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PubMed1989

Prospective use of optimal sampling theory: steady-state ciprofloxacin pharmacokinetics in critically ill trauma patients.

We examined the use of optimal sampling theory to determine a sparse sampling design to estimate pharmacokinetic parameters of ciprofloxacin in patients who had sustained trauma. Two serum sampling strategies, consisting of six sampling times each, were derived on the basis of the patient's renal function (patients with creatinine clearance greater than or equal to 6 L/hr/1.73 m2 and patients with creatinine clearances less than 6 L/hr/1.73 m2). Two additional serum samples were obtained for other aspects to the study. A timed urine collection was also obtained. Pharmacokinetic parameter estimates were determined by comodeling the serum and urine data with a three-compartment open model (parameterized as microconstants) with a bayesian algorithm and by noncompartmental analysis. Bayesian-derived parameter estimates were total body clearance of drug from plasma, 29.8 L/hr/1.73 m2; renal clearance, 17.0 L/hr/1.73 m2; and nonrenal clearance, 12.7 L/hr/1.73 m2 and were not significantly different from noncompartmentally derived parameters (p = 0.80, p = 0.65 and p = 0.333, respectively). The study demonstrates the use of optimal sampling theory to determine an informative yet relatively sparse sampling strategy for a drug with a complex pharmacokinetic model.

Adult↗

PubMed1993

On the use of Bayesian probability theory for analysis of exponential decay data: an example taken from intravoxel incoherent motion experiments.

Traditionally, the method of nonlinear least squares (NLLS) analysis has been used to estimate the parameters obtained from exponential decay data. In this study, we evaluated the use of Bayesian probability theory to analyze such data; specifically, that resulting from intravoxel incoherent motion NMR experiments. Analysis was done both on simulated data to which different amounts of Gaussian noise had been added and on actual data derived from rat brain. On simulated data, Bayesian analysis performed substantially better than NLLS under conditions of relatively low signal-to-noise ratio. Bayesian probability theory also offers the advantages of: a) not requiring initial parameter estimates and hence not being susceptible to errors due to incorrect starting values and b) providing a much better representation of the uncertainty in the parameter estimates in the form of the probability density function. Bayesian analysis of rat brain data was used to demonstrate the shape of the probability density function from data sets of different quality.

Animals↗

PubMed1981

Functional renal imaging through factor analysis.

Functional images tend to be noisy, since they are formed from parameter values estimated from noisy time-activity curves. Factor analysis provides a rapid method for fitting smooth curves to these noisy curves. Noise in functional images is reduced by estimating parameter values from the smooth curves. The method is illustrated for three parameters: TMAX (time to maximum value), RISE (increase from first to maximum value), and RISMX (maximum increase between successive values). When curve-fitting through factor analysis is used to generate functional renal images from clinical studies or to estimate parameter values for simulated noisy renogram curves, noise is reduced for the TMAX and RISMX parameters and accuracy is improved for the RISE parameter.

Factor Analysis, Statistical↗

PubMed2001

Minimally invasive estimation of systemic vascular parameters.

A cardiovascular parameter estimator to identify the systemic vascular parameters was developed using an extended Kalman filter (EKF) algorithm. Measurements from a ventricular assist device (VAD) and arterial pressure were used in the estimator. The systemic vascular parameters are important indices of heart condition. However, obtaining these parameters usually requires invasive measurements, which are difficult to obtain under most clinical environments. Including a VAD model into the estimator and using the signals from a VAD to identify the cardiovascular parameters for VAD patients would minimize the need for indwelling sensors. This paper illustrates the use of a Novacor left ventricular assist system (LVAS) model with a cardiovascular model in the estimator to identify the systemic vascular parameters: characteristic resistance, blood inertance at the aorta, systemic compliance, and systemic resistance. Performance of the estimator was evaluated using data from a computer simulation and from a mock circulatory system experiment. Robustness of the estimator to the available measurements was also described. The estimation results showed that the estimates converged with reasonable accuracy in a limited time when the LVAS pump volume and arterial pressure were used as measurements. These parameter estimates can provide additional diagnostic information for patient and device monitoring and can be used for future VAD control development.

Algorithms↗

PubMed1991

Ultrasonic differentiation of intraocular melanomas: parameters and estimation methods.

In this study, the estimation of ultrasound parameters is evaluated for in vivo differentiation of intraocular melanomas. For this purpose, both tissue and image parameters of the ultrasound signal are considered. These parameters comprised, respectively, the frequency dependent attenuation and backscattering coefficient of the melanoma tissue, and the first and second-order statistics of the amplitude-modulated and phase-derivative images of the melanomas. A diffraction correction procedure has been applied prior to the estimation of the parameters to correct the ultrasound signals for the echographic equipment used and for the various distances of the region-of-interest to the transducer. In addition, a pre-processing to select a homogeneous region from the tumours was implemented to obtain consistent estimates of the ultrasound parameters, because the accuracy and the precision of the parameters would be greatly reduced by the inhomogeneity of the melanoma tissue. The estimation methods are evaluated by means of the accuracy and precision of the parameters estimated from simulated ultrasound data and data obtained from a tissue-mimicking phantom. The mutual correlations of the parameters are discussed for the ultrasound data obtained from the melanomas. This study enabled a preselection of the independent ultrasound parameters that could be used in a discriminant analysis to perform a differentiation of intraocular melanomas. The sensitivity and specificity of differentiating spindle cell type from mixed-epitheloid meleanomas were 92 and 89 percent, respectively.

Choroid Neoplasms↗

PubMed2000

Frequency-selective quantification of biomedical magnetic resonance spectroscopy data.

In this paper the possibility of obtaining accurate estimates of parameters of selected peaks in the presence of unknown or uninteresting spectral features in biomedical magnetic resonance spectroscopy (MRS) signals is investigated. This problem is denoted by frequency-selective parameter estimation. A new time-domain technique based on maximum-phase finite impulse response (FIR) filters is presented. The proposed method is compared to a number of existing approaches: the application of a weighting function in the time domain, frequency domain fitting using a polynomial baseline, and the time-domain HSVD filter method. The ease of use and low computational complexity of the FIR filter method make it an attractive approach for frequency-selective parameter estimation. The methods are validated using simulations of relevant (13)C and (31)P MRS examples.

Adenosine Triphosphate↗

PubMed1988

Estimation of test error rates, disease prevalence and relative risk from misclassified data: a review.

We review methods for the analysis of categorical clinical and epidemiological data, in which the observations are subject to misclassification. Under certain conditions, it is possible to estimate error parameters such as sensitivity, specificity, relative risk, or predictive value, even though no definitive classification (gold standard) is available. The parameter estimates are obtained by modelling the data, using maximum likelihood, with or without some constraints. The models recognize that the true classification of an individual is unknown, and so are sometimes referred to as "latent class" models. The latent class approach provides a unified framework for various methods found in a dispersed literature, characterising each by the number of populations or subgroups in the data, and the number of observations made on each individual; the statistical degrees of freedom are implied by the sampling design. Data sets with less than three replicate observations per individual necessarily require constraints for parameter estimation to be possible. Data sets with three or more replicates lead directly to estimates of the misclassification rates, subject to some simple assumptions. Some more complex problems are also discussed, including data where the response variable has more than two levels, sequential and irregular designs and the effects of assumption violations.

Classification↗

PubMed1999

Pharmacokinetics of paracetamol in adults after cardiac surgery.

The pharmacokinetics of paracetamol in adults after cardiac surgery have not been described. Twenty patients were randomized to receive either paracetamol 2 g through a nasogastric tube and as a suppository eight hours later or vice versa. Arterial blood samples were taken at 0.5, one, two, four, six and eight hours after dosing. Each patient was studied for 16 h. There were 16 males and three females. One patient was excluded because of sampling errors. The mean age was 59 (SD 8) years and the mean weight 84 kg (16). The time-concentration profiles for each individual were used to estimate pharmacokinetic parameters using a non-linear mixed effects model (NONMEM). Population parameter estimates with coefficient of variation (CV%), standardized to a 70 kg person, for a one-compartment model with first order input, lag time and first order elimination were volume of distribution 127l (28) and clearance 26.4 l/h (29) Rectal paracetamol had an absorption half-life (Tabs) of 2.02 h (31) with a lag time of 0.28 h. The absorption half-life for the oral preparation was 1.49 h (81) with a lag time of 0.17 h. The relative bioavailability of the rectal compared to the oral formulation was 0.98 (18). Concentrations after either nasogastric or rectal paracetamol 2 g were below a target concentration of 10 mg/l, which is associated with analgesia. Absorption after nasogastric administration was slow compared to healthy adults (Tabs 0.06 to 0.7 h) and the bioavailability was half that expected, due to nasogastric loss. Parameter estimates had large variability. Paracetamol is unlikely to have useful clinical impact in the majority of patients when standard doses (6 g/day) are given on day 1 after cardiac surgery.

Acetaminophen↗

PubMed1999

Introducing optimal experimental design in predictive modeling: a motivating example.

Predictive microbiology emerges more and more as a rational quantitative framework for predicting and understanding microbial evolution in food products. During the mathematical modeling of microbial growth and/or inactivation, great, but not always efficient, effort is spent on the determination of the model parameters from experimental data. In order to optimize experimental conditions with respect to parameter estimation, experimental design has been extensively studied since the 1980s in the field of bioreactor engineering. The so-called methodology of optimal experimental design established in this research area enabled the reliable estimation of model parameters from data collected in well-designed fed-batch reactor experiments. In this paper, we introduce the optimal experimental design methodology for parameter estimation in the field of predictive microbiology. This study points out that optimal design of dynamic input signals is necessary to maximize the information content contained within the resulting experimental data. It is shown that from few dynamic experiments, more pertinent information can be extracted than from the classical static experiments. By introducing optimal experimental design into the field of predictive microbiology, a new promising frame for maximization of the information content of experimental data with respect to parameter estimation is provided. As a case study, the design of an optimal temperature profile for estimation of the parameters D(ref) and z of an Arrhenius-type model for the maximum inactivation rate kmax as a function of the temperature, T, was considered. Microbial inactivation by heating is described using the model of Geeraerd et al. (1999). The need for dynamic temperature profiles in experiments aimed at the simultaneous estimation of the model parameters from measurements of the microbial population density is clearly illustrated by analytical elaboration of the mathematical expressions involved on the one hand, and by numerical simulations on the other.

Bacteria↗

PubMed2004

Estimating transmission parameters of F4+ E. coli for F4-receptor-positive and -negative piglets: one-to-one transmission experiment.

F4+ Escherichia coli is an important agent of post-weaning diarrhoea in piglets. Piglets that express an adhesion site for F4+ E. coli in their small intestine (F4R+) shed higher numbers of F4+ E. coli than piglets lacking this site (F4R-). We hypothesized that F4R+ piglets are more infectious and more susceptible for F4+ E. coli. This implies that in populations with F4R+ and F4R- piglets, the transmission would be dependent on the frequency of both types of animals. To quantify the difference in infectiousness and susceptibility, a one-to-one transmission experiment was performed with 20 pairs consisting of one inoculated and one contact piglet. Based on the contact infections observed, transmission parameters were estimated with generalized linear models. F4R+ piglets were infectious for other piglets and the reproduction ratio (R0) for homogeneous F4R+ populations, that is the average number of secondary infections that one F4R+ pig will cause during its entire infectious period in a population of susceptible F4R+ individuals only, was estimated as 7.1. F4R+ piglets were more susceptible than F4R- piglets and reducing the fraction of F4R+ piglets of a population will reduce transmission. It was calculated that in order to prevent major outbreaks of F4+ E. coli (R0 < 1), the fraction of F4R+ piglets must be lower than 0.14.

Adhesins, Escherichia coli↗

PubMed2005

B-domain deleted recombinant factor VIII preparations are bioequivalent to a monoclonal antibody purified plasma-derived factor VIII concentrate: a randomized, three-way crossover study.

BACKGROUND: Deletion of the B-domain of recombinant blood coagulation factor VIII (BDDrFVIII) increases the manufacturing yield of the product but does not impair in vitro or in vivo functionality. BDDrFVIII (ReFacto) has been developed with the additional benefit of being formulated without human albumin. OBJECTIVE: The primary objective of this three-way crossover-design study was to compare the pharmacokinetic (PK) parameters of two BDDrFVIII formulations (one reconstituted with 5 mL of sterile water, the other reconstituted with 4 mL sodium chloride 0.9% USP) with those of a plasma-derived, full-length FVIII preparation (Hemofil M) in patients with haemophilia A to determine bioequivalence. METHODS: A series of blood samples were collected over a period of 48 h after i.v. administration of each of the FVIII preparations. Plasma FVIII activity was determined using a validated chromogenic substrate assay. Plasma FVIII activity vs. time curves was characterized for a standard set of PK parameter estimates. Two parameter estimates, the maximum plasma concentration (Cmax) and the area under plasma concentration vs. time curves (AUCs), were used to evaluate bioequivalence. The two preparations were considered bioequivalent if the 90% confidence intervals for the ratio of geometric means for Cmax and AUCs fell within the bioequivalence window of 80% to 125%. RESULTS/CONCLUSION: Results show that each BDDrFVIII formulation is bioequivalent to Hemofil M and the two formulations of BDDrFVIII are bioequivalent to each other.

Adolescent↗

PubMed2007

Estimating optimal parameters for MRF stereo from a single image pair.

This paper presents a novel approach for estimating the parameters for MRF-based stereo algorithms. This approach is based on a new formulation of stereo as a maximum a posterior (MAP) problem in which both a disparity map and MRF parameters are estimated from the stereo pair itself. We present an iterative algorithm for the MAP estimation that alternates between estimating the parameters while fixing the disparity map and estimating the disparity map while fixing the parameters. The estimated parameters include robust truncation thresholds for both data and neighborhood terms, as well as a regularization weight. The regularization weight can be either a constant for the whole image or spatially-varying, depending on local intensity gradients. In the latter case, the weights for intensity gradients are also estimated. Our approach works as a wrapper for existing stereo algorithms based on graph cuts or belief propagation, automatically tuning their parameters to improve performance without requiring the stereo code to be modified. Experiments demonstrate that our approach moves a baseline belief propagation stereo algorithm up six slots in the Middlebury rankings.

Algorithms↗

PubMed1991

The estimation of parameters from bulked samples.

An estimation procedure has been developed for the estimation of parameters from bulked sample using the parametric bootstrap and density estimation in conjunction with the one-step maximum-likelihood estimator. It is shown that the proposed estimation procedure provides an asymptotically efficient estimator for parameters of interest when the density for the mean of the bulked samples has a certain form. The lognormal density (with sigma 2 assumed known) is an important distribution with the proper form. The finite sample performance for bulked samples based on underlying lognormal observations was examined by Monte Carlo study. The results indicate that the proposed procedure leads to a reduction in mean squared error compared to known procedures.

Biopharmaceutics↗

PubMed1996

Experimental design and estimation of parameters in complex radioligand binding systems.

A computer was used to simulate data from typical radioligand binding experiments with a 2-site competitive-allosteric model of a receptor. The 4 equilibrium parameters of this model cannot be estimated by fitting the model to equilibrium data. Data from simulations of association experiments give satisfactory estimates of the 9 competitive-allosteric model parameters. From the kinetic parameters, equilibrium constants may be calculated. Combining data from equilibrium simulations with data from association simulations provided estimates of the model parameters with smaller standard deviations. A further improvement in design was shown possible by including simulated experiments in which receptor was preincubated with inhibitor before adding ligand. This improvement was documented using Monte Carlo replications of parameter estimates using competing experimental designs. Replications also revealed certain biases in the parameter estimates and could provide a means of estimating those biases when parameter estimates are made using experimental rather than simulated data. Simulations offer a powerful tool in planning experiments designed to estimate kinetic parameters of a receptor system. This is especially true with complex systems that may require pooling data from different kinds of experiments in order to estimate the kinetic parameters.

Binding, Competitive↗

PubMed1996

Is it possible to estimate the parameters of the sigmoid Emax model with truncated data typical of clinical studies?

Many drug concentration-effect relationships are described by the nonlinear sigmoid E(max) model. Clinical considerations frequently limit the magnitude of effect intensity that may be produced; the most pronounced effect intensity may be considerably below E(max). We have tested and quantified the influence of this limitation on the estimatability of the sigmoid E(max) model parameters. We have used the estimated parameter values to calculate data descriptors (drug concentrations required to produce certain effect intensities) and compared these with concentrations determined by using exact parameter values. We found that when the highest measured effect intensity was less than 95% of E(max), E(max) and EC50 were poorly estimated (high coefficient of variation and pronounced bias). Nevertheless, the fit to the data was quite good and the data descriptors were estimated with precision within the range for which data were available but not beyond. Baseline effect was estimated with good precision but the sigmoidicity parameter (gamma) was highly variable. Thus, where clinical considerations prevent determination of concentration-effect data near the maximum effect intensity, E(max) and EC50 estimations are unreliable. The use of estimable data descriptors is proposed to characterize the concentration-effect relationship under these conditions.

Dose-Response Relationship, Drug↗

PubMed2005

The effect of logarithmic compression on estimation of the Nakagami parameter for ultrasonic tissue characterization: a simulation study.

Previous studies have demonstrated that the Nakagami parameter estimated using the envelopes of backscattered ultrasound is useful in detecting variations in the concentration of scatterers in tissues. The signal processing in those studies was linear, whereas nonlinear logarithmic compression is routinely employed in existing ultrasonic scanners. We therefore explored the effect of the logarithmic compression on the estimation of the Nakagami parameter in this study. Computer simulations were used to produce backscattered signals of various scatterer concentrations for the estimation of the Nakagami parameters before and after applying the logarithmic compression on the backscattered envelopes. The simulated results showed that the logarithmic compression would move the statistics of the backscattered envelopes towards post-Rayleigh distributions for most scatterer concentrations. Moreover, the Nakagami parameter calculated using compressed backscattered envelopes is more sensitive than that calculated using uncompressed envelopes in differentiating variations in the scatterer concentration, making the former better at quantifying the scatterer concentration in biological tissues.

Algorithms↗

PubMed1996

Evaluation of respirometric data: identification of features that preclude data fitting with existing kinetic expressions.

The use of respirometric for from the evaluation of intrinsic biodegradation kinetic parameters for single organic compounds is discussed. Emphasis is placed on the preliminary assessment of the data set to determine whether it is suitable for kinetic parameter estimation. Careful preliminary examination of the data avoids attempting parameter estimation with unacceptable data. Furthermore, the use of unbiased respirometric data helps ensure that the estimated parameters truly reflect the intrinsic kinetics for biodegradation of a single substrate by the culture tested. Both experimental and theoretical oxygen uptake curves are used to illustrate how various conditions can limit the utility of a given data set. The effect of substrate inhibition, dual or multiple substrate limited growth, inaccuracies in the initial conditions assumed for curve fitting, and the use of poorly acclimated cultures are discussed. Techniques are presented which allow identification of whether a data set is unsuitable and should not be used for parameter estimation. In addition, experimental procedures which can help avoid the collection of aberrant data are discussed.

Biodegradation, Environmental↗

PubMed1998

Estimation of ventricular volume and elastance from the arterial pressure waveform.

We propose that it is possible to estimate cardiovascular parameters from the arterial pressure waveform, including ventricular maximal elastance and end-diastolic volume, if cardiac output is also known. We tested this hypothesis by means of a parameter estimation algorithm applied to simulated arterial pressure signals. The program first estimated three coefficients representing products of passive parameters from the diastolic part of the simulated arterial pressure waveform. Second, it estimated three parameter products pertaining to the ventricular function from the systolic part of the waveform. Third, mean blood flow was entered, enabling the program to compute individual parameters. This program was tested on 200 computer-generated arterial pressure signals, obtained by simulating the model with random but bounded parameters. Correlation between estimated parameters with those actually used in the simulations was excellent. Even though the value of this computer simulation is limited to the simplified model used and requires experimental validation, it demonstrates that the technique is theoretically feasible.

Blood Flow Velocity↗