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Results for “Monte Carlo Method”

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PubMed2005

Design of radiation shielding for the proton therapy facility at the National Cancer Center in Korea.

The design of radiation shielding was evaluated for a proton therapy facility being established at the National Cancer Center in Korea. The proton beam energy from a 230 MeV cyclotron is varied for therapy using a graphite target. This energy variation process produces high radiation and thus thick shielding walls surround the region. The evaluation was first carried out using analytical expressions at selected locations. Further detailed evaluations have been performed using the Monte Carlo method. Dose equivalent values were calculated to be compared with analytical results. The analytical method generally yielded more conservative values. With consideration of adequate occupancy factors annual dose equivalent rates are kept <1 mSv y(-1) in all areas. Construction of the building is expected to be completed near the end of 2004 and the installation of therapy equipment will begin a few months later.

Computer Simulation↗

PubMed1992

A comparison of several tests for censored paired data.

This paper reviews several tests for censored paired data and uses Monte Carlo methods to evaluate their sizes and powers. Each of the tests maintains its size. The Akritas test and the paired Prentice-Wilcoxon test are somewhat more powerful than the Gehan statistic or the generalized signed rank test for most of the distributions studied. If the survival times follow an exponential distribution, then the Gehan and the generalized signed rank tests are more powerful against a location shift alternative.

Computer Simulation↗

PubMed2002

Spatial modeling of wetland condition in the U.S. Prairie Pothole Region.

We propose a spatial modeling framework for wetland data produced from a remote-sensing-based waterfowl habitat survey conducted in the U.S. Prairie Pothole Region (PPR). The data produced from this survey consist of the area containing water on many thousands of wetland basins (i.e., prairie potholes). We propose a two-state model containing wet and dry states. This model provides a concise description of wet probability, i.e., the probability that a basin contains water, and the amount of water contained in wet basins. The two model components are spatially linked through a common latent effect, which is assumed to be spatially correlated. Model fitting and prediction is carried out using Markov chain Monte Carlo methods. The model primarily facilitates mapping of habitat conditions, which is useful in varied monitoring and assessment capacities. More importantly, the predictive capability of the model provides a rigorous statistical framework for directing management and conservation activities by enabling characterization of habitat structure at any point on the landscape.

Animals↗

PubMed1994

Propagation of uncertainty in risk assessments: the need to distinguish between uncertainty due to lack of knowledge and uncertainty due to variability.

In quantitative uncertainty analysis, it is essential to define rigorously the endpoint or target of the assessment. Two distinctly different approaches using Monte Carlo methods are discussed: (1) the end point is a fixed but unknown value (e.g., the maximally exposed individual, the average individual, or a specific individual) or (2) the end point is an unknown distribution of values (e.g., the variability of exposures among unspecified individuals in the population). In the first case, values are sampled at random from distributions representing various "degrees of belief" about the unknown "fixed" values of the parameters to produce a distribution of model results. The distribution of model results represents a subjective confidence statement about the true but unknown assessment end point. The important input parameters are those that contribute most to the spread in the distribution of the model results. In the second case, Monte Carlo calculations are performed in two dimensions producing numerous alternative representations of the true but unknown distribution. These alternative distributions permit subject confidence statements to be made from two perspectives: (1) for the individual exposure occurring at a specified fractile of the distribution or (2) for the fractile of the distribution associated with a specified level of individual exposure. The relative importance of input parameters will depend on the fractile or exposure level of interest. The quantification of uncertainty for the simulation of a true but unknown distribution of values represents the state-of-the-art in assessment modeling.

Humans↗

PubMed2001

Markov chain Monte Carlo linkage analysis of complex quantitative phenotypes.

We report a Markov chain Monte Carlo analysis of the five simulated quantitative traits in Genetic Analysis Workshop 12 using the Loki software. Our objectives were to determine the efficacy of the Markov chain Monte Carlo method and to test a new scoring technique. Our initial blind analysis, on replicate 42 (the "best replicate") successfully detected four out of the five disease loci and found no false positives. A power analysis shows that the software could usually detect 4 of the 10 trait/gene combinations at an empirical point-wise p-value of 1.5 x 10(-4).

Chromosome Mapping↗

PubMed1997

Visualization of significant differences in somatotopic maps: a distributed t-test.

In order to test for differences in the properties of two populations of cells within a somatotopic map we need to be able to compare data sets in which sampled cells are randomly scattered throughout the map, and the variable being compared varies with location in the map. We can describe cell properties as exponentially smoothed surfaces fitted to data in the plane of the map, where all data contribute to the computation of the value of each grid point on the surface, with weights which decline exponentially with distance from the grid point. Means, variances and Student's t values can be computed at all grid points, keeping in mind the fact that grid points' t values are not independent of each other. We used Monte Carlo methods to demonstrate that two random samples of 500 values from two populations of 100,000 values at 4000 grid can provide a very useful picture of regions with significant differences. We recommended this procedure, or analogous approaches using other statistical tests, for any analysis where it is necessary to compare values of dependent variables when matched locations on the independent axis or plane cannot be sampled in the two populations.

Afferent Pathways↗

PubMed2001

Familial risk ratio of sarcoidosis in African-American sibs and parents.

While sarcoidosis is thought to aggregate in families, little is known about the risk to relatives of sarcoidosis patients. To estimate the familial risk ratio (lambda) of sarcoidosis in sibs and parents of cases, the authors studied 179 African-American families ascertained through an index sarcoidosis case diagnosed at Henry Ford Hospital in Detroit, Michigan. Among those relatives enrolled between 1997 and 1999, 12 of 327 (3.7%) sibs and 11 of 161 (6.8%) parents reported a history of sarcoidosis. The lambda in this sample of relatives, estimated by computing an age, sex, and race standardized incidence ratio, was 2.24 (95% confidence interval: 1.16, 3.92) for sibs and 2.82 (95% confidence interval: 1.41, 5.05) for parents. For sibs and parents combined, lambda was 2.49 (95% confidence interval: 1.58, 3.73). Results stratified by proband characteristics indicated that lambda was greater for relatives of younger (lambda = 2.93, 95% confidence interval: 1.52, 5.12) and male (lambda = 3.98, 95% confidence interval: 1.99, 7.12) probands. A higher lambda was also found for male family members and sibs born later in the birth order. A Monte Carlo method was also used to estimate lambda, with similar results obtained. Overall, these results indicate that, in African Americans, sibs and parents of sarcoidosis cases have about a 2.5-fold increased risk for sarcoidosis and that heterogeneity in disease risk may exist among family members.

Adult↗

PubMed2003

A chain of evidence with mixed comparisons: models for multi-parameter synthesis and consistency of evidence.

Multi-parameter evidence synthesis is a generalization of meta-analysis in which several parameters are estimated jointly. Here this approach is applied to a common form of data structure in which mixed pairwise comparisons are made between treatments in a 'chain of evidence' structure. The data set investigated here, which first appeared in the confidence profile method literature, features three types of data relating to thrombolytic treatment following acute myocardial infarction. There is information on reperfusion (coronary patency) following treatment, information on survival in reperfused and non-reperfused patients (conditional survival), and independent information on the effect of treatment on survival without specifying reperfusion state (overall survival). The objective of this study is to explore models for combining these three types of evidence within a single model, and some of the evidence consistency issues that arise. Bayesian Markov chain Monte Carlo methods are used to fit two models. The first, proposed in the confidence profile literature, assumes there are no differences between studies in baseline effects (equal study effects). The second model assumes fixed treatment effects but allows for study differences in baseline reperfusion and conditional survival rates by assuming random study effects. The equal study effects model fits the data poorly, and cross-validation shows that the overall survival evidence is not consistent with the reperfusion and conditional survival evidence under this model. The evidence appears to be consistent within the more loosely structured random study effects model, but results are sensitive to prior assumptions about the between-study variance. The inconsistency between the three evidence types relates to overall survival, rather than to the effect of treatment on survival. Multi-parameter evidence synthesis, with suitable checks for evidence consistency, can be used to help determine whether chains of evidence 'add up' epidemiologically within an overall model, and to construct parameter distributions for an entire model simultaneously, consistent with all the available data.

Bayes Theorem↗

PubMed2005

[Atomic hydrogen emission line and the high quality diamond film].

The process of atomic hydrogen emission in CH4/H2 gas mixture in EACVD is simulated by Monte Carlo method. In the simulation two basic types of collision between electron and H2 molecule are considered: elastic collision and inelastic collision. Four types of inelastic processes have been considered, namely vibrational excitation, dissociation, electron excitation (contains Halpha, Hbeta and Hgamma) and ionization. For e-CH4 collision, elastic momentum transfer, vibrational excitation, dissociation, dissociative excitation (contains Halpha, Hbeta and Hgamma), ionization and dissociative ionization are considered. The relationship between the number of H, CH3 and the ratio of atomic hydrogen emission line intensity under different experimental conditions is investigated. A method to obtain the optimum experimental condition for diamond deposition by the atomic hydrogen emission line is given. The result is of great importance to depositing high quality diamond films by controlling the conditions of technology efficiently.

Diamond↗

PubMed1999

Applying Bayesian ideas to the development of medical guidelines.

Measurements of the quality of health care, in particular the underuse and overuse of medical therapies and diagnostic tests, often involve employment of medical practice guidelines to assess the appropriateness of treatments. This paper presents a case study of a Bayesian analysis for the development of medical guidelines based on expert opinion, using ordinal categorical rater data. We develop guidelines for the use of coronary angiography following an acute myocardial infarction (AMI) for 890 clinical indications using statistical models fit to appropriateness ratings obtained from a nine-member expert panel. The main foci of our analyses were on the estimation of an appropriateness score for each of the clinical indications, an associated measure of precision, and functions of the underlying score. We considered two classes of models that assume the ratings are either in the form of grouped normal data or are ungrouped variables arising from a normal distribution, while permitting rater effects and indication heterogeneity in both. We estimated models using Markov chain Monte Carlo methods and constructed indices quantifying appropriateness based on posterior probabilities of selected model parameters. We compared our model-based approach to the standard approach currently employed in medical guideline development and found that the standard approach correctly identified 99 per cent of the appropriate indications while overestimating appropriateness 18 per cent of the time compared to our model-based approach.

Bayes Theorem↗

PubMed1991

Simulation program for estimating statistical power of Cox's proportional hazards model assuming no specific distribution for the survival time.

Small sample properties of the maximum partial likelihood estimates for Cox's proportional hazards model depend on the sample size, the true values of regression coefficients, covariate structure, censoring pattern and possibly baseline hazard functions. Therefore, it would be difficult to construct a formula or table to calculate the exact power of a statistical test for the treatment effect in any specific clinical trial. The simulation program, written in SAS/IML, described in this paper uses Monte-Carlo methods to provide estimates of the exact power for Cox's proportional hazards model. For illustrative purposes, the program was applied to real data obtained from a clinical trial performed in Japan. Since the program does not assume any specific function for the baseline hazard, it is, in principle, applicable to any censored survival data as long as they follow Cox's proportional hazards model.

Clinical Trials as Topic↗

PubMed1989

Structural differences between human and rat lungs: implications for Monte Carlo modeling of aerosol deposition.

The geometrical structure of the lung is one of the main factors governing inhaled particle deposition; structural differences among different species are, therefore, of great importance for extrapolation modeling. A statistical analysis of morphometric data for the human and rat tracheobronchial tree reveals significant interspecies differences in airway branching patterns: compared to the relatively dichotomous and symmetric structure of the human lung, the rat lung displays a more monopodial airway branching pattern. Thus, for the rat lung, we recommend characterizing the properties of a given airway, i.e., its size, physiologic function, and distance from the trachea, by its diameter rather than by a theoretically assigned generation number. A Monte Carlo method is used to construct an airway geometry along each inhaled particle's path by randomly selecting airway parameters from their frequency distributions and the correlations among them. While the airway geometry is selected randomly, particle deposition in individual airways is calculated analytically. These stochastic deposition calculations allow for structural differences between the human and rat lung, and the variability of the airway system within each species.

Aerosols↗

PubMed1993

Precision of a new bedside method for estimation of the circulating blood volume.

The present study is a theoretical and experimental evaluation of a modification of the carbon monoxide method for estimation of the circulating blood volume (CBV) with respect to the precision of the method. The CBV was determined from measurements of the CO-saturation of hemoglobin before and after ventilation with a gas mixture containing 20-50 ml of CO for a period of 10-15 min. A special Water's to and fro system was designed in order to avoid any leakage when measuring during intermittent positive pressure ventilation (IPPV). Blood samples were taken before and immediately after ventilation with the CO gas mixture. The amount of CO administered during each determination of CBV resulted in an increase in the CO saturation of hemoglobin of 2.1%-3.9%. A theoretical noise propagation analysis was performed by means of the Monte Carlo method. The analysis showed that a CO dose corresponding to an increase of less than 2% will result in an unacceptable coefficient of variation of repeated estimates. In the experimental study the coefficient of variation of repeated estimates of CBV was determined from duplicate measurements of CBV in nine healthy subjects and in nine intensive care patients. The coefficients of variation were 6.2% and 4.7% in healthy and diseased subjects, respectively. Furthermore, the day-to-day variation of the method with respect to the total amount of circulating hemoglobin (nHb) and CBV was determined from duplicate estimates separated by 24-48 h. In conclusion, determination of CBV can be performed with an amount of CO that gives rise to a harmless increase in the carboxyhemoglobin concentration.(ABSTRACT TRUNCATED AT 250 WORDS)

Blood Circulation↗

PubMedDate not supplied

Formation of secondary structures in polypetides. A Monte Carlo simulation.

The lattice approximation of a polypetide chain was used in the computer simulation. The residues of a model polypetide were represented by the chain of a-carbons located on a very flexible [310] lattice. The force field contained the long-range contact potential between the residues as well as the local preferences in forming helical structures. The chain consisted of two types of residues: hydrophillic (P) and hydrophobic (H), forming a typical repeatable helical septet -HHPPHPP-. The simulations were performed by means of the Replica Exchange Monte Carlo method combined with th e Histogram method. A series of simulations were performed enabling one to investigate the influence of both components of the force field on the transition temperature and the characteristics of the coil-to-globule transition. The properties of low-temperature ordered structures were determined. The thermodynamical description of the mod el polypeptide was also given. The phase transition was found to be sharp and cooperative for longer chains and strong helical potential.

Algorithms↗

PubMed1995

A new optimal wavelength for treatment of port wine stains?

In this study we investigate light penetration into skin in order to define the optimal wavelength for the treatment of port wine stains. A two-layer model (epidermis and dermis) is applied with a cylindric tube representing the ectatic blood vessel. Light propagation is calculated by the Monte Carlo method. Values for the optical properties of the skin were not only taken from the literature, but also derived from measurements of the spatially resolved reflectance on the human forearm applying a multilayer model. Using the new values, the maximal depth of selective vascular injury better fits experimental and clinical observations, compared to the values in literature. In addition, the optimal wavelength for treatment of port wine stains is shifted to longer wavelengths.

Hamartoma↗

PubMedDate not supplied

Studies of x-ray energy absorption and quantum noise properties of x-ray screens by use of Monte Carlo simulation.

The imaging properties of the phosphor layer in fluorescent screens or image intensifiers are related to its x-ray absorption characteristics. In this study, we applied Monte Carlo methods for the simulation of x-ray photon diffusion in a phosphor layer. The K-reabsorption factor, absorbed x-ray energy, quantum absorption efficiency, statistical factor, and noise-equivalent absorption were determined as a function of the incident energy and angle of the x rays for eight commonly used phosphor layers. These basic physical quantities will be useful for the prediction of the information transfer properties of a phosphor layer.

Elementary Particles↗

PubMed2002

Conformational studies of blood group A and blood group B oligosaccharides using NMR residual dipolar couplings.

The conformations of two synthetic trisaccharides of blood group A and B (alpha-L-Fucp-(1-->2)-[alpha-D-GalpNAc-(1-->3)]-alpha-D-Galp and alpha-L-Fucp-(1-->2)-[alpha-D-Galp-(1-->3)]-alpha-D-Galp, respectively) and of a type A tetrasaccharide alditol, Fucp-(1-->2)-[alpha-D-GalpNAc-(1-->3)]-beta-D-Galp-(1-->3)-GalNAc-ol, were studied by NMR measurements of one-bond C-H residual dipolar couplings in partially oriented liquid crystal solutions. The conformations of the three oligosaccharides were analyzed by generating thousands of structures using a Monte-Carlo method. Two different strategies were applied to calculate theoretical dipolar couplings for these structures. In the first method, the orientation of the molecule was calculated from the optimal fit of the molecular model to the experimental data, while in the second method the orientation tensor was calculated directly from the moment of inertia of the molecular model. Both methods of analysis give similar results but with slightly better agreement with experiment for the former one. The analysis of the results implies a single unique conformation for both blood group epitopes in solution in disagreement with theoretical models suggesting the existence of two conformers in solution.

ABO Blood-Group System↗

PubMed2005

Effects of dynamic changes of tissue properties during laser-induced interstitial thermotherapy (LITT).

A two-dimensional model including the effects of dynamic changes in the physical properties on tissue temperature and damage was developed to describe laser energy transport, heat transfer, and damage accumulation during laser-induced interstitial thermotherapy (LITT). The Monte Carlo method was used to simulate photon transport in a tissue in the nonuniform optical property field, with the finite difference method used to solve the Pennes bioheat equation to calculate the temperature distribution and the Arrhenius equation used to predict the extent of thermal damage. The numerical results showed that the dynamic changes in the optical properties, thermal properties, and blood perfusion rate significantly affected damage volume accumulation and temperature history and should be included in numerical simulations of the LITT treatment.

Blood Flow Velocity↗