the performance of UNet-based models on magnetic-resonance (MR)-Linac-based intensity-modulated radiation therapy (IMRT) dose calculations.Approach. The UNet-based models, including the standard-UNet, cascaded-UNet, dense-dilated-UNet, residual-UNet, HD-UNet, and attention-aware-UNet, were implemented. The model input is patient CT and IMRT field dose in water, and the output is patient dose calculated by DL model. The reference dose was calculated by the Monaco Monte Carlo module. Twenty training and ten test cases of prostate patients were included. The accuracy of the DL-calculated doses was measured using gamma analysis, and the calculation efficiency was evaluated by inference time.Results. All the studied models effectively corrected low-accuracy doses in water to high-accuracy patient doses in a magnetic field. The gamma passing rates between reference and DL-calculated doses were over 86% (1%/1 mm), 98% (2%/2 mm), and 99% (3%/3 mm) for all the models. The inference times ranged from 0.03 (graphics processing unit) to 7.5 (central processing unit) seconds. Each model demonstrated different strengths in calculation accuracy and efficiency; Res-UNet achieved the highest accuracy, HD-UNet offered high accuracy with the fewest parameters but the longest inference, dense-dilated-UNet was consistently accurate regardless of model levels, standard-UNet had the shortest inference but relatively lower accuracy, and the others showed average performance. Therefore, the best-performing model would depend on the specific clinical needs and available computational resources.Significance. The feasibility of using common UNet-based models for MR-Linac-based dose calculations has been explored in this study. By using the same model input type, patient training data, and computing environment, a fair assessment of the models' performance was present.

A Geant4 shielding design for the first US carbon multi-ion hybrid synchrotron facility.

The Mayo Clinic Florida Integrated Oncology Building will be the home of the first spot-scanning only carbon/proton hybrid therapy system by Hitachi, Ltd. It will provide proton beams up to kinetic energies of 230 MeV and carbon beams up to 430 MeV n-1for clinical deployment. To provide adequate radiation protection, the Geant4 (v10.6) Monte Carlo toolkit was utilized to quantify the ambient dose equivalent at a 10 mm depth (H*(10)) for photons and neutrons. To perform accurate calculations of the ambient dose equivalent, three-dimensional computer-aided design files of the entire planned facility were imported into Geant4, as well as certain particle system components such as the bending magnets, fast Faraday cup, and gantry. Particle fluence was scored using 60 cm diameter spheres, which were strategically placed throughout areas of interests. Analytical calculations were performed as first-pass design checks. Major shielding slabs were optimized using Geant4 simulations iteratively, with more than 20 alternative designs evaluated within Geant4. The 430 MeV n-1carbon beams played the most significant role in concrete thickness Requirements. The primary wall thickness for the carbon fixed beam room is 4 meters. The presence of the proton gantry structure in the simulation caused the ambient dose equivalent to increase by around 67% at the maze entrance, but a decrease in the high energy beam transport corridor. All shielding primary and secondary goals for clinical operations were met per state regulation and national guidelines.

Dosimetric Assessment of a High Precision System for Mouse Proton Irradiation to Assess Spinal Cord Toxicity.

The uncertainty associated with the relative biological effectiveness (RBE) in proton therapy, particularly near the Bragg peak (BP), has led to the shift towards biological-based treatment planning. Proton RBE uncertainty has recently been reported as a possible cause for brainstem necrosis in pediatric patients treated with proton therapy. Despite this, in vivo studies have been limited due to the complexity of accurate delivery and absolute dosimetry. The purpose of this investigation was to create a precise and efficient method of treating the mouse spinal cord with various portions of the proton Bragg curve and to quantify associated uncertainties for the characterization of proton RBE. Mice were restrained in 3D printed acrylic boxes, shaped to their external contour, with a silicone insert extending down to mold around the mouse. Brass collimators were designed for parallel opposed beams to treat the spinal cord while shielding the brain and upper extremities of the animal. Up to six animals may be accommodated for simultaneous treatment within the restraint system. Two plans were generated targeting the cervical spinal cord, with either the entrance (ENT) or the BP portion of the beam. Dosimetric uncertainty was measured using EBT3 radiochromic film with a dose-averaged linear energy transfer (LETd) correction. Positional uncertainty was assessed by collecting a library of live mouse scans (n = 6 mice, two independent scans per mouse) and comparing the following dosimetric statistics from the mouse cervical spinal cord: Volume receiving 90% of the prescription dose (V90); mean dose to the spinal cord; and LETd. Film analysis results showed the dosimetric uncertainty to be ±1.2% and ±5.4% for the ENT and BP plans, respectively. Preliminary results from the mouse library showed the V90 to be 96.3 ± 4.8% for the BP plan. Positional uncertainty of the ENT plan was not measured due to the inherent robustness of that treatment plan. The proposed high-throughput mouse proton irradiation setup resulted in accurate dose delivery to mouse spinal cords positioned along the ENT and BP. Future directions include adapting the setup to account for weight fluctuations in mice undergoing fractionated irradiation.

Robust radiobiological optimization of ion beam therapy utilizing Monte Carlo and microdosimetric kinetic model.

To develop a Monte Carlo (MC)-based and robust ion beam therapy optimization system that separates the optimization algorithm from the relative biological effectiveness (RBE) modeling. Robustly optimized dose distributions were calculated and compared across three ion therapy beams (proton, helium, carbon). The effect of different averaging techniques in calculating RBE in mixed beams was also investigated. Ion particles were transported in TOPAS MC. The microdosimetric-kinetic model (MKM) parameter, saturation corrected specific energy ([Formula: see text]), was calculated with a customized MKM implementation in TOPAS MC. Intensity modulated ion therapy robust optimization was performed by a quasi-Newton iterative method based on dose-volume objective function. The robust optimization took setup and range uncertainties into account. In the present work, the biological dose for each individual spot was calculated, and then summed together to calculate total biological dose. In other published works, radiosensitive parameters, such as [Formula: see text], were first averaged over all beam spots within a mixed-beam field, after which biological dose was calculated using the averaged radiosensitive parameters. The difference between the two mixed-beam biological dose calculations was quantified. Robust plans were achieved with the three particle types. The effect of averaging [Formula: see text] depended on particle type. The difference between biological doses calculated with individual [Formula: see text] and averaged [Formula: see text] may be greater than 3% for a carbon beam. MC based radiobiological and robust optimization was made flexible to incorporate dose-volume histogram constraints and to be independent of RBE models. Iterative optimization with RBE models was feasible. Evaluation of the RBE calculation for mixed beam could be necessary if better accuracy was demanded.

Incorporation of Biologic Response Variance Modeling Into the Clinic: Limiting Risk of Brachial Plexopathy and Other Late Effects of Breast Cancer Proton Beam Therapy.

PURPOSE: The relative biologic effectiveness (RBE) rises with increasing linear energy transfer toward the end of proton tracks. Presently, there is no consensus on how RBE heterogeneity should be accounted for in breast cancer proton therapy treatment planning. Our purpose was to determine the dosimetric consequences of incorporating a brachial plexus (BP) biologic dose constraint and to describe other clinical implications of biologic planning. METHODS AND MATERIALS: We instituted a biologic dose constraint for the BP in the context of MC1631, a randomized trial of conventional versus hypofractionated postmastectomy intensity modulated proton therapy (IMPT). IMPT plans of 13 patients treated before the implementation of the biologic dose constraint (cohort A) were compared with IMPT plans of 38 patients treated on MC1631 after its implementation (cohort B) using (1) a commercially available Eclipse treatment planning system (RBE = 1.1); (2) an in-house graphic processor unit-based Monte Carlo physical dose simulation (RBE = 1.1); and (3) an in-house Monte Carlo biologic dose (MCBD) simulation that assumes a linear relationship between RBE and dose-averaged linear energy transfer (product of RBE and physical dose = biologic dose). RESULTS: Before implementation of a BP biologic dose constraint, the Eclipse mean BP D0.01 cm3 was 107%, and the MCBD estimate was 128% (ie, 64 Gy [RBE = biologic dose] in 25 fractions for a 50-Gy [RBE = 1.1] prescription), compared with 100.0% and 116.0%, respectively, after the implementation of the constraint. Implementation of the BP biologic dose constraint did not significantly affect clinical target volume coverage. MCBD plans predicted greater internal mammary node coverage and higher heart dose than Eclipse plans. CONCLUSIONS: Institution of a BP biologic dose constraint may reduce brachial plexopathy risk without compromising target coverage. MCBD plan evaluation provides valuable information to physicians that may assist in making clinical judgments regarding relative priority of target coverage versus normal tissue sparing.

Biologic Dose and Imaging Changes in Pediatric Brain Tumor Patients Receiving Spot Scanning Proton Therapy.

PURPOSE: To evaluate the incidence of imaging changes in our pediatric brain tumor population treated with spot-scanning proton therapy and analyze the spatial correlation of imaging changes with a novel biologic dose model. METHODS AND MATERIALS: All pediatric patients treated during the first year of our institution's experience who received a minimum treatment planning dose (TPD) of 5040 cGyE with available follow-up magnetic resonance imaging scans were selected for analysis. Posttreatment magnetic resonance imaging scans were fused with the treatment planning computed tomography. All T1 post-gadolinium enhancement, T2 fluid attenuated inversion recovery changes, TPD, and biologic dose (BD) volumes outside of the original gross tumor volume were contoured for analysis. RESULTS: Thirty patients were included in the analysis, 7 of whom developed posttreatment radiologic changes. The volumetric overlap of the T2 fluid attenuated inversion recovery changes and BD volumes was significantly greater than the overlap with the TPD volumes. Median volumetric overlaps of 85%, 18%, and 0% were observed with the BD105%, BD110%, and TPD105%, respectively. A nonsignificant increase in the volumetric overlap of the T1C+ changes and BD volumes was also observed. No correlation was observed between the total volume of BD110%, BD105%, or physical dose 105% and the development of imaging changes. CONCLUSIONS: Within our pediatric brain tumor population treated with spot-scanning proton therapy, our BD model demonstrated superior volumetric overlap with posttreatment T2 changes compared with the TPD model. Using a BD model in treatment planning for spot-scanning proton therapy may help avoid delivery of excessive BD to critical structures and may help minimize the risk of radiation-related late effects.

A linear relationship for the LET-dependence of Gafchromic EBT3 film in spot-scanning proton therapy.

Radiochromic film (RCF) is a valuable dosimetric tool, primarily due to its sub-millimeter spatial resolution. For accurate proton dosimetry, the dependence of film response on linear energy transfer (LET) must be characterized and calibrated. In this work, we characterized film under-response, or 'quenching', as a function of dose-weighted linear energy transfer (LETd) in several proton fields and established a simple, linear relationship with LETd. We performed measurements as a function of depth in a PMMA phantom irradiated by a spot-scanning proton beam. The fields had energies of 71.3 MeV, 71.3 MeV with filter, and 159.9 MeV. At each depth (measurements taken in depth step sizes of 0.5-1 mm in the Bragg peak), we measured dose with a PTW Markus ion chamber and EBT3 RCF. EBT3 under-response was characterized by the ratio of dose measured with film to that with ion chamber. LETd values for our experimental setup were calculated using in-house clinical Monte Carlo code. Measured film under-response increased with LETd, from approximately 10% under-response for LETd = 5 keV µm-1 to approximately 20% for LETd = 8 keV µm-1. The under-response for all measurements was plotted versus LETd. A linear fit to the data was performed, yielding a function for under-response, [Formula: see text], with respect to LETd: [Formula: see text]. Finally, the linear under-response relationship was applied to a film measurement within a spread-out Bragg peak (SOBP). Without correcting for LETd-dependence in the SOBP measurement, the discrepancy between film and Monte Carlo profiles was greater than 15% at the distal edge. With correction, the corrected film profile was within 2% and 1 mm of the Monte Carlo profile. RCF response depends on LETd, potentially under-responding by >15% in clinically-relevant scenarios. Therefore, it is insufficient to perform only a dose calibration; LET calibration is also necessary for accurate proton film dosimetry. The LETd-dependence of EBT3 can be described by a single, linear function over a range of clinically-relevant proton therapy LETd values.

A Monte-Carlo-based and GPU-accelerated 4D-dose calculator for a pencil beam scanning proton therapy system.

PURPOSE: The presence of respiratory motion during radiation treatment leads to degradation of the expected dose distribution, both for target coverage and healthy tissue sparing, particularly for techniques like pencil beam scanning proton therapy which have dynamic delivery systems. While tools exist to estimate this degraded four-dimensional (4D) dose, they typically have one or more deficiencies such as not including the particular effects from a dynamic delivery, using analytical dose calculations, and/or using nonphysical dose-accumulation methods. This work presents a clinically useful 4D-dose calculator that addresses each of these shortcomings. METHODS: To quickly compute the 4D dose, the three main tasks of the calculator were run on graphics processing units (GPUs). These tasks were (a) simulating the delivery of the plan using measured delivery parameters to distribute the plan amongst 4DCT phases characterizing the patient breathing, (b) using an in-house Monte Carlo simulation (MC) dose calculator to determine the dose delivered to each breathing phase, and (c) accumulating the doses from the various breathing phases onto a single phase for evaluation. The accumulation was performed by individually transferring the energy and mass of dose-grid subvoxels, a technique that models the transfer of dose in a more physically realistic manner. The calculator was run on three test cases, with lung, esophagus, and liver targets, respectively, to assess the various uncertainties in the beam delivery simulation as well as to characterize the dose-accumulation technique. RESULTS: Four-dimensional doses were successfully computed for the three test cases with computation times ranging from 4-6 min on a server with eight NVIDIA Titan X graphics cards; the most time-consuming component was the MC dose engine. The subvoxel-based dose-accumulation technique produced stable 4D-dose distributions at subvoxel scales of 0.5-1.0 mm without impairing the total computation time. The uncertainties in the beam delivery simulation led to moderate variations of the dose-volume histograms for these cases; the variations were reduced by implementing repainting or phase-gating motion mitigation techniques in the calculator. CONCLUSIONS: A MC-based and GPU-accelerated 4D-dose calculator was developed to estimate the effects of respiratory motion on pencil beam scanning proton therapy treatments. After future validation, the calculator could be used to assess treatment plans and its quick runtime would make it easily usable in a future 4D-robust optimization system.

A robust intensity modulated proton therapy optimizer based on Monte Carlo dose calculation.

PURPOSE: Accuracy of dose calculation models and robustness under various uncertainties are key factors influencing the quality of intensity modulated proton therapy (IMPT) plans. To mitigate the effects of uncertainties and to improve the dose calculation accuracy, an all-scenario robust IMPT optimization based on accurate Monte Carlo (MC) dose calculation was developed. METHODS: In the all-scenario robust IMPT optimization, dose volume histograms (DVHs) were computed for the nominal case and for each uncertainty scenario. All scenarios were weighted by DVH values dynamically throughout optimization iterations. In contrast, probabilistic approach weighted scenarios with fixed scenario weights and worst case optimizations picked one single scenario - the worst scenario for each iteration. Uncertainties in patient setup and proton range were considered in all clinical cases studied. Graphics processing unit (GPU) computation was employed to reduce the computational time in both the MC dose calculation and optimization stages. A previously published adaptive quasi-Newton method for proton optimization was extended to include robustness. To validate the all-scenario algorithm extension, it was compared with the single scenario optimization target volume (OTV) based approach in clinical cases of three different disease sites. Additional comparisons with worst case optimization methods were conducted to evaluate the performance of the all-scenario robust optimization against other robust optimizations. RESULTS: The all-scenario robust IMPT optimization spared organs at risk (OARs) better than the OTV-based method while maintaining target coverage and improving the robustness of targets and OARs. Compared with composite and voxel-wise worst case optimization, the all-scenario robust optimization converged faster, and arrived at solutions of tighter DVH robustness spread, better target coverage and lower OAR dose. CONCLUSION: An all-scenario robust IMPT treatment planning system was developed using an adaptive quasi-Newton optimization method. The optimization system was GPU-accelerated and based on MC dose calculation. Improved performance was observed in clinical cases when compared with worst case optimization methods.

Neutron shielding for a new projected proton therapy facility: A Geant4 simulation study.

In this work, we used the Monte Carlo-based Geant4 simulation toolkit to calculate the ambient dose equivalents due to the secondary neutron field produced in a new projected proton therapy facility. In particular the facility geometry was modeled in Geant4 based on the CAD design. Proton beams were originated with an energy of 250MeV in the gantry rooms with different angles with respect to the patient; a fixed 250MeV proton beam was also modeled. The ambient dose equivalent was calculated in several locations of interest inside and outside the facility, for different scenarios. The simulation results were compared qualitatively to previous work on an existing facility bearing some similarities with the design under study, showing that the ambient dose equivalent ranges obtained are reasonable. The ambient dose equivalents, calculated by means of the Geant4 simulation, were compared to the Australian regulatory limits and showed that the new facility will not pose health risks for the public or staff, with a maximum equivalent dose rate equal to 7.9mSv/y in the control rooms and maze exit areas and 1.3·10-1mSv/y close to the walls, outside the facility, under very conservative assumptions. This work represents the first neutron shielding verification analysis of a new projected proton therapy facility and, as such, it may serve as a new source of comparison and validation for the international community, besides confirming the viability of the project from a radioprotection point of view.

Clinically Applicable Monte Carlo-based Biological Dose Optimization for the Treatment of Head and Neck Cancers With Spot-Scanning Proton Therapy.

PURPOSE: Our aim is to demonstrate the feasibility of fast Monte Carlo (MC)-based inverse biological planning for the treatment of head and neck tumors in spot-scanning proton therapy. METHODS AND MATERIALS: Recently, a fast and accurate graphics processor unit (GPU)-based MC simulation of proton transport was developed and used as the dose-calculation engine in a GPU-accelerated intensity modulated proton therapy (IMPT) optimizer. Besides dose, the MC can simultaneously score the dose-averaged linear energy transfer (LETd), which makes biological dose (BD) optimization possible. To convert from LETd to BD, a simple linear relation was assumed. By use of this novel optimizer, inverse biological planning was applied to 4 patients, including 2 small and 1 large thyroid tumor targets, as well as 1 glioma case. To create these plans, constraints were placed to maintain the physical dose (PD) within 1.25 times the prescription while maximizing target BD. For comparison, conventional intensity modulated radiation therapy (IMRT) and IMPT plans were also created using Eclipse (Varian Medical Systems) in each case. The same critical-structure PD constraints were used for the IMRT, IMPT, and biologically optimized plans. The BD distributions for the IMPT plans were obtained through MC recalculations. RESULTS: Compared with standard IMPT, the biologically optimal plans for patients with small tumor targets displayed a BD escalation that was around twice the PD increase. Dose sparing to critical structures was improved compared with both IMRT and IMPT. No significant BD increase could be achieved for the large thyroid tumor case and when the presence of critical structures mitigated the contribution of additional fields. The calculation of the biologically optimized plans can be completed in a clinically viable time (<30 minutes) on a small 24-GPU system. CONCLUSIONS: By exploiting GPU acceleration, MC-based, biologically optimized plans were created for small-tumor target patients. This optimizer will be used in an upcoming feasibility trial on LETd painting for radioresistant tumors.

Clinical Implementation of a Proton Dose Verification System Utilizing a GPU Accelerated Monte Carlo Engine.

PURPOSE: To develop a clinical infrastructure that allows for routine Monte Carlo dose calculation verification of spot scanning proton treatment plans and includes a simple biological model to aid in normal tissue protection. MATERIALS AND METHODS: A graphical processing unit accelerated Monte Carlo dose engine was used as the calculation engine for dose verification on spot scanning proton plans. An infrastructure was built around this engine that allows for seamless exporting of treatment plans from the treatment planning system and importing of dose distribution from the Monte Carlo calculation via DICOM (digital imaging and communications in medicine). An easy-to-use Web-based interface was developed so that the application could be run from any computer. In addition to the standard relative biological effectiveness = 1.1 for proton therapy, a simple linear equation dependent on dose-weighted linear energy transfer was included. This was used to help detect possible high biological dose in critical structures. RESULTS: More than 270 patients were treated at our proton center in the first year of operation. Because most plans underwent multiple iterations before final approval, more than 1000 plans have been run through the system from multiple users with minimal downtime. The average time from plan export to importing of the Monte Carlo doses was less than 15 minutes. Treatment plans have been modified based on the nominal Monte Carlo dose or the biological dose. CONCLUSION: Monte Carlo dose calculation verification of spot scanning proton treatment plans is feasible in a clinical environment. The 3-dimensional dose verification, particularly near heterogeneities, has resulted in plan modifications. The biological dose data provides actionable feedback for end of range effects, especially in pediatric patients.

A GPU-accelerated and Monte Carlo-based intensity modulated proton therapy optimization system.

PURPOSE: Conventional spot scanning intensity modulated proton therapy (IMPT) treatment planning systems (TPSs) optimize proton spot weights based on analytical dose calculations. These analytical dose calculations have been shown to have severe limitations in heterogeneous materials. Monte Carlo (MC) methods do not have these limitations; however, MC-based systems have been of limited clinical use due to the large number of beam spots in IMPT and the extremely long calculation time of traditional MC techniques. In this work, the authors present a clinically applicable IMPT TPS that utilizes a very fast MC calculation. METHODS: An in-house graphics processing unit (GPU)-based MC dose calculation engine was employed to generate the dose influence map for each proton spot. With the MC generated influence map, a modified least-squares optimization method was used to achieve the desired dose volume histograms (DVHs). The intrinsic CT image resolution was adopted for voxelization in simulation and optimization to preserve spatial resolution. The optimizations were computed on a multi-GPU framework to mitigate the memory limitation issues for the large dose influence maps that resulted from maintaining the intrinsic CT resolution. The effects of tail cutoff and starting condition were studied and minimized in this work. RESULTS: For relatively large and complex three-field head and neck cases, i.e., >100,000 spots with a target volume of ∼ 1000 cm(3) and multiple surrounding critical structures, the optimization together with the initial MC dose influence map calculation was done in a clinically viable time frame (less than 30 min) on a GPU cluster consisting of 24 Nvidia GeForce GTX Titan cards. The in-house MC TPS plans were comparable to a commercial TPS plans based on DVH comparisons. CONCLUSIONS: A MC-based treatment planning system was developed. The treatment planning can be performed in a clinically viable time frame on a hardware system costing around 45,000 dollars. The fast calculation and optimization make the system easily expandable to robust and multicriteria optimization.

A simplified methodology to produce Monte Carlo dose distributions in proton therapy.

The purpose of this study was to develop a simplified methodology that will produce Monte Carlo (MC) dose distribution for proton therapy which can be used as a clinical aid in determining the adequacy of proton plans produced from the treatment planning system (TPS). The Geant4 Monte Carlo toolkit was used for all simulations. The geometry of the double scatter nozzle in the simulation was a simplification of the treatment nozzle. The proton source was modeled as discrete energy layers, each with a unique energy distribution and weighting factor. The simplified MC system was designed to give the same dose distribution as the measured data used to commission the TPS. After the simplified MC system was finalized, a series of verification comparisons were made between it, measurements, and the clinically used TPS. Comparisons included the lateral profile of a stair-shaped compensator that simulated a sharp lateral heterogeneity and depth-dose measurements through heterogeneous materials. The simplified MC system matched measurements to within 2% or 2 mm for all commissioning data under investigation; moreover, the distal edge and lateral penumbra was within 1 mm of the measurements. The simplified MC system was able to better reproduce the measured profiles for a stair-shaped compensator than the TPS. Both MC and TPS matched the measured depth dose through heterogeneous materials to within 2% or 2 mm. The simplified MC system was straightforward to implement, and produced accurate results when compared to measurements. Therefore, it holds promise as a clinically useful methodology to validate the relative dose distribution of patient treatment plans produced by the treatment planning systems.

Effects of minimum monitor unit threshold on spot scanning proton plan quality.

PURPOSE: To investigate the influence of the minimum monitor unit (MU) on the quality of clinical treatment plans for scanned proton therapy. METHODS: Delivery system characteristics limit the minimum number of protons that can be delivered per spot, resulting in a min-MU limit. Plan quality can be impacted by the min-MU limit. Two sites were used to investigate the impact of min-MU on treatment plans: pediatric brain tumor at a depth of 5-10 cm; a head and neck tumor at a depth of 1-20 cm. Three-field, intensity modulated spot scanning proton plans were created for each site with the following parameter variations: min-MU limit range of 0.0000-0.0060; and spot spacing range of 2-8 mm. Comparisons were based on target homogeneity and normal tissue sparing. For the pediatric brain, two versions of the treatment planning system were also compared to judge the effects of the min-MU limit based on when it is accounted for in the optimization process (Eclipse v.10 and v.13, Varian Medical Systems, Palo Alto, CA). RESULTS: The increase of the min-MU limit with a fixed spot spacing decreases plan quality both in homogeneous target coverage and in the avoidance of critical structures. Both head and neck and pediatric brain plans show a 20% increase in relative dose for the hot spot in the CTV and 10% increase in key critical structures when comparing min-MU limits of 0.0000 and 0.0060 with a fixed spot spacing of 4 mm. The DVHs of CTVs show min-MU limits of 0.0000 and 0.0010 produce similar plan quality and quality decreases as the min-MU limit increases beyond 0.0020. As spot spacing approaches 8 mm, degradation in plan quality is observed when no min-MU limit is imposed. CONCLUSIONS: Given a fixed spot spacing of ≤4 mm, plan quality decreases as min-MU increased beyond 0.0020. The effect of min-MU needs to be taken into consideration while planning proton therapy treatments.

Optimizing mini-ridge filter thickness to reduce proton treatment times in a spot-scanning synchrotron system.

PURPOSE: Study the contributors to treatment time as a function of Mini-Ridge Filter (MRF) thickness to determine the optimal choice for breath-hold treatment of lung tumors in a synchrotron-based spot-scanning proton machine. METHODS: Five different spot-scanning nozzles were simulated in TOPAS: four with MRFs of varying maximal thicknesses (6.15-24.6 mm) and one with no MRF. The MRFs were designed with ridges aligned along orthogonal directions transverse to the beam, with the number of ridges (4-16) increasing with MRF thickness. The material thickness given by these ridges approximately followed a Gaussian distribution. Using these simulations, Monte Carlo data were generated for treatment planning commissioning. For each nozzle, standard and stereotactic (SR) lung phantom treatment plans were created and assessed for delivery time and plan quality. RESULTS: Use of a MRF resulted in a reduction of the number of energy layers needed in treatment plans, decreasing the number of synchrotron spills needed and hence the treatment time. For standard plans, the treatment time per field without a MRF was 67.0 ± 0.1 s, whereas three of the four MRF plans had treatment times of less than 20 s per field; considered sufficiently low for a single breath-hold. For SR plans, the shortest treatment time achieved was 57.7 ± 1.9 s per field, compared to 95.5 ± 0.5 s without a MRF. There were diminishing gains in time reduction as the MRF thickness increased. Dose uniformity of the PTV was comparable across all plans; however, when the plans were normalized to have the same coverage, dose conformality decreased with MRF thickness, as measured by the lung V20%. CONCLUSIONS: Single breath-hold treatment times for plans with standard fractionation can be achieved through the use of a MRF, making this a viable option for motion mitigation in lung tumors. For stereotactic plans, while a MRF can reduce treatment times, multiple breath-holds would still be necessary due to the limit imposed by the proton extraction time. To balance treatment time and normal tissue dose, the ideal MRF choice was shown to be the thinnest option that is able to achieve the desired breath-hold timing.

Design and characterization of an economical (192)Ir hemi-brain small animal irradiator.

PURPOSE: To describe the design and dosimetric characterization of a simple and economical small animal irradiator. MATERIALS AND METHODS: A high dose rate (HDR) (192)Ir brachytherapy source from a commercially available afterloader was used with a 1.3 cm thick tungsten collimator to provide sharp beam penumbra suitable for hemi-brain irradiation of mice. The unit was equipped with continuous gas anesthesia to allow robust animal immobilization. Dosimetric characterization of the device was performed with Gafchromic film measurements. RESULTS: The tungsten collimator provided a sharp penumbra suitable for hemi-brain irradiation, and dose rates on the order of 200 cGy/minute were achieved. The sharpness of the penumbra attainable with this device compares favorably to those measured experimentally for 6 MV photons, and 6 and 20 MeV electron beams from a linear accelerator, and was comparable to those measured for a 300 kVp orthovoltage beam and a Monte Carlo simulated 90 MeV proton beam. CONCLUSIONS: Due to its simplicity and low cost, the apparatus described is an attractive alternative for small animal irradiation experiments requiring steep dose gradients.

Proton therapy dose distribution comparison between Monte Carlo and a treatment planning system for pediatric patients with ependymoma.

PURPOSE: Compare dose distributions for pediatric patients with ependymoma calculated using a Monte Carlo (MC) system and a clinical treatment planning system (TPS). METHODS: Plans from ten pediatric patients with ependymoma treated using double scatter proton therapy were exported from the TPS and calculated in our MC system. A field by field comparison of the distal edge (80% and 20%), distal fall off (80% to 20%), field width (50% to 50%), and penumbra (80% to 20%) were examined. In addition, the target dose for the full plan was compared. RESULTS: For the 32 fields from the 10 patients, the average differences of distal edge at 80% and 20% on central axis between MC and TPS are -1.9 ± 1.7 mm (p < 0.001) and -0.6 ± 2.3 mm (p = 0.13), respectively. Excluding the fields that ranged out in bone or an air cavity, the 80% difference was -0.9 ± 1.7 mm (p = 0.09). The negative value indicates that MC was on average shallower than TPS. The average difference of the 63 field widths of the 10 patients is -0.7 ± 1.0 mm (p < 0.001), negative indicating on average the MC had a smaller field width. On average, the difference in the penumbra was 2.3 ± 2.1 mm (p < 0.001). The average of the mean clinical target volume dose differences is -1.8% (p = 0.001), negative indicating a lower dose for MC. CONCLUSIONS: Overall, the MC system and TPS gave similar results for field width, the 20% distal edge, and the target coverage. For the 80% distal edge and lateral penumbra, there was slight disagreement; however, the difference was less than 2 mm and occurred primarily in highly heterogeneous areas. These differences highlight that the TPS dose calculation cannot be automatically regarded as correct.

Novel assessment of renal motion in children as measured via four-dimensional computed tomography.

OBJECTIVES: Abdominal intensity-modulated radiation therapy and proton therapy require quantification of target and organ motion to optimize localization and treatment. Although addressed in adults, there is no available literature on this issue in pediatric patients. We assessed physiologic renal motion in pediatric patients. METHODS AND MATERIALS: Twenty free-breathing pediatric patients at a median age of 8 years (range, 2-18 years) with intra-abdominal tumors underwent computed tomography simulation and four-dimensional computed tomography acquisition (slice thickness, 3 mm). Kidneys and diaphragms were contoured during eight phases of respiration to estimate center-of-mass motion. We quantified center of kidney mass mobility vectors in three dimensions: anteroposterior (AP), mediolateral (ML), and superoinferior (SI). RESULTS: Kidney motion decreases linearly with decreasing age and height. The 95% confidence interval for the averaged minima and maxima of renal motion in children younger than 9 years was 5-9 mm in the ML direction, 4-11 mm in the AP direction, and 12-25 mm in the SI dimension for both kidneys. In children older than 9 years, the same confidence interval reveals a widening range of motion that was 5-16 mm in the ML direction, 6-17 mm in the AP direction, and 21-52 mm in the SI direction. Although not statistically significant, renal motion correlated with diaphragm motion in older patients. The correlation between diaphragm motion and body mass index was borderline (r = 0.52, p = 0.0816) in younger patients. CONCLUSIONS: Renal motion is age and height dependent. Measuring diaphragmatic motion alone does not reliably quantify pediatric renal motion. Renal motion in young children ranges from 5 to 25 mm in orientation-specific directions. The vectors of motion range from 5 to 52 mm in older children. These preliminary data represent novel analyses of pediatric intra-abdominal organ motion.