Purpose: The motivation of this study was to find and eliminate the cause of errors in dose‐averaged linear energy transfer (LET) calculations from therapeutic protons in small targets, such as biological cell layers, calculated using the geant 4 Monte Carlo code. Furthermore, the purpose was also to provide a recommendation to select an appropriate LET quantity from geant 4 simulations to correlate with biological effectiveness of therapeutic protons.Methods: The authors developed a particle tracking step based strategy to calculate the average LET quantities (track‐averaged LET, LET_t and dose‐averaged LET, LET_d) using geant 4 for different tracking step size limits. A step size limit refers to the maximally allowable tracking step length. The authors investigated how the tracking step size limit influenced the calculated LET_t and LET_d of protons with six different step limits ranging from 1 to 500 μm in a water phantom irradiated by a 79.7‐MeV clinical proton beam. In addition, the authors analyzed the detailed stochastic energy deposition information including fluence spectra and dose spectra of the energy‐deposition‐per‐step of protons. As a reference, the authors also calculated the averaged LET and analyzed the LET spectra combining the Monte Carlo method and the deterministic method. Relative biological effectiveness (RBE) calculations were performed to illustrate the impact of different LET calculation methods on the RBE‐weighted dose.Results: Simulation results showed that the step limit effect was small for LET_t but significant for LET_d. This resulted from differences in the energy‐deposition‐per‐step between the fluence spectra and dose spectra at different depths in the phantom. Using the Monte Carlo particle tracking method in geant 4 can result in incorrect LET_d calculation results in the dose plateau region for small step limits. The erroneous LET_d results can be attributed to the algorithm to determine fluctuations in energy deposition along the tracking step in geant 4. The incorrect LET_d values lead to substantial differences in the calculated RBE.Conclusions: When the geant 4 particle tracking method is used to calculate the average LET values within targets with a small step limit, such as smaller than 500 μm, the authors recommend the use of LET_t in the dose plateau region and LET_d around the Bragg peak. For a large step limit, i.e., 500 μm, LET_d is recommended along the whole Bragg curve. The transition point depends on beam parameters and can be found by determining the location where the gradient of the ratio of LET_d and LET_t becomes positive.

As a proton-therapy beam passes through the field-limiting aperture, some of the protons are scattered off the edges of the collimator. The edge-scattered protons can degrade the dose distribution in a patient or phantom, and these effects are difficult to model with analytical methods such as those available in treatment planning systems. The objective of this work was to quantify the dosimetric impact of edge-scattered protons for a representative variety of clinical treatment beams. The dosimetric impact was assessed using Monte Carlo simulations of proton beams from a contemporary treatment facility. The properties of the proton beams were varied, including the penetration range (6.4-28.5 cm), width of the spread-out Bragg peak (SOBP; 2-16 cm), field size (3 x 3 cm(2) to 15 x 15 cm(2)) and air gap, i.e. the distance between the collimator and the phantom (8-48 cm). The simulations revealed that the dosimetric impact of edge-scattered protons increased strongly with increasing range (dose increased by 6-20% with respect to the dose at the center of the spread-out Bragg peak), decreased strongly with increasing field size (dose changed by 2-20%), increased moderately with increasing air gap (dose increased by 2-6%) and increased weakly with increasing SOBP width (dose change <4%). In all cases examined, the effects were largest at shallow depths. We concluded that the dose deposited by edge-scattered protons can distort the dose proximal to the target with varying contributions due to the proton range, treatment field size, collimator position and thickness, and width of the SOBP. Our findings also suggest that accurate predictions of dose per monitor-unit calculations may require taking into account the dose from protons scattered from the edge of the patient-specific collimator, particularly for fields of small lateral size and deep depths.

By the end of 2002, 33 398 patients worldwide had been treated with proton radiotherapy, 10 829 for eye diseases. The dose prediction algorithms used today for ocular proton therapy treatment planning rely on parameterizations of measured proton dose distributions, i.e., broad-beam and pencil-beam techniques, whose predictive capabilities are inherently limited by severe approximations and simplifications in modelling the radiation transport physics. In contrast, the Monte Carlo radiation transport technique can, in principle, provide accurate predictions of the proton treatment beams by taking into account all the physical processes involved, including coulombic energy loss, energy straggling, multiple Coulomb scattering, elastic and nonelastic nuclear interactions, and the transport of secondary particles. It has not been shown, however, whether it is possible to commission a proton treatment planning system by using data exclusively from Monte Carlo simulations of the treatment apparatus and a phantom. In this work, we made benchmark comparisons between Monte Carlo predictions and measurements of an ocular proton treatment beamline. The maximum differences between absorbed dose profiles from simulations and measurements were 6% and 0.6 mm, while typical differences were less than 2% and 0.2 mm. The computation time for the entire virtual commissioning process is less than one day. The study revealed that, after a significant development effort, a Monte Carlo model of a proton therapy apparatus is sufficiently accurate and fast for commissioning a treatment planning system.

Large amounts of high quality biophysical data are needed to improve current biological effects models but such data are lacking and difficult to obtain. The present study aimed to more efficiently measure the spatial distribution of relative biological effectiveness (RBE) of charged particle beams using a novel high-accuracy and high-throughput experimental platform. Clonogenic survival was selected as the biological endpoint for two lung cancer cell lines, H460 and H1437, irradiated with protons, carbon, and helium ions. Ion-specific multi-step microplate holders were fabricated such that each column of a 96-well microplate is spatially situated at a different location along a particle beam path. Dose, dose-averaged linear energy transfer (LET_d), and dose-mean lineal energy (y_d) were calculated using an experimentally validated Geant4-based Monte Carlo system. Cells were irradiated at the Heidelberg Ion Beam Therapy Center (HIT). The experimental results showed that the clonogenic survival curves of all tested ions were y_d-dependent. Both helium and carbon ions achieved maximum RBEs within specific y_d ranges before biological efficacy declined, indicating an overkill effect. For protons, no overkill was observed, but RBE increased distal to the Bragg peak. Measured RBE profiles strongly depend on the physical characteristics such as y_d and are ion specific.