Comparing stochastic proton interactions simulated using TOPAS-nBio to experimental data from fluorescent nuclear track detectors.

Whilst Monte Carlo (MC) simulations of proton energy deposition have been well-validated at the macroscopic level, their microscopic validation remains lacking. Equally, no gold-standard yet exists for experimental metrology of individual proton tracks. In this work we compare the distributions of stochastic proton interactions simulated using the TOPAS-nBio MC platform against confocal microscope data for Al2O3:C,Mg fluorescent nuclear track detectors (FNTDs). We irradiated [Formula: see text] mm3 FNTD chips inside a water phantom, positioned at seven positions along a pristine proton Bragg peak with a range in water of 12 cm. MC simulations were implemented in two stages: (1) using TOPAS to model the beam properties within a water phantom and (2) using TOPAS-nBio with Geant4-DNA physics to score particle interactions through a water surrogate of Al2O3:C,Mg. The measured median track integrated brightness (IB) was observed to be strongly correlated to both (i) voxelized track-averaged linear energy transfer (LET) and (ii) frequency mean microdosimetric lineal energy, [Formula: see text], both simulated in pure water. Histograms of FNTD track IB were compared against TOPAS-nBio histograms of the number of terminal electrons per proton, scored in water with mass-density scaled to mimic Al2O3:C,Mg. Trends between exposure depths observed in TOPAS-nBio simulations were experimentally replicated in the study of FNTD track IB. Our results represent an important first step towards the experimental validation of MC simulations on the sub-cellular scale and suggest that FNTDs can enable experimental study of the microdosimetric properties of individual proton tracks.

Reference dosimetry in magnetic fields: formalism and ionization chamber correction factors.

PURPOSE: Magnetic resonance imaging-guided radiotherapy (MRIgRT) provides superior soft-tissue contrast and real-time imaging compared with standard image-guided RT, which uses x-ray based imaging. Several groups are developing integrated MRIgRT machines. Reference dosimetry with these new machines requires accounting for the effects of the magnetic field on the response of the ionization chambers used for dose calibration. Here, the authors propose a formalism for reference dosimetry with integrated MRIgRT devices. The authors also examined the suitability of the TPR10 (20) and %dd(10)x beam quality specifiers in the presence of magnetic fields and calculated detector correction factors to account for the effects of the magnetic field for a range of detectors. METHODS: The authors used full-head and point-source Monte Carlo models of an MR-linac along with detailed detector models of an Exradin A19, an NE2571, and several PTW Farmer chambers to calculate magnetic field correction factors for six commercial ionization chambers in three chamber configurations. Calculations of ionization chamber response (performed with geant4) were validated with specialized Fano cavity tests. %dd(10)x values, TPR10 (20) values, and Spencer-Attix water-to-air restricted stopping power ratios were also calculated. The results were further validated against measurements made with a preclinical functioning MR-linac. RESULTS: The TPR10 (20) was found to be insensitive to the presence of the magnetic field, whereas the relative change in %dd(10)x was 2.4% when a transverse 1.5 T field was applied. The parameters chosen for the ionization chamber calculations passed the Fano cavity test to within ∼0.1%. Magnetic field correction factors varied in magnitude with detector orientation with the smallest corrections found when the chamber was parallel to the magnetic field. CONCLUSIONS: Reference dosimetry can be performed with integrated MRIgRT devices by using magnetic field correction factors, but care must be taken with the choice of beam quality specifier and chamber orientation. The uncertainties achievable under this formalism should be similar to those of conventional formalisms, although this must be further quantified.

Commissioning dose computation models for spot scanning proton beams in water for a commercially available treatment planning system.

PURPOSE: To present our method and experience in commissioning dose models in water for spot scanning proton therapy in a commercial treatment planning system (TPS). METHODS: The input data required by the TPS included in-air transverse profiles and integral depth doses (IDDs). All input data were obtained from Monte Carlo (MC) simulations that had been validated by measurements. MC-generated IDDs were converted to units of Gy mm(2)/MU using the measured IDDs at a depth of 2 cm employing the largest commercially available parallel-plate ionization chamber. The sensitive area of the chamber was insufficient to fully encompass the entire lateral dose deposited at depth by a pencil beam (spot). To correct for the detector size, correction factors as a function of proton energy were defined and determined using MC. The fluence of individual spots was initially modeled as a single Gaussian (SG) function and later as a double Gaussian (DG) function. The DG fluence model was introduced to account for the spot fluence due to contributions of large angle scattering from the devices within the scanning nozzle, especially from the spot profile monitor. To validate the DG fluence model, we compared calculations and measurements, including doses at the center of spread out Bragg peaks (SOBPs) as a function of nominal field size, range, and SOBP width, lateral dose profiles, and depth doses for different widths of SOBP. Dose models were validated extensively with patient treatment field-specific measurements. RESULTS: We demonstrated that the DG fluence model is necessary for predicting the field size dependence of dose distributions. With this model, the calculated doses at the center of SOBPs as a function of nominal field size, range, and SOBP width, lateral dose profiles and depth doses for rectangular target volumes agreed well with respective measured values. With the DG fluence model for our scanning proton beam line, we successfully treated more than 500 patients from March 2010 through June 2012 with acceptable agreement between TPS calculated and measured dose distributions. However, the current dose model still has limitations in predicting field size dependence of doses at some intermediate depths of proton beams with high energies. CONCLUSIONS: We have commissioned a DG fluence model for clinical use. It is demonstrated that the DG fluence model is significantly more accurate than the SG fluence model. However, some deficiencies in modeling the low-dose envelope in the current dose algorithm still exist. Further improvements to the current dose algorithm are needed. The method presented here should be useful for commissioning pencil beam dose algorithms in new versions of TPS in the future.

SU-E-T-91: Validation of Geant4 Physics for Ionization Chamber Calculations in Radiotherapy Photon Beams.

PURPOSE: To determine the accuracy of the GEANT4 Monte Carlo toolkit for ionization chamber calculations in radiotherapy photon beams. METHODS: First, we used the Fano cavity example included in the GEANT4 distribution to validate calculations under Fano conditions. We determined a combination of parameters and physics list that provided results consistent within +/- 0.5% with the Fano theorem. Next we performed simulations to investigate the accuracy of using GEANT4 for ionization chamber calculations. Eight ionization chambers were modeled using detailed manufacturer specifications including A1, A1SL, NE2571, PTW30010, PTW30012, PTW31010, PTW31014 and PTW31016. The absorbed dose to water for a cylindrical water cavity and the absorbed dose to air in the ionization chambers' cavities were scored for 1.25 MeV photons. The ratio of these quantities was then compared to values from EGSnrc simulations. RESULTS: Simulations using the Fano cavity example yielded results within +/- 0.5% with the Fano theorem across 1.25, 3 and 4 MeV incident photon energies. The most accurate and consistent results were obtained using the G4eIonisation ionization model and G4GoudsmitSaundersonMscModel multiple scattering (MS) model with a maximum step size limitation of 0.001 mm, which yielded results accurate to +/- 0.3% for all energies. This set of parameters and physics processes as well as the G4UrbanMscModel93 MS model were used for the ionization chamber calculations. The calculated quantities were compared to those used in Muir and Rogers 2010 (Med. Phys. 37: 5939-5950) and agreed to within sub-percentage differences for most chambers. CONCLUSIONS: The GEANT4 toolkit can achieve sub-percentage accuracy for ionization chamber calculations in radiotherapy photon beams. This is achieved by using either the G4GoudsmitSaundersonMscModel or G4UrbanMscModel93 MS models. Although less accurate (+/- 0.5%), simulations employing the G4UrbanMscModel93 MS model are on average two orders magnitude faster than that of the G4GoudsmitSaundersonMscModel MS model (+/- 0.3%). Natural Sciences and Engineering Research Council of Canada.