Evaluation of a commercial electron treatment planning system based on Monte Carlo techniques (eMC)

Auto-commissioning of a Monte Carlo electron beam model with application to photon MLC shaped electron fields

Objective.Presently electron beam treatments are delivered using dedicated applicators. An alternative is the usage of the already installed photon multileaf collimator (pMLC) enabling efficient electron treatments. Currently, the commissioning of beam models is a manual and time-consuming process. In this work an auto-commissioning procedure for the Monte Carlo (MC) beam model part representing the beam above the pMLC is developed for TrueBeam systems with electron energies from 6 to 22 MeV.Approach.The analytical part of the electron beam model includes a main source representing the primary beam and a jaw source representing the head scatter contribution each consisting of an electron and a photon component, while MC radiation transport is performed for the pMLC. The auto-commissioning of this analytical part relies on information pre-determined from MC simulations, in-air dose profiles and absolute dose measurements in water for different field sizes and source to surface distances (SSDs). For validation calculated and measured dose distributions in water were compared for different field sizes, SSDs and beam energies for eight TrueBeam systems. Furthermore, a sternum case in an anthropomorphic phantom was considered and calculated and measured dose distributions were compared at different SSDs.Main results.Instead of the manual commissioning taking up to several days of calculation time and several hours of user time, the auto-commissioning is carried out in a few minutes. Measured and calculated dose distributions agree generally within 3% of maximum dose or 2 mm. The gamma passing rates for the sternum case ranged from 96% to 99% (3% (global)/2 mm criteria, 10% threshold).Significance.The auto-commissioning procedure was successfully implemented and applied to eight TrueBeam systems. The newly developed user-friendly auto-commissioning procedure allows an efficient commissioning of an MC electron beam model and eases the usage of advanced electron radiotherapy utilizing the pMLC for beam shaping.

Empirical method for modeling the percent depth dose curves of electron beam in radiation therapy

Introduction: This study presents an empirical method to model the electron beam percent depth dose curve (PDD) using the primary and tail functions in radiation therapy. The modeling parameters N and n can be used to derive the depth relative stopping power of the electron energy in radiation therapy.

Methods and Materials: The electrons PDD curves were modeled with the primary-tail function in this study. The primary function included exponential function and main parameters of N, µ while the tail function was composed by a sigmoid function with the main parameter of n. The PDD for five electron energies were modeled by the primary and tail function by adjusting the parameters of N, µ and n. The R50 and Rp can be derived from the modeled straight line of 80% to 20% region of PDD. The same electron energy with different cone sizes was also modeled with the primary-tail function. The stopping power for different electron energies at different depths can also be derived from the parameters of N, µ and n. Percent ionization depth curve can then be derived from the percent depth dose by dividing its depth relevant stopping power for comparing with the original water phantom measurement.

Results: The main parameters N, n increase, but µ decreases in primary-tail function when electron energy increased. The relationship of parameters n, N and LN(-µ) with electron energy are n = 31.667 E0 - 88, N = 0.9975 E0 - 2.8535, LN(-µ) = -0.1355 E0 - 6.0986, respectively. Stopping power of different electron energy can be derived from n and N with the equation: stopping power = (−0.042 ln N E 0 + 1.072)e(−n−E0·5·10−5+0.0381·d), where d is the depth in water. Percent depth dose was derived from the percent reading curve by multiplying the stopping power relevant to the depth in water at certain electron energy.

Conclusion: The PDD of electrons at different energies and field sizes can be modeled with an empirical model to deal with the stopping power calculation. The primary-tail equation provides a uncomplicated solution than a pencil beam or other numerical algorism for investigators to research the behavior of electron beam in radiation therapy.

The Study of Field Equivalence Determined by the Modeled Percentage Depth Dose in Electron Beam Radiation Therapy

Introduction

This study presents an empirical method to model the curve of electron beam percent depth dose (PDD) by using the primary-tail function in electron beam radiation therapy. The modeling parameters N and n can be used to predict the minimal side length when the field size is reduced below that required for lateral scatter equilibrium (LSE) in electron radiation therapy.

Methods and Materials

The electrons' PDD curves were modeled by the primary-tail function in this study. The primary function included the exponential function and the main parameters of N and μ, while the tail function was composed of a sigmoid function with the main parameter of n. The PDD of five electron energies was modeled by the primary and tail function by adjusting the parameters of N, μ, and n. The R₅₀ and R_p can be derived from the modeled straight line of 80% to 20% region of PDD. The same electron energy with different cone sizes was also modeled by the primary-tail function. The stopping power of different electron energies in different depths can also be derived from the parameters N, μ, and n.

Results

The main parameters N and n increase but μ decreases in the primary-tail function for characterizing the electron beam PDD when the electron energy increased. The relationship of parameter n, N, and ln(−μ) with electron energy are n = 31.667E₀ − 88, N = 0.9975E₀ − 2.8535, and ln(−μ) = −0.1355E₀ − 6.0986, respectively. Percent depth dose was derived from the percent reading curve by multiplying the stopping power relevant to the depth in water at a certain electron energy. The stopping power of different electron energies can be derived from n and N with the following equation: stopping power = (−0.042ln(N_E0) + 1.072)e^{(−n_E0 · 5 · 10−5 + 0.0381)·x}, where x is the depth in water. The lateral scatter equivalence (LSE) of the clinical electron beam can be described by the parameters E₀, n, and N in the equation of S_eq = (n_E0 − N_E0)^0.288/(E₀/n_E0)^0.0195. The LSE was compared with the root mean square scatter angular distribution method and shows the agreement of depth dose distributions within ±2%.

Conclusions

The PDD of the electron beam at different energies and cone sizes can be modeled with an empirical model to deal with what is the minimal field size without changing the percent depth dose when approximate LSE is given in centimeters of water.

Dosimetric Comparison of Treatment Plans Computed With Finite Size Pencil Beam and Monte Carlo Algorithms Using the InCise™ Multileaf Collimator-Equipped Cyberknife® System

Purpose:

InCise™ multileaf collimator (MLC) was introduced for CyberKnife^® (CK) Robotic Radiosurgery System (CK-MLC) in 2015, and finite size pencil beam (FSPB) was the only available dose computation algorithm for treatment plans of CK-MLC system. The more advanced Monte Carlo (MC) dose calculation algorithm of lnCise™ was initially released in 2017 for the CK Precision™ treatment planning system (TPS) (v1.1) with new graphic processing unit (GPU) platform. GPU based TPS of the CK offers more accurate, faster treatment planning time and intuitive user interface with smart three-dimensional editing tools and fully automated autosegmentation tools. The MC algorithm used in CK TPS simulates the energy deposited by each individual photon and secondary particles to calculate more accurate dose. In the present study, the dose disparities between MC and FSPB algorithms for selected Stereotactic Ablative Radiation Therapy (SABR) CK-MLC treatment plans are quantified.

Materials and Methods:

A total of 80 CK-MLC SABR plans computed with FSPB were retrospectively reviewed and compared with MC computed results, including plans for detached lung cancer (or tumors fully surrounded by lung tissues, n = 21), nondetached lung cancer (or tumor touched the chest wall or mediastinum, n = 23), intracranial (n = 21), and pancreas lesions (n = 15). Dosimetric parameters of each planning target volume and major organs at risk (OAR) are compared in terms of normalized percentage deviations (N_dev).

Results:

This study revealed an average of 24.4% overestimated D₉₅ values in plans using FSPB over MC for detached lung (n = 21) and 14.9% for nondetached lung (n = 23) lesions. No significant dose differences are found in intracranial (0.3%, n = 21) and pancreatic (0.9%, n = 15) cases. Furthermore, no significant differences were found in N_dev of OARs.

Conclusion:

In this study, it was found that FSPB overestimates dose to inhomogeneous treatment sites. This indicates, the employment of MC algorithm in CK-MLC-based lung SABR treatment plans is strongly suggested.

Beam modeling and beam model commissioning for Monte Carlo dose calculation-based radiation therapy treatment planning: Report of AAPM Task Group 157

Dose calculation plays an important role in the accuracy of radiotherapy treatment planning and beam delivery. The Monte Carlo (MC) method is capable of achieving the highest accuracy in radiotherapy dose calculation and has been implemented in many commercial systems for radiotherapy treatment planning. The objective of this task group was to assist clinical physicists with the potentially complex task of acceptance testing and commissioning MC-based treatment planning systems (TPS) for photon and electron beam dose calculations. This report provides an overview on the general approach of clinical implementation and testing of MC-based TPS with a specific focus on models of clinical photon and electron beams. Different types of beam models are described including those that utilize MC simulation of the treatment head and those that rely on analytical methods and measurements. The trade-off between accuracy and efficiency in the various source-modeling approaches is discussed together with guidelines for acceptance testing of MC-based TPS from the clinical standpoint. Specific recommendations are given on methods and practical procedures to commission clinical beam models for MC-based TPS.

Convolution-based modified Clarkson integration (CMCI) for electron cutout factor calculation

Electron therapy is widely used to treat shallow tumors because of its characteristic sharp dose fall‐off beyond a certain range. A customized cutout is typically applied to block radiation to normal tissues. Determining the final monitor unit (MU) for electron treatment requires an output factor for the cutout, which is usually generated by measurement, especially for highly irregular cutouts. However, manual measurement requires a lengthy quality assurance process with possible errors. This work presents an accurate and efficient cutout output factor prediction model, convolution‐based modified Clarkson integration (CMCI), to replace patient‐specific output factor measurement. Like the Clarkson method, we decompose the field into basic sectors. Unlike the Clarkson integration method, we use annular sectors for output factor estimation. This decomposition method allows calculation via convolution. A 2D distribution of fluence is generated, and the output factor at any given point can be obtained. We applied our method to 10 irregularly shaped cutouts for breast patients for 6E, 9E, and 15E beams and compared the results with measurements and the electron Monte Carlo (eMC) calculation using the Eclipse planning system. While both the CMCI and eMC methods showed good agreement with chamber measurements and film measurements in relative distributions at the nominal source to surface distance (SSD) of 100 cm, eMC generated larger errors than the CMCI method at extended SSDs, with up to −9.28% deviations from the measurement for 6E beam. At extended SSD, the mean absolute errors of our method relative to measurements were 0.92 and 1.14, while the errors of eMC were 1.42 and 1.79 for SSD 105 cm and 110 cm, respectively. These results indicate that our method is more accurate than eMC, especially for low‐energy beams, and can be used for MU calculation and as a QA tool for electron therapy.

Dosimetric validation of Monaco treatment planning system on an Elekta VersaHD linear accelerator

The purpose of this study is to perform dosimetric validation of Monaco treatment planning system version 5.1. The Elekta VersaHD linear accelerator with high dose rate flattening filter‐free photon modes and electron energies was used in this study. The dosimetric output of the new Agility head combined with the FFF photon modes warranted this investigation into the dosimetric accuracy prior to clinical usage. A model of the VersaHD linac was created in Monaco TPS by Elekta using commissioned beam data including percent depth dose curves, beam profiles, and output factors. A variety of 3D conformal fields were created in Monaco TPS on a combined Plastic water/Styrofoam phantom and validated against measurements with a calibrated ion chamber. Some of the parameters varied including source to surface distance, field size, wedges, gantry angle, and depth for all photon and electron energies. In addition, a series of step and shoot IMRT, VMAT test plans, and patient plans on various anatomical sites were verified against measurements on a Delta⁴ diode array. The agreement in point dose measurements was within 2% for all photon and electron energies in the homogeneous phantom and within 3% for photon energies in the heterogeneous phantom. The mean ± SD gamma passing rates of IMRT test fields yielded 93.8 ± 4.7% based on 2% dose difference and 2 mm distance‐to‐agreement criteria. Eight previously treated IMRT patient plans were replanned in Monaco TPS and five measurements on each yielded an average gamma passing rate of 95% with 6.7% confidence limit based on 3%, 3 mm gamma criteria. This investigation on dosimetric validation ensures accuracy of modeling VersaHD linac in Monaco TPS thereby improving patient safety.

Full Monte Carlo and measurement-based overall performance assessment of improved clinical implementation of eMC algorithm with emphasis on lower energy range

New version 13.6.23 of the electron Monte Carlo (eMC) algorithm in Varian Eclipse™ treatment planning system has a model for 4MeV electron beam and some general improvements for dose calculation. This study provides the first overall accuracy assessment of this algorithm against full Monte Carlo (MC) simulations for electron beams from 4MeV to 16MeV with most emphasis on the lower energy range. Beams in a homogeneous water phantom and clinical treatment plans were investigated including measurements in the water phantom. Two different material sets were used with full MC: (1) the one applied in the eMC algorithm and (2) the one included in the Eclipse™ for other algorithms. The results of clinical treatment plans were also compared to those of the older eMC version 11.0.31. In the water phantom the dose differences against the full MC were mostly less than 3% with distance-to-agreement (DTA) values within 2mm. Larger discrepancies were obtained in build-up regions, at depths near the maximum electron ranges and with small apertures. For the clinical treatment plans the overall dose differences were mostly within 3% or 2mm with the first material set. Larger differences were observed for a large 4MeV beam entering curved patient surface with extended SSD and also in regions of large dose gradients. Still the DTA values were within 3mm. The discrepancies between the eMC and the full MC were generally larger for the second material set. The version 11.0.31 performed always inferiorly, when compared to the 13.6.23.

A Review of Radiotherapy-Induced Late Effects Research after Advanced Technology Treatments

The number of incident cancers and long-term cancer survivors is expected to increase substantially for at least a decade. Advanced technology radiotherapies, e.g., using beams of protons and photons, offer dosimetric advantages that theoretically yield better outcomes. In general, evidence from controlled clinical trials and epidemiology studies are lacking. To conduct these studies, new research methods and infrastructure will be needed. In the paper, we review several key research methods of relevance to late effects after advanced technology proton-beam and photon-beam radiotherapies. In particular, we focus on the determination of exposures to therapeutic and stray radiation and related uncertainties, with discussion of recent advances in exposure calculation methods, uncertainties, in silico studies, computing infrastructure, electronic medical records, and risk visualization. We identify six key areas of methodology and infrastructure that will be needed to conduct future outcome studies of radiation late effects.

Comparison of CCC and ETAR dose calculation algorithms in pituitary adenoma radiation treatment planning; Monte Carlo evaluation

Aims

To verify the accuracy of two common absorbed dose calculation algorithms in comparison to Monte Carlo (MC) simulation for the planning of the pituitary adenoma radiation treatment.

Materials and methods

After validation of Linac's head modelling by MC in water phantom, it was verified in Rando phantom as a heterogeneous medium for pituitary gland irradiation. Then, equivalent tissue-air ratio (ETAR) and collapsed cone convolution (CCC) algorithms were compared for a conventional three small non-coplanar field technique. This technique uses 30 degree physical wedge and 18 MV photon beams.

Results

Dose distribution findings showed significant difference between ETAR and CCC of delivered dose in pituitary irradiation. The differences between MC and dose calculation algorithms were 6.40 ± 3.44% for CCC and 10.36 ± 4.37% for ETAR. None of the algorithms could predict actual dose in air cavity areas in comparison to the MC method.

Conclusions

Difference between calculation and true dose value affects radiation treatment outcome and normal tissue complication probability. It is of prime concern to select appropriate treatment planning system according to our clinical situation. It is further emphasised that MC can be the method of choice for clinical dose calculation algorithms verification.

Monte Carlo simulation of electron modes of a Siemens Primus linac (8, 12 and 14 MeV)

Background

Electron mode is used for treatment of superficial tumours in linac-based radiotherapy.

Purpose

The aim of present study is simulation of 8, 12 and 14 MeV electrons from a Siemens Primus linac using MCNPX Monte Carlo (MC) code and verification of the results based on comparison of the results with the measured data.

Materials and methods

Electron mode for 8, 12 and 14 MeV electron energies of a Siemens Primus linac was simulated using MCNPX MC code. Percent depth dose (PDD) data for 10 × 10, 15 × 15 and 25 × 25 cm2 applicators obtained from MC simulations were compared with the corresponding measured data.

Results

Gamma index values were less than unity in most of points for all the above-mentioned energies and applicators. However, for 25 × 25 cm2 applicator in 8 MeV energy, 10 × 10 cm2 applicator and 15 × 15 cm2 applicator in 14 MeV energy, there were four data points with gamma indices higher than unity. However among these data points, there are a number of cases with relatively large value of gamma index, these cases are positioned on the bremsstrahlung tail of the PDD curve which is not normally used in treatment planning.

Conclusion

There was good agreement between the results of MC simulations developed in this study and the measured values. The obtained simulation programmes can be used in dosimetry of electron mode of Siemens Primus linac in the cases in which it is not easily feasible to perform experimental in-phantom measurements.

Monte Carlo dose calculation improvements for low energy electron beams using eMC

The electron Monte Carlo (eMC) dose calculation algorithm in Eclipse (Varian Medical Systems) is based on the macro MC method and is able to predict dose distributions for high energy electron beams with high accuracy. However, there are limitations for low energy electron beams. This work aims to improve the accuracy of the dose calculation using eMC for 4 and 6 MeV electron beams of Varian linear accelerators. Improvements implemented into the eMC include (1) improved determination of the initial electron energy spectrum by increased resolution of mono-energetic depth dose curves used during beam configuration; (2) inclusion of all the scrapers of the applicator in the beam model; (3) reduction of the maximum size of the sphere to be selected within the macro MC transport when the energy of the incident electron is below certain thresholds. The impact of these changes in eMC is investigated by comparing calculated dose distributions for 4 and 6 MeV electron beams at source to surface distance (SSD) of 100 and 110 cm with applicators ranging from 6 x 6 to 25 x 25 cm(2) of a Varian Clinac 2300C/D with the corresponding measurements. Dose differences between calculated and measured absolute depth dose curves are reduced from 6% to less than 1.5% for both energies and all applicators considered at SSD of 100 cm. Using the original eMC implementation, absolute dose profiles at depths of 1 cm, d(max) and R50 in water lead to dose differences of up to 8% for applicators larger than 15 x 15 cm(2) at SSD 100 cm. Those differences are now reduced to less than 2% for all dose profiles investigated when the improved version of eMC is used. At SSD of 110 cm the dose difference for the original eMC version is even more pronounced and can be larger than 10%. Those differences are reduced to within 2% or 2 mm with the improved version of eMC. In this work several enhancements were made in the eMC algorithm leading to significant improvements in the accuracy of the dose calculation for 4 and 6 MeV electron beams of Varian linear accelerators.

Verification of a commercial implementation of the Macro-Monte-Carlo electron dose calculation algorithm using the virtual accelerator approach

In this work, the accuracy of the implementation of the Macro Monte Carlo electron dose calculation algorithm into the radiation therapy treatment planning system Eclipse is evaluated. This implementation - called eMC - uses a particle source based on the Rotterdam Initial Phase-Space model. A three-dimensional comparison of eMC calculated dose to dose distributions resulting from full treatment head simulations with the Monte Carlo code package EGSnrc is performed using the 'virtual accelerator' approach. Calculated dose distributions are compared for a homogeneous tissue equivalent phantom and a water phantom with air and bone inhomogeneities. The performance of the eMC algorithm in both phantoms can be considered acceptable within the 2%/2 mm Gamma index criterion. A systematic underestimation of dose by the eMC algorithm within the air inhomogeneity is found.