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PubMed1992

Deconvolution analysis of hormone data.

Deconvolution analysis of hormone data poses special problems in view of the sparse, noisy, and short data series typically available for analysis; the unknown true nature of the underlying secretory event; and potentially large variations in dissipation or clearance kinetics in different settings. Consequently, deconvolution techniques, which concern themselves with the estimation of hormone secretion and/or clearance based on serial circulating hormone concentration measurements, face a particular challenge. Ideal features of deconvolution algorithms are summarized in Table IV. Specific deconvolution techniques available to analyze hormone data include both waveform-defined procedures and waveform-independent algorithms. These approaches should be viewed as complementary rather than antagonistic. All deconvolution techniques are subject to individual limitations and specific strengths. Independently of the method employed, error propagation is necessary so as to define the statistical uncertainty intrinsic to the estimate of secretion and clearance. Such calculations of experimental uncertainty should include error inherent in the sample collection, processing, and assay as well as error in the kinetic constants and/or anticipated departures of the biological process from the algebraic structure of the convolution formulation. Moreover, more complex convolution statements will be required to describe the full range of behavior of hormone data in a systems view. The applications of such newer convolution methods as well as currently available techniques include model synthesis, model testing, and analysis of the interactions among multiple pulse generators.

Algorithms↗

PubMed1991

Absorption profiles of rectally administered midazolam estimated by deconvolution.

UNLABELLED: An algebraic deconvolution procedure adopted from the literature has been used to estimate the absorption profiles of rectally administered midazolam (0.3 mg/kg) in 8 healthy subjects. The extent of absorption estimated by the conventional AUC approach has previously been published and was compared to the deconvolution results. In the original study the sampling period was 840 min. When a deconvolution approach is used there may be no need to sample after the absorption is completed. Thus in this communication only samples drawn within the first 120 min and 300 min were used. The bioavailability estimated by the AUC ratio (mean 0.52 +/- SDrel 16%) is compared to the deconvolution results obtained using only data points within 120 (0.46 +/- 22%) (p = 0.02) and 300 min (0.51 +/- 20%) (p = 0.6) after drug administration. The absorption is almost complete after 120 min. Regarding the absorption rates 40% (range 27.55%) of the dose is absorbed after 60 min. The relative (normalised) absorption profiles showed that 79% (range 63-90%) of the maximum absorbed amount is absorbed within 60 min. IN CONCLUSION: Information regarding the rectal absorption of midazolam can be obtained from a sampling period of approximately 5 hours using the deconvolution approach. The algorithm used is relative easy to implement and is very easy to use with polyexponential parameters obtained by curve fitting as input.

Administration, Rectal↗

PubMed1979

Deconvolution analysis in radionuclide quantitation of left-to-right cardiac shunts.

A poor bolus injection results in an unsatisfactory quantitative radionuclide angiocardiogram in as many as 20% of children with possible, left-to-right (L-R) cardiac shunts. Deconvolution analysis was applied to similar studies in experimental animals to determine whether dependence on the input bolus could be minimized. Repeated good-bolus, prolonged (greater than 2.5 sec), or multiple-peak injections were made in four normal dogs and seven dogs with surgically created atrial septal defects (ASD). QP/QS was determined using the gamma function. The mean QP/QS from ten good-bolus studies in each animal was used as the standard for comparison. In five trials in normal animals, where a prolonged or double-peak bolus led to a shunt calculation (QP/QS greater than 1.2 : 1), deconvolution resulted in QP/QS = 1.0. Deconvolution improved shunt quantitation in eight of ten trials in animals that received a prolonged bolus. The correlation between the reference QP/QS and the QP/QS calculated from uncorrected bad bolus studies was only 0.39 (p greater than 0.20). After deconvolution using a low pass filter, the correlation improved significantly (r = 0.77, p less than 0.01). The technique gave inconsistent results with multiple-peak bolus injections. Deconvolution analysis in these studies is useful in preventing normals from being classified as shunts, and in improving shunt quantitation after a prolonged bolus. Clinical testing of this technique in children with suspected L-R shunts seems warranted.

Angiocardiography↗

PubMed1992

Bioavailability of hydroxychloroquine tablets assessed with deconvolution techniques.

Four deconvolution methods (staircase, delta function, and least squares methods using single and sequential first-order input functions) were used to assess the absolute bioavailability of hydroxychloroquine tablets in nine healthy fasting volunteers. The volunteers received, in a random crossover design, a 155-mg oral tablet and a 155-mg iv infusion of racemic hydroxychloroquine. The mean fractions of the dose absorbed, calculated using the four deconvolution methods, were not statistically different (p = 0.70). The mean fraction absorbed (+/- SD) was 0.67 +/- 0.12, which was not significantly different from that reported previously in a conventional bioavailability study (p = 0.22). The mean absorption half-life was calculated to be 4.0 +/- 1.3 h. The mean lag time before absorption commenced was 0.57 +/- 0.30 h. The fraction of the dose absorbed ranged from 0.44 to 0.86. Low and/or variable bioavailability of hydroxychloroquine may be a cause of therapeutic failure in some patients. Validation of the deconvolution methods means that these techniques may now be used to assess the bioavailability of hydroxychloroquine in patients. An advantage of these methods is that samples need only be collected over the expected time period of absorption, rather than the whole time drug can be detected in the body, as is required in conventional area under the concentration-time curve ratio methods. Deconvolution studies may be completed in 2 weeks rather than the 10 months required for a conventional bioavailability study of hydroxychloroquine.

Adult↗

PubMed1992

An algorithm for constrained deconvolution based on reparameterization.

The method of deconvolution is the most general method of evaluating drug absorption. Deconvolution does not normally subscribe to a particular structured model for the input function that would ensure non-negativity of the calculated input rate. Unfortunately, the increased flexibility gained by this "model independence" sometimes results in a calculated input rate that becomes negative in the late absorption phase. A method for constrained deconvolution is proposed to overcome this deficiency. The method is based on a reparameterization of the input function in a "model-free" context. The reparameterization schemes proposed are optimal in the sense that they give the input function its maximum flexibility possible while at the same time ensuring non-negativity. The method makes use of "deconvolution through convolution." The basic procedure of this technique is, during the curve fitting, to iteratively adjust the input function so that when it is convolved with the unit impulse response function it results in a curve that best fits the data from the extravascular administration. Cimetidine data from oral and iv administrations are deconvolved by the proposed method to demonstrate the basic procedures involved. The proposed method is easy to implement since it relies on simple curve-fitting procedures as routinely performed in pharmacokinetics. The procedure can be carried out using any of the many curve-fitting programs available that allow the user to supply the function to be fitted and allow simple bounds to be specified for the fitted parameters. The convolution required by the method can be done analytically using a previously published computer program.

Algorithms↗

PubMed1991

Analyzing pulsatile endocrine data in patients with chronic renal failure: a brief review of deconvolution techniques.

Deconvolution analysis provides an important new technique to evaluate underlying hormone secretory rates quantitatively based upon serially measured plasma hormone concentrations with or without prior knowledge of the half-time of hormone disappearance from the blood. Information about endocrine gland secretion is particularly important in chronic renal failure, wherein the decreased metabolic clearance rates of various hormones would otherwise confound the interpretation of plasma hormone concentrations. Here we review two particularly useful techniques of deconvolution, one of which is a waveform-defined algorithm and the other waveform independent. The first method can be used to estimate both hormone half-life and secretory rates in vivo. The second methodology allows calculation of in vivo hormone secretion rates without assuming any special form for the secretion event, but requires a priori knowledge of hormone half-life. We illustrate examples of these two deconvolution approaches, and discuss why the interpretations of hormone concentration measurements in earlier studies (where deconvolution methods were not employed) must be viewed with caution. Based on such considerations, additional investigations of in vivo hormone secretory pathophysiology will be required in children and adults with chronic renal failure.

Endocrine Glands↗

PubMed1990

Obtaining meaningful results from Fourier deconvolution of reaction time data.

The technique of Fourier deconvolution is a powerful tool for testing distributional predictions of stage models of reaction time. However, direct application of Fourier theory to reaction time data has sometimes produced disappointing results. This article reviews Fourier transform theory as it applies to the problem of deconvolving a component of the reaction time distribution. Problems encountered in deconvolution are shown to be due to the presence of noise in the Fourier transforms of the sampled distributions, which is amplified by the operation of deconvolution. A variety of filtering techniques for the removal of noise are discussed, including window functions, adaptive kernel smoothing, and optimal Wiener filtering. The best results were obtained using a window function whose pass band was determined empirically from the power spectrum of the deconvolved distribution. These findings are discussed in relation to other, nontrigonometric approaches to the problem of deconvolution.

Computer Simulation↗

PubMed1992

Estimation of organ transport function: model-free deconvolution by recursive quadratic programming optimization.

A model-free deconvolution method is proposed for evaluating the frequency distribution function of organ transit times. The deconvolution is treated as a nonlinear constrained optimization problem and it is solved by using a modified constrained variable metric approach. The only constraint implemented in the solution is that all the discrete transport function values are not allowed to become negative. The method is tested on model mathematical systems of known analytical transport functions. The tests are performed on systems that included noise in both the input and output functions. The criteria of successful deconvolution are the reconvolution error and, most importantly, the deviation of the computed transport function from the known analytical one. The proposed method is then applied, as a pilot experiment, to biological data obtained from an isolated, perfused rabbit lung preparation contained within a plethysmograph. The results indicate that this type of deconvolution produces stable estimates which faithfully follow the analytical function while negating the need to assume either any functional form for the behavior of the transport function or any educated initial guess of its values.

Algorithms↗

PubMedDate not supplied

Improved quantification of radionuclide uptake using deconvolution and windowed subtraction techniques for scatter compensation in single photon emission computed tomography.

A comparison of two methods of scatter compensation in single photon emission computed tomography (SPECT) imaging is made on the basis of improvements in quantification. The methods, scatter-window subtraction and constrained deconvolution of an average point source response function (PSRF), are described; the theoretical basis of each method is also briefly assessed. Improvements in relative quantification offered by each method are measured by examining ratios of counts in hot cylinders to counts in a slightly radioactive background. The cylinder/background concentration ratio was varied by a factor of five; the sizes of the cylinders remained constant. Keeping the diameter of the cylinders constant allowed for an assessment of the effect of concentration differences, without the conflicting effect of variation in the size of the hot source. Results showed that while both scatter-window subtraction and constrained deconvolution offer quantification improvements in the final image, the method of prereconstruction deconvolution of a planar PSRF from each planar projection is substantially more successful than either scatter-window subtraction or other methods of implementing the deconvolution procedure.

Biophysical Phenomena↗

PubMed1991

The influence of noise on quantal EPSP size obtained by deconvolution in spinal motoneurons in the cat.

1. The amplitudes of quantal components that make up single-fiber excitatory postsynaptic potentials (EPSPS) were determined by a deconvolution technique and by simulation studies and were compared with the background noise. 2. A strong correlation was found between the sizes of EPSP quantal components and the standard deviation of the noise from which the data were extracted by deconvolution. A similar correlation was then shown in published data from several other laboratories. 3. EPSPS having amplitudes less than 100 microV were recorded that had little or no variance in their amplitudes. Most of these EPSPS showed a much smaller peak variance than would be expected if they fluctuated among amplitudes in steps of approximately 100 microV--the proposed mean value for the amplitude of the quantal EPSP. 4. Deconvolution of simulated data with the maximum likelihood algorithm resulted in the suppression of components less than 1.5 SD of the background noise. The remaining components were approximately equally spaced. No way was found to detect this error, and rejection of deconvolved data with components less than 1.5 noise SD did not eliminate it. The resulting erroneous data showed a strong correlation between the amplitudes of the components obtained and the noise standard deviation. 5. It is concluded that at least some EPSPS generated by single Ia-afferents on motoneurons are composed of quantal components significantly less than 100 microV and that deconvolution procedures are not capable of detecting such small components.

Action Potentials↗

PubMed1992

A computer program (DCN) for numerical convolution and deconvolution of pharmacokinetic functions.

A program adapted for use on microcomputers (DCN) has been developed which permits one to perform operations of numerical convolution and deconvolution using polyexponential functions, that are often implemented in pharmacokinetic analysis. The program is written in Microsoft GWBASIC and can be used in personal computers with no modification. The user supplies information relating to the coefficients and exponentials defining the polyexponential equation of the response and weighting functions and the program performs the deconvolution operation by numerical integration using trapezoidal rule and provides numerical and graphic information concerning the input function. The program can be applied to the deconvolution of many linear pharmacokinetic systems and allows one to solve problems related to drug release, absorption, distribution, as well as others. Additionally, the program is able to perform the convolution operation if information about the input and weighting functions and is also able to simulate pharmacokinetic processes. The efficacy of the program was evaluated by comparison with several deconvolution algorithms, in particular that proposed by Veng-Pedersen and Iga.

Algorithms↗

PubMed1992

Pulsatile secretion of LH in the ram: a re-evaluation using a discrete deconvolution analysis.

The purpose of the present experiment was to characterize LH secretion pulsatility in rams by analysing the instantaneous secretion rate profile obtained by deconvoluting the plasma concentration profile. Plasma LH concentration profiles were obtained by collecting blood samples every 6 min for 24 h during two different sessions separated by an interval of 15 days. Individual kinetic parameters of ovine LH (oLH) were determined following i.v. injection of oLH. By deconvoluting the plasma concentration profile, it was shown that a pulse has an effective duration of only 20.41 +/- 7.69 (S.D.) min whereas the mean duration estimated from measurement of plasma concentrations was 61.00 +/- 15.16 min. The number of pulses was similar before and after deconvolution (7.80 +/- 1.99 vs 9.70 +/- 3.44 pulses/24 h respectively). Using deconvolution the calculated production rate was 2.26 +/- 0.94 micrograms/kg per 24 h, about 50% of this production being located in the pulses. Statistical analysis of pulsatility revealed that pulse occurrence was a nonperiodic event and that the amplitude of LH pulses and the associated amount of LH released were correlated with the duration of the preceding quiescence period, but had no statistically significant influence on the duration of the following quiescence period.

Animals↗

PubMed2025

OmicsTweezer: A distribution-independent cell deconvolution model for multi-omics Data.

Cell deconvolution estimates cell type proportions from bulk omics data, enabling insights into tissue microenvironments and disease. However, practical applications are often hindered by batch effects between bulk data and referenced single-cell data, a challenge that is frequently overlooked. To address this discrepancy, we developed OmicsTweezer, a distribution-independent cell deconvolution model. By integrating optimal transport with deep learning, OmicsTweezer aligns simulated and real data in a shared latent space, effectively mitigating data shifts and inter-omics distribution differences. OmicsTweezer is versatile, capable of deconvolving bulk RNA-seq, bulk proteomics, and spatial transcriptomics. Extensive evaluations on simulated and real-world datasets demonstrate its robustness and accuracy. Furthermore, applications in prostate and colon cancer showcase OmicsTweezer's ability to identify biologically meaningful cell types. As a unified deconvolution framework for multi-omics data, OmicsTweezer offers an efficient and powerful tool for studying disease microenvironments.

Humans↗

PubMedDate not supplied

Reblurred deconvolution method for chemical shift removal in F-19 (PFOB) MR imaging.

Perfluorocarbons such as perfluoroctylbromide (PFOB) can be used as contrast agents in the vascular system for fluorine-19 magnetic resonance imaging or as synthetic oxygen carriers. F-19 imaging has been proposed for studying the vascular system, capillary flow, tissue perfusion, and tumor oxygenation. A major difficulty is that F-19 compounds often have complex multipeak spectra. These peaks result in chemical shift artifacts, lower signal-to-noise ratios, and blurred images. Each peak also excites a different section when a section-select gradient is applied. Direct inverse filtering is the simplest deconvolution method for correcting such artifacts; however, two major difficulties present themselves: functional singularity and noise amplification at high frequencies. The use of a new reblurred deconvolution (RED) method appears to overcome these problems. Although this method is based on iterative deconvolution in the spatial domain, the computational overhead is negligible. Since the point spread function and object data are already available in the time domain as FID data, RED appears to be useful for eliminating chemical shift artifacts and suppressing noise amplification while restoring the original image without loss of resolution.

Contrast Media↗

PubMed1992

Deconvolution of the circular dichroism spectra of proteins: the circular dichroism spectra of the antiparallel beta-sheet in proteins.

A recently developed algorithm, called Convex Constraint Analysis (CCA), was successfully applied to determine the circular dichroism (CD) spectra of the pure beta-pleated sheet in globular proteins. On the basis of X-ray diffraction determined secondary structures, the original data set used (Perczel, A., Hollosi, M., Tusnady, G. Fasman, G.D. Convex constraint analysis: A natural deconvolution of circular dichroism curves of proteins, Prot. Eng., 4:669-679, 1991), was improved by the addition of proteins with high beta-pleated sheet content. The analysis yielded CD curves of the pure components of the main secondary structural elements (alpha-helix, antiparallel beta-pleated sheet, beta-turns, and unordered conformation), as well as a curve attributed to the "aromatic contribution" in the wavelength range of 195-240 nm. Upon deconvolution the curves obtained were assigned to various secondary structures. The calculated weights (percentages determining the contributions of each pure component curve in the measured CD spectra of a given protein) were correlated with the X-ray diffraction determined percentages in an assignment procedure and were evaluated. The Pearson product correlation coefficients (R) are significant for all five components. The new pure component curves, which were obtained through deconvolution of the protein CD spectra alone, are promising candidates for determining the percentages of the secondary structural components in globular proteins without the necessity of adopting an X-ray database. The CD spectrum of the CheY protein was interesting because it has the characteristic shape associated with the alpha-helical structure, but upon analysis yielded a considerable amount of beta-sheet in agreement with the X-ray structure.

Circular Dichroism↗

PubMed1991

Deconvolution method for accurate determination of overlapping peak areas in chromatograms.

A method is described for deconvoluting chromatograms which contain overlapping peaks. Parameters can be selected to ensure that attenuation of peak areas is uniform over any desired range of peak widths. A simple extension of the method greatly reduces the negative overshoot frequently encountered with deconvolutions. The deconvoluted chromatograms are suitable for integration by conventional methods.

Chromatography↗

PubMed1991

Ideal versus human observer for long-tailed point spread functions: does deconvolution help?

The ideal observer represents a Bayesian approach to performing detection tasks. Since such tasks are frequently used as a prototype tasks for radiological imaging systems, the detectability measured at the output of an ideal detector can be used as a figure of merit to characterize the imaging system. For the detectability achieved by the ideal observer to be a good figure of merit, it should predict the ability of the human observer to perform the same detection task. Of great general interest, especially to the medical community, are imaging devices with long-tailed point spread functions (PSFs). Such PSFs may occur due to septal penetration in collimators, veiling glare in image intensifiers or scattered radiation in the body. We have investigated the effect that this type of PSF has on human visual signal detection and whether any improvement in performance can be gained by deconvolving the tails of the PSF. For the ideal observer, it is straightforward to show that the performance is independent of any linear, invertible deconvolution filter. Our psychophysical studies show, however, that performance of the human observer is indeed improved by deconvolution. The ideal observer is, therefore, not a good predictor of human observer performance for detection of a signal imaged through a long-tailed PSF. We offer some explanations for this discrepancy by using some characteristics of the visual process and suggest a standard of comparison for the human observer that takes into account these characteristics. A look at the performance of the non-prewhitening (npw) ideal observer, before and after deconvolution, also brings some good insight into this study.

Bayes Theorem↗

PubMed2025

Enhancing and accelerating cell type deconvolution of large-scale spatial transcriptomics slices with dual network model.

MOTIVATION: Cell type deconvolution deciphers spatial distribution of mRNA transcripts at single cell level by integrating single-cell RNA sequencing (scRNA-seq) and spatial transcriptomics data to infer mixture of cell types of spots in slices. Current algorithms are criticized for neglecting connection between scRNA-seq and spatial transcriptomics data, as well as time-consuming, hampering their application to large-scale datasets. RESULTS: In this study, we propose a joint learning nonnegative matrix factorization algorithm for fast cell type deconvolution (aka jMF2D), which integrates scRNA-seq and spatial transcriptomics data with network models. To bridge scRNA-seq and spatial transcriptomics data, jMF2D jointly learns cell type similarity network to enhance quality of signatures of cell types, thereby promoting accuracy and efficiency of deconvolution. Experiments demonstrate that jMF2D outperforms state-of-the-art baselines in terms of accuracy by saving about 90% running time on various datasets generated by different platforms. Furthermore, it can also facilitates the identification of spatial domains and bio-marker genes, providing an efficient and effective model for analyzing spatial transcriptomics data. AVAILABILITY AND IMPLEMENTATION: The software is coded using python, and is free available for academic https://github.com/xkmaxidian/jMF2D.

Algorithms↗