Citations

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.

Abstract Background: A range pull-back device, such as a machine-related range shifter (MRS) or a universal patient-related range shifter (UPRS), is needed in pencil beam scanning technique to treat shallow tumors. Methods: three UPRS made by QFix (Avondale, PA, USA) allow treating targets across the body: U-shaped bolus (UB), anterior lateral bolus (ALB) and couch top bolus (CTB). HN patients who used the UPRS were tested. The in-air spot sizes were measured and compared in this study at snout positions: 15 cm, 25 cm, and 35 cm. A solid water phantom with the ALB placed at 0, 10 and 20 cm air gaps to the phantom surface was also measured using a single-field optimized pencil beam scanning field. The two dimensional dose maps at the middle of the spread-out Bragg peak were measured using ion chamber array MatriXX PT (IBA-Dosimetry, Schwarzenbruck, Germany) located at iso-center and compared with the treatment planning system. Results: A UPRS can be consistently placed close to the patient and maintains a relatively small spot size resulting in improved dose distributions. However, when a UPRS is non-removable (e.g. thick couch top), the quality of volumetric imaging is degraded due to their high Z material construction, hindering the value of Image-Guided Radiation Therapy (IGRT). Limitations of using UPRS with small air gaps include reduced couch weight limit, potential collision with patient or immobilization devices and challenges using non-coplanar fields with certain UPRS. Our experience showed the combination of a U-shaped bolus exclusively for a head-and-neck target and an MRS as complimentary for head-and-neck targets as well as for all other treatment sites may be ideal to preserve the dosimetric advantages of pencil beam scanning proton treatments across the body. Conclusion: We have described how to implement UPRS and MRS for various clinical indications using the PBS technique, and comprehensively reviewed the advantage and disadvantages of URPS and MRS. We recommend the removable UB to be employed for the brain and HN treatments only while an automated MRS is used for all proton beams that require RS but not convenient or feasible to UB.

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.

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.

PurposeAt our institution, all proton patient plans undergo patient‐specific quality assurance (PSQA) prior to treatment delivery. For intensity‐modulated proton beam therapy, quality assurance is complex and time consuming, and it may involve multiple measurements per field. We reviewed our PSQA workflow and identified the steps that could be automated and developed solutions to improve efficiency.MethodsWe used the treatment planning system's (TPS) capability to support C# scripts to develop an Eclipse scripting application programming interface (ESAPI) script and automate the preparation of the verification phantom plan for measurements. A local area network (LAN) connection between our measurement equipment and shared database was established to facilitate equipment control, measurement data transfer, and storage. To improve the analysis of the measurement data, a Python script was developed to automatically perform a 2D–3D γ‐index analysis comparing measurements in the plane of a two‐dimensional detector array with TPS predictions in a water phantom for each acquired measurement.ResultsDevice connection via LAN granted immediate access to the plan and measurement information for downstream analysis using an online software suite. Automated scripts applied to verification plans reduced time from preparation steps by at least 50%; time reduction from automating γ‐index analysis was even more pronounced, dropping by a factor of 10. On average, we observed an overall time savings of 55% in completion of the PSQA per patient plan.ConclusionsThe automation of the routine tasks in the PSQA workflow significantly reduced the time required per patient, reduced user fatigue, and frees up system users from routine and repetitive workflow steps allowing increased focus on evaluating key quality metrics.

AbstractPurposeTo compare dosimetric performance of volumetric‐modulated arc therapy (VMAT) and small‐spot intensity‐modulated proton therapy for stage III non‐small‐cell lung cancer (NSCLC).Methods and MaterialsA total of 24 NSCLC patients were retrospectively reviewed; 12 patients received intensity‐modulated proton therapy (IMPT) and the remaining 12 received VMAT. Both plans were generated by delivering prescription doses to clinical target volumes (CTV) on averaged 4D‐CTs. The dose‐volume‐histograms (DVH) band method was used to quantify plan robustness. Software was developed to evaluate interplay effects with randomized starting phases of each field per fraction. DVH indices were compared using Wilcoxon rank sum test.ResultsCompared with VMAT, IMPT delivered significantly lower cord Dmax, heart Dmean, and lung V5 Gy[RBE] with comparable CTV dose homogeneity, and protection of other OARs. In terms of plan robustness, the IMPT plans were statistically better than VMAT plans in heart Dmean, but were statistically worse in CTV dose coverage, cord Dmax, lung Dmean, and V5 Gy[RBE]. Other DVH indices were comparable. The IMPT plans still met the standard clinical requirements with interplay effects considered.ConclusionsSmall‐spot IMPT improves cord, heart, and lung sparing compared to VMAT and achieves clinically acceptable plan robustness at least for the patients included in this study with motion amplitude less than 11 mm. Our study supports the usage of IMPT to treat some lung cancer patients.

PurposeThe purpose of this study was to develop a fast method for proton range quality assurance (QA) using a dual step wedge and two‐dimensional (2D) scintillator and to evaluate the robustness, sensitivity, and long‐term reproducibility of this method.MethodsAn in‐house customized dual step wedge and a 2D scintillator were developed to measure proton ranges. Proton beams with homogenous fluence were delivered through wedge, and the images captured by the scintillator were used to calculate the proton ranges by a simple trigonometric method. The range measurements of 97 energies, comprising all clinically available synchrotron energies at our facility (ranges varying from 4 to 32 cm) were repeated ten times in all four gantry rooms for range baseline values. They were then used for evaluating room‐to‐room range consistencies. The robustness to setup uncertainty was evaluated by measuring ranges with ±2 mm setup deviations in the x, y, and z directions. The long‐term reproducibility was evaluated by 1 month of daily range measurements by this method.ResultsRanges of all 97 energies were measured in less than 10 minutes including setup time. The reproducibility in a single day and daily over 1 month is within 0.1 and 0.15 mm, respectively. The method was very robust to setup uncertainty, with measured range consistencies within 0.15 mm for ±2 mm couch shifts. The method was also sensitive enough for validating range consistencies among gantry rooms and for detecting small range variations.ConclusionsThe new method of using a dual step wedge and scintillator for proton range QA was efficient, highly reproducible, and robust. This method of proton range QA was highly feasible and appealing from a workflow point of view.