Modelling small block aperture in an in-house developed GPU-accelerated Monte Carlo-based dose engine for pencil beam scanning proton therapy.

Purpose. To enhance an in-house graphic-processing-unit accelerated virtual particle (VP)-based Monte Carlo (MC) proton dose engine (VPMC) to model aperture blocks in both dose calculation and optimization for pencil beam scanning proton therapy (PBSPT)-based stereotactic radiosurgery (SRS).Methods and materials. A module to simulate VPs passing through patient-specific aperture blocks was developed and integrated in VPMC based on simulation results of realistic particles (primary protons and their secondaries). To validate the aperture block module, VPMC was first validated by an opensource MC code, MCsquare, in eight water phantom simulations with 3 cm thick brass apertures: four were with aperture openings of 1, 2, 3, and 4 cm without a range shifter, while the other four were with same aperture opening configurations with a range shifter of 45 mm water equivalent thickness. Then, VPMC was benchmarked with MCsquare and RayStation MC for 10 patients with small targets (average volume 8.4 c.c. with range of 0.4-43.3 c.c.). Finally, 3 typical patients were selected for robust optimization with aperture blocks using VPMC.Results. In the water phantoms, 3D gamma passing rate (2%/2 mm/10%) between VPMC and MCsquare was 99.71 ± 0.23%. In the patient geometries, 3D gamma passing rates (3%/2 mm/10%) between VPMC/MCsquare and RayStation MC were 97.79 ± 2.21%/97.78 ± 1.97%, respectively. Meanwhile, the calculation time was drastically decreased from 112.45 ± 114.08 s (MCsquare) to 8.20 ± 6.42 s (VPMC) with the same statistical uncertainties of ~0.5%. The robustly optimized plans met all the dose-volume-constraints (DVCs) for the targets and OARs per our institutional protocols. The mean calculation time for 13 influence matrices in robust optimization by VPMC was 41.6 s and the subsequent on-the-fly 'trial-and-error' optimization procedure took only 71.4 s on average for the selected three patients.Conclusion. VPMC has been successfully enhanced to model aperture blocks in dose calculation and optimization for the PBSPT-based SRS.

Modelling small block aperture in an in-house developed GPU-accelerated Monte Carlo-based dose engine for pencil beam scanning proton therapy.

Purpose: To enhance an in-house graphic-processing-unit (GPU) accelerated virtual particle (VP)-based Monte Carlo (MC) proton dose engine (VPMC) to model aperture blocks in both dose calculation and optimization for pencil beam scanning proton therapy (PBSPT)-based stereotactic radiosurgery (SRS). Methods and Materials: A module to simulate VPs passing through patient-specific aperture blocks was developed and integrated in VPMC based on simulation results of realistic particles (primary protons and their secondaries). To validate the aperture block module, VPMC was first validated by an opensource MC code, MCsquare, in eight water phantom simulations with 3cm thick brass apertures: four were with aperture openings of 1, 2, 3, and 4cm without a range shifter, while the other four were with same aperture opening configurations with a range shifter of 45mm water equivalent thickness. Then, VPMC was benchmarked with MCsquare and RayStation MC for 10 patients with small targets (average volume 8.4 cc with range of 0.4 - 43.3 cc). Finally, 3 typical patients were selected for robust optimization with aperture blocks using VPMC. Results: In the water phantoms, 3D gamma passing rate (2%/2mm/10%) between VPMC and MCsquare was 99.71±0.23%. In the patient geometries, 3D gamma passing rates (3%/2mm/10%) between VPMC/MCsquare and RayStation MC were 97.79±2.21%/97.78±1.97%, respectively. Meanwhile, the calculation time was drastically decreased from 112.45±114.08 seconds (MCsquare) to 8.20±6.42 seconds (VPMC) with the same statistical uncertainties of ~0.5%. The robustly optimized plans met all the dose-volume-constraints (DVCs) for the targets and OARs per our institutional protocols. The mean calculation time for 13 influence matrices in robust optimization by VPMC was 41.6 seconds and the subsequent on-the-fly "trial-and-error" optimization procedure took only 71.4 seconds on average for the selected three patients. Conclusion: VPMC has been successfully enhanced to model aperture blocks in dose calculation and optimization for the PBSPT-based SRS.

Virtual particle Monte Carlo: A new concept to avoid simulating secondary particles in proton therapy dose calculation.

BACKGROUND: In proton therapy dose calculation, Monte Carlo (MC) simulations are superior in accuracy but more time consuming, compared to analytical calculations. Graphic processing units (GPUs) are effective in accelerating MC simulations but may suffer thread divergence and racing condition in GPU threads that degrades the computing performance due to the generation of secondary particles during nuclear reactions. PURPOSE: A novel concept of virtual particle (VP) MC (VPMC) is proposed to avoid simulating secondary particles in GPU-accelerated proton MC dose calculation and take full advantage of the computing power of GPU. METHODS: Neutrons and gamma rays were ignored as escaping from the human body; doses of electrons, heavy ions, and nuclear fragments were locally deposited; the tracks of deuterons were converted into tracks of protons. These particles, together with primary and secondary protons, are considered to be the realistic particles. Histories of primary and secondary protons were replaced by histories of multiple VPs. Each VP corresponded to one proton (either primary or secondary). A continuous-slowing-down-approximation model, an ionization model, and a large angle scattering event model corresponding to nuclear interactions were developed for VPs by generating probability distribution functions (PDFs) based on simulation results of realistic particles using MCsquare. For efficient calculations, these PDFs were stored in the Compute Unified Device Architecture textures. VPMC was benchmarked with TOPAS and MCsquare in phantoms and with MCsquare in 13 representative patient geometries. Comparisons between the VPMC calculated dose and dose measured in water during patient-specific quality assurance (PSQA) of the selected 13 patients were also carried out. Gamma analysis was used to compare the doses derived from different methods and calculation efficiencies were also compared. RESULTS: Integrated depth dose and lateral dose profiles in both homogeneous and inhomogeneous phantoms all matched well among VPMC, TOPAS, and MCsquare calculations. The 3D-3D gamma passing rates with a criterion of 2%/2 mm and a threshold of 10% was 98.49% between MCsquare and TOPAS and 98.31% between VPMC and TOPAS in homogeneous phantoms, and 99.18% between MCsquare and TOPAS and 98.49% between VPMC and TOPAS in inhomogeneous phantoms, respectively. In patient geometries, the 3D-3D gamma passing rates with 2%/2 mm/10% between dose distributions from VPMC and MCsquare were 98.56 ± 1.09% in patient geometries. The 2D-3D gamma analysis with 3%/2 mm/10% between the VPMC calculated dose distributions and the 2D measured planar dose distributions during PSQA was 98.91 ± 0.88%. VPMC calculation was highly efficient and took 2.84 ± 2.44 s to finish for the selected 13 patients running on four NVIDIA Ampere GPUs in patient geometries. CONCLUSION: VPMC was found to achieve high accuracy and efficiency in proton therapy dose calculation.

GPU-accelerated Monte Carlo-based online adaptive proton therapy: A feasibility study.

PURPOSE: To develop an online graphic processing unit (GPU)-accelerated Monte Carlo-based adaptive radiation therapy (ART) workflow for pencil beam scanning (PBS) proton therapy to address interfraction anatomical changes in patients treated with PBS. METHODS AND MATERIALS: A four-step workflow was developed using our in-house developed GPU-accelerated Monte Carlo-based treatment planning system to implement online Monte Carlo-based ART for PBS. The first step conducts diffeomorphic demon-based deformable image registration (DIR) to propagate contours on the initial planning CT (pCT) to the verification CT (vCT) to form a new structure set. The second step performs forward dose calculation of the initial plan on the vCT with the propagated contours after manual approval (possible modifications involved). The third step triggers a reoptimization of the plan depending on whether the verification dose meets the clinical requirements or not. A robust evaluation will be done for both the verification plan in the second step and the reopotimized plan in the third step. The fourth step involves a two-stage (before and after delivery) patient-specific quality assurance (PSQA) of the reoptimized plan. The before-delivery PSQA is to compare the plan dose to the dose calculated using an independent fast open-source Monte Carlo code, MCsquare. The after-delivery PSQA is to compare the plan dose to the dose recalculated using the log file (spot MU, spot position, and spot energy) collected during the delivery. Jaccard index (JI), dice similarity coefficients (DSCs), and Hausdorff distance (HD) were used to assess the quality of the propagated contours in the first step. A commercial plan evaluation software, ClearCheck™, was integrated into the workflow to carry out efficient plan evaluation. 3D Gamma analysis was used during the fourth step to ensure the accuracy of the plan dose from reoptimization. Three patients with three different disease sites were chosen to evaluate the feasibility of the online ART workflow for PBS. RESULTS: For all three patients, the propagated contours were found to have good volume conformance [JI (lowest-highest: 0.833-0.983) and DSC (0.909-0.992)] but suboptimal boundary coincidence [HD (2.37-20.76 mm)] for organs-at-risk. The verification dose evaluated by ClearCheck™ showed significant degradation of the target coverage due to the interfractional anatomical changes. Reoptimization on the vCT resulted in great improvement of the plan quality to a clinically acceptable level. 3D Gamma analyses of PSQA confirmed the accuracy of the plan dose before delivery (mean Gamma index = 98.74% with a threshold of 2%/2 mm/10%), and after delivery based on the log files (mean Gamma index = 99.05% with a threshold of 2%/2 mm/10%). The average time cost for the complete execution of the workflow was around 858 s, excluding the time for manual intervention. CONCLUSION: The proposed online ART workflow for PBS was demonstrated to be efficient and effective by generating a reoptimized plan that significantly improved the plan quality.

Technical note: Evaluation and second check of a commercial Monte Carlo dose engine for small-field apertures in pencil beam scanning proton therapy.

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 cm3 ) 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.

Costs of Definitive Chemoradiation, Surgery, and Adjuvant Radiation Versus De-Escalated Adjuvant Radiation per MC1273 in HPV+ Cancer of the Oropharynx.

PURPOSE: De-escalated treatment for human papillomavirus (HPV)+ oropharynx squamous cell carcinoma (OPSCC) has shown promising initial results. Health-care policy is increasingly focusing on high-value care. This analysis compares the cost of care for HPV+ OPSCC treated with definitive chemoradiation (CRT), surgery and adjuvant radiation (RT), and surgery and de-escalated CRT on MC1273. METHODS AND MATERIALS: MC1273 is a prospective, phase 2 study evaluating adjuvant CRT to 30 to 36 Gy plus docetaxel for HPV+ OPSCC after surgery for high-risk patients. Matched standard-of-care control groups were retrospectively identified for patients treated with definitive CRT or adjuvant RT. Standardized costs were evaluated before radiation, during treatment (during RT), and at short-term (6 month) and long-term (7-24 month) follow-up periods. RESULTS: A total of 56 definitive CRT, 101 adjuvant RT, and 66 MC1273 patients were included. The CRT arm had more T3-4 disease (63% vs 17-21%) and higher N2c-N3 disease (52% vs 20-24%) vs both other groups. The total treatment costs in the CRT, adjuvant RT, and MC1273 groups were $47,763 (standard deviation [SD], $19,060], $57,845 (SD, $17,480), and $46,007 (SD, $9019), respectively, and the chemotherapy and/or RT costs were $39,936 (SD, $18,480), $26,603 (SD, $12,542), and $17,864 (SD, $3288), respectively. The per-patient, per-month, average short-term follow-up costs were $3860 (SD, $10,525), $1072 (SD, $996), and $972 (SD, $833), respectively, and the long-term costs were $978 (SD, $2294), $485 (SD, $1156), and $653 (SD, $1107), respectively. After adjustment for age, T-stage, and N-stage, treatment costs remained lower for CRT and MC1273 versus adjuvant RT ($45,450 and $47,114 vs $58,590, respectively; P < .001), whereas the total per-patient, per-month follow-up costs were lower in the MC1273 study group and adjuvant RT versus CRT ($853 and $866 vs $2030, respectively; P = .03). CONCLUSIONS: MC1273 resulted in 10% and 20% reductions in global costs compared with standard-of-care adjuvant RT and definitive CRT treatments. Substantial cost savings may be an added benefit to the already noted low toxicity and maintained quality of life of treatment per MC1273.

Understanding American Indian Perceptions Toward Radiation Therapy.

Many American Indian (AI) and Alaska native (AN) patients do not complete guideline-concordant cancer care for the 4 most common cancers. Our aim was to better understand AI/AN attitudes toward radiation therapy (RT). Patients eligible for this survey study were AI/AN patients with cancer at the Phoenix Indian Medical Center who either received previous RT or were recommended to receive RT. An 18-item questionnaire was administered to each of the 50 participants from October 1, 2018, through February 15, 2019. Willingness to travel for RT was compared to respondent characteristics, concerns regarding RT, and obstacles to obtain RT. Duration of RT was important to 78% of patients: 24% would consider traveling 25 miles or more for a standard course, and 48% would travel that distance for a shorter course (P < .001). The top-ranked barriers to RT were transportation, cost of treatment, and insurance compatibility. The top-ranked concerns about RT were adverse effects, cost of treatment, and fear of RT. Concerns about adverse effects were associated with the radiation team's inability to explain the treatment (P = .05). Transportation concerns were significantly associated with accessibility (P = .02), communication with the RT team (P = .02), and fear of RT (P = .04). AI/AN patients are concerned about the adverse effects of RT and the logistics of treatment, particularly costs, transportation, and insurance compatibility. Use of culturally specific education and hypofractionation regimens may increase acceptance of RT for AI/AN patients with cancer, and this hypothesis will be tested in a future educational intervention-based study.

Hybrid 3D analytical linear energy transfer calculation algorithm based on precalculated data from Monte Carlo simulations.

PURPOSE: The 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. METHODS: We 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. RESULTS: The 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. CONCLUSIONS: Our 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.