Bues, Martin

Abstract Purpose To evaluate the accuracy of the RayStation Monte Carlo dose engine (RayStation MC) in modeling small‐field block apertures in proton pencil beam scanning. Furthermore, we evaluate the suitability of MCsquare as a second check for RayStation MC. Methods We have enhanced MCsquare to model block apertures. To test the accuracy of both RayStation MC and the newly enhanced MCsquare, we compare the dose predictions of each to in‐water dose measurements obtained using diode detectors and radiochromic film. Nine brass apertures with openings of 1, 2, 3, 4, and 5 cm and either 2 cm or 4 cm thickness were used in the irradiation of a water phantom. Two measurement setups were used, one with a range shifter and 119.7 MeV proton beam energy and the other with no range shifter and 147 MeV proton beam energy. To further test the validity of RayStation MC and MCsquare in modeling block apertures and to evaluate MCsquare as a second check tool, 10 small‐field (average target volume 8.3 cm 3 ) patient treatment plans were calculated by each dose engine followed by a statistical comparison. Results Comparing to the absolute dose measurements in water, RayStation MC differed by 1.2% ± 1.0% while MCsquare differed by −1.8% ± 3.7% in the plateau region of a pristine Bragg peak. Compared to the in‐water film measurements, RayStation MC and MCsquare both performed well with an average 2D‐3D gamma passing rate of 99.4% and 99.7% (3%/3 mm), respectively. A t ‐test comparing the agreement with the film measurements between RayStation MC and MCsquare suggested that the relative spatial dose distributions calculated by MCsquare and RayStation MC were statistically indistinguishable. Directly comparing the dose calculations between MCsquare and RayStation MC over 10 patients resulted in an average 3D‐3D gamma passing rates of 98.5% (3%/3 mm) and 94.1% (2%/2 mm), respectively. Conclusion The validity of RayStation MC algorithm for use with patient‐specific apertures has been expanded to include small apertures. MCsquare has been enhanced to model apertures and was found to be an adequate second check of RayStation MC in this scenario.

AbstractPurposeDue to the employment of quadratic programming using soft constraints to implement dose volume constraints and the “trial‐and‐error” procedure needed to achieve a clinically acceptable plan, conventional dose volume constraints (upper limit) are not adequately effective in controlling small and isolated hot spots in the dose/linear energy transfer (LET) distribution. Such hot spots can lead to adverse events. In order to mitigate the risk of brain necrosis, one of the most clinically significant adverse events in patients receiving intensity‐modulated proton therapy (IMPT) for base of skull (BOS) cancer, we propose per‐voxel constraints to minimize hot spots in LET‐guided robust optimization.Methods and materialsTen BOS cancer patients treated with IMPT were carefully selected by meeting one of the following conditions: (1) diagnosis of brain necrosis during follow‐up; and (2) considered high risk for brain necrosis by not meeting dose constraints to the brain. An optimizing structure (BrainOPT) and an evaluating structure (BrainROI) that both contained the aforementioned hot dose regions in the brain were generated for optimization and evaluation, respectively. Two plans were generated for every patient: one using conventional dose‐only robust optimization, the other using LET‐guided robust optimization. The impact of LET was integrated into the optimization via a term of extra biological dose (xBD). A novel optimization tool of per‐voxel constraints to control small and isolated hot spots in either the dose, LET, or combined (dose/LET) distribution was developed and used to minimize dose/LET hot spots of the selected structures. Indices from dose‐volume histogram (DVH) and xBD dose‐volume histogram (xBDVH) were used in the plan evaluation. A newly developed tool of the dose‐LET‐volume histogram (DLVH) was also adopted to illustrate the underlying mechanism. Wilcoxon signed‐rank test was used for statistical comparison of the DVH and xBDVH indices between the conventional dose‐only and the LET‐guided robustly optimized plans.ResultsPer‐voxel constraints effectively and efficiently minimized dose hot spots in both dose‐only and LET‐guided robust optimization and LET hot spots in LET‐guided robust optimization. Compared to the conventional dose‐only robust optimization, the LET‐guided robust optimization could generate plans with statistically lower xBD hot spots in BrainROI (VxBD,50 Gy[RBE], p = 0.009; VxBD,60 Gy[RBE], p = 0.025; xBD1cc, p = 0.017; xBD2cc, p = 0.022) with comparable dose coverage, dose hot spots in the target, and dose hot spots in BrainROI. DLVH analysis indicated that LET‐guided robust optimization could either reduce LET at the same dose level or redistribute high LET from high dose regions to low dose regions.ConclusionPer‐voxel constraint is a powerful tool to minimize dose/LET hot spots in IMPT. The LET‐guided robustly optimized plans outperformed the conventional dose‐only robustly optimized plans in terms of xBD hot spots control.

AbstractPurposeTo measure diode sensitivity degradation (DSD) induced by cumulative proton dose delivered to a commercial daily quality assurance (QA) device.MethodsAt our institution, six Daily QA 3 (DQA3, Sun Nuclear Corporation, Melbourne, FL, USA) devices have been used for daily proton pencil beam scanning QA in four proton gantry rooms over a span of 4 years. DQA3 diode counts were cross‐calibrated using a homogenous field with a known dose of 1 Gy. The DSD rate (ΔR%/100 Gy) was calculated using linear regression on time‐series plots of diode counts and an estimate of cumulative dose per year based on the cross‐calibration. The effect of DSD on daily QA spot position measurements was quantified by converting DSD to baseline spot position shift.ResultsThe average dose delivered to the four inner DQA3 diodes was 104 ± 5 Gy/year, and the rate of DSD was ‐5.1% ± 1.0/100 Gy with the exception of one DQA3 device that had a significantly higher rate of DSD (–12%/100 Gy). The R2s of the linear fit to time‐series plots were between 0.92 and 0.98. The DSD rates were not constant but decreases with accumulated doses. The four center diodes, which received 40% of the cumulative dose received by inner diodes, had a DSD rate of –7.2% ± 0.9/100 Gy. For our daily QA program, 1 year of DSD was equivalent to a 0.2 mm shift in spot position.ConclusionsThe DSD rate of DQA3 diodes determined by long‐term proton daily QA data was about –5%/100 Gy, which is more than 10 times greater than the reported DSD rate from photon irradiation. DQA3 diodes may be used for daily proton QA programs, provided that they are recalibrated at an appropriate frequency that should be determined specifically for different daily QA programs.

AbstractPurposeTo validate breast tissue expander metallic port (MP) models in a commercial treatment planning system (TPS) in proton pencil beam scanning (PBS) treatments for breast cancer patients with breast tissue expanders.Methods and materialsThree types of MPs taken out of a Mentor CPX4, a Natrelle 133, and a PMT Integra breast tissue expanders and a 650 cc saline filled Mentor CPX4 expander were placed on top of acrylic slabs, and scanned using a Siemens Somatom Definition AS Open RT CT scanner. Structure templates for each of the MPs were designed within Eclipse TPS. The CT numbers for the metallic parts were overridden to reflect measured or calculated relative proton stopping powers (RPSPs). Mock targets were contoured in acrylic to represent postmastectomy chest‐wall radiation therapy (PMRT) targets. Plans with different beam incident angles were optimized using the Eclipse TPS to deliver uniform prescription dose to the target using Hitachi Probeat‐V PBS beams. Eclipse calculated doses and an in‐house Monte Carlo (MC) code calculated doses were compared to the measured Gafchromic EBT3 film doses in acrylic.ResultsTPS/MC and film dose comparison results showed that (1) 3%/2 mm/10% threshold Gamma pass rates were better than 90.8% in the acrylic target region for all plans; (2) comparing TPS and film doses for the individual beam plans in the MP dose shadow areas, the area with dose difference above 5% ([ΔA] 5%) ranged from 1.1 to 5.0 cm2, and the maximum dose difference ([ΔD] 0.01 cm2) ranged from 12.5% to 25.0%; (3) comparing MC and film doses for the individual beam plans in the MP dose shadow areas, the (ΔA) 5% varied from 1.1 to 2.9 cm2 and (ΔD) 0.01 cm2 varied from 8.5% to 24.2%; (4) for a plan composed of three individual beams treating through the Mentor CPX4 expander, the TPS (ΔA) 5% was less than 0.13 cm2, and the (ΔD) 0.01 cm2 was less than 6% in the MP dose shadow areas.ConclusionsIt is feasible to treat patients with tissue expanders using multiple PBS beams using a structure template with CT number overridden to represent the measured/calculated RPSP for MPs for PBS treatment planning. MC dose was more accurate than analytical dose in the areas with high dose gradient caused by the density heterogeneity of the breast tissue expander MPs.

Abstract Purpose The multiple energy extraction (MEE) delivery technique for synchrotron‐based proton delivery systems reduces beam delivery time by decelerating the beam multiple times during one accelerator spill, but this might cause additional plan quality degradation due to intrafractional motion. We seek to determine whether MEE causes significantly different plan quality degradation compared to single energy extraction (SEE) for lung cancer treatments due to the interplay effect. Methods Ten lung cancer patients treated with IMPT at our institution were nonrandomly sampled based on a representative range of tumor motion amplitudes, tumor volumes, and respiratory periods. Dose‐volume histogram (DVH) indices from single‐fraction SEE and MEE four‐dimensional (4D) dynamic dose distributions were compared using the Wilcoxon signed‐rank test. Distributions of monitor units (MU) to breathing phases were investigated for features associated with plan quality degradation. SEE and MEE DVH indices were compared in fractionated deliveries of the worst‐case patient treatment scenario to evaluate the impact of fractionation. Results There were no clinically significant differences in target mean dose, target dose conformity, or dose to organs‐at‐risk between SEE and MEE in single‐fraction delivery. Three patients had significantly worse dose homogeneity with MEE compared to SEE (single‐fraction mean D 5% ‐D 95% increased by up to 9.6% of prescription dose), and plots of MU distribution to breathing phases showed synchronization patterns with MEE but not SEE. However, after 30 fractions the patient in the worst‐case scenario had clinically acceptable target dose homogeneity and coverage with MEE (mean D 5% –D 95% increased by 1% compared to SEE). Conclusions For some patients with breathing periods close to the mean spill duration, MEE resulted in significantly worse single‐fraction target dose homogeneity compared to SEE due to the interplay effect. However, this was mitigated by fractionation, and target dose homogeneity and coverage were clinically acceptable after 30 fractions with MEE.

AbstractPurposeTo demonstrate that variation in chemical composition has a negligible effect on the mapping curve from relative electron density (RED) to proton stopping power ratio (SPR), and to establish the theoretical framework of using Megavoltage (MV) computed tomography (CT), instead of kilovoltage (kV) dual energy CT, to accurately estimate proton SPR.MethodsA simulation study was performed to evaluate the effect of chemical composition variation on kVCT number and proton SPR. The simulation study involved both reference and simulated human tissues. The reference human tissues, together with their physical densities and chemical compositions, came from the ICRP publication 23. The simulated human tissues were created from the reference human tissues assuming that elemental percentage weight followed a Gaussian distribution. For all tissues, kVCT number and proton SPR were obtained through (a) theoretical calculation from tissue’s physical density and chemical composition which served as the ground truth, and (b) estimation from RED using the calibration curves established from the stoichiometric method. Deviations of the estimated values from the calculated values were quantified as errors in using RED to estimate kVCT number and proton SPR.ResultsGiven a chemical composition variation of 5% (1σ) of the nominal percentage weights, the total estimation error of using RED to estimate kVCT number was 0.34%, 0.62%, and 0.77% and the total estimation error of using RED to estimate proton SPR was 0.30%, 0.22%, and 0.16% for fat tissues, non‐fat soft tissues and bone tissues, respectively.ConclusionChemical composition had a negligible effect on the method of using RED to determine proton SPR. RED itself is sufficient to accurately determine proton SPR. MVCT number maintains a superb linear relationship with RED because it is highly dominated by Compton scattering. Therefore, MVCT has great potential in reducing the proton range uncertainty.

Proton therapy is an expanding radiotherapy modality in the United States and worldwide. With the number of proton therapy centers treating patients increasing, so does the need for consistent, high‐quality clinical commissioning practices. Clinical commissioning encompasses the entire proton therapy system's multiple components, including the treatment delivery system, the patient positioning system, and the image‐guided radiotherapy components. Also included in the commissioning process are the x‐ray computed tomography scanner calibration for proton stopping power, the radiotherapy treatment planning system, and corresponding portions of the treatment management system. This commissioning report focuses exclusively on intensity‐modulated scanning systems, presenting details of how to perform the commissioning of the proton therapy and ancillary systems, including the required proton beam measurements, treatment planning system dose modeling, and the equipment needed.

Purpose Intensity‐modulated proton therapy (IMPT) is sensitive to uncertainties from patient setup and proton beam range, as well as interplay effect. In addition, respiratory motion may vary from cycle to cycle, and also from day to day. These uncertainties can severely degrade the original plan quality and potentially affect patient’s outcome. In this work, we developed a new tool to comprehensively consider the impact of all these uncertainties and provide plan robustness evaluation under them. Methods We developed a comprehensive plan robustness evaluation tool that considered both uncertainties from patient setup and proton beam range, as well as respiratory motion simultaneously. To mimic patients' respiratory motion, the time spent in each phase was randomly sampled based on patient‐specific breathing pattern parameters as acquired during the four‐dimensional (4D)‐computed tomography (CT) simulation. Spots were then assigned to one specific phase according to the temporal relationship between spot delivery sequence and patients’ respiratory motion. Dose in each phase was calculated by summing contributions from all the spots delivered in that phase. The final 4D dynamic dose was obtained by deforming all doses in each phase to the maximum exhalation phase. Three hundred (300) scenarios (10 different breathing patterns with 30 different setup and range uncertainty scenario combinations) were calculated for each plan. The dose‐volume histograms (DVHs) band method was used to assess plan robustness. Benchmarking the tool as an application’s example, we compared plan robustness under both three‐dimensional (3D) and 4D robustly optimized IMPT plans for 10 nonrandomly selected patients with non‐small cell lung cancer. Results The developed comprehensive plan robustness tool had been successfully applied to compare the plan robustness between 3D and 4D robustly optimized IMPT plans for 10 lung cancer patients. In the presence of interplay effect with uncertainties considered simultaneously, 4D robustly optimized plans provided significantly better CTV coverage (D 95% , P = 0.002), CTV homogeneity (D 5% ‐D 95% , P = 0.002) with less target hot spots (D 5% , P = 0.002), and target coverage robustness (CTV D 95% bandwidth, P = 0.004) compared to 3D robustly optimized plans. Superior dose sparing of normal lung (lung D mean , P = 0.020) favoring 4D plans and comparable normal tissue sparing including esophagus, heart, and spinal cord for both 3D and 4D plans were observed. The calculation time for all patients included in this study was 11.4 ± 2.6 min. Conclusion A comprehensive plan robustness evaluation tool was successfully developed and benchmarked for plan robustness evaluation in the presence of interplay effect, setup and range uncertainties. The very high efficiency of this tool marks its clinical adaptation, highly practical and versatile nature, including possible real‐time intra‐fractional interplay effect evaluation as a potential application for future use.

PurposeTo commission an open source Monte Carlo (MC) dose engine, “MCsquare” for a synchrotron‐based proton machine, integrate it into our in‐house C++‐based I/O user interface and our web‐based software platform, expand its functionalities, and improve calculation efficiency for intensity‐modulated proton therapy (IMPT).MethodsWe commissioned MCsquare using a double Gaussian beam model based on in‐air lateral profiles, integrated depth dose of 97 beam energies, and measurements of various spread‐out Bragg peaks (SOBPs). Then we integrated MCsquare into our C++‐based dose calculation code and web‐based second check platform “DOSeCHECK.” We validated the commissioned MCsquare based on 12 different patient geometries and compared the dose calculation with a well‐benchmarked GPU‐accelerated MC (gMC) dose engine. We further improved the MCsquare efficiency by employing the computed tomography (CT) resampling approach. We also expanded its functionality by adding a linear energy transfer (LET)‐related model‐dependent biological dose calculation.ResultsDifferences between MCsquare calculations and SOBP measurements were <2.5% (<1.5% for ~85% of measurements) in water. The dose distributions calculated using MCsquare agreed well with the results calculated using gMC in patient geometries. The average 3D gamma analysis (2%/2 mm) passing rates comparing MCsquare and gMC calculations in the 12 patient geometries were 98.0 ± 1.0%. The computation time to calculate one IMPT plan in patients’ geometries using an inexpensive CPU workstation (Intel Xeon E5‐2680 2.50 GHz) was 2.3 ± 1.8 min after the variable resolution technique was adopted. All calculations except for one craniospinal patient were finished within 3.5 min.ConclusionsMCsquare was successfully commissioned for a synchrotron‐based proton beam therapy delivery system and integrated into our web‐based second check platform. After adopting CT resampling and implementing LET model‐dependent biological dose calculation capabilities, MCsquare will be sufficiently efficient and powerful to achieve Monte Carlo‐based and LET‐guided robust optimization in IMPT, which will be done in the future studies.

PurposeThe dose‐averaged linear energy transfer (LETd) for intensity‐modulated proton therapy (IMPT) calculated by one‐dimensional (1D) analytical models deviates from more accurate but time‐consuming Monte Carlo (MC) simulations. We developed a fast hybrid three‐dimensional (3D) analytical LETd calculation that is more accurate than 1D analytical model.MethodsWe used the Geant4 MC code to generate 3D LETd distributions of monoenergetic proton beams in water for all energies and used a customized error function to fit the LETd lateral profiles at various depths to the MC simulation. The 3D LETd calculation kernel was a lookup table of these fitted coefficients, and LETd was determined directly from spot energies and voxel coordinates during analytical dose calculations. We validated our new method by comparing the calculated LETd distributions to MC results using 3D Gamma index analysis with 3%/2 mm criteria in 12 patient geometries. The significance of the improvement in Gamma index analysis passing rates over the 1D analytical model was determined using the Wilcoxon rank‐sum test.ResultsThe passing rate of 3D Gamma analysis comparing LETd distributions from the hybrid 3D method and the 1D method to MC simulations was significantly improved from 94.0% ± 2.5% to 98.0% ± 1.0% (P = 0.0003). The typical time to calculate dose and LETd simultaneously using an Intel Xeon E5‐2680 2.50 GHz workstation was approximately 2.5 min.ConclusionsOur new method significantly improved the LETd calculation accuracy compared to the 1D method while maintaining significantly shorter calculation time even comparing with the GPU‐based fast MC code.