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At least 217 records · Page 12Linked to original sources

PubMed2005

Modeling elastic properties in finite-element analysis: how much precision is needed to produce an accurate model?

The influence of elastic properties on finite-element analysis was investigated using a finite-element model of a Macaca fascicularis skull. Four finite-element analyses were performed in which the model was assigned different sets of elastic properties. In analysis 1, elastic properties were modeled isotropically using published data obtained from human limb bones. Analyses 2-4 used data obtained from skulls of a closely allied species, M. mulatta, but varied as to how those data were incorporated into the model. In analysis 2, the model was assigned a single set of isotropic elastic properties. In analysis 3, each region within the model was assigned its own set of isotropic elastic properties. Finally, in analysis 4, each region received its own set of orthotropic elastic properties. Although a qualitative assessment indicates that the locations of strain concentrations across the model are broadly similar in all analyses, a quantitative assessment of strain indicates some differences between the analyses. When strain data from the finite-element analyses were compared to strain data derived from in vivo experiments, it was found that the model deformed most realistically using the orthotropic elastic properties employed in analysis 4. Results suggest that finite-element analyses can be adversely affected when elastic properties are modeled imprecisely, and that modelers should attempt to obtain elastic properties data about the species and skeletal elements that are the subjects of their analyses.

Anatomy↗

PubMed2003

Pharmacokinetic/pharmacodynamic modeling of the effects of intravenous immunoglobulin on the disposition of antiplatelet antibodies in a rat model of immune thrombocytopenia.

Recently, our laboratory reported that intravenous immunoglobulin (IVIG) treatment increased antiplatelet antibody (7E3) clearance in a rat model of immune thrombocytopenic purpura (ITP). However, due to the multifaceted nature of IVIG therapy, the contribution of this increase in antiplatelet antibody clearance to the total therapeutic effect of IVIG was unclear. The purposes of the present study were to (1). develop a new, mechanistic model of immune gamma globulin (IgG) pharmacokinetics, (2). develop a pharmacokinetic/pharmacodynamic (PK/PD) model relating 7E3 concentrations to the platelet count time course observed following 7E3 treatment, and (3). use these mathematical models to gain insight into the significance of increased 7E3 clearance relative to the total effect of IVIG on 7E3-induced thrombocytopenia. A mechanism-based PK model was developed that adequately characterized IVIG effects on 7E3 pharmacokinetics. The structure of this model is based on competition between IgG molecules for occupancy of the protective FcRn receptor. The model accurately captured antiplatelet antibody concentration versus time data in the presence and absence of IVIG therapy, in the rat, in 'wild-type' mice, and in 'knockout' mice lacking expression of the FcRn receptor. An indirect response PK/PD model was also developed, which accurately characterized 7E3 effects on platelet counts. Using these models, it was estimated that 50 +/- 11% of the total protective effect of IVIG in this acute model of ITP can be accounted for by IVIG effects on 7E3 disposition.

Animals↗

PubMed2006

Uncalibrated modelling of conservative tracer and pesticide leaching to groundwater: comparison of potential Tier II exposure assessment models.

The Root Zone Water Quality Model (RZWQM) and Pesticide Root Zone Model (PRZM) are currently being considered by the Office of Pesticide Programs (OPP) in the United States Environmental Protection Agency (US EPA) for Tier II screening of pesticide leaching to groundwater (November 2005). The objective of the present research was to compare RZWQM and PRZM based on observed conservative tracer and pesticide pore water and soil concentrations collected in two unique groundwater leaching studies in North Carolina and Georgia. These two sites had been used previously by the Federal Insecticide, Fungicide and Rodenticide Act (FIFRA) Environmental Model Validation Task Force (EMVTF) in the validation of PRZM. As in the FIFRA EMVTF PRZM validation, 'cold' modelling using input parameters based on EPA guidelines/databases and 'site-specific' modelling using field-measured soil and hydraulic parameters were performed with a recently released version of RZWQM called RZWQM-NAWQA (National Water Quality Assessment). Model calibration was not performed for either the 'cold' or 'site-specific' modelling. The models were compared based on predicted pore water and soil concentrations of bromide and pesticides throughout the soil profile. Both models tended to predict faster movement through the soil profile than observed. Based on a quantitative normalised objective function (NOF), RZWQM-NAWQA generally outperformed or was equivalent to PRZM in simulating pore water and soil concentrations. Both models were more successful in predicting soil concentrations (i.e. NOF < 1.0 for site-specific data, which satisfies site-specific applicability) than they were at predicting pore water concentrations.

Environment↗

PubMed2006

Multilevel modelling of clustered grouped survival data using Cox regression model: an application to ART dental restorations.

In some controlled clinical trials in dental research, multiple failure time data from the same patient are frequently observed that result in clustered multiple failure time. Moreover, the treatments are often delivered by more than one operator and thus the multiple failure times are clustered according to a multilevel structure when the operator effects are assumed to be random. In practice, it is often too expensive or even impossible to monitor the study subjects continuously, but they are examined periodically at some regular pre-scheduled visits. Hence, discrete or grouped clustered failure time data are collected. The aim of this paper is to illustrate the use of the Monte Carlo Markov chain (MCMC) approach and non-informative prior in a Bayesian framework to mimic the maximum likelihood (ML) estimation in a frequentist approach in multilevel modelling of clustered grouped survival data. A three-level model with additive variance components model for the random effects is considered in this paper. Both the grouped proportional hazards model and the dynamic logistic regression model are used. The approximate intra-cluster correlation of the log failure times can be estimated when the grouped proportional hazards model is used. The statistical package WinBUGS is adopted to estimate the parameter of interest based on the MCMC method. The models and method are applied to a data set obtained from a prospective clinical study on a cohort of Chinese school children that atraumatic restorative treatment (ART) restorations were placed on permanent teeth with carious lesions. Altogether 284 ART restorations were placed by five dentists and clinical status of the ART restorations was evaluated annually for 6 years after placement, thus clustered grouped failure times of the restorations were recorded. Results based on the grouped proportional hazards model revealed that clustering effect among the log failure times of the different restorations from the same child was fairly strong (corr(child)=0.55) but the effects attributed to the dentists could be regarded as negligible (corr(dentist)=0.03). Gender and the location of the restoration were found to have no effects on the failure times and no difference in failure times was found between small restorations placed on molars and non-molars. Large restorations placed on molars were found to have shorter failure times compared to small restorations. The estimates of the baseline parameters were increasing indicating increasing hazard rates from interval 1 to 6. Results based on the logistic regression models were similar. In conclusion, the use of the MCMC approach and non-informative prior in a Bayesian framework to mimic the ML estimation in a frequentist approach in multilevel modelling of clustered grouped survival data can be easily applied with the use of the software WinBUGS.

Adolescent↗

PubMed1985

Modelling whole blood oxygen equilibrium: comparison of nine different models fitted to normal human data.

The ability of nine different models, prominent in the literature, to meaningfully characterize the oxygen-hemoglobin equilibrium curve (OHEC) of normal individuals was examined. Previously reported data (N = 33), obtained using the DCA-1 (Radiometer, Copenhagen), and new data (N = 8), obtained using the Hemox-Analyzer (TCS, Southampton, PA), from blood samples of normal, non-smoking volunteers were used and these devices were found to give statistically similar results. The OHECs were digitized and fitted to the models using least-squares techniques developed in this laboratory. The "goodness-of-fit" was determined by the root-mean-squared (RMS) error, the number of parameters, and the parameter redundancy, i.e., correlation between the parameters. The best RMS error did not necessarily indicate the best model. Most literature models consist of ratios of similar-order polynomials. These showed considerable parameter redundancy which made the curve fitting difficult. The best fits gave RMS errors as low as 0.2% saturation. The Hill model gave a good characterization over the saturation range 20%-98% with RMS errors of about 0.6% saturation. On the other hand, good characterizations over the entire range were given by several other models. The relative advantages and disadvantages of each model have been compared as well as the difficulties in fitting several of the models. No single model is best under all circumstances. The best model depends upon the particular circumstances for which it is to be utilized.

Hemoglobins↗

PubMed1988

Pharmacokinetic model equations for the one- and two-compartment models with first-order processes in which the absorption and exponential elimination or distribution rate constants are equal.

In fitting the one-compartment open model with first-order processes to empirical data, it has frequently been found for single-dose administration that the absorption and elimination rate constants approach each other. If these rate constants tend to be equal, such combinations are impossible to solve with the general model equation. In 1968, Dost published a special model function by which the problems associated with the general model function can be circumvented. No solution, however, has been published for multiple-dose functions with the one-compartment model in which the absorption and elimination rate constants are equal. For a two-compartment open model with first-order processes, similar problems arise if the absorption and exponential distribution rate constants approach each other. Although this type of problems is often encountered in pharmacokinetic curve-fitting to empirical data, no exact solution has been published. Equations are given for multiple-dose administration with the one-compartment open model in which the absorption and elimination rate constants are equal, and for single-dose and multiple-dose administration with the two-compartment open model in which the absorption and exponential distribution rate constants are equal. Included are criteria to decide whether the new or the classical model functions should be applied in the case of a two-compartment open model.

Models, Biological↗

PubMed1992

Neural networks in pharmacodynamic modeling. Is current modeling practice of complex kinetic systems at a dead end?

Neural networks (NN) are computational systems implemented in software or hardware that attempt to simulate the neurological processing abilities of biological systems, in particular the brain. Computational NN are classified as parallel distributed processing systems that for many tasks are recognized to have superior processing capability to the classical sequential Von Neuman computer model. NN are recognized mainly in terms of their adaptive learning and self-organization features and their nonlinear processing capability and are considered most suitable to deal with complex multivariate systems that are poorly understood and difficult to model by classical inductive, logically structured modeling techniques. A NN is applied to demonstrate one of the potentially many applications of NN for modeling complex kinetic systems. The NN was used to predict the effect of alfentanil on the heart rate resulting from a complex infusion scheme applied to six rabbits. Drug input-drug effect data resulting from a repeated, triple infusion rate scheme lasting from 30 to 180 min was used to train the NN to recognize and emulate the input-effect behavior of the system. With the NN memory fixed from the 30- to 180-min learning phase the NN was then tested for its ability to predict the effect resulting from a multiple infusion rate scheme applied in the subsequent 180 to 300 min of the experiment. The NN's ability to emulate the system (30-180 min) was excellent and its predictive extrapolation capability (180-300 min) was very good (mean relative prediction accuracy of 78%). The NN was best in predicting the higher intensity effect and was able to identify and predict an overshoot phenomenon likely caused by a withdrawal effect from acute tolerance. Current modeling philosophy and practice is discussed on the basis of the alternative offered by NN in the modeling of complex kinetic systems. In modeling such systems it is questioned whether traditional modeling practice that insists on structure relevance and conceptually pleasing structures has any practical advantages over the empirical NN approach that largely ignores structure relevance but concentrates on the emulation of the behavior of the kinetic system. The traditional searching for appropriate models of complex kinetic systems is a painstakingly slow process. In contrast, the search for empirical models using NN will continue to improve, limited only by technological advances supporting the very promising NN developments.

Alfentanil↗

PubMed2002

Mechanical analysis of the lumbar vertebrae in a three-dimensional finite element method model in which intradiscal pressure in the nucleus pulposus was used to establish the model.

We established a three-dimensional finite element method (FEM) model of the 4th and 5th vertebrae, using computed tomography (CT) images (2-mm slice thickness) of a healthy 29-year-old man. Because of the lack of specific data regarding the material characteristics of the nucleus pulposus of intervertebral discs, we used intradiscal pressure in the nucleus pulposus to establish the model. We referred to data from Nachemson and from Sato et al. regarding intradiscal pressure and to the methods of Shirazi-Adl for data for other material characteristics (see text for these references). The mid-position model bears a load of 294 N in the vertical direction, while the models of the flexed and extended positions bear loads of 15 N-m. In addition, a degenerative disc model without intradiscal pressure was created for the standing model. The use of these models allowed the investigation of von Mises stress on the vertebral endplates and the annulus fibrosus. We also examined von Mises stress on the facet joint in normal and degenerative disc models. There was increased von Mises stress on the vertebral endplate in the anterior, center portions. von Mises stress on the annulus fibrosus increased in the posterior portion, the entrance to the neural foramen, and the exit of the neural foramen. von Mises stress was greater during flexion in the posterior portion; in particular, increasing to about 1.6 times the level seen with other postures. No changes were observed in von Mises stress on the vertebral endplates or annulus fibrosus in the degenerative disc model, but von Mises stress on the facet joints was about 2.5 times that seen in the normal disc model.

Adult↗

PubMed2006

Frequentist model-averaged estimators and tests for univariate twin models.

Parameter estimates from analyses of univariate twin data usually do not reflect the uncertainty due to the model selection phase of the data analysis. To address the effect of model selection uncertainty on parameter estimates, we introduce frequentist model-averaged estimators for univariate twin data analysis that use information-theoretic criteria to assign model weights. We conduct simulation studies to examine the performance of model-averaged estimators of additive genetic variance, and for tests for additive genetic variance based on model-averaged estimators. In simulation studies with small or moderate sample sizes, model-averaged estimators of additive genetic variance typically have lower mean-squared error than either (i) estimators from individual twin models, or (ii) estimators obtained from a decision procedure where the best-fitting model from likelihood-ratio testing is used to estimate additive genetic variance. For each sample size simulated, bootstrap tests based on model-averaged estimators have higher power to detect additive genetic variance than currently-used tests in most cases.

Analysis of Variance↗

PubMed1996

Segment inertial parameter evaluation in two anthropometric models by application of a dynamic linked segment model.

The estimation of segment inertial parameters (SIPs) is an important source of error in inverse dynamic analysis. In most individual cases SIPs are derived from extrapolation of known SIPs of a certain population through regression equations (proportional models). Another well-known method is the use of mathematical approximation of the shape of human body segments combined with estimations of segment densities (geometric models). In the current study five males and five females performed four different lifting movements in the sagittal plane. A full body linked segment model was applied twice to the same data set, once using a proportional and once using a geometric anthropometric model. As a full body linked segment model is an overdetermined system of equations, four equations could be formed to test the summed effect of SIP errors on the inverse dynamic analysis. The overall performance in terms of coefficients of correlation was better for the geometric model as compared to the proportional model. When a back lifting movement was performed, the equations indicated systematic errors in the proportional model. However, when a leg lifting movement was performed, the equations indicated systematic errors in the geometric model. Therefore, analyzing only one kind of movement does not suffice to draw conclusions with respect to the reliability of an anthropometric model.

Adolescent↗

PubMed2005

Sensitivity of a Hill-based muscle model to perturbations in model parameters.

Musculoskeletal simulations of human movement commonly use Hill muscle models to predict muscle forces, but their sensitivity to model parameter values is not well understood. The purpose of this study was to evaluate muscle model sensitivity to perturbations in 14 Hill muscle model parameters in forward dynamic simulations of running and walking by varying each by +/-50%. Three evaluations of the muscle model were performed based on: (1) calculating the sensitivity of the muscle model only, (2) determining the continuous partial derivatives of the muscle equations with respect to each parameter, and (3) evaluating the effects on the running and walking simulations. Model evaluations were found to be very sensitive (percent change in outputs greater than parameter perturbation) to parameters defining the series elastic component (tendon), force-length curve of the contractile element and maximum isometric force. For some parameters, the range of literature values was larger than the model sensitivity. Model evaluations were insensitive to parameters defining the parallel elastic element, force-velocity curve of the contractile element and muscle activation time constants. The derivative method provided similar results, but also provided a generic, continuous equation that can easily be applied to other motions. The sensitivities of the running and walking simulations were reduced compared to the sensitivity of the muscle model alone. Results demonstrate the importance of evaluating sensitivity of a musculoskeletal simulation in a controlled manner and provide an indication of which parameters must be selected most carefully based on the sensitivity of a given movement.

Biomechanical Phenomena↗

PubMed2003

Using network models to approximate spatial point-process models.

Spatial effects are fundamental to ecological and epidemiological systems, yet the incorporation of space into models is potentially complex. Fixed-edge network models (i.e. networks where each edge has the same fixed strength of interaction) are widely used to study spatial processes but they make simplistic assumptions about spatial scale and structure. Furthermore, it can be difficult to parameterize such models with empirical data. By comparison, spatial point-process models are often more realistic than fixed-edge network models, but are also more difficult to analyze. Here we develop a moment closure technique that allows us to define a fixed-edge network model which predicts the prevalence and rate of epidemic spread of a continuous spatial point-process epidemic model. This approach provides a systematic method for accurate parameterization of network models using data from continuously distributed populations (such as data on dispersal kernels). Insofar as point-process models are accurate representations of real spatial biological systems, our example also supports the view that network models are realistic representations of space.

Animals↗

PubMed2003

A sensibility analysis of model selection in modeling the reactive transport of cesium in crushed granite.

We performed a sensibility analysis of model selection in modeling the reactive transport of cesium in crushed granite through model calibration and validation. Based on some solid phase analysis data and kinetic batch experimental results, we hypothesized three two-site sorption models in the LEHGC reactive transport model to fit the breakthrough curves (BTCs) from the corresponding column experiments. The analysis of breakthrough curves shows that both the empirical two-site kinetic linear sorption model and the semi-mechanistic/semi-empirical two-site kinetic surface complexation model, regardless of their complexity, can match our experimental data fairly well under given test conditions. A numerical experiment to further compare the two models shows that they behave differently when the pore velocity is not of the same order of magnitude as our test velocities. This result indicates that further investigations to help determine a better model are needed. We suggest that a multistage column experiment, which tests over the whole range of practical flow velocities, should be conducted to help alleviate inadequate hypothesized models.

Calibration↗

PubMed2002

A general approach to transform a lake model for one radionuclide (radiocesium) to another (radiostrontium) and critical model tests using data for four Ural lakes contaminated by the fallout from the Kyshtym accident in 1957.

This paper presents results of a model test carried out within the framework of the COMETES project (EU). The aim of the work was to change the structure of the MOIRA lake model for radiocesium so that it can be applied more generally for, in principle, all types of radionuclides and heavy metals. This general lake model is used within the MOIRA decision support system (DSS; MOIRA and COMETES are acronyms for EU-projects). The model is based on a set of differential equations and a specific modelling structure. It incorporates all important fluxes to, from and within lakes in a general manner. Yet the model is driven by a minimum of variables accessible from standard maps and monitoring programs. The model can be separated into two parts, a general part with equations applicable for all types of water pollutants and a substance-specific part. This model has previously been validated for 137Cs from many lakes covering a wide domain and yielded excellent predictive power. The alterations discussed in this work are meant to be general and radiostrontium is used as a typical element. Radiostrontium is known to be more mobile than radiocesium and all abiotic parts of the model handling fixation and mobility have been altered. The new model for 90Sr has been critically tested using data from four lakes heavily contaminated with 90Sr from the Kyshtym accident in the Southern Urals, Russia, using empirical data from a period from 1958 to 1995 for 90Sr in fish (here goldfish), water and sediments.

Cesium Radioisotopes↗

PubMed2003

Comparison of available benchmark dose softwares and models using trichloroethylene as a model substance.

By using trichloroethylene as a model substance the U.S. EPA benchmark dose software was compared to the software by Crump and the software by Kalliomaa. Dose-response and dose-effect data on the liver, kidneys, central nervous system (CNS), and tumours were selected for the evaluation. Based on the present study the U.S. EPA software is preferable to the other softwares for dichotomous data. A wider range in benchmark doses was often observed for dichotomous data when the numbers of dose levels were limited. The log-logistic model in most cases gave the best fit when ranking the dichotomous models. In addition, the log-logistic model often implied a more conservative benchmark dose. For continuous data it was more difficult to find a model describing the data. The softwares by Kalliomaa and by the U.S. EPA offered the best opportunities for benchmark dose modelling of continuous data. Flexible models, like the Hill- and the Mult model, are needed for S-shaped continuous data but these models demand more dose levels in order to describe the data. Since the number of dose levels are important for model selection study design is important and should be further evaluated.

Benchmarking↗

PubMed2002

A model for evaluating physico-chemical substance properties required by consequence analysis models.

Modeling systems for analyzing the consequences of chemical emergencies require as input values a number of physico-chemical substance properties, commonly as a function of temperature at atmospheric pressure. This paper presents a mathematical model "CHEMIC", which can be used for evaluating such substance properties, assuming that six basic constant quantities are available (molecular weight, freezing or melting point, normal boiling point, critical temperature, critical pressure and critical volume). The model has been designed to yield reasonably accurate numerical predictions, while at the same time keeping the amount of input data to a minimum. The model is based on molecular theory or thermodynamics, together with empirical corrections. Mostly, model equations are based on the so-called law of corresponding states. The model evaluates substance properties as a function of temperature at atmospheric pressure. These include seven properties commonly required by consequence analysis and heavy gas dispersion modeling systems: vapor pressure, vapor and liquid densities, heat of vaporization, vapor and liquid viscosities and binary diffusion coefficient. The model predictions for vapor pressure, vapor and liquid densities and heat of vaporization have been evaluated by using the Clausius-Clapeyron equation. We have also compared the predictions of the CHEMIC model with those of the DATABANK database (developed by the AEA Technology, UK), which includes detailed semi-empirical correlations. The computer program CHEMIC could be easily introduced into consequence analysis modeling systems in order to extend their performance to address a wider selection of substances.

Atmospheric Pressure↗

PubMed2000

TR146 cells grown on filters as a model of human buccal epithelium: V. Enzyme activity of the TR146 cell culture model, human buccal epithelium and porcine buccal epithelium, and permeability of leu-enkephalin.

The objective of the present study was to characterise the TR146 cell culture model as an in vitro model of human buccal mucosa with respect to the enzyme activity in the tissues. For this purpose, the contents of aminopeptidase, carboxypeptidase and esterase in homogenate supernatants of the TR146 cell culture model, and human and porcine buccal epithelium were compared. The esterase activity in the intact cell culture model and in the porcine buccal mucosa was compared. Further, the TR146 cell culture model was used to study the permeability rate and metabolism of leu-enkephalin. The activity of the three enzymes in the TR146 homogenate supernatants was in the same range as the activity in homogenate supernatants of human buccal epithelium. In the TR146 cell culture model, the activity of aminopeptidase (13.70+/-2.10 nmol/min per mg protein) was approx. four times the activity of carboxypeptidase (3.73+/-0.53 nmol/min per mg protein), whereas the level of esterase activity was significantly higher (223.39+/-69.82 nmol/min per mg protein). In the TR146 cell culture model, the apical esterase activity was found significantly higher than the basal activity, and found comparable to the porcine buccal mucosa. However, the esterase activity on the serosal side of the porcine buccal mucosa was higher than in the TR146 cell culture model. Approx. 1.5% of leu-enkephalin permeated the TR146 cell layers within 5 h (P(app) 7.38+/-0.83x10(-7) cm/s) and approx. 77% of intact peptide was still present in the donor phase after 5 h. The present study suggests that the TR146 cell culture model is a valuable in vitro model for permeability and metabolism studies with enzymatically labile drugs, such as leu-enkephalin, intended for buccal drug delivery.

Aminopeptidases↗

PubMedDate not supplied

The double-tuck model: a new animal model of arterial thrombosis.

PURPOSE: To develop an animal model of a fibrin- and platelet-rich intraluminal arterial thrombus with abnormal mural substrate to simulate in situ thrombosis of human atherosclerotic arteries. MATERIALS AND METHODS: Parallel studies of the crush-thrombin model (CT) and double-tuck model (DT) were performed and evaluated with use of angiography and histologic analysis. Ten Yorkshire swine (1-6 months; 20-30 kg; 10 females) underwent right femoral and carotid cutdowns performed after administration of general anesthesia (4 mL intravenous thiopental sodium, isoflurane 2% in 1 L of oxygen). After angiography, the CT model was created in the left carotid artery and the DT model was performed in the right carotid artery. Angiograms were obtained at 20 minutes (n = 1), at 1 hour (n = 3), at 2 hours (n = 4), and at 3 hours (n = 2) before sacrifice. After sacrifice, histologic specimens were stained with hematoxylin-eosin (H-E stain) and phosphotungstic acid hematoxylin for fibrin. The specimens were examined for endothelial irregularity and adhesion, platelet aggregation, fibrin layering, vessel wall injury, and adventitial hemorrhage. The findings were quantified as 0 = absent, 1+ = slight, 2+ = moderate, and 3+ = severe. RESULTS: Angiographic results were similar. However, histologic analysis of the CT model showed severe damage to the arterial wall with dissection in nine of 10 animals. In the DT model, no dissection was found (n = 10). Endothelial irregularity was found in six of 10 arteries treated with the CT method, as compared with nine of 10 arteries prepared with the DT model; endothelial adhesion was found in five DT arteries and in four CT arteries. Platelet aggregation was present equally in both methods. A fibrin- and platelet-rich thrombus was created in five of 10 examined arteries by both methods. CONCLUSIONS: The DT model creates endothelial irregularity leading to formation of a platelet- and fibrin-rich thrombus, adherent to the vessel wall without damage to the media. This contrasts with the CT method, which created medial dissection in nine of 10 arteries. One hour is the minimum time required to produce a good quality thrombus; 2 hours is the optimum time. The DT model is proposed as a useful tool in the development of new devices, drugs, and biotechnologic advances.

Angiography↗