Simulation of Siemens ONCOR™ Expression linear accelerator using phase space in the MCNPX code

Monte Carlo Simulation for the Radixact™ Tomotherapy Linac Using EGSnrc

Purpose

When exact information regarding the treatment head and initial electron beam is available, the Monte Carlo (MC) approach can properly simulate any linear accelerator. However, manufacturers seldom offer information such as the incident electron beam's energy, radial intensity (spot size), or angular spread. This research aims to forecast these features and verify an MC-simulated linear accelerator model using measurements.

Materials and Methods

The BEAMnrc code simulated a 6 MV photon beam from a Radixact™ Tomotherapy Linac. Percentage depth dose and beam profile calculations were conducted using DOSYXZnrc by various electron energies and spot sizes and compared to measurements using a Gamma index with two distinct criterion sets. Furthermore, the fine-tuned electron energy and spot size profiles were created to minimize any disparities using distinct angle spreads. Finally, the output factors (OFs) for various field sizes were compared.

Results

The MC model's fine-tuned electron energy was determined to be 5.8 MeV, with 88.6% of the calculation points passing the 1%/1 mm γ test. A circular radial intensity of 1.4 mm best represented the 6 MV photon beam regarding spot size. Furthermore, a mean angular spread of 0.05 reduced the disparity in cross-field profile between computation and measurement. The most considerable disparities between the MC model OFs and observations were 1.5%.

Conclusion

Using the BEAMnrc code, a reliable MC model of the Radixact™ Tomotherapy Linac can be created, as shown in this paper. This model can be used to compute dose distributions with confidence.

Dosimetric verification of lung phantom calculated by collapsed cone convolution: A Monte Carlo and experimental evaluation

OBJECTIVE

To evaluate the dose calculation accuracy in the Prowess Panther treatment planning system (TPS) using the collapsed cone convolution (CCC) algorithm.

METHODS

The BEAMnrc Monte Carlo (MC) package was used to predict the dose distribution of photon beams produced by the Oncor® linear accelerator (linac). The MC model of an 18 MV photon beam was verified by measurement using a p-type diode dosimeter. Percent depth dose (PDD) and dose profiles were used for comparison based on three field sizes: 5×5, 10×10, and 20×20cm2. The accuracy of the CCC dosimetry was also evaluated using a plan composed of a simple parallel-opposed field (11×16cm2) in a lung phantom comprised of four tissue simulating media namely, lung, soft tissue, bone and spinal cord. The CCC dose calculation accuracy was evaluated by MC simulation and measurements according to the dose difference and 3D gamma analysis. Gamma analysis was carried out through comparison of the Monte Carlo simulation and the TPS calculated dose.

RESULTS

Compared to the dosimetric results measured by the Farmer chamber, the CCC algorithm underestimated dose in the planning target volume (PTV), right lung and lung-tissue interface regions by about -0.11%, -1.6 %, and -2.9%, respectively. Moreover, the CCC algorithm underestimated the dose at the PTV, right lung and lung-tissue interface regions in the order of -0.34%, -0.4% and -3.5%, respectively, when compared to the MC simulation. Gamma analysis results showed that the passing rates within the PTV and heterogeneous region were above 59% and 76%. For the right lung and spinal cord, the passing rates were above 80% for all gamma criteria.

CONCLUSIONS

This study demonstrates that the CCC algorithm has potential to calculate dose with sufficient accuracy for 3D conformal radiotherapy within the thorax where a significant amount of tissue heterogeneity exists.

Equivalent dose calculation in simulation of lung cancer treatment and analysis of dose distribution profile

Currently, lung cancer is one of the most lethal types of cancer (IARC, 2012), the pathology being detected in advanced stage, when the tumor has considerable volume because the disease in most cases asymptomatic in the early stages (INCA, 2016). Dosimetry analysis of healthy organs under real conditions is not feasible. Therefore, computational simulations are used to aid in dose verification in organs of patients submitted to radiotherapy. The goal of this study was to calculate the equivalent dose, due to photons, in the surrounding of healthy organs of patients submitted to radiotherapy for lung cancer, through computational modeling. The simulation was performed using the MCNPX code (MNCPX, 2006), Rex and Regina phantoms (ICRP 110, 2009), radiotherapy room, Siemens Oncor Expression accelerator operating at 6 MV and treatment protocol adopted at the INCA (National Cancer Institute - Brazil). The results obtained, considering the dose due to photons for both phantoms indicate that organs located inside the thoracic cavity received higher dose, being the bronchi, heart and esophagus more affected, due to their anatomical positioning. Clinical data describe the development of bronchiolitis, esophagitis and cardiomyopathies with decreased cardiopulmonary function as one of the major effects of lung cancer treatment. In the Regina phantom, the second largest dose was in the region of the breasts with 615.73 mSv/Gy, while in the Rex the dose was 514.06 mSv/Gy, event related to the difference of anatomical structure of the organ. A qualitative analysis was performed between the dose deposition profile of the treatment planning system and the simulated treatment through the tmesh command and a similar profile of dose distribution was verified throughout the patient's body.

Conversion coefficients for determination of dispersed photon dose during radiotherapy: NRUrad input code for MCNP

Radiotherapy is a common cancer treatment module, where a certain amount of dose will be delivered to the targeted organ. This is achieved usually by photons generated by linear accelerator units. However, radiation scattering within the patient’s body and the surrounding environment will lead to dose dispersion to healthy tissues which are not targets of the primary radiation. Determination of the dispersed dose would be important for assessing the risk and biological consequences in different organs or tissues. In the present work, the concept of conversion coefficient (F) of the dispersed dose was developed, in which F = (D_d/D_t), where D_d was the dispersed dose in a non-targeted tissue and D_t is the absorbed dose in the targeted tissue. To quantify D_d and D_t, a comprehensive model was developed using the Monte Carlo N-Particle (MCNP) package to simulate the linear accelerator head, the human phantom, the treatment couch and the radiotherapy treatment room. The present work also demonstrated the feasibility and power of parallel computing through the use of the Message Passing Interface (MPI) version of MCNP5.