Monte Carlo framework for commissioning a synchrotron-based discrete spot scanning proton beam system and treatment plan verification.

This study aimed to develop a Monte Carlo (MC) framework for commissioning the narrow proton beams (spot size sigma, 5.2 mm 2 mm at isocenter for 69.4 MeV-221.3 MeV for the main beam option and 4.1 mm 1.3 mm for the minibeam option respectively) of a synchrotron-based proton therapy system and design an independent absolute dose calculation engine for intensity-modulated proton treatments. A proton therapy system (Hitachi PROBEAT-V) was simulated using divergent and convergent beam models at the nozzle entrance. The innovative source weighting scheme for the MC simulation with TOPAS (TOol for PArticle Simulations) was implemented using dose output data for the absolute dose calculations. The results of the MC simulation were compared to the experimental data, analyzed and used to commission the treatment planning system. Two MC models, divergent and convergent beams were implemented. The convergent beam model produced a high level of agreement when MC and measurements were analyzed. The beam ellipticity did not result in significant differences between MC simulated and treatment planning system calculated doses. A model of a synchrotron-based spot scanning proton therapy system has been developed and implemented in the TOPAS MC transport code framework. The dose computation engine is useful for treatment plan verification with primary and minibeam beam option.

Proton therapy delivery method affects dose-averaged linear energy transfer in patients.

The dosimetric advantages of proton therapy have led to its rapid proliferation in recent decades. This has been accompanied by a shift in technology from older units that deliver protons by passive scattering (PS) to newer units that increasingly use pencil-beam scanning (PBS). The biologic effectiveness of proton physical dose purportedly rises with increasing dose-weighted average linear energy transfer (LETD). The objective of this study was to determine the extent to which proton delivery methods affect LETD. We calculated LETDfrom simple, dosimetrically matched, and clinical treatment plans with TOPAS Monte-Carlo transport code. Simple treatment plans comprised single fields of PS and PBS protons in a water phantom. We performed simulations of matched and clinical treatment plans by using the treatment and anatomic data obtained from a cohort of children with craniopharyngioma who previously received PS or PBS proton therapy. We compared the distributions of LETDfrom PS and PBS delivery methods in clinically relevant ROIs. Wilcoxon signed-rank tests comparing single fields in water revealed that the LETDvalues from PBS were significantly greater than those from PS inside and outside the targeted volume (p < 0.01). Statistical tests comparing LETD-volume histograms from matched and clinical treatment plans showed that LETDwas generally greater for PBS treatment plans than for PS treatment plans (p < 0.05). In conclusion, the proton delivery method affects LETDboth inside and outside of the target volume. These findings suggest that PBS is more biologically effective than PS. Given the rapid expansion of PBS proton therapy, future studies are needed to confirm the applicability of treatment evaluation methods developed for PS proton therapy to those for modern PBS treatments to ensure their safety and effectiveness for the growing population of patients receiving proton therapy. This study uses data from two clinical trials: NCT01419067 and NCT02792582.

Automation of Monte Carlo-based treatment plan verification for proton therapy.

PURPOSE: Independent calculations of proton therapy plans are an important quality control procedure in treatment planning. When using custom Monte Carlo (MC) models of the beamline, deploying the calculations can be laborious, time consuming, and require in-depth knowledge of the computational environment. We developed an automated framework to remove these barriers and integrate our MC model into the clinical workflow. MATERIALS AND METHODS: The Eclipse Scripting Application Programming Interface was used to initiate the automation process. A series of MATLAB scripts were then used for preprocessing of input data and postprocessing of results. Additional scripts were used to monitor the calculation process and appropriately deploy calculations to an institutional high-performance computing facility. The automated framework and beamline models were validated against 160 patient specific QA measurements from an ionization chamber array and using a ±3%/3 mm gamma criteria. RESULTS: The automation reduced the human-hours required to initiate and run a calculation to 1-2 min without leaving the treatment planning system environment. Validation comparisons had an average passing rate of 99.4% and were performed at depths ranging from 1 to 15 cm. CONCLUSION: An automated framework for running MC calculations was developed which enables the calculation of dose and linear energy transfer within a clinically relevant workflow and timeline. The models and framework were validated against patient specific QA measurements and exhibited excellent agreement. Before this implementation, execution was prohibitively complex for an untrained individual and its use restricted to a research environment.