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Evaluation of an electron Monte Carlo dose calculation algorithm for electron beam.

ABSTRACT: The electron Monte Carlo (eMC) dose calculation algorithm of the Eclipse treatment planning system is based heavily upon Monte Carlo simulation of the linac head and modeling of the linac beam characteristics with minimal measurement of beam data. Commissioning of the eMC algorithm on multiple identical linacs provided a unique opportunity to systematically evaluate the algorithm with actual measurements of clinically relevant beam and dose parameters. In this study, measured and eMC calculated dose distributions were compared both along and perpendicular to electron beam direction for electron energy/applicator/depth combination using measurement data from four Varian 21EX CLINAC linear accelerator (Varian Medical System, Palo Alto, CA). Cutout factors for sizes down to 3 x 3 cm were also compared. Comparisons between the measurement and the eMC calculated values show that the R90, R80, R50, and R10 values mostly agree within 3 mm. Measure and Calculated bremsstrahlung dose Dx correlates well statistically although eMC calculated Dx values are consistently smaller than the measured, with maximum discrepancy of 1% for the 20 MeV electron beams. Surface dose agrees mostly within 2%. Field width and penumbra agree mostly within 3mm. Calculation grid size is found to have a significant effect on the dose calculation. A grid size of 5 mm can produce erroneous dose distributions. Using a grid size of 2.5 mm and a 3% accuracy specified for the eMC to stop calculation iteration, the absolute output agrees with measurements within 3% for field sizes of 5 x 5 cm or larger. For cutout of 3 x 3 cm, however, the output disagreement can reach 8%. Our result indicate that eMC algorithm in Eclipse provides acceptable agreement with measurement data for most clinical situations. Calculation grid size of 2.5 mm or smaller is recommended.

SUBMITTER: Hu YA

PROVIDER: S-EPMC5722292 | biostudies-literature | 2008 Jun

REPOSITORIES: biostudies-literature

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Evaluation of an electron Monte Carlo dose calculation algorithm for electron beam.

Hu Ye Angela YA Song Haijun H Chen Zhe Z Zhou Sumin S Yin Fang-Fang FF

Journal of applied clinical medical physics 20080623 3

The electron Monte Carlo (eMC) dose calculation algorithm of the Eclipse treatment planning system is based heavily upon Monte Carlo simulation of the linac head and modeling of the linac beam characteristics with minimal measurement of beam data. Commissioning of the eMC algorithm on multiple identical linacs provided a unique opportunity to systematically evaluate the algorithm with actual measurements of clinically relevant beam and dose parameters. In this study, measured and eMC calculated ...[more]

PMID: 18716583

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Project description:Stereotactic body radiation therapy (SBRT) has been increasingly used as an efficacious treatment modality for early-stage non-small cell lung cancer. The accuracy of dose calculations is compromised due to the presence of inhomogeneity. For the purpose of a consistent prescription, radiation doses were calculated without heterogeneity correction in several RTOG trials. For patients participating in these trials, recalculations of the planned doses with more accurate dose methods could provide better correlations between the treatment outcomes and the planned doses. Using a Monte Carlo (MC) dose calculation algorithm as a gold standard, we compared the recalculated doses with the MC algorithm to the original pencil beam (PB) calculations for our institutional clinical lung SBRT plans. The focus of this comparison is to investigate the volume and location dependence on the differences between the two dose calculations. Thirty-one clinical plans that followed RTOG and other protocol guidelines were retrospectively investigated in this study. Dosimetric parameters, such as D1, D95, and D99 for the PTV and D1 for organs at risk, were compared between two calculations. Correlations of mean lung dose and V20 of lungs between two calculations were investigated. Significant dependence on tumor size and location was observed from the comparisons between the two dose calculation methods. When comparing the PB calculations without heterogeneity correction to the MC calculations with heterogeneity correction, we found that in terms of D95 of PTV: (1) the two calculations resulted in similar D95 for edge tumors with volumes greater than 25.1 cc; (2) an average overestimation of 5% in PB calculations for edge tumors with volumes less than 25.1 cc; and (3) an average overestimation of 9% or underestimation of 3% in PB calculations for island tumors with volumes smaller or greater than 22.6 cc, respectively. With heterogeneity correction, the PB calculations resulted in an average reduction of 23.8% and 15.3% in the D95 for the PTV for island and edge lesions, respectively, when compared to the MC calculations. For organs at risks, very small differences were found among all the comparisons. Excellent correlations for mean dose and V20 of lungs were observed between the two calculations. This study demonstrated that using a single scaling factor may be overly simplified when accounting for the effects of heterogeneity correction. Accurate dose calculations, such as the Monte Carlo algorithms, are highly recommended to understand dose responses in lung SBRT.

Project description:Purpose/objectivesMonte Carlo (MC) dose calculation has appeared in primary commercial treatment-planning systems and various in-house platforms. Dual-energy computed tomography (DECT) and metal artifact reduction (MAR) techniques complement MC capabilities. However, no publications have yet reported how proton therapy centers implement these new technologies, and a national survey is required to determine the feasibility of including MC and companion techniques in cooperative group clinical trials.Materials/methodsA 9-question survey was designed to query key clinical parameters: scope of MC utilization, validation methods for heterogeneities, clinical site-specific imaging guidance, proton range uncertainties, and how implants are handled. A national survey was distributed to all 29 operational US proton therapy centers on 13 May 2019.ResultsWe received responses from 25 centers (86% participation). Commercial MC was most commonly used for primary plan optimization (16 centers) or primary dose evaluation (18 centers), while in-house MC was used more frequently for secondary dose evaluation (7 centers). Based on the survey, MC was used infrequently for gastrointestinal, genitourinary, gynecology and extremity compared with other more heterogeneous disease sites (P < .007). Although many centers had published DECT research, only 3/25 centers had implemented DECT clinically, either in the treatment-planning system or to override implant materials. Most centers (64%) treated patients with metal implants on a case-by-case basis, with a variety of methods reported. Twenty-four centers (96%) used MAR images and overrode the surrounding tissue artifacts; however, there was no consensus on how to determine metal dimension, materials density, or stopping powers.ConclusionThe use of MC for primary dose calculation and optimization was prevalent and, therefore, likely feasible for clinical trials. There was consensus to use MAR and override tissues surrounding metals but no consensus about how to use DECT and MAR for human tissues and implants. Development and standardization of these advanced technologies are strongly encouraged for vendors and clinical physicists.

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Project description:BackgroundAny Monte Carlo simulation of dose delivery using medical accelerator-generated megavolt photon beams begins by simulating electrons of the primary electron beam interacting with a target. Because the electron beam characteristics of any single accelerator are unique and generally unknown, an appropriate model of an electron beam must be assumed before MC simulations can be run. The purpose of the present study is to develop a flexible framework with suitable regression models for estimating parameters of the model of primary electron beam in simulators of medical linear accelerators using real reference dose profiles measured in a water phantom.MethodsAll simulations were run using PRIMO MC simulator. Two regression models for estimating the parameters of the simulated primary electron beam, both based on machine learning, were developed. The first model applies Principal Component Analysis to measured dose profiles in order to extract principal features of the shapes of the these profiles. The PCA-obtained features are then used by Support Vector Regressors to estimate the parameters of the model of the electron beam. The second model, based on deep learning, consists of a set of encoders processing measured dose profiles, followed by a sequence of fully connected layers acting together, which solve the regression problem of estimating values of the electron beam parameters directly from the measured dose profiles. Results of the regression are then used to reconstruct the dose profiles based on the PCA model. Agreement between the measured and reconstructed profiles can be further improved by an optimization procedure resulting in the final estimates of the parameters of the model of the primary electron beam. These final estimates are then used to determine dose profiles in MC simulations.ResultsAnalysed were a set of actually measured (real) dose profiles of 6 MV beams from a real Varian 2300 C/D accelerator, a set of simulated training profiles, and a separate set of simulated testing profiles, both generated for a range of parameters of the primary electron beam of the Varian 2300 C/D PRIMO simulator. Application of the two-stage procedure based on regression followed by reconstruction-based minimization of the difference between measured (real) and reconstructed profiles resulted in achieving consistent estimates of electron beam parameters and in a very good agreement between the measured and simulated photon beam profiles.ConclusionsThe proposed framework is a readily applicable and customizable tool which may be applied in tuning virtual primary electron beams of Monte Carlo simulators of linear accelerators. The codes, training and test data, together with readout procedures, are freely available at the site: https://github.com/taborzbislaw/DeepBeam .

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Evaluation of an electron Monte Carlo dose calculation algorithm for electron beam.

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Evaluation of an electron Monte Carlo dose calculation algorithm for electron beam.

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