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Results for “Deconvolution”

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PubMed1989

Numerical stability of pharmacokinetic deconvolution algorithms.

The sensitivity of pharmacokinetic deconvolution algorithms with respect to simulated experimental error has been studied. Approximations of cumulative absorption profiles reconstructed from simulated data sets with normally distributed random error were compared with corresponding known input functions. The coincidence of both functions was assessed in 600 numerical experiments by the nonparametric Kolmogorov-Smirnov test. A constrained iterative nonlinear regression procedure based on the analytical convolution of multiphasic zero-order input functions with linear disposition models was found to perform well under conditions where the results of direct numerical deconvolution and model-based mass balance methods were unsatisfactory.

Absorption↗

PubMed1992

Adaptive computer program for determination of absorption profiles by numerical deconvolution: application to amoxicillin absorption.

We have developed a specific numerical deconvolution program for the Apple Macintosh microcomputer. After comparison with other methods, we used the program to evaluate the influence of nifedipine on the absorption and bioavailability of amoxicillin. The technique provided a model-independent approach. This study shows that the simultaneous administration of nifedipine with amoxicillin leads to a significant increase in both the total quantity of amoxicillin absorbed (+22%) and the rate of absorption. Parameters of clearance, volume of distribution, and elimination were unaffected. Numerical deconvolution analysis showed that nifedipine did not modify the absorption kinetics of amoxicillin, which are characterized by a lag time followed by a constant rate of absorption, suggesting zero-order kinetics with first-order kinetics at the end of the process. The results suggest the existence of a specialized, saturable transport molecule for this antibiotic.

Adult↗

PubMed1994

Deconvolution method for assessing the absorption of a drug with reversible metabolic pathways.

A method has been established to determine the input rate for a drug with reversible metabolic processes. This method is based on linear system properties without imposing a compartment model for describing the disposition of the drug and the metabolite and their interconnections. The solution is a deconvolution method in N-dimensional space. A general solution has been obtained for calculating the parameters needed to describe the input function. The specific solution for a staircase input function (point-area deconvolution) is explicitly derived. Using a staircase input function is not a robust method and can give negative input values when applied to simulated data sets with a large amount of variability. This suggests the need for more robust functional forms to describe the input function.

Absorption↗

PubMed2002

Perfusion quantification using Gaussian process deconvolution.

The quantification of perfusion using dynamic susceptibility contrast MRI (DSC-MRI) requires deconvolution to obtain the residual impulse response function (IRF). In this work, a method using the Gaussian process for deconvolution (GPD) is proposed. The fact that the IRF is smooth is incorporated as a constraint in the method. The GPD method, which automatically estimates the noise level in each voxel, has the advantage that model parameters are optimized automatically. The GPD is compared to singular value decomposition (SVD) using a common threshold for the singular values, and to SVD using a threshold optimized according to the noise level in each voxel. The comparison is carried out using artificial data as well as data from healthy volunteers. It is shown that GPD is comparable to SVD with a variable optimized threshold when determining the maximum of the IRF, which is directly related to the perfusion. GPD provides a better estimate of the entire IRF. As the signal-to-noise ratio (SNR) increases or the time resolution of the measurements increases, GPD is shown to be superior to SVD. This is also found for large distribution volumes.

Cerebrovascular Circulation↗

PubMed1994

Automated processing for proton spectroscopic imaging using water reference deconvolution.

Automated formation of MR spectroscopic images (MRSI) is necessary before routine application of these methods is possible for in vivo studies; however, this task is complicated by the presence of spatially dependent instrumental distortions and the complex nature of the MR spectrum. A data processing method is presented for completely automated formation of in vivo proton spectroscopic images, and applied for analysis of human brain metabolites. This procedure uses the water reference deconvolution method (G. A. Morris, J. Magn. Reson. 80, 547(1988)) to correct for line shape distortions caused by instrumental and sample characteristics, followed by parametric spectral analysis. Results for automated image formation were found to compare favorably with operator dependent spectral integration methods. While the water reference deconvolution processing was found to provide good correction of spatially dependent resonance frequency shifts, it was found to be susceptible to errors for correction of line shape distortions. These occur due to differences between the water reference and the metabolite distributions.

Artifacts↗

PubMed1992

Differentiation between transmembrane helices and peripheral helices by the deconvolution of circular dichroism spectra of membrane proteins.

The interpretation of the circular dichroism (CD) spectra of proteins to date requires additional secondary structural information of the proteins to be analyzed, such as X-ray or NMR data. Therefore, these methods are inappropriate for a CD database whose secondary structures are unknown, as in the case of the membrane proteins. The convex constraint analysis algorithm (Perczel, A., Hollósi, M., Tusnády, G., & Fasman, G. D., 1991, Protein Eng. 4, 669-679), on the other hand, operates only on a collection of spectral data to extract the common spectral components with their spectral weights. The linear combinations of these derived "pure" CD curves can reconstruct the original data set with great accuracy. For a membrane protein data set, the five-component spectra so obtained from the deconvolution consisted of two different types of alpha helices (the alpha helix in the soluble domain and the alpha T helix, for the transmembrane alpha helix), a beta-pleated sheet, a class C-like spectrum related to beta turns, and a spectrum correlated with the unordered conformation. The deconvoluted CD spectrum for the alpha T helix was characterized by a positive red-shifted band in the range 195-200 nm (+95,000 deg cm2 dmol-1), with the intensity of the negative band at 208 nm being slightly less negative than that of the 222-nm band (-50,000 and -60,000 deg cm2 dmol-1, respectively) in comparison with the regular alpha helix, with a positive band at 190 nm and two negative bands at 208 and 222 nm with magnitudes of +70,000, -30,000, and -30,000 deg cm2 dmol-1, respectively.

Adenosine Triphosphatases↗

PubMed2006

Study of automated mass spectral deconvolution and identification system (AMDIS) in pesticide residue analysis.

The effects of overlapping levels and concentration ratios of overlapping components, and of scan rates of the mass spectrometer, on the capability of the automated mass spectral deconvolution and identification system (AMDIS) in pesticide residue analysis were studied. To investigate the capability of AMDIS in removing interferences from the overlapping peaks, this system was applied to data files obtained from the gas chromatography/mass spectrometry (GC/MS) analysis of two overlapping (co-eluting) pesticides (beta-HCH and PCNB) in full scan mode. Differences in overlap levels, the concentration ratios of the two overlapping components and the scan rates of the instrument were studied. When the difference in scan number of overlapping compounds was equal to 1 scan, AMDIS incompletely extracted 'purified' mass spectra but as the difference increased to 3 or more scans, complete correct spectra could be extracted. The results also show that when the scan rate was in the range of 0.4-0.90 s/scan and the concentration ratios of the target compound/interference were above 1/5, there were ideal deconvolution results for this approach. To further study the application of AMDIS to pesticide residue analysis, AMDIS was applied to the identification of pesticides spiked in real samples (cabbage and rice). Typical pesticides being evaluated were identified using AMDIS at concentrations >50 ng/g in the extracts.

Brassica↗

PubMed1995

Spectral lineshape determination by self-deconvolution.

A data-processing method is described for the determination of spectral lineshapes using deconvolution of the data with an initial estimate of the same spectrum, referred to as self-deconvolution. The method is demonstrated using computer-simulation studies and experimental data, and is shown to accurately determine amplitude and phase lineshape distortions which may be caused by field inhomogeneity and gradient eddy-current effects. The results indicate that the method is robust in the presence of noise and errors in the initial spectral estimate. Once the spectral lineshape is determined it can be incorporated into a parametric spectral-analysis procedure, thereby reducing the number of parameters to be determined and improving the accuracy of the fit. A proposed application of the method is for spatially resolved in vivo NMR studies where local susceptibility effects and gradient eddy-current effects cause significant deviation of the spectral lineshape from a Lorentzian lineshape.

Algorithms↗

PubMed1999

Determination of coupling constants by deconvolution of multiplets in NMR

The structures of multiplets in one- and two-dimensional NMR spectra can be simplified by recursive deconvolution in the frequency domain. Deconvolution procedures are described for in-phase and antiphase doublets of delta functions. Recursive simplification is illustrated by applications to double-quantum-filtered correlation spectra (DQF-COSY) and selective correlation spectra (soft-COSY). Coupling constants can be measured reliably even if signals of opposite signs lead to partial cancellation. Copyright 1999 Academic Press.

Journal Article↗

PubMed2001

Deconvolution and measurement of spin-spin splittings by modified J doubling in the frequency domain.

A new implementation of J doubling in the frequency domain is proposed. This modified J doubling uses novel sets of delta functions [..., +1, -1, +1, +1, -1, +1, ...] for in-phase multiplets and [..., -1, -1, -1, +1, +1, +1, ...] for antiphase multiplets. The convolution process together with the couplings found by it generates a deconvoluted multiplet that preserves the integral and the position of the original one. If the number of delta functions tends to infinity, the whole operation behaves like a formal deconvolution of the multiplet, which is a linear process. Modified J doubling allows for multistage procedures. This makes it possible to analyze 2D multiplets and to measure coupling constants as small as 0.11 Hz with an accuracy of +/-0.03 Hz.

Journal Article↗

PubMed1981

Deconvolution analysis of 99mTc-methylene diphosphonate kinetics in metabolic bone disease.

The kinetics of 99mTc-methylene diphosphonate (MDP) and 47Ca were studied in three patients with osteoporosis, three patients with hyperparathyroidism, and two patients with osteomalacia. The activities of 99mTc-MDP were recorded in the lumbar spine, paravertebral soft tissues, and in venous blood samples for 1 h after injection. The results were submitted to deconvolution analysis to determine regional bone accumulation rates. 47Ca kinetics were analysed by a linear two-compartment model quantitating short-term mineral exchange, exchangeable bone calcium, and calcium accretion. The 99mTc-MDP accumulation rates were small in osteoporosis, greater in hyperparathyroidism, and greatest in osteomalacia. No correlations were obtained between 99mTc-MDP bone accumulation rates and the results of 47Ca kinetics. However, there was a significant relationship between the level of serum alkaline phosphatase and bone accumulation rates (R = 0.71, P less than 0.025). As a result deconvolution analysis of regional 99mTc-MDP kinetics in dynamic bone scans might be useful to quantitate osseous tracer accumulation in metabolic bone disease. The lack of correlation between the results of 99mTc-MDP kinetics and 47Ca kinetics might suggest a preferential binding of 99mTc-MDP to the organic matrix of the bone, as has been suggested by other authors on the basis of experimental and clinical investigations.

Adult↗

PubMed1988

The appended curve technique for deconvolutional analysis--method and validation.

Deconvolutional analysis (DCA) is useful in correction of organ time activity curves (response function) for variations in blood activity (input function). Despite enthusiastic reports of applications of DCA in renal and cardiac scintigraphy, routine use has awaited an easily implemented algorithm which is insensitive to statistical noise. The matrix method suffers from the propagation of errors in early data points through the entire curve. Curve fitting or constraint methods require prior knowledge of the expected form of the results. DCA by Fourier transforms (FT) is less influenced by single data points but often suffers from high frequency artifacts which result from the abrupt termination of data acquisition at a nonzero value. To reduce this artifact, we extend the input (i) and response curves to three to five times the initial period of data acquisition (P) by appending a smooth low frequency curve with a gradual taper to zero. Satisfactory results have been obtained using a half cosine curve of length 2-3P. The FTs of the input and response I and R, are computed and R/I determined. The inverse FT is performed and the curve segment corresponding to the initial period of acquisition (P) is retained. We have validated this technique in a dog model by comparing the mean renal transit times of 131I-iodohippuran by direct renal artery injection to that calculated by deconvolution of an intravenous injection. The correlation was excellent (r = 0.97, P less than 0.005). The extension of the data curves by appending a low frequency "tail" before DCA reduces the data termination artifact. This method is rapid, simple, and easily implemented on a microcomputer.(ABSTRACT TRUNCATED AT 250 WORDS)

Animals↗

PubMed1985

Deconvolution applied to the kinetics of extracorporal drug removal. Haemodialysis of cefsulodin.

A novel approach to the evaluation of the kinetics of drug removal by an extracorporal device (ECD), e.g., haemodialysis, haemofiltration, and haemoperfusion, is presented. The rate and extent of extracorporal drug removal (ECR) are determined by deconvolution. The proposed method is model independent in the sense that no specific models of corporal or extracorporal disposition are required. The estimation of various derived functions and parameters useful for describing ECR such as clearance and fractional drug removal are facilitated by the technique. The kinetics of cefsulodin elimination by haemodialysis in 3 patients were evaluated using the deconvolution approach. The results indicated that cefsulodin was dialyzable with approximately 50% of the drug in the body removed by haemodialysis over 3-4 h.

Cefsulodin↗

PubMed1986

A note on appropriate constraints on the initial input response when applying deconvolution.

When deconvolution is employed to estimate cumulative input profiles, nonzero initial values may result unless certain constraints are imposed on the function used to approximate the input response c(t). It is shown that the initial value of the response to a nonimpulse input is zero, i.e., c(t0) = 0, where t0 is the input lag time. If, in addition, the initial value of the impulse response is zero, i.e., c delta (0) = 0, then c'(t0) = 0. Therefore, it is appropriate to impose the constraint c(t0) = 0 in general and c'(t0) = 0 when c delta (0) = 0 if c(t) is the response to a nonimpulse input. The use of such constraints is demonstrated in an example where the cumulative in vivo dissolution profile is estimated by deconvolution.

Animals↗

PubMed1990

Comments on two recent deconvolution methods.

In a recent paper Vajda et al. presented a deconvolution method based on the assumptions that the response of a system and the input function to a system are described by first-order linear processes. The method is similar to one proposed by Veng-Pedersen, and obtains similar results. In this article a simpler, not new, and now generally available method for this special use is considered to point out potential risks associated with all three deconvolution methods.

Cimetidine↗

PubMed1988

Numerical deconvolution using system identification methods.

A deconvolution method is presented for use in pharmacokinetic applications involving continuous models and small samples of discrete observations. The method is based on the continuous-time counterpart of discrete-time least squares system identification, well established in control engineering. The same technique, requiring only the solution of a linear regression problem, is used both in system identification and input identification steps. The deconvolution requires no a priori information, since the proposed procedure performs system identification (including optimal selection of model order), selects the form of the input function and calculates its parametric representation and its values at specified time points.

Models, Biological↗

PubMed1995

A nonparametric subject-specific population method for deconvolution: II. External validation.

A lot of attention has been given in the past to deconvolution and in particular to its nonparametric variants. In a companion paper (1), we present a fully nonparametric deconvolution method in which subject specificity is explicitly taken into account. To do so we use so-called "longitudinal splines." A longitudinal spline is a nonparametric function composed of a template spline, in common to all subjects, and of a distortion spline representing the difference of the subject's function from the template. In this paper we concentrate on testing and documenting the performance of this nonparametric methodology in terms of the approximation of unknown functions. We simulate population data using parametric functions, and use longitudinal splines to recover the unknown functions. We consider different estimation methods including (1) parametric nonlinear mixed effect, (2) least squares, and (3) two-stage. Methods 2-3 are more robust than Method 1, and obtain reliable estimates of the unknown functions. The lack of robustness of Method 1 appears to be due to the misspecifications of the distribution of the subjects' parameters. Results also suggest that in a data-rich situation nonparametric nonlinear mixed-effect models should be preferred.

Models, Theoretical↗

PubMed1999

Linear spectral deconvolution of catabolic plasma concentration decay in dialysis.

Deconvolution can be a useful step in the process of modelling biological data, as it produces an overview of the information content of the data, as well as directions about the structure of the mathematical model able to describe the generating system. This paper concerns the application of a deconvolution technique, spectral analysis, to the modelling process of the concentrations of metabolites sampled in plasma during dialysis: the spectral analysis consists in linearly identifying the whole spectrum of multi-exponential decays, describing the compartmental nature of the process. The application to urea and creatinin time series provides a careful determination of the spectra of the exponential decays, thus giving interesting insight into the system kinetics: a sharp, slow decay (about 0.23 h-1 for urea and 0.17 h-1 for creatinin) affects all the subjects, whereas a variable set of smaller and faster components accounts for interpatient variability as well as for the multicompartmental nature of the process. The power ratio of the components is an index of the relative amount of volume in the related compartments. The identified spectra provide a description of the data that, although computed in a very simple way, is consistent with the results of the classical identification techniques previously applied in building compartmental models of dialysis.

Computational Biology↗