Objective: Simulating the photon transport process, recording the distribution of the dose which is caused by various of interactions and secondary particles, summarizing and analyzing the weightiness of each contribution. Methods: The PENELOPE package provides the basic Monte Carlo(MC) code which simulates the processes of photon and electron transport Considering the concerned physical problems, the author modifies the PENELOPE program to simulate the track of photon transport process, meanwhile records the contribution of dose which is provided by various of interactions and secondary particles in this article. Results: Firstly, in the same condition, recording the distribution from 4 source different energies(30 keV, 40keV, 50 keV, 60 keV), the distribution of the central axis total dose and the distributions which are caused by secondary Soft collision and secondary hard inelastic collision, and the distribution of the central axis dose provided by secondary particles. Secondly, in the same condition, recording the distribution of the central axis dose caused by secondary Compton scattering and secondary Photonelectric scattering. Conclusion: In different source of energy, the distribution of the central axis dose proffered by secondary soft collision play a major role; the contribution of secondary Photonelectric scattering decreased with the ascent of energy; the contribution from the first generation secondary particles is stronger than others.

The hybrid pencil beam model (HPBM) is an effective algorithm for calculating electron dose distribution in radiotherapy. The mean energy distribution of incident electron beam in phantom is one of the factors that affect the calculation accuracy of HPBM, especially in field edge areas near the end of the electron range. A new fitted formula based on Monte Carlo (MC) simulation data for electron beams with energy range of 6-20 MeV in the homogeneous water phantom is proposed in this paper. The precision of the fitted formula within the scope of the energy was evaluated by comparing the electron dose distribution of ECWG measured data with that obtained from HPBM which took the mean electron energy that calculated by the fitted formula and the existed empirical formula, respectively. The results showed that the accuracy of dose distribution that obtained by the mean electron energy calculated with the fitted formula increased about 1%.
Algorithms ; Electrons ; Humans ; Monte Carlo Method ; Phantoms, Imaging ; Radiotherapy Planning, Computer-Assisted ; Water

Dose calculation algorithms based on the Monte Carlo (MC) method are widely regarded as the most accurate tool available in radiotherapy. The MC simulation in radiotherapy has been split into two parts, the radiation source simulation and patient simulation. In this research, a virtual source for simulating the linear accelerator head was constructed with measurement-driven models. The dependence between the calculation accuracy and the specification of various parameters was studied by comparison between the measurement data and calculation results. It has been shown that the dose profile obtained by MC simulation can be consistent with measurement data, suggesting that the compound effect of primary photons and secondary photons are considered with appropriate parameter specification. The requirement of modeling for MC simulation can be met in clinical conditions.
Computer Simulation ; Humans ; Models, Biological ; Monte Carlo Method ; Phantoms, Imaging ; Radiotherapy Dosage ; Radiotherapy Planning, Computer-Assisted ; methods ; Radiotherapy, Conformal ; methods

As a method of dosimetric verification in radiotherapy, gamma index has been widely used for evaluating dose distribution in research and clinical cases. However, for three-dimensional dose distributions, gamma index calculation is very time consuming for the computers. In this paper, based on a pre-sorting technique, we implement a parallel computing algorithm of gamma index on graphic processing unit (GPU). Dose comparisons are performed for seven cases to test our new implementation. It was shown that the GPU-based gamma index calculations achieved a speedup of ten-folds in comparison with corresponding CPU implementation without losing accuracy. The result showed that utilizing GPU parallel computing to speed up gamma index calculations could be reliable and efficient in the implementation.
Algorithms ; Computer Graphics ; Humans ; Radiometry ; methods ; Radiotherapy Dosage ; Radiotherapy Planning, Computer-Assisted ; methods ; Software

To investigate the γ pass rate limit of plan verification equipment for volumetric modulated arc therapy (VMAT) plan verification and its sensitivity on the opening and closing errors of multi-leaf collimator (MLC), 50 cases of nasopharyngeal carcinoma VMAT plan with clockwise and counterclockwise full arcs were randomly selected. Eight kinds of MLC opening and closing errors were introduced in 10 cases of them, and 80 plans with errors were generated. Firstly, the plan verification was conducted in the form of field-by-field measurement and true composite measurement. The γ analysis with the criteria of 3% dose difference, distance to agreement of 2 mm, 10% dose threshold, and absolute dose global normalized conditions were performed for these fields. Then gradient analysis was used to investigate the sensitivity of field-by-field measurement and true composite measurement on MLC opening and closing errors, and the receiver operating characteristic curve (ROC) was used to investigate the optimal threshold of γ pass rate for identifying errors. Tolerance limits and action limits for γ pass rates were calculated using statistical process control (SPC) method for another 40 cases. The error identification ability using the tolerance limit calculated by SPC method and the universal tolerance limit (95%) were compared with using the optimal threshold of ROC. The results show that for the true composite measurement, the clockwise arc and the counterclockwise arc, the descent gradients of the γ passing rate with per millimeter MLC opening error are 10.61%, 7.62% and 6.66%, respectively, and the descent gradients with per millimeter MLC closing error are 9.75%, 7.36% and 6.37%, respectively. The optimal thresholds obtained by the ROC method are 99.35%, 97.95% and 98.25%, respectively, and the tolerance limits obtained by the SPC method are 98.98%, 97.74% and 98.62%, respectively. The tolerance limit calculated by SPC method is close to the optimal threshold of ROC, both of which could identify all errors of ±2 mm, while the universal tolerance limit can only partially identify them, indicating that the universal tolerance limit is not sensitive on some large errors. Therefore, considering the factors such as ease of use and accuracy, it is suggested to use the true composite measurement in clinical practice, and to formulate tolerance limits and action limits suitable for the actual process of the institution based on the SPC method. In conclusion, it is expected that the results of this study can provide some references for institutions to optimize the radiotherapy plan verification process, set appropriate pass rate limit, and promote the standardization of plan verification.
Humans ; Radiotherapy, Intensity-Modulated ; Immune Tolerance ; Nasopharyngeal Carcinoma ; ROC Curve ; Nasopharyngeal Neoplasms/radiotherapy*