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Results for “Monte Carlo Method”

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PubMed1994

Sister-chromatid exchanges and their distribution in human lymphocytes in relation to age, sex and smoking.

The effects of age, sex and smoking on sister-chromatid exchange (SCE) frequency and distribution in human lymphocytes were assessed by means of multiple linear regression. Differences in SCE scores were associated with all above variables: SCE increased with age and cigarette smoking intensity, and higher SCE frequencies were observed in females. Changes in SCE distribution were associated with age and smoking: the ratio of sample variance to sample mean (heterogeneity index) increased with age and smoking intensity. Cell proliferation kinetics, as measured by replication index, inversely correlated with age. Monte Carlo methods were used to show that in the occupational study, analysis of 20-50 persons per group and 25 cells per person may be recommended.

Adult↗

PubMed1998

Estimating equations with incomplete categorical covariates in the Cox model.

Incomplete covariate data is a common occurrence in many studies in which the outcome is survival time. When a full likelihood is specified, a useful technique for obtaining parameter estimates is the EM algorithm. We propose a set of estimating equations to estimate the parameters of Cox's proportional hazards model when some covariate values are missing. These estimating equations can be solved by an algorithm similar to the EM algorithm. Because of the computational burden of finding a solution to these estimating equations, we propose obtaining parameter estimates via Monte Carlo methods. Asymptotic variances of the parameter estimates are also derived. We present a clinical trials example with three covariates, two of which have some missing values.

Algorithms↗

PubMed2002

Combined segregation and linkage analysis of HLA markers in familial psoriasis.

Marker-based segregation analysis (MBSA) is a modification of a published method of combined linkage and segregation analysis (Am J Hum Genet 51: 1111-1126, 1992), to determine whether a candidate gene known to be associated with the disease of interest is truly segregating with the disease in families. Here we outline the conceptual basis of MBSA and present a Monte Carlo method for significance testing. The method is applied to PSORS1, a locus within the major histocompatibility complex (MHC) for which linkage and linkage disequilibrium with psoriasis has already been demonstrated. The results are very consistent with our current knowledge of PSORS1, and suggest that MBSA can provide useful information on genotype-phenotype relationships such as penetrance and allelic heterogeneity.

Chromosome Mapping↗

PubMed2005

[Bayesian representation of prior information and MCMC method in microwave imaging].

Microwave imaging for dielectric objects was considered in this paper. Applying Bayesian approach to represent prior information about permittivity distribution of observed object by prior probability density and combine measurements information of scattering field, we obtained posterior probability density that included synthetic information about the observed object. And then, Gibbs sampler, one of Markov Chain Monte Carlo method, was used to sample the posterior probability density. The sample mean was regarded as an evaluation of the permittivity distribution. The results of simulation imaging with "blocky" objects showed that this set of methods made good use of information and had the advantages of feasibility and very strong anti-noise ability. In addition,it is capable of describing (definite or indefinite) prior information in a convenient and controllable way, as well as capable of giving the "complete" solution, i.e., the occurrence probability of every permittivity distribution.

Bayes Theorem↗

PubMed1999

Clinical implementation of a Monte Carlo treatment planning system.

The purpose of this study was to implement the Monte Carlo method for clinical radiotherapy dose calculations. We used the EGS4/BEAM code to obtain the phase-space data for 6-20 MeV electron beams and 4, 6, and 15 MV photon beams for Varian Clinac 1800, 2100C, and 2300CD accelerators. A multiple-source model was used to reconstruct the phase-space data for both electron and photon beams, which retained the accuracy of the Monte Carlo beam data. The multiple-source model reduced the phase-space data storage requirement by a factor of 1000 and the accelerator simulation time by a factor of 10 or more. Agreement within 2% was achieved between the Monte Carlo calculations and measurements of the dose distributions in homogeneous and heterogeneous phantoms for various field sizes, source-surface distances, and beam modulations. The Monte Carlo calculated electron output factors were within 2% of the measured values for various treatment fields while the heterogeneity correction factors for various lung and bone phantoms were within 1% for photon beams and within 2% for electron beams. The EGS4/DOSXYZ Monte Carlo code was used for phantom and patient dose calculations. The results were compared to the dose distributions produced by a conventional treatment planning system and an intensity-modulated radiotherapy inverse-planning system. Significant differences (>5% in dose and >5 mm shift in isodose lines) were found between Monte Carlo calculations and the analytical calculations implemented in the commercial systems. Treatment sites showing the largest dose differences were for head and neck, lung, and breast cases.

Algorithms↗

PubMed1989

An epidemiological model of rinderpest. I. Description of the model.

The development of an epidemiological model of rinderpest in cattle and wildlife populations is described. The model uses a state-transition structure, incorporating a stochastic element through the use of Monte-Carlo methods modified to allow large populations to be simulated. The potential applications include the estimation of "safe" host population immunity rates and the design of cost-effective rinderpest vaccination programmes.

Animals↗

PubMed2001

A 4D approach to the analysis of functional brain images: application to FMRI data.

This paper presents a new approach to functional magnetic resonance imaging (FMRI) data analysis. The main difference lies in the view of what comprises an observation. Here we treat the data from one scanning session (comprising t volumes, say) as one observation. This is contrary to the conventional way of looking at the data where each session is treated as t different observations. Thus instead of viewing the v voxels comprising the 3D volume of the brain as the variables, we suggest the usage of the vt hypervoxels comprising the 4D volume of the brain-over-session as the variables. A linear model is fitted to the 4D volumes originating from different sessions. Parameter estimation and hypothesis testing in this model can be performed with standard techniques. The hypothesis testing generates 4D statistical images (SIs) to which any relevant test statistic can be applied. In this paper we describe two test statistics, one voxel based and one cluster based, that can be used to test a range of hypotheses. There are several benefits in treating the data from each session as one observation, two of which are: (i) the temporal characteristics of the signal can be investigated without an explicit model for the blood oxygenation level dependent (BOLD) contrast response function, and (ii) the observations (sessions) can be assumed to be independent and hence inference on the 4D SI can be made by nonparametric or Monte Carlo methods. The suggested 4D approach is applied to FMRI data and is shown to accurately detect the expected signal.

Brain Chemistry↗

PubMedDate not supplied

Height and secular trend in conscripts born in the Central Apennines (Italy), 1865-1972.

OBJECTIVE: The main aim of the research was to evaluate the effects of prolonged isolation on the secular trend of height in an internal zone of the central Apennines (Abruzzo, Province of L'Aquila). METHODS: Personal data for 1006 military conscripts in five sample years from 1865 to 1972 were used. The mean, standard deviation, median, skewness and kurtosis were calculated. Normal distribution of the data was assessed by the Kolmogorov-Smirnov test (Monte Carlo method). Differences between the means were tested by ANOVA and the Tukey test. RESULTS: Mean height increased from 161.3 +/- 5.97 cm in 1865 to 172.6 +/- 6.28 cm in 1972. The increases were slight, but constant, in the first 80 years: between 0.44 and 0.86 cm/decade, but greater thereafter: 2.37 cm/decade between 1945 and 1972. Regarding the frequency distribution, skewness showed negative values only in 1865 (-0.37 +/- 0.21). The Kolmogorov-Smirnov test did not show significance for any period. CONCLUSIONS: The results confirm that the mean heights in south-central Italy, including Abruzzo, were lower than those of the more economically advanced regions of northern Italy in each period. The difference has decreased greatly in the last few generations, but the secular trend is continuing in these communities. This seems to be due to prolonged isolation which has retarded economic development and favoured endogamy and genetic drift. However, it has also prevented the negative effects of wars, since there was no reduction of the secular trend in those periods.

Adolescent↗

PubMed2007

Random changepoint modelling of HIV immunologic responses.

We propose a changepoint model for the analysis of longitudinal CD4 T-cell counts for HIV infected subjects following highly active antiretroviral treatment. The profile of CD4 counts for each subject follows a simple, 'broken stick' changepoint model, with random subject-specific parameters, including the changepoint. The model accounts for baseline covariates. The longitudinal CD4 records are censored at the time of the subject going off-study-treatment. This is a potentially informative drop-out mechanism, which we address by modelling it jointly with the CD4 count outcome. The drop-out model incorporates terms from the CD4 model, including the changepoint. The estimation is done in a Bayesian framework, with implementation via Markov chain Monte Carlo methods in the WinBUGS software. Model selection using DIC indicates that the data support the complex random changepoint and informative censoring model.

Antiretroviral Therapy, Highly Active↗

PubMed1990

Global parameter optimization for cardiac potassium channel gating models.

Quantitative ion channel model evaluation requires the estimation of voltage dependent rate constants. We have tested whether a unique set of rate constants can be reliably extracted from nonstationary macroscopic voltage clamp potassium current data. For many models, the rate constants derived independently at different membrane potentials are not unique. Therefore, our approach has been to use the exponential voltage dependence predicted from reaction rate theory (Stevens, C. F. 1978. Biophys. J. 22:295-306; Eyring, H., S. H. Lin, and S. M. Lin. 1980. Basic Chemical Kinetics. Wiley and Sons, New York) to couple the rate constants derived at different membrane potentials. This constrained the solution set of rate constants to only those that also obeyed this additional set of equations, which was sufficient to obtain a unique solution. We have tested this approach with data obtained from macroscopic delayed rectifier potassium channel currents in voltage-clamped guinea pig ventricular myocyte membranes. This potassium channel has relatively simple kinetics without an inactivation process and provided a convenient system to determine a globally optimized set of voltage-dependent rate constants for a Markov kinetic model. The ability of the fitting algorithm to extract rate constants from the macroscopic current data was tested using "data" synthesized from known rate constants. The simulated data sets were analyzed with the global fitting procedure and the fitted rate constants were compared with the rate constants used to generate the data. Monte Carlo methods were used to examine the accuracy of the estimated kinetic parameters. This global fitting approach provided a useful and convenient method for reliably extracting Markov rate constants from macroscopic voltage clamp data over a broad range of membrane potentials. The limitations of the method and the dependence on initial guesses are described.

Analysis of Variance↗

PubMed1987

Distribution of different fibre types in human skeletal muscles: a method for the detection of neurogenic disorders.

Human skeletal muscles are composed of two distinguishable types of fibres, which in healthy muscles appear to be randomly arranged. Large groups of one fibre type are commonly regarded as evidence of a neuropathological process affecting the peripheral nerves or the nerve cells in the spinal cord. An objective method that detects non-random arrangements as a sign of a neurogenic disorder, particularly in its early stages, could improve diagnosis. The randomness, or otherwise, of the fibre type arrangement is here considered in terms of the numbers of fibres surrounded entirely by others of the same type (enclosed fibres). The distribution of the number of enclosed fibres is studied for a free-sampling model using Monte Carlo methods. The negative binomial distribution is shown to fit closely, where the parameters can be expressed in terms of the number of fibres and the fibre type proportion in a sample area. This result permits the calculation of significance levels for a sample area and the combination of information in several sample areas. Finally, the method is applied to whole cross-sections of 24 male human autopsied muscles.

Humans↗

PubMed2001

Marginal likelihood estimation for proportional odds models with right censored data.

One major aspect in medical research is to relate the survival times of patients with the relevant covariates or explanatory variables. The proportional hazards model has been used extensively in the past decades with the assumption that the covariate effects act multiplicatively on the hazard function, independent of time. If the patients become more homogeneous over time, say the treatment effects decrease with time or fade out eventually, then a proportional odds model may be more appropriate. In the proportional odds model, the odds ratio between patients can be expressed as a function of their corresponding covariate vectors, in which, the hazard ratio between individuals converges to unity in the long run. In this paper, we consider the estimation of the regression parameter for a semiparametric proportional odds model at which the baseline odds function is an arbitrary, non-decreasing function but is left unspecified. Instead of using the exact survival times, only the rank order information among patients is used. A Monte Carlo method is used to approximate the marginal likelihood function of the rank invariant transformation of the survival times which preserves the information about the regression parameter. The method can be applied to other transformation models with censored data such as the proportional hazards model, the generalized probit model or others. The proposed method is applied to the Veteran's Administration lung cancer trial data.

Antineoplastic Agents↗

PubMedDate not supplied

Use of fast Fourier transforms in calculating dose distributions for irregularly shaped fields for three-dimensional treatment planning.

In three-dimensional radiation treatment planning, essentially all fields are irregular and compensated. Consequently, it is important to predict accurately dose for such fields to ensure adequate coverage of the target region and sparing of healthy tissues. Traditional approaches, namely, those involving scatter integration and extended source and those utilizing negatively weighted fields, are inaccurate, especially near the boundaries defined by blocks and collimators. In the method presented in this paper, dose distributions for arbitrarily shaped beams are calculated by two-dimensional convolution of the relative primary photon fluence distributions and kernels representing the cross-sectional profiles of a pencil beam at a series of depths. The pencil beam dose distributions are computed, once and for all, with the Monte Carlo method for photon energy spectrum for each treatment machine. The finite size of the source, which is important for cobalt machines, is also taken into account using convolution of the source with the relative primary fluence distribution. Convolutions are performed using fast Fourier transforms on an array processor. Results of calculations are in excellent agreement with measured data. While no data are presented for fields modified by compensators, the method of calculation should apply at least as well for such fields since the variations in fluence distribution for compensated fields are not as sharp as for points near the block boundaries.

Biophysical Phenomena↗

PubMed2002

Parametric links among Monte Carlo, phase-field, and sharp-interface models of interfacial motion.

Parametric links are made among three mesoscale simulation paradigms: phase-field, sharp-interface, and Monte Carlo. A two-dimensional, square lattice, 1/2 Ising model is considered for the Monte Carlo method, where an exact solution for the interfacial free energy is known. The Monte Carlo mobility is calibrated as a function of temperature using Glauber kinetics. A standard asymptotic analysis relates the phase-field and sharp-interface parameters, and this allows the phase-field and Monte Carlo parameters to be linked. The result is derived without bulk effects but is then applied to a set of simulations with the bulk driving force included. An error analysis identifies the domain over which the parametric relationships are accurate.

Journal Article↗

PubMed1991

Replication index in cultured human lymphocytes: methods for statistical analysis and possible role in genetic toxicology.

The replication index (RI) is an index of cytokinetics in cultured cells. This paper presents statistical methods for the analysis of RI data. It also proposes formulas for the calculation of RI and its standard error. The proposed statistical analysis may be applied only in cases when replicate cultures are used. If duplicate or repeated cultures are used, the interculture variation may provide a more suitable error term for RI. Determining the RI in human blood cultures may be useful in genotoxicity testing, because inhibition of DNA synthesis will result in a decrease of the RI. Monte Carlo methods are used to show that the sensitivity of the proposed method is roughly equivalent to that of a chi 2 test. Power studies indicate that for the study sample, no less than 200 cells should be analyzed when assessing the RI.

Cell Division↗

PubMed2002

Hierarchical Bayesian model for prevalence inferences and determination of a country's status for an animal pathogen.

Certification that a country, region or state is "free" from a pathogen or has a prevalence less than a threshold value has implications for trade in animals and animal products. We develop a Bayesian model for assessment of (i) the probability that a country is "free" of or has an animal pathogen, (ii) the proportion of infected herds in an infected country, and (iii) the within-herd prevalence in infected herds. The model uses test results from animals sampled in a two-stage cluster sample of herds within a country. Model parameters are estimated using modern Markov-chain Monte Carlo methods. We demonstrate our approach using published data from surveys of Newcastle disease and porcine reproductive and respiratory syndrome in Switzerland, and for three simulated data sets.

Animals↗

PubMed2000

Approach to Monte Carlo calculation of the buckling of supercoiled DNA loops.

The short supercoiled circular DNA molecules are shown to be glassy systems and canonical Metropolis Monte Carlo simulations of the systems tend to get stuck in local metastable energy basins. A Monte Carlo algorithm is developed to alleviate the problem of "ergodicity breaking" of the glassy systems, in which the Markov process is driven by an explicitly analytic weight factor with enhanced probability in both low- and high-energy regions. To characterize the degree of puckering of the supercoiled DNA loops, a different quantity of aplanarity is introduced as the shortest principal axis of configurational ellipsoid of DNA. With the suggested Monte Carlo method, the quantitative correlation between supercoiling degree and buckling of DNA is attained. With supercoiling stress increasing, the conformational transition from a circle to mono-, diplo-, or triple interwound superhelical structure will take place in a successive but decreasingly abrupt mode.

Algorithms↗

PubMed2002

A Monte Carlo investigation of fluence profiles collimated by an electron specific MLC during beam delivery for modulated electron radiation therapy.

Modulated electron radiation therapy (MERT) is able to deliver conformal dose to shallow tumors while significantly reducing dose to distal structures and surrounding tissues. An electron specific multileaf collimator (eMLC) has been proposed and constructed as an effective means of delivering electron beams for MERT. The aim of this work is to apply the Monte Carlo method to investigate the fluence profiles collimated by the eMLC in order to achieve accurate beam delivery for MERT. In this work, the EGS4/BEAM code was used to simulate the eMLC collimated electron beams of 6-20 MeV generated from a Varian Clinac 2100C linear accelerator. An attempt was made to describe the fluence profiles with an analytic Sigmoid function. The function parameters were determined by the fittings of the Monte Carlo simulated fluence profiles. How the function parameters depend on the eMLC aperture size, the off-axis location, and the electron beam energy has been investigated. It has been found that the eMLC collimated fluence profiles are dependent on beam energy, while almost independent of leaf location or dimension of MLC aperture. There is little difference in the fluence profiles collimated by the leaf side and the leaf end for the straight-edged leaves. It is possible that these energy-dependent Sigmoid functions can serve as operators to account for the energy dependence of the eMLC collimated fluence profiles. These operators can be incorporated into the inverse planning algorithm to derive desired dose distributions using a set of electron beams of variable energy and field size suitable for delivery by the eMLC.

Computer Simulation↗