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Electron beam irradiation on novel coronavirus (COVID-19): A Monte-Carlo simulation.

ABSTRACT: The novel coronavirus pneumonia triggered by COVID-19 is now raging the whole world. As a rapid and reliable killing COVID-19 method in industry, electron beam irradiation can interact with virus molecules and destroy their activity. With the unexpected appearance and quickly spreading of the virus, it is urgently necessary to figure out the mechanism of electron beam irradiation on COVID-19. In this study, we establish a virus structure and molecule model based on the detected gene sequence of Wuhan patient, and calculate irradiated electron interaction with virus atoms via a Monte Carlo simulation that track each elastic and inelastic collision of all electrons. The characteristics of irradiation damage on COVID-19, atoms' ionizations and electron energy losses are calculated and analyzed with regions. We simulate the different situations of incident electron energy for evaluating the influence of incident energy on virus damage. It is found that under the major protecting of an envelope protein layer, the inner RNA suffers the minimal damage. The damage for a ∼100-nm-diameter virus molecule is not always enhanced by irradiation energy monotonicity, for COVID-19, the irradiation electron energy of the strongest energy loss damage is 2 keV.

SUBMITTER: Feng G

PROVIDER: S-EPMC7351116 | biostudies-literature | 2020 Apr

REPOSITORIES: biostudies-literature

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Electron beam irradiation on novel coronavirus (COVID-19): A Monte-Carlo simulation.

Feng Guobao G Liu Lu L Cui Wanzhao W Wang Fang F

Chinese physics B = Zhongguo wu li B 20200401 4

The novel coronavirus pneumonia triggered by COVID-19 is now raging the whole world. As a rapid and reliable killing COVID-19 method in industry, electron beam irradiation can interact with virus molecules and destroy their activity. With the unexpected appearance and quickly spreading of the virus, it is urgently necessary to figure out the mechanism of electron beam irradiation on COVID-19. In this study, we establish a virus structure and molecule model based on the detected gene sequence of ...[more]

PMID: 34191933

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Project description:A recently introduced brachytherapy system for partial breast irradiation, MammoSite, consists of a balloon applicator filled with contrast solution and a catheter for insertion of an 192Ir high-dose-rate (HDR) source. In using this system, the treatment dose is typically prescribed to be delivered 1 cm from the balloon's surface. Most treatment-planning systems currently in use for brachytherapy procedures use water-based dosimetry with no correction for heterogeneity. Therefore, these systems assume that full scatter exists regardless of the amount of tissue beyond the prescription line. This assumption might not be a reasonable one, especially when the tissue beyond the prescription line is thin. In such a case, the resulting limited scatter could cause an underdose to be delivered along the prescription line. We used Monte Carlo simulations to investigate how the thickness of the tissue between the surface of the balloon and the skin or lung affected the treatment dose delivery. Calculations were based on a spherical water phantom with a diameter of 30 cm and balloons with diameters of 4 cm, 5 cm, and 6 cm. The dose modification factor is defined as the ratio of the dose rate at the typical prescription distance of 1 cm from the balloon's surface with full scatter obtained using the water phantom to the dose rate with a finite tissue thickness (from 0 cm to 10 cm) beyond the prescription line. The dose modification factor was found to be dependent on the balloon diameter and was 1.098 for the 4-cm balloon and 1.132 for the 6-cm balloon with no tissue beyond the prescription distance at the breast-skin interface. The dose modification factor at the breast-lung interface was 1.067 for the 4-cm balloon and 1.096 for the 6-cm balloon. Even 5 cm of tissue beyond the prescription distance could not result in full scatter. Thus, we found that considering the effect of diminished scatter is important to accurate dosimetry. Not accounting for the dose modification factor may result in delivering a lower dose than is prescribed.

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 .

Dataset Information

Electron beam irradiation on novel coronavirus (COVID-19): A Monte-Carlo simulation.

Publications

Electron beam irradiation on novel coronavirus (COVID-19): A Monte-Carlo simulation.

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