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Biomedical subjects

U Rösler

Publications and source records attributed to U Rösler.

15 recordsLinked to original sources
PubMed1999

Errors of the backextrapolation method in determination of the blood volume.

Backextrapolation is an empirical method to calculate the central volume of distribution (for example the blood volume). It is based on the compartment model, which says that after an injection the substance is distributed instantaneously in the central volume with no time delay. The occurrence of recirculation is not taken into account. The change of concentration with time of indocyanine green (ICG) was observed in an in vitro model, in which the volume was recirculating in 60 s and the clearance of the ICG could be varied. It was found that the higher the elimination of ICG, the higher was the error of the backextrapolation method. The theoretical consideration of Schröder et al (Biomed. Tech. 42 (1997) 7-11) was proved. If the injected substance is eliminated somewhere in the body (i.e. not by radioactive decay), the backextrapolation method produces large errors.

Artifacts↗
PubMed1999

Optimizing deconvolution techniques by the application of the Münchhausen meta algorithm.

A deconvolution applied to disturbed data often gives poor results, due to fundamental difficulties associated with ill-posed problems. Many numerical and theoretical methods have been invented to circumvent this phenomenon. Their performance varies, depending on the given problem and data. The main aim of this paper is to provide a decision rule for choosing a method for deconvolution and application of this method to the same data. We have called this meta-algorithm Münchhausen. In this paper we introduce and describe for the first time the basic principle of artificial disturbance of the data in the set-up of deconvolution. We demonstrate some interesting features of the random procedure Münchhausen, such as the non parametric set-up, robustness to disturbance of the data and last but not least good performance.

Algorithms↗
PubMed1998

Simulation of the initial concentration-time course after intravenous application of the drug.

In this paper we present a widely applicable computational method for the description of the initial concentration-time-course after intravenous injection of a substance. The intravascular concentration-time course, r, is described as r = c0 + g x r, where the asterisk denotes the convolution operation, c0 is the concentration-time course during the first passage of the substance and g is the transport function of the body. If the body transport function is known, then the concentration-time course of a substance can be predicted. The site of interest can be chosen arbitrarily, i.e. the concentration-time course in the arterial circulation supplying any organ can be described. This might be of special interest for the optimal design of intravenous injections of contrast media, where initial concentrations at the region of interest determine the success of the diagnostic procedure.

Animals↗
PubMed1997

[LOGNORMAL-NLSQ-technique. Evaluation of a new mathematical method for determining blood volume].

This paper describes the investigation of a new mathematical method of calculating blood volume. The new method determines the blood volume by calculating the product of the mean circulation transit time. The mean transit time is calculated from the body transport function. To examine the accuracy of the LOGNORMAL-NLSQ technique, 45 concentration time curves were measured in an in vitro recirculation model with variable clearance. The calculated volume was 4% smaller than the actual volume. This may be attributed to the functional dead space within the model, and is tolerable for clinical situations. The LOGNORMAL-NLSQ technique might acquire considerable importance in future, especially since it provides accurate results very quickly.

Blood Flow Velocity↗
PubMed1995

Computation of the initial distribution of a drug by repetitive convolution with a circulatory transport function.

Hereby we present a widely applicable computational method for the description of recirculation and distribution phenomena occurring immediately after intravenous injection of a substance. The intravascular concentration-time course, r, is described as r = c0 + g * r, where the asterisk denotes the convolution operation, c0 is the concentration-time course during the first passage of the substance at an arterial measuring site and g is the transport function of the body. If the body transport function is known, then the arterial concentration-time course of a substance can be predicted for different amounts, injection times and elimination rates. The site of interest can be chosen arbitrarily, i.e. the concentration-time course in the arterial circulation supplying any organ can be described. This might be of special interest for the optimal design of intravenous injections of contrast media, where initial concentrations at the region of interest determine the success of the diagnostic procedure.

Animals↗
PubMed1994

[Dynamic blood volume determination using the body transport function].

This paper describes a dynamic blood volume determination which is faster and more accurate than the classic method. The new method determines blood volume by means of the product of the mean transit time of the circulation and the cardiac output. The mean transit time is calculated from the body transport function. To examine the precision of the dynamic method the blood volume of 24 patients was determined in both the dynamic and the classical way, using radioactively labelled erythrocytes. The comparison of the two methods resulted in a correlation coefficient of r = 0.77. The dynamic method of blood volume determination will be helpful especially in risk patients to accurately determine the quantities of fluids to be administered.

Biological Transport↗
PubMed1992

Calculation of body transport function.

A new model for simulation of recirculation has been developed which describes the measured concentration-time course of a drug in the aorta. It is based on repetitive convolution of the injected input dilution curve with a body transport function plus the input dilution curve. If the basic shape of a body transport function, i.e. such as log-normal distribution, is known, it is possible to calculate the parameters of this function with a non-linear least-squares procedure from measured tracer dilution data. In the present investigation this algorithm is used to estimate the body transport function for experimental data, obtained in two experiments with sheep. Once the body transport function is known, the formula can be used to describe the dispersion of a drug. Intravascular concentration time curves at different places in the body can also be predicted or the blood volume can be estimated.

Algorithms↗
PubMed1991

Deterministic in contrast to stochastic modeling.

The first attempt to model a process is often a deterministic setup with differential equations. The existing stochastic influence is suppressed and hopefully negligible. However, sometimes the stochastic component is important. We demonstrate and clarify this for a growth process. The deterministic approach is given by Yn + 1 = Yn + g(Yn) or dYt = g(Yt)dt, Y0 = 1, g a positive function. The corresponding stochastic equation is Xn + 1 = Xn + g(Xn)(1 + xi n) or dXt = g(Xt)dt + f(Xt)dWt, xi some random variable, W the Brownian motion. We compare the asymptotic behavior of the deterministic solution versus the stochastic solution.

Models, Theoretical↗
PubMed1989

Polymerase chain reaction: replication errors and reliability of gene diagnosis.

The impact of replication errors on the reliability of polymerase chain reaction (PCR) data is studied theoretically. Practical applications of our results to RFLP analysis and oligonucleotide probing confirm that for practical purposes replication errors can be neglected if a large number of starting templates (e.g. 100,000) is being used. For single locus analysis in single cells, however, the probability of false diagnosis due to such errors is of the order of 1 percent.

DNA Replication↗
PubMedDate not supplied

Simulation of arterial drug concentration after intravenous application.

The aim of this study was to develop a widely applicable model for circulatory indicator dispersion which could describe the pharmacokinetics of early drug distribution. The model assumes that the substance is injected into the right atrium and measured in the aorta. The dilution curve results from the dispersion and recirculation of the indicator in the body. The concentration time curve in the aorta, r, can be described as r = c0 + g* r, where g is the transport function of the body and c0 is the concentration time course, which is measured for the first time in the aorta. If the body transport function is known, then the aortic dilution curve of a drug can be predicted for different elimination rates and injection times. The site of interest can be chosen arbitrarily, i.e. the concentration of inflow into the kidney or any other organ can be described.

Animals↗
PubMedDate not supplied

[Asymptotic behavior of calculated concentration time curves].

The measured concentration time curve of an injected substance is often used as a basis for calculating the distribution volume. For the first time, the present paper describes a generally applicable formula for calculating the asymptote of a concentration time curve in medical applications. With a knowledge of this formula, previously unexplained phenomena (varying results obtained from two different methods of calculating the distribution volume) can now be understood. At the same time, errors of methodology (choice of injection and measuring sites) can be avoided.

Biological Availability↗
PubMedDate not supplied

Influence of long-time transportation stress on re-activation of Salmonella typhimurium DT104 in experimentally infected pigs.

In this study a Salmonella Typhimurium infection model in swine was used in order to investigate the influence of pre-mortal stress induced by long time period transportation on the re-activation of Salmonella in experimentally infected pigs. Salmonella free pigs were exposed to a highly virulent strain of Salmonella Typhimurium DT104 by direct intragastrical administration. Clinical parameters were monitored and the shedding rate in faeces was qualitatively and quantitatively determined by standard bacteriological procedures for 21 days. The distribution of the challenge organism in 14 different internal organs of transported and nontransported animals was determined. All infected animals developed clinical signs of salmonellosis 12 to 24 hours post infection. About 88 to 100% of the fecal samples were culture-positive up to post exposure day 6, and then varied from 71 to 92% until slaughter, respectively. At necropsy S. Typhimurium was recovered most frequently from caecum and ileocolic lymph nodes (83%), colon (79%), palatine tonsils (71%) and mandibular lymph nodes (62.5%). A negative impact of transportation stress on the shedding rate and the general condition of the animals was observed.

Animals↗
PubMedDate not supplied

Improvement of an invA-based PCR for the specific detection of Salmonella typhimurium in organs of pigs.

The aim of this study was to investigate the suitability of the invA-based polymerase chain reaction (PCR) assay for the specific detection of Salmonella in organs of experimentally infected pigs and to compare these results to classical bacterial culture. While the PCR conditions specified in the "Deutsche Industrie Norm", DIN 10135 (section 35 LMBG, 1999), cutle based on the publication of Rahn et al. 1992, revealed various unspecific amplification products, modifications of the PCR conditions allowed the specific amplification of the invA fragment from inner organs. The modified PCR assay correlates exactly with cultivation results (as required by DIN Norm 6579) and enables the detection of Salmonella within 48 hours with equal sensitivity compared to routine cultivation.

Animals↗