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Fulltext Monte Carlo method with heuristic adjustment for irregularly shaped food product volume measurement

Siswantoro J, Prabuwono AS, Abdullah A, Idrus B

ScientificWorldJournal, 2014;2014:683048.
PMID: 24892069 DOI: 10.1155/2014/683048

Volume measurement plays an important role in the production and processing of food products. Various methods have been proposed to measure the volume of food products with irregular shapes based on 3D reconstruction. However, 3D reconstruction comes with a high-priced computational cost. Furthermore, some of the volume measurement methods based on 3D reconstruction have a low accuracy. Another method for measuring volume of objects uses Monte Carlo method. Monte Carlo method performs volume measurements using random points. Monte Carlo method only requires information regarding whether random points fall inside or outside an object and does not require a 3D reconstruction. This paper proposes volume measurement using a computer vision system for irregularly shaped food products without 3D reconstruction based on Monte Carlo method with heuristic adjustment. Five images of food product were captured using five cameras and processed to produce binary images. Monte Carlo integration with heuristic adjustment was performed to measure the volume based on the information extracted from binary images. The experimental results show that the proposed method provided high accuracy and precision compared to the water displacement method. In addition, the proposed method is more accurate and faster than the space carving method.

Matched MeSH terms: Monte Carlo Method*
Predicting graded young modulus values of Ti alloys modified by ion implantation

Hassan MH

Med J Malaysia, 2004 May;59 Suppl B:164-5.
PMID: 15468869

There has been, and is still, concern about the high elastic modulus of Ti alloys compared to bone. Any reduction in the Young's modulus value of the implant is expected to enhance stress redistribution to the adjacent bone tissues, minimize stress shielding and eventually prolong device lifetime. Dynamic Monte Carlo simulation is used to predict the gradual reduction in Young's modulus values between the bulk of Ti alloys and the modified surface layers due to Ca ion implantation. The simulation can be used as a screening step when applying new alloys and/or coatings.

Matched MeSH terms: Monte Carlo Method
Population pharmacokinetics of orally administered mefloquine in healthy volunteers and patients with uncomplicated Plasmodium falciparum malaria

Reuter SE, Upton RN, Evans AM, Navaratnam V, Olliaro PL

J Antimicrob Chemother, 2015 Mar;70(3):868-76.
PMID: 25377567 DOI: 10.1093/jac/dku430

BACKGROUND: The determination of dosing regimens for the treatment of malaria is largely empirical and thus a better understanding of the pharmacokinetic/pharmacodynamic properties of antimalarial agents is required to assess the adequacy of current treatment regimens and identify sources of suboptimal dosing that could select for drug-resistant parasites. Mefloquine is a widely used antimalarial, commonly given in combination with artesunate.
PATIENTS AND METHODS: Mefloquine pharmacokinetics was assessed in 24 healthy adults and 43 patients with Plasmodium falciparum malaria administered mefloquine in combination with artesunate. Population pharmacokinetic modelling was conducted using NONMEM.
RESULTS: A two-compartment model with a single transit compartment and first-order elimination from the central compartment most adequately described mefloquine concentration-time data. The model incorporated population parameter variability for clearance (CL/F), central volume of distribution (VC/F) and absorption rate constant (KA) and identified, in addition to body weight, malaria infection as a covariate for VC/F (but not CL/F). Monte Carlo simulations predict that falciparum malaria infection is associated with a shorter elimination half-life (407 versus 566 h) and T>MIC (766 versus 893 h).
CONCLUSIONS: This is the first known population pharmacokinetic study to show falciparum malaria to influence mefloquine disposition. Protein binding, anaemia and other factors may contribute to differences between healthy individuals and patients. As VC/F is related to the earlier portion of the concentration-time profiles, which occurs during acute malaria, and CL/F is more related to the terminal phase during convalescence after treatment, this may explain why malaria was found to be a covariate for VC/F but not CL/F.

Matched MeSH terms: Monte Carlo Method
Fulltext Population pharmacokinetic meta-analysis of individual data to design the first randomized efficacy trial of vancomycin in neonates and young infants

Jacqz-Aigrain E, Leroux S, Thomson AH, Allegaert K, Capparelli EV, Biran V, et al.

J Antimicrob Chemother, 2019 08 01;74(8):2128-2138.
PMID: 31049551 DOI: 10.1093/jac/dkz158

OBJECTIVES: In the absence of consensus, the present meta-analysis was performed to determine an optimal dosing regimen of vancomycin for neonates.
METHODS: A 'meta-model' with 4894 concentrations from 1631 neonates was built using NONMEM, and Monte Carlo simulations were performed to design an optimal intermittent infusion, aiming to reach a target AUC0-24 of 400 mg·h/L at steady-state in at least 80% of neonates.
RESULTS: A two-compartment model best fitted the data. Current weight, postmenstrual age (PMA) and serum creatinine were the significant covariates for CL. After model validation, simulations showed that a loading dose (25 mg/kg) and a maintenance dose (15 mg/kg q12h if <35 weeks PMA and 15 mg/kg q8h if ≥35 weeks PMA) achieved the AUC0-24 target earlier than a standard 'Blue Book' dosage regimen in >89% of the treated patients.
CONCLUSIONS: The results of a population meta-analysis of vancomycin data have been used to develop a new dosing regimen for neonatal use and to assist in the design of the model-based, multinational European trial, NeoVanc.

Matched MeSH terms: Monte Carlo Method
Fulltext Robust Wavelength Selection Using Filter-Wrapper Method and Input Scaling on Near Infrared Spectral Data

Silalahi DD, Midi H, Arasan J, Mustafa MS, Caliman JP

Sensors (Basel), 2020 Sep 03;20(17).
PMID: 32899292 DOI: 10.3390/s20175001

The extraction of relevant wavelengths from a large dataset of Near Infrared Spectroscopy (NIRS) is a significant challenge in vibrational spectroscopy research. Nonetheless, this process allows the improvement in the chemical interpretability by emphasizing the chemical entities related to the chemical parameters of samples. With the complexity in the dataset, it may be possible that irrelevant wavelengths are still included in the multivariate calibration. This yields the computational process to become unnecessary complex and decreases the accuracy and robustness of the model. In multivariate analysis, Partial Least Square Regression (PLSR) is a method commonly used to build a predictive model from NIR spectral data. However, in the PLSR method and common commercial chemometrics software, there is no standard wavelength selection procedure applied to screen the irrelevant wavelengths. In this study, a new robust wavelength selection procedure called the modified VIP-MCUVE (mod-VIP-MCUVE) using Filter-Wrapper method and input scaling strategy is introduced. The proposed method combines the modified Variable Importance in Projection (VIP) and modified Monte Carlo Uninformative Variable Elimination (MCUVE) to calculate the scale matrix of the input variable. The modified VIP uses the orthogonal components of Partial Least Square (PLS) in investigating the informative variable in the model by applying the amount of variation both in X and y{SSX,SSY}, simultaneously. The modified MCUVE uses a robust reliability coefficient and a robust tolerance interval in the selection procedure. To evaluate the superiority of the proposed method, the classical VIP, MCUVE, and autoscaling procedure in classical PLSR were also included in the evaluation. Using artificial data with Monte Carlo simulation and NIR spectral data of oil palm (Elaeis guineensis Jacq.) fruit mesocarp, the study shows that the proposed method offers advantages to improve model interpretability, to be computationally extensive, and to produce better model accuracy.

Matched MeSH terms: Monte Carlo Method
Self-Organizing Traffic Flow Prediction with an Optimized Deep Belief Network for Internet of Vehicles

Goudarzi S, Kama MN, Anisi MH, Soleymani SA, Doctor F

Sensors (Basel), 2018 Oct 15;18(10).
PMID: 30326567 DOI: 10.3390/s18103459

To assist in the broadcasting of time-critical traffic information in an Internet of Vehicles (IoV) and vehicular sensor networks (VSN), fast network connectivity is needed. Accurate traffic information prediction can improve traffic congestion and operation efficiency, which helps to reduce commute times, noise and carbon emissions. In this study, we present a novel approach for predicting the traffic flow volume by using traffic data in self-organizing vehicular networks. The proposed method is based on using a probabilistic generative neural network techniques called deep belief network (DBN) that includes multiple layers of restricted Boltzmann machine (RBM) auto-encoders. Time series data generated from the roadside units (RSUs) for five highway links are used by a three layer DBN to extract and learn key input features for constructing a model to predict traffic flow. Back-propagation is utilized as a general learning algorithm for fine-tuning the weight parameters among the visible and hidden layers of RBMs. During the training process the firefly algorithm (FFA) is applied for optimizing the DBN topology and learning rate parameter. Monte Carlo simulations are used to assess the accuracy of the prediction model. The results show that the proposed model achieves superior performance accuracy for predicting traffic flow in comparison with other approaches applied in the literature. The proposed approach can help to solve the problem of traffic congestion, and provide guidance and advice for road users and traffic regulators.

Matched MeSH terms: Monte Carlo Method
Fulltext Tailoring bismuth borate glasses by incorporating PbO/GeO2 for protection against nuclear radiation

Kumar A, Jain A, Sayyed MI, Laariedh F, Mahmoud KA, Nebhen J, et al.

Sci Rep, 2021 Apr 08;11(1):7784.
PMID: 33833308 DOI: 10.1038/s41598-021-87256-1

Nuclear radiation shielding capabilities for a glass series 20Bi2O3 - xPbO - (80 - 2x)B2O3 - xGeO2 (where x = 5, 10, 20, and 30 mol%) have been investigated using the Phy-X/PSD software and Monte Carlo N-Particle transport code. The mass attenuation coefficients (μm) of selected samples have been estimated through XCOM dependent Phy-X/PSD program and MCNP-5 code in the photon-energy range 0.015-15 MeV. So obtained μm values are used to calculate other γ-ray shielding parameters such as half-value layer (HVL), mean-free-path (MFP), etc. The calculated μm values were found to be 71.20 cm2/g, 76.03 cm2/g, 84.24 cm2/g, and 90.94 cm2/g for four glasses S1 to S4, respectively. The effective atomic number (Zeff)values vary between 69.87 and 17.11 for S1 or 75.66 and 29.11 for S4 over 0.05-15 MeV of photon-energy. Sample S4, which has a larger PbO/GeO2 of 30 mol% in the bismuth-borate glass, possesses the lowest MFP and HVL, providing higher radiation protection efficiency compared to all other combinations. It shows outperformance while compared the calculated parameters (HVL and MFP) with the commercial shielding glasses, different alloys, polymers, standard shielding concretes, and ceramics. Geometric Progression (G-P) was applied for evaluating the energy absorption and exposure buildup factors at energies 0.015-15 MeV with penetration depths up to 40 mfp. The buildup factors showed dependence on the MFP and photon-energy as well. The studied samples' neutron shielding behavior was also evaluated by calculating the fast neutron removal cross-section (ΣR), i.e. found to be 0.139 cm-1 for S1, 0.133 cm-1 for S2, 0.128 cm-1 for S3, and 0.12 cm-1 for S4. The results reveal a great potential for using a glass composite sample S4 in radiation protection applications.

Matched MeSH terms: Monte Carlo Method
Fulltext Using 157Gd doped carbon and 157GdF4 nanoparticles in proton-targeted therapy for effectiveness enhancement and thermal neutron reduction: a simulation study

Tabbakh F, Hosmane NS, Tajudin SM, Ghorashi AH, Morshedian N

Sci Rep, 2022 Oct 18;12(1):17404.
PMID: 36258012 DOI: 10.1038/s41598-022-22429-0

There are two major problems in proton therapy. (1) In comparison with the gamma-ray therapy, proton therapy has only ~ 10% greater biological effectiveness, and (2) the risk of the secondary neutrons in proton therapy is another unsolved problem. In this report, the increase of biological effectiveness in proton therapy has been evaluated with better performance than 11B in the presence of two proposed nanomaterials of 157GdF4 and 157Gd doped carbon with the thermal neutron reduction due to the presence of 157Gd isotope. The present study is based on the microanalysis calculations using GEANT4 Monte Carlo tool and GEANT4-DNA package for the strand breaks measurement. It was found that the proposed method will increase the effectiveness corresponding to the alpha particles by more than 100% and also, potentially will decrease the thermal neutrons fluence, significantly. Also, in this work, a discussion is presented on a significant contribution of the secondary alpha particles in total effectiveness in proton therapy.

Matched MeSH terms: Monte Carlo Method
Application of parallel ensemble Monte Carlo technique in charge dynamics simulation

Othman A, Umar R, Gopir G

Sains Malaysiana, 2008;37.

In the past, simulating charge dynamics in solid state devices, such as current mobility, transient current drift velocities are done on mainframe systems or on high performance computing facilities. This is due to the fact that, such simulations are costly in terms of computational requirements when implemented on a single processor-based personal computers (PCs). When simulating charge dynamics, large ensembles of particles are usually preferred, such as exceeding 40000 particles, to ensure a numerically sound result. When implementing this type of simulation on a single processor PCs using the conventional ensemble or single particle Monte Carlo method, the computational time is very long even on the fast 2.0 MHz PCs. Lately, a more efficient, easily made available tools and cost effective solution to this problem is the application of an array of PCs employed in a parallel application. This is done using a computer cluster network in a master-slave model. In this paper we report the development of a LINUX cluster for the purpose of implementing parallel ensemble Monte Carlo modelling for solid states device. We have proposed the use of Parallel Virtual Machine (PVM) standards when running the parallel algorithm of the ensemble MC simulation. Some results of the development are also presented in this paper.

Matched MeSH terms: Monte Carlo Method
Analysis of t-year return level for partial duration rainfall series

Ling WS, Noriszura Ismail

Sains Malaysiana, 2012;41:1389-1401.

This paper aims to estimate the Generalized Pareto Distribution (GPD) parameters and predicts the T-year return levels of extreme rainfall events using the Partial Duration Series (PDS) method based on the hourly rainfall data of five stations in Peninsular Malaysia. In particular, the GPD parameters are estimated using five methods namely the method of Moments (MOM), the probability weighted moments (PWM), the L-moments (LMOM), the Trimmed L-moments (TLMOM) and the Maximum Likelihood (ML) and the performance of the T-year return level of each estimation method is analyzed based on the RMSE measure obtained from Monte Carlo simulation. In addition, we suggest the weighted average model, a model which assigns the inverse variance of several methods as weights, to estimate the T-year return level. This paper contributes to the hydrological literatures in terms of three main elements. Firstly, we suggest the use
of hourly rainfall data as an alternative to provide a more detailed and valuable information for the analysis of extreme rainfall events. Secondly, this study applies five methods of parametric approach for estimating the GPD parameters and predicting the T-year return level. Finally, in this study we propose the weighted average model, a model that assigns the inverse variance of several methods as weights, for the estimation of the T-year return level.

Matched MeSH terms: Monte Carlo Method
Preliminary study on bayesian extreme rainfall analysis: a case study of Alor Setar, Kedah, Malaysia

Annazirin Eli, Mardhiyyah Shaffie, Wan Zawiah W

Sains Malaysiana, 2012;41:1403-1410.

Statistical modeling of extreme rainfall is essential since the results can often facilitate civil engineers and planners to estimate the ability of building structures to survive under the utmost extreme conditions. Data comprising of annual maximum series (AMS) of extreme rainfall in Alor Setar were fitted to Generalized Extreme Value (GEV) distribution using method of maximum likelihood (ML) and Bayesian Markov Chain Monte Carlo (MCMC) simulations. The weakness of ML method in handling small sample is hoped to be tackled by means of Bayesian MCMC simulations in this study. In order to obtain the posterior densities, non-informative and independent priors were employed. Performances of parameter estimations were verified by conducting several goodness-of-fit tests. The results showed that Bayesian MCMC method was slightly better than ML method in estimating GEV parameters.

Matched MeSH terms: Monte Carlo Method
Performance of two-samples pseudo-median procedure

Nor Aishah Ahad, Sharipah Soaad Syed Yahaya, Abdul Rahman Othman

Sains Malaysiana, 2012;41:1149-1154.

This article investigates the performance of two-sample pseudo-median based procedure in testing differences between groups. The procedure is a modification of the one-sample Wilcoxon procedure using the pseudo-median of differences between group values as the central measure of location. The test was conducted on two groups with moderate sample
sizes of symmetric and asymmetric distributions. The performance of the procedure was measured in terms of Type I error and power rates computed via Monte Carlo methods. The performance of the procedure was compared against the t-test and Mann-Whitney-Wilcoxon test. The findings from this study revealed that the pseudo-median procedure performed very
well in controlling Type I error rates close to the nominal value. The pseudo-median procedure outperformed the MannWhitney-Wilcoxon test and is comparable to the t-test in controlling Type I error and maintaining adequate power.

Matched MeSH terms: Monte Carlo Method
A unit root test based on the modified least squares estimator

Wararit Panichkitkosolkul

Sains Malaysiana, 2014;43:1623-1633.

A unit root test based on the modified least squares (MLS) estimator for first-order autoregressive process is proposed and compared with unit root tests based on the ordinary least squares (OLS), the weighted symmetric (WS) and the modified weighted symmetric (MWS) estimators. The percentiles of the null distributions of the unit root test are also reported. The empirical probabilities of type I error and powers of the unit root tests were estimated via Monte Carlo simulation. The simulation results showed that all unit root tests can control the probability of type I error for all situations. The empirical power of the test is higher than the other unit root tests, and Apart from that, the and tests also provide the highest empirical power. As an illustration, the monthly series of U.S. nominal interest rates on three-month treasury bills is analyzed.

Matched MeSH terms: Monte Carlo Method
Sensitivity analysis of the refinement to the mann-whitney test

Abdul Rahman Othman, Lai CH

Sains Malaysiana, 2014;43:1095-1100.

The aim of researchers when comparing two independent groups is to collect large normally distributed samples unless they lack the resources to access them. In these situations, there are a myriad of non-parametric tests to select, of which the Mann Whitney U test is the most commonly used. In spite of its great advantages of usage, the U test is capable of producing inflated Type I error when applied in situation of heterogeneity or distinct variances. This current study will present a viable alternative called the refined Mann-Whitney test (RMW). A Monte Carlo evaluation test is conducted on RMW using artificial data of various combinations of extreme test conditions. This study reviews that the RMW test justified its development by enhancing the performance of the U test. The RMW test is able to control well its Type I error rates even though it has a lower power.

Matched MeSH terms: Monte Carlo Method
Stochastic lead time demand estimation via Monte Carlo simulation technique in supply chain planning

Mahdavi M, Mahdavi M

Sains Malaysiana, 2014;43:629-636.

This paper considers a Monte Carlo simulation based method for estimating cycle stocks (production lot-sizing stocks) in a typical batch production system, where a variety of products is scheduled for production at determined periods of time. Delivery time is defined as the maximum lead time and pre-assembly processing time of the product's raw materials in the method. The product's final assembly cycle and delivery time, which were obtained via the production schedule and supply chain simulation, respectively, were both considered to estimate the demand distribution of product based on total duration. Efficient random variates generators were applied to model the lead time of the supply chain's stages. In order to support the performance reliability of the proposed method, a real case study is conducted and numerically analyzed.

Matched MeSH terms: Monte Carlo Method
A monte carlo simulation study on high leverage collinearity-enhancing observation and its effect on multicollinearity pattern

Habshah Midi, Bagheri A, Rahmatullah Imon A

Sains Malaysiana, 2011;40:1437-1447.

Outliers in the X-direction or high leverage points are the latest known source of multicollinearity. Multicollinearity is a nonorthogonality of two or more explanatory variables in multiple regression models, which may have important influential impacts on interpreting a fitted regression model. In this paper, we performed Monte Carlo simulation studies to achieve two main objectives. The first objective was to study the effect of certain magnitude and percentage of high leverage points, which are two important issues in tending the high leverage points to be collinearity-enhancing observations, on the multicollinarity pattern of the data. The second objective was to investigate in which situations these points do make different degrees of multicollinearity, such as moderate or severe. According to the simulation results, high leverage points should be in large magnitude for at least two explanatory variables to guarantee that they are the cause of multicollinearity problems. We also proposed some practical Lower Bound (LB) and Upper Bound (UB) for High Leverage Collinearity Influential Measure (HLCIM) which is an essential measure in detecting the degree of multicollinearity. A well-known example is used to confirm the simulation results.

Matched MeSH terms: Monte Carlo Method
Fulltext Cost-effectiveness of assisted reproductive technologies in Saudi Arabia: Comparing in vitro fertilization with intrauterine insemination

Almaslami F, Aljunid SM

SAGE Open Med, 2020;8:2050312120931988.
PMID: 32587695 DOI: 10.1177/2050312120931988

Objectives: The aim of this study was to compare the cost-effectiveness of in vitro fertilization and intrauterine insemination for the management of unexplained, mild male and mild female factor infertility in Saudi Arabia.
Methods: A cost-effectiveness analysis from a societal perspective was conducted for couples seeking assisted reproductive technology services between January and December 2016 in one of the largest private hospitals in Saudi Arabia. Activity-Based Costing and Step-Down Costing methodologies with expert interviews were used to compute the costs of in vitro fertilization and intrauterine insemination. A total of 710 assisted reproductive technology procedures were observed by the embryologist in charge. The costs calculated included direct and indirect costs. A cost-effectiveness analysis and a Monte Carlo simulation probabilistic sensitivity analysis were conducted.
Results: The average cost per in vitro fertilization and intrauterine insemination cycle was SR 27,360 (range: SR 19,541-29,618) and SR 10,143 (range: SR 7568-11,976), respectively, and the live birth rate per initiated in vitro fertilization and intrauterine insemination cycle was 20.7% and 7.9%, respectively, resulting in an average cost per live birth per in vitro fertilization and intrauterine insemination treatment cycle of SR 132,174 (95% confidence interval: 120,802-143,546) and SR 128,392 (95% confidence interval: 124,468-132,316), respectively. The incremental cost-effectiveness ratio was SR 134,508 per extra live birth implicit in a decision to treat with in vitro fertilization. Probabilistic sensitivity analysis confirms the robustness of the cost-effectiveness results.
Conclusion: This study found that from a societal perspective, one in vitro fertilization treatment cycle was more cost-effective than intrauterine insemination in Saudi Arabia.

Matched MeSH terms: Monte Carlo Method
Biological polymeric shielding design for an X-ray laboratory using Monte Carlo codes

Tajudin SM, Tabbakh F

Radiol Phys Technol, 2019 Sep;12(3):299-304.
PMID: 31302871 DOI: 10.1007/s12194-019-00522-w

Photon irradiation facilities are often shielded using lead despite its toxicity and high cost. In this study, three Monte Carlo codes, EGS5, MCNPX, and Geant4, were utilized to investigate the efficiency of a relatively new polymeric base compound (CnH2n), as a radiation shielding material for photons with energies below 150 keV. The proposed compound with the densities of 6 and 8 g cm-3 were doped with the weight percentages of 8.0 and 15.0% gadolinium. The probabilities of photoelectric effect and Compton scattering were relatively equal at low photon energies, thus the shielding design was optimized using three Monte Carlo codes for the conformity of calculation results. Consequently, 8% Gd-doped polymer with thickness less than 2 cm and density of 6 g cm-3 was adequate for X-ray room shielding to attenuate more than 95% of the 150-keV incident photons. An average dose rate reduction of 88% can be achieved to ensure safety of the radiation area.

Matched MeSH terms: Monte Carlo Method*
Photon dose rate distribution inside and outside a brachytherapy room

Aminordin Sabri AH, Mohamad Tajudin S, Abdul Aziz MZ, Furuta T

Radiol Phys Technol, 2023 Mar;16(1):109-117.
PMID: 36729272 DOI: 10.1007/s12194-023-00703-8

In a brachytherapy room irradiated with an Iridium-192 (192Ir) source, the spatial distributions of photon dose rates were measured and calculated for the dose distribution both inside and outside the room. The spatial distributions were measured using a thermoluminescent dosimeter (LiF-100) on the surfaces of the concrete walls and barriers of the irradiation room. The calculations were performed using the particle and heavy ion transport code system (PHITS) by considering the detailed model of the brachytherapy room and the radiation source used in the measurements. The measured and calculated doses exhibited a similar distribution pattern within and outside the brachytherapy room. To reduce the edge effect at the entrance door, the addition of a 3-mm thick lead layer on the surface of the concrete wall on the left doorstop is recommended. For the 60Co source, with the existing walls and lead door thickness, the dose at the control console and in front of the entrance maze increased by a factor of approximately 60.

Matched MeSH terms: Monte Carlo Method
Skin dose measurements using radiochromic films, TLDS and ionisation chamber and comparison with Monte Carlo simulation

Alashrah S, Kandaiya S, Maalej N, El-Taher A

Radiat Prot Dosimetry, 2014 Dec;162(3):338-44.
PMID: 24300340 DOI: 10.1093/rpd/nct315

Estimation of the surface dose is very important for patients undergoing radiation therapy. The purpose of this study is to investigate the dose at the surface of a water phantom at a depth of 0.007 cm as recommended by the International Commission on Radiological Protection and International Commission on Radiation Units and Measurement with radiochromic films (RFs), thermoluminescent dosemeters and an ionisation chamber in a 6-MV photon beam. The results were compared with the theoretical calculation using Monte Carlo (MC) simulation software (MCNP5, BEAMnrc and DOSXYZnrc). The RF was calibrated by placing the films at a depth of maximum dose (d(max)) in a solid water phantom and exposing it to doses from 0 to 500 cGy. The films were scanned using a transmission high-resolution HP scanner. The optical density of the film was obtained from the red component of the RGB images using ImageJ software. The per cent surface dose (PSD) and percentage depth dose (PDD) curve were obtained by placing film pieces at the surface and at different depths in the solid water phantom. TLDs were placed at a depth of 10 cm in a solid water phantom for calibration. Then the TLDs were placed at different depths in the water phantom and were exposed to obtain the PDD. The obtained PSD and PDD values were compared with those obtained using a cylindrical ionisation chamber. The PSD was also determined using Monte Carlo simulation of a LINAC 6-MV photon beam. The extrapolation method was used to determine the PSD for all measurements. The PSD was 15.0±3.6% for RF. The TLD measurement of the PSD was 16.0±5.0%. The (0.6 cm(3)) cylindrical ionisation chamber measurement of the PSD was 50.0±3.0%. The theoretical calculation using MCNP5 and DOSXYZnrc yielded a PSD of 15.0±2.0% and 15.7±2.2%. In this study, good agreement between PSD measurements was observed using RF and TLDs with the Monte Carlo calculation. However, the cylindrical chamber measurement yielded an overestimate of the PSD. This is probably due to the ionisation chamber calibration factor that is only valid in charged particle equilibrium condition, which is not achieved at the surface in the build-up region.

Matched MeSH terms: Monte Carlo Method*

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