A comparison between track-structure, condensed-history Monte Carlo simulations and MIRD cellularS-values

Abstract

The S-value is a standard measure in cellular dosimetry. S-values are calculated by applying analytical methods or by Monte Carlo simulation. In Monte Carlo simulation, particles are either tracked individually event-by-event or close events are condensed and processed collectively in different steps. Both of these methods have been employed for estimation of cellular S-values, but there is no consistency between the published results. In the present paper, we used the Geant4-DNA track-structure physics model as the reference to estimate the cellular S-values. We compared the results with the corresponding values obtained from the following three condensed-history physics models of Geant4: Penelope, Livermore and standard. The geometry and source were exactly the same in all the simulations. We utilized mono-energetic electrons with an initial kinetic energy in the range 1-700 keV as the source of radiation. We also compared our results with the MIRD S-values. We first drew an overall comparison between different data series and then compared the dependence of results on the energy of particles and the size of scoring compartments. The overall comparison indicated a very good linear correlation (R > 91%) and small bias (3%) between the results of the track-structure model and the condensed-history physics model. The bias between MIRD and the results of Monte Carlo track-structure simulation was considerable (-8%). However, the point-by-point comparison revealed differences of up to 28% between the condensed-history and the track-structure MC codes for self-absorption S-values in the 10-50 keV energy range. For the cross-absorption S-values, the difference was up to 34%. In this energy range, the difference between the MIRD S-values and the Geant4-DNA results was up to 68%. Our findings suggest that the consistency/inconsistency of the results obtained with different MC simulations depends on the size of the scoring volumes, the energy of the particles, the step-size in electron tracking and the energy cutoff used in the MC codes.

The effect of nucleus size on the cell dose in targeted radionuclide therapy – A monte carlo study

“…Geant4-DNA package has used in many previous studies to calculate the S-value in different aspects, including geometries,[ 7 ] particles,[ 13 ] and physics. [ 14 ] Its results show a good agreement with other MC codes and analytical method.…”

“…We validated our model against the available data which has obtained from general purpose codes for 10 keV to 1 MeV incident electron energies ( t -test and P ≤ 0.05). [ 6 7 14 ] Then, the obtained data were compared with analytical MIRD data. [ 7 14 ]…”

THE ENERGY DEPOSITION DISTRIBUTION AT THE MICRO AND NANO-SCALE FOR MOLECULAR TARGETED RADIOTHERAPY: COMPARISON BETWEEN 125I, 99MTc AND 64Cu

“…One of the main problems for MC simulation validations at micro and nano scale is the lack of experimental data [12]. For this reason, several studies often use MIRD values for comparison with MC calculated values.…”

“…MC simulations are considered as the most reliable method for estimating the energy deposition in complex geometries [12].…”

Dosimetry of Bone-Seeking Radiopharmaceuticals for Palliative Therapy of Bone Metastases: A Simulation Study Using GATE Monte Carlo Code

“…Livermore physics model was selected for the simulations. In this model, electron and photon cut-off energies are 100.0 eV and 250.0 eV, respectively [30]. That means, when the energy of particles falls below these threshold values during simulation, the tracking is terminated, and the remaining energy of the particle is deposited at that spot.…”