6.3 Monte Carlo codes optimized for radiation therapy and out-of-field doses for small fields

Considering the ability of Monte Carlo techniques to calculate absorbed dose in non-equilibrium conditions, it can be an ideal tool for clinical use. However, due to its lengthy computational sessions, it is difficult to use them in clinic. In the above section, we discussed about the general purpose of Monte Carlo tools which can model different types of particles (gamma, electron, positron, etc.) and different kinds of physics models to simulate the interactions of particles over the large range of energy of incident particles. The introduction of Monte Carlo-based treatment planning systems, which uses some approximations and simplification in comparison to full Monte Carlo codes, can help to overcome the limitations of contemporary TPS. In Monte Carlo-based TPS, a part of dose calculation is performed using Monte Carlo methods, and the remaining part is performed using approximation-based algorithms [123, 124]. Another option is to use Monte Carlo codes that are optimized specially for radiation therapy applications. TG105 report can provide more information about the use of Monte Carlo methods for clinical applications [125]. However, it is possible that the highly efficient Monte Carlo codes that can completely simulate the radiation transport within acceptable timeframe will be still required. Hence, the use of Monte Carlo methods in small-field dosimetry will increase the confidence in the accuracy of calculation of dose distributions.

Apart from the difficulty in calculating dose deposited within the field, TPS algorithms are also not able to calculate the doses out-of-field accurately, since the measurement data obtained to be used for commissioning of TPS extends only a few centimeters beyond the edges of the field. Penumbra region is defined as a region of steep dose fall, where radiation dose falls from 80 to 20% of maximum dose within the field. The dose protruding beyond the field is not considered in the calculation

Prospective Monte Carlo Simulation for Choosing High Efficient Detectors for Small-Field… DOI: http://dx.doi.org/10.5772/intechopen.89150

of the dose distribution or its contribution to the procedure of inverse optimization. Hence, the dose distribution obtained from TPS is expected to be inaccurate in regions beyond the edges of the primary field. The predictions in low-dose regions near the primary field by TPS have been shown to be inaccurate as well. Jang et al. [126] investigated the inaccuracies in dose calculation in low-dose regions for intensity-modulated radiotherapy (IMRT) and reason behind these inaccurate calculations by comparing their results against Monte Carlo methods. Authors reported error up to 25% in low-dose regions and found that the inadequate modeling of transmission through MLC leaves and leaf scatter in TPS to be the main cause of error. In the treatments performed using IMRT techniques, doses of 2 Gy per fraction is delivered over large fractions to deliver a total dose of 60–70 Gy to the tumor volume. However, stereotactic radiotherapy follows hypofractionated regime, in which doses of 10–20 Gy per fraction is delivered. Hence, the dose deposited out-of-field due to each fraction is of concern. Petti et al. [127] investigated the doses outside the treatment field and cause of it for treatment using Cyber Knife and compared them against the doses obtained using Gamma Knife and IMRT for similar treatment. The out-of-field doses were found higher by a factor of two to five for Gamma Knife and by a factor of four for IMRT treatments. According to the authors, the leakage radiation is the main cause of out-of-field doses. Chuang et al. [128] investigated for the reduction in out-of-field doses after installation of shielding upgrade and reported the reduction of 20–50% in out-of-field doses. Comparison of difference in peripheral doses absorbed using different equipment for stereotactic treatment was made by Di Betta et al. [129] and used the data for estimation of risk of stochastic effects. Authors reported that the risk of adverse side effects for treatment using 5 Gy per fraction due out-of-field doses is negligible. Lastly, there are relatively fewer studies available on out-of-field doses due to the small fields. More studies are required on it, which can be helpful to investigate the effects of out-of-field doses.

## 7. Conclusion

chamber IC-10 and attributed this variation to the volume averaging effect of the chamber. Paskalev et al. [115] investigated the dose distribution for circular field (1.5 and 3 mm) for 10 MV photon beam using Varian Clinac-18 and reported maximum variation of 0.3 mm between the measured and calculated 50% isodose surface. Tsougos et al. [116] performed a Monte Carlo-based dosimetric study for in-house developed 6 MV SRT unit and compared it against conventional dosimet-

Theory, Application, and Implementation of Monte Carlo Method in Science and Technology

Cyberknife unit for three different collimator opening diameters ranging from 5 to 10 mm. Comparison was made between the experimental and Monte Carlo results. Heydarian et al. [118] investigated the dosimetric parameters of a SRS linac using experimental measurements and Monte Carlo methods and reported good agreement between the Monte Carlo and experimental data. Scott et al. [29] investigated the effect of source occlusion on output of the linac for small-field sizes and large focal spot sizes and found that output factors are sensitive to the dimensions of the electron spot size hitting the target. Sargison et al. [119] proposed a methodology for measurement and reporting of relative output factors for small fields using both experimental and Monte Carlo methods. In 2014, Sargison et al. [120] presented two scientific quantitative definitions of very small-field size and reported that careful methodology is required for setting of field sizes and placement of detectors for field sizes less than 12 mm for 6 MV photon beams. In 2019, Francescon et al. [121] investigated the sensitivity of dosimetric correction factors to interunit variation and reported variation up to 9% between the measured data corrected using the recommendations of TRS-483 and Monte Carlo results. Casar et al. [122] provided detector-specific output correction factors for small-field sizes using the recom-

6.3 Monte Carlo codes optimized for radiation therapy and out-of-field doses

Considering the ability of Monte Carlo techniques to calculate absorbed dose in non-equilibrium conditions, it can be an ideal tool for clinical use. However, due to its lengthy computational sessions, it is difficult to use them in clinic. In the above section, we discussed about the general purpose of Monte Carlo tools which can model different types of particles (gamma, electron, positron, etc.) and different kinds of physics models to simulate the interactions of particles over the large range of energy of incident particles. The introduction of Monte Carlo-based treatment planning systems, which uses some approximations and simplification in comparison to full Monte Carlo codes, can help to overcome the limitations of contemporary TPS. In Monte Carlo-based TPS, a part of dose calculation is performed using Monte Carlo methods, and the remaining part is performed using approximation-based algorithms [123, 124]. Another option is to use Monte Carlo codes that are optimized specially for radiation therapy applications. TG105 report can provide more information about the use of Monte Carlo methods for clinical applications [125]. However, it is possible that the highly efficient Monte Carlo codes that can

completely simulate the radiation transport within acceptable timeframe will be still required. Hence, the use of Monte Carlo methods in small-field dosimetry will increase the confidence in the accuracy of calculation of dose distributions. Apart from the difficulty in calculating dose deposited within the field, TPS algorithms are also not able to calculate the doses out-of-field accurately, since the measurement data obtained to be used for commissioning of TPS extends only a few centimeters beyond the edges of the field. Penumbra region is defined as a region of steep dose fall, where radiation dose falls from 80 to 20% of maximum dose within the field. The dose protruding beyond the field is not considered in the calculation

ric techniques. Francescon et al. [117] investigated total scatter factor for

mendations of TRS-483.

for small fields

68

Considering the importance of accurate small-field dosimetry, this chapter discusses all important aspects related to it in details. It includes the physics of small radiation fields, cavity theory, and methodology of small-field dosimetry to understand the response of dosimeters and brief discussion on several dosimeters. It also discusses the recommendations of COP for dosimetry of small radiation fields. Moreover, it discusses the small and long cavity theories for computing the accurate dose response. In addition, pencil beam algorithms as a tool for the dose response evaluation is reported, and uses of Monte Carlo simulation in categorizing the primary and scattering components of the radiotherapeutic photon beam are handled. Also this chapter focuses on the application and importance of Monte Carlo techniques in small-field dosimetry and treatment methods that are based on small fields, such as stereotactic treatments and IMRT. Available general purpose Monte Carlo codes used for applications in radiotherapy is also mentioned. Such Monte Carlo codes have the ability to simulate transport of radiation within a medium in great details. EGSnrc, Geant4, PENELOPE, and MCNP are some of the most commonly used Monte Carlo codes for small-field dosimetry studies. Its accurate algorithm to model the transport of radiation and easy-to-use graphical user interface of BEAM code of EGSnrc makes it one of the most widely used MC code. A thorough recent literature review is performed on the small-field dosimetric studies performed using Monte Carlo codes. The studies on out-of-field doses, limitation of contemporary treatment planning systems, use of Monte Carlo codes
