Liu, Wei

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.

Purpose To compare the dosimetric performances of small‐spot three‐dimensional (3D) and four‐dimensional (4D) robustly optimized intensity‐modulated proton (IMPT) plans in the presence of uncertainties and interplay effect simultaneously for distal esophageal carcinoma. Method and Materials Thirteen (13) patients were selected and re‐planned with small‐spot ( ~ 2–6 mm) 3D and 4D robust optimization in IMPT, respectively. The internal clinical target volumes (CTV high3d , CTV low3d ) were used in 3D robust optimization. Different CTVs (CTV high4d , CTV low4d ) were generated by subtracting an inner margin of the motion amplitudes in three cardinal directions from the internal CTVs and used in 4D robust optimization. All patients were prescribed the same dose to CTVs (50 Gy[RBE] for CTV high3d /CTV high4d and 45 Gy[RBE] for CTV low3d /CTV low4d ). Dose–volume histogram (DVH) indices were calculated to assess plan quality. Comprehensive plan robustness evaluations that consisted of 300 perturbed scenarios (10 different motion patterns to consider irregular motion (sampled from a Gaussian distribution) and 30 different uncertainties scenarios (sampled from a 4D uniform distribution) combined), were performed to quantify robustness to uncertainties and interplay effect simultaneously. Wilcoxon signed‐rank test was used for statistical analysis. Results Compared to 3D robustly optimized plans, 4D robustly optimized plans had statistically improved target coverage and better sparing of lungs and heart (heart D mean , P = 0.001; heart V 30Gy[RBE] , P = 0.001) in the nominal scenario. 4D robustly optimized plans had better robustness in target dose coverage (CTV high4d V 100% , P = 0.002) and the protection of lungs and heart (heart D mean , P = 0.001; heart V 30Gy[RBE] , P = 0.001) when uncertainties and interplay effect were considered simultaneously. Conclusions Even with small spots in IMPT, 4D robust optimization outperformed 3D robust optimization in terms of normal tissue protection and robustness to uncertainties and interplay effect simultaneously. Our findings support the use of 4D robust optimization to treat distal esophageal carcinoma with small spots in IMPT.

AbstractPurposePatient‐Specific Quality Assurance (PSQA) measurement analysis depends on generating metrics representative of calculation and measurement agreement. Considering the heightened capability of discrete spot scanning protons to modulate individual dose voxels, a dose plane comparison approach that maintained all of the capabilities of the well‐established γ test, but that also provided a more intuitive error parameterization, was desired.MethodsAnalysis was performed for 300 dose planes compared by searching all calculated points within a fixed radius around each measured pixel to determine the dose deviation. Dose plane agreement is reported as the dose difference minimum (DDM) within an empirically established search radius: ΔDmin(r). This per‐pixel metric is aggregated into a histogram binned by dose deviation. Search‐radius criteria were based on a weighted‐beamlet 3σ spatial deviation from imaging isocenter. Equipment setup error was mitigated during analysis using tracked image registration, ensuring beamlet deviations to be the dominant source of spatial error. The percentage of comparison points with <3% dose difference determined pass rate.ResultsThe mean beamlet radial deviation was 0.38mm from x‐ray isocenter, with a standard deviation of 0.19mm, such that 99.9% of relevant pencil beams were within 1 mm of nominal. The dose‐plane comparison data showed no change in passing rate between a 3%/1mm ΔDmin(r) analysis (97.6 +/‐ 3.6%) and a 3%/2mm γ test (97.7 +/‐ 3.2%).ConclusionsPSQA dose‐comparison agreements corresponding to a search radius outside of machine performance limits are likely false positives. However, the elliptical shape of the γ test is too dose‐restrictive with a spatial‐error threshold set at 1 mm. This work introduces a cylindrical search shape, proposed herein as more relevant to plan quality, as part of the new DDM planar‐dose comparison algorithm. DDM accepts all pixels within a given dose threshold inside the search radius, and carries forward plan‐quality metrics in a straightforward manner for evaluation.

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.

Abstract Purpose To compare the dosimetric performances of intensity‐modulated proton therapy (IMPT) plans generated with two different beam angle configurations (the Right–Left oblique posterior beams and the Superior–Inferior oblique posterior beams) for the treatment of distal esophageal carcinoma in the presence of uncertainties and interplay effect. Methods and Materials Twenty patients’ IMPT plans were retrospectively selected, with 10 patients treated with the R‐L oblique posterior beams (Group R‐L) and the other 10 patients treated with the S‐I oblique posterior beams (Group S‐I). Patients in both groups were matched by their clinical target volumes (CTVs—high and low dose levels) and respiratory motion amplitudes. Dose‐volume‐histogram (DVH) indices were used to assess plan quality. DVH bandwidth was calculated to evaluate plan robustness. Interplay effect was quantified using four‐dimensional (4D) dynamic dose calculation with random respiratory starting phase of each fraction. Normal tissue complication probability (NTCP) for heart, liver, and lung was calculated, respectively, to estimate the clinical outcomes. Wilcoxon signed‐rank test was used for statistical comparison between the two groups. Results Compared with plans in Group R‐L, plans in Group S‐I resulted in significantly lower liver D mean and lung V 30Gy[RBE] with slightly higher but clinically acceptable spinal cord D max . Similar plan robustness was observed between the two groups. When interplay effect was considered, plans in Group S‐I performed statistically better for heart D mean and V 30Gy[RBE] , lung Dmean and V 5Gy[RBE] , and liver D mean , with slightly increased but clinically acceptable spinal cord D max . NTCP for liver was significantly better in Group S‐I. Conclusions IMPT plans in Group S‐I have better sparing of liver, heart, and lungs at the slight cost of spinal cord maximum dose protection, and are more interplay‐effect resilient compared to IMPT plans in Group R‐L. Our study supports the routine use of the S‐I oblique posterior beams for the treatments of distal esophageal carcinoma.

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.

Purpose: To describe and validate the dose calculation algorithm of an independent second-dose check software for spot scanning proton delivery systems with full width at half maximum between 5 and 14 mm and with a negligible spray component. Methods: The analytical dose engine of our independent second-dose check software employs an altered pencil beam algorithm with 3 lateral Gaussian components. It was commissioned using Geant4 and validated by comparison to point dose measurements at several depths within spread-out Bragg peaks of varying ranges, modulations, and field sizes. Water equivalent distance was used to compensate for inhomogeneous geometry. Twelve patients representing different disease sites were selected for validation. Dose calculation results in water were compared to a fast Monte Carlo code and ionization chamber array measurements using dose planes and dose profiles as well as 2-dimensional–3-dimensional and 3-dimensional–3-dimensional γ-index analysis. Results in patient geometry were compared to Monte Carlo simulation using dose–volume histogram indices, 3-dimensional–3-dimensional γ-index analysis, and inpatient dose profiles. Results: Dose engine model parameters were tuned to achieve 1.5% agreement with measured point doses. The in-water γ-index passing rates for the 12 patients using 3%/2 mm criteria were 99.5% ± 0.5% compared to Monte Carlo. The average inpatient γ-index analysis passing rate compared to Monte Carlo was 95.8% ± 2.9%. The average difference in mean dose to the clinical target volume between the dose engine and Monte Carlo was −0.4% ± 1.0%. For a typical plan, dose calculation time was 2 minutes on an inexpensive workstation. Conclusions: Following our commissioning process, the analytical dose engine was validated for all treatment sites except for the lung or for calculating dose–volume histogram indices involving point doses or critical structures immediately distal to target volumes. Monte Carlo simulations are recommended for these scenarios.

PurposeTo clinically implement and comprehensively evaluate two independent methods for beam monitor calibration of scanning proton beam.MethodsSeven proton energies that represent the lowest to highest energy proton beams were selected. Single energy layer circular fields of diameter 15 cm with 2.5 mm spot spacing and 10 times of repainting (FS15cm) were designed for all energies. The effective measurement points of Bragg peak chamber (BPC), advanced Markus chamber (AMC) and farmer chamber (FC) were all aligned to 2 cm depth in water using SSD setup. The BPC and AMC were cross‐calibrated with farmer chamber (FC) using the field FS15cm. In order to evaluate BPC's lateral response uniformity, a collimated narrow proton beam (5.8 mm diameter) was delivered to the active area and edge of the BPC. The dose area product (DAP) was measured using two methods by two BPCs, one AMC and one FC. For method 1, a single spot proton beam was delivered to the geometric center of the BPC. For method 2, the fields FS15cm were delivered to FC and AMC, respectively. Accumulated charges by these chambers were converted to DAPs, and the quantitative difference of DAPs between both methods was calculated. The causes of the uncertainties were discussed, and the advantages of the two methods were compared.ResultsThe two BPCs showed different lateral response uniformity. BPC1 has a uniform response from the center up to a radius of 3.5 cm. BPC2 has a uniform response only to 2 cm and the response dropped 1% to 2% at 3.5 cm from center. BPC2 also has significant over‐response compared to BPC1. A 2.2% systematic error would be transferred to DAP if the over‐response from BPC2 was not considered. The DAPs measured by method 1 with two BPCs and by method 2 with FC and AMC were consistent to 0.5%. The major uncertainty component of method 1 is from the cross‐calibration of the BPC.ConclusionsThe two independent methods for DAP were shown to give consistent results, given the sources of uncertainties were carefully addressed in the measurements. Direct measurement of DAP with BPC is very efficient, but it may be subject to more than 2% systematic error if the BPC lateral response is not carefully evaluated.