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BACKGROUND: Radiation therapy using electron beams is a promising method due to its physical dose distribution. Monte Carlo (MC) code is the best and most accurate technique for forespeaking the distribution of dose in radiation treatment of patients. MATERIAL AND METHODS: We report an MC simulation of a linac head and depth dose on central axis, along with profile calculations. The purpose of the present research is to carefully analyze the application of MC methods for the calculation of dosimetric parameters for electron beams with energies of 8-14 MeV at a Siemens Primus linac. The principal components of the linac head were simulated using MCNPX code for different applicators. RESULTS: The consequences of measurements and simulations revealed a good agreement. Gamma index values were below 1 for most points, for all energy values and all applicators in percent depth dose and dose profile computations. A number of states exhibited rather large gamma indices; these points were located at the tail of the percent depth dose graph; these points were less used in in radiotherapy. In the dose profile graph, gamma indices of most parts were below 1. The discrepancies between the simulation results and measurements in terms of Zmax, R90, R80 and R50 were insignificant. The results of Monte Carlo simulations showed a good agreement with the measurements. CONCLUSION: The software can be used for simulating electron modes of a Siemens Primus linac when direct experimental measurements are not feasible.
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OBJECTIVE: The aim of the present study is to simulate 6 MV and 18 MV photon beam energies of a Siemens Primus Plus medical linear accelerator (Linac) and to verify the simulation by comparing the results with the measured data. METHODS: The main components of the head of Siemens Primus Plus linac were simulated using MCNPX Monte Carlo (MC) code. To verify the results, experimental data of percentage depth dose (PDD) and beam dose profile for 5 × 5 cm2, 10 × 10 cm2 and 20 × 20 cm2 field sizes were measured and compared with simulation results. Moreover, gamma function was used to compare the measurement and simulation data. RESULTS: The results show a good agreement, within 1%, was observed between the data calculated by the simulations and those obtained by measurement for 6 MV photon beam, while it was within 2% for 18 MV photon beam, except in the build-up region for both beams. Gamma index values were less than unity in most data points for all the mentioned energies and fields. To calculate the dose in the phantom, cells were selected in different modes, one of the modes due to the lack of dose gradient and overlapping, produced better results than others produce. CONCLUSION: There was good settlement between measured and MC simulation values in this research. The simulation programs can be used for photon modes of Siemens Primus Plus linac in conditions in which it is not possible to perform experimental measurements.
RESUMEN
A data-based mathematical model was formulated to assess the epidemiological consequences of heterosexual, intravenous drug use (IVDU) and perinatal transmission in New York City (NYC). The model was analysed to clarify the relationship between heterosexual and IVDU transmission and to provide qualitative and quantitative insights into the HIV epidemic in NYC. The results demonstrated the significance of the dynamic interaction of heterosexual and IVDU transmission. Scenario analysis of the model was used to suggest a new explanation for the stabilization of the seroprevalence level that has been observed in the NYC IVDU community; the proposed explanation does not rely upon any IVDU or sexual behavioural changes. Gender-specific risks of heterosexual transmission in IVDUs were also explored by scenario analysis. The results showed that the effect of the heterosexual transmission risk factor on increasing the risk of HIV infection depends upon the level of IVDU. The model was used to predict future numbers of adult and pediatric AIDS cases; a sensitivity analysis of the model showed that the confidence intervals on these prediction estimates were extremely wide. This prediction variability was due to the uncertainty in estimating the values of the models' thirty variables (twenty biological-behavioural transmission parameters and the initial sizes of ten subgroups). However, the sensitivity analysis revealed that only a few key variables were significant in contributing to the AIDS case prediction variability; partial rank correlation coefficients were calculated and used to identify and to rank the importance of these key variables. The results suggest that long-term precise estimates of the future number of AIDS cases will only be possible once the values of these key variables have been evaluated accurately.
