Evaluation of the conformity of intensity-modulated radiation therapy and volumetric modulated arc therapy using AAPM TG 119 protocol
Dang Thi Minh Tam, Phan Long Ho, Phan Quoc Uy, Nguyen Trung Hieu, Vo Tan Linh, Nguyen Thi Hoa, Nguyen Thi The Lam, Bui Thi Thuy Nga, Truong Huu Thanh, Tran Thien Thanh, Chau Van Tao
Radiation and Environmental Biophysics
Abstract:
The aim of this work was to evaluate the conformity of intensity-modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT), and verify the accuracy of the planning and delivery system used in this work based on the AAPM TG-119 protocol. The Eclipse 13.6 treatment planning system (TPS) was used to plan the TG-119 test suite, which included four test cases: MultiTarget, Prostate, Head/Neck, and C-Shape for IMRT and VMAT techniques with 6 MV and 10 MV acceleration voltages. The results were assessed and discussed in terms of the TG-119 protocol and the results of previous studies. In addition, point dose and planar dose measurements were done using a semiflex ion chamber and an electronic portal imaging device (EPID), respectively. The planned doses of all test cases met the criteria of the TG-119 protocol, except those for the spinal cord of the C-Shape hard case. There were no significant differences between the treatment planning doses and the doses given in the TG-119 report, with p-values ranging from 0.974 to 1 (p > 0.05). Doses to the target volumes were similar in the IMRT and VMAT plans, but the organs at risk (OARs) doses were different depending on the test case. The planning results showed that IMRT is more conformal than VMAT in certain cases. For the point dose measurements, the confidence limit (CLpoint) of 0.030 and 0.021 were better than the corresponding values of 0.045 and 0.047 given in the TG-119 report for high-dose and low-dose areas, respectively. Regarding the planar dose measurements, the CLplanar value of 0.38 obtained in this work was lower than that given in the TG-119 report (12.4). It is concluded that the dosimetry measurements performed in this study showed better confidence limits than those provided in the TG 119 report. IMRT remains more conformal in certain circumstances than the more progressive VMAT. Whenselecting the method of delivering a dose to the patient, several factors must be considered, including the radiotherapy technique, energy, treatment site, and tumour geometry.
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Evaluating coincidence summing factor using marinelli beaker on coaxial HPGe detector by Monte Carlo simulation and calculating
Le Hoang Minh, Le Quang Vuong, Tran Thien Thanh, Chau Van Tao
Nucl. Sci. and Tech., Vol.12, No. 1 (2022), pp. 49-55
Abstract:
This investigation aims to compare the full energy peak efficiencies in the energy range of 46-1836 keV on a type-p coaxial HPGe and estimate the coincidence summing factor for the case of Marinelli Beaker samples used by two general Monte-Carlo simulation software MCNP and PENELOPE. The radioactive nuclides used in determining the coincidence summing factor include 22Na, 60Co, 88Y, 133Ba, 134Cs, 154Eu, and 208Tl, which are prepared in HCl 2M solution and contained in a Marinelli beaker with the source’s volume of 3000 ml. The results demonstrate there is a good agreement between the two simulation software with an average discrepancy of 1.3%. On the other hand, the simulation coincidence summing factor values are also compared with the results from the calculating software ETNA with an average discrepancy of approximately 3.1%.
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Estimation of Thickness Samples Using Gamma Scattering Techniques Based on Machine Learning Approach
Huynh Thanh Nhan, Le Hoang Minh, Vo Hoang Nguyen, Nguyen Duy Thong, Tran Thien Thanh, Chau Van Tao
IEEJ Transactions on Sensors and Micromachines
Abstract:
Gamma-ray scattering is a powerful method in the non-destructive testing field. Many researches related to gamma-ray scattering is being used in the world. Gamma-ray scattering can be used to determine thickness, structure as well as components in a material. Along with computer science, application of computer science in many scientific fields may constitute good achievements such as precision and speed of data analysis. In this paper, Machine learning is being used in gamma-ray scattering to determine thickness of material based on gamma-ray spectrum. To provide a dataset for machine learning, Monte Carlo was used for Ti, Mn, Fe, Co, Cu, Zn samples from 1mm to 50mm. In Machine learning, 8th-degree polynomial regression method is used.
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Bui Ngoc Thien, Vu Ngoc Ba, Nguyen Thi Thao Vy, Truong Thi Hong Loan
Chemosphere Volume 259, November 2020, 127432
Abstract:
In this study, soil-to-plant transfer factor and annual organ equivalent dose due to ingestion of natural radionuclides in 13 popular food crop samples in Ho Chi Minh city, Vietnam were estimated. The obtained data show that the radioactive elements transported from soil to plants play an essential role as indicators for the nutritional needs of plant and the ability to accumulate radioisotopes and heavy metal elements for environmental decontamination. It is found that B. alba and C. gigantean is useful for decontamination of high content potassium in soil, otherwise, P. fruticosa and C. gigantean may be used for soil with high concentration of 210Pb and 226Ra. In addition, biological effects of the plant ingestion in human body were assessed. The doses due to ingestion of food crop samples varied from organ to organ, depending on the organotrophic properties of the radionuclides. For examples, equivalent dose for 40K in large intestine is higher than other organs. In contrast, equivalent dose for 238U, 226Ra, 210Pb and 232Th were mostly at bone surface. In general, the obtained dose values of lower than the average value recommended by UNSCEAR for food crop ingestion pose no threat to the public’s health. However, close investigations are needed in the near future.
Establishment of an experimental system for X-ray fluorescence analysis with excitation using 3H/Zr source: Evaluation and applications
Van Thi Thu Trang, Nguyen Van Hanh, Huynh Truc Phuong
Spectrochimica Acta Part B: Atomic Spectroscopy 205 (2023) 106694
Abstract:
The goal of this study is to establish and assess an experimental apparatus for X-ray fluorescence analysis with elemental excitation in materials using a 3H/Zr source. The limits of detection and quantification, as well as analytical sensitivity, were estimated using a linear curve methodology. Furthermore, accuracy and precision were assessed by quantitatively analyzing the components of the reference material. The limits of detection and quantification of elements such as S, K, Ca, Ti, V, Cr, Mn, Fe, Ni, Cu, Zn, As, Ta, and Pb were estimated to range from 3.7 mg kg-1 to 573 mg kg-1, depending on the analyte. Analytical sensitivities were found to be between 1.2 and 867 cps/%. The measured elemental concentrations in the reference sample were compared with the inductively coupled plasma mass spectrometry method, and all bias (%) values were found to be lower than 10%. This study also determined the levels of Ca, Ti, Mn, and Fe in cement and K, Ca, Cr, Mn, Fe, and Zn in tea leaves. The results showed that the 3H/Zr source could detect and quantify components at concentrations of a few mg kg-1 or higher. X-ray fluorescence spectrometry is suggested for the analysis of the concentration of various elements in environmental, geological, food, and other samples.
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Enhancing Neutron/Gamma Discrimination in the Low-Energy Region for EJ-276 Plastic Scintillation Detector Using Machine Learning
IEEE Transactions on Nuclear Science
Abstract:
Pulse Shape Discrimination (PSD) techniques, particularly the widely employed charge integration ratio method (Q-ratio), have proven effective in discriminating fast neutrons from gamma rays in organic scintillation detectors. However, the effectiveness of Q-ratio diminishes in the low-energy region (below 150 keVee) due to overlapping signal, leading to a suboptimal Figure of Merit (FOM). In this study, we use machine learning (ML) technique, particularly the one-dimensional Convolutional Neural Network (1D-CNN), to enhance the neutron/gamma discrimination and compares the results with the traditional charge integration ratio in the low-energy region. Our investigation focuses on the EJ-276 plastic scintillator, a commercial product of ELJEN technology known for its good separation of gamma and fast neutron signals based on timing characteristics. Experimental data were acquired using 252Cf and 60Co radioisotope sources. A comprehensive comparative analysis between the traditional Q-ratio method and ML algorithms is conducted for the low energy region. Our main objective is to evaluate and enhance neutron/gamma discrimination capabilities of plastic scintillators in this low-energy region.
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