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PubMed2006

Application of automated mass spectrometry deconvolution and identification software for pesticide analysis in surface waters.

A new approach to surface water analysis has been investigated in order to enhance the detection of different organic contaminants in Nathan Creek, British Columbia. Water samples from Nathan Creek were prepared by liquid/liquid extraction using dichloromethane (DCM) as an extraction solvent and analyzed by gas chromatography mass spectrometry method in scan mode (GC-MS scan). To increase sensitivity for pesticides detection, acquired scan data were further analyzed by Automated Mass Spectrometry Deconvolution and Identification Software (AMDIS) incorporated into the Agilent Deconvolution Reporting Software (DRS), which also includes mass spectral libraries for 567 pesticides. Extracts were reanalyzed by gas chromatography mass spectrometry single ion monitoring (GC-MS-SIM) to confirm and quantitate detected pesticides. Pesticides: atrazine, dimethoate, diazinone, metalaxyl, myclobutanil, napropamide, oxadiazon, propazine and simazine were detected at three sampling sites on the mainstream of the Nathan Creek. Results of the study are further discussed in terms of detectivity and identification level for each pesticide found. The proposed approach of monitoring pesticides in surface waters enables their detection and identification at trace levels.

Automation↗

PubMed1987

Theoretical aspects of multiple deconvolution analysis for quantification of left to right cardiac shunts.

A new method for quantification of left to right cardiac shunts by Bourguignon et al based on multiple deconvolution analysis is critically analysed within the framework of a simple mathematical model. Underlying assumptions are explicitly stated and their validity discussed. It turns out that some reinterpretation of the method is necessary. Using the same ideas as in multiple deconvolution analysis, a new relation for the pulmonary to systemic flow ratio is proposed on a theoretical basis. This technique may be useful when diagnosing left to right cardiac shunts with radiocardiographic methods.

Coronary Circulation↗

PubMed1987

Error analysis by simulation studies in renography deconvolution.

The renogram, defined as the time-activity curve obtained from measurements with a gamma detector over the kidneys after a prior injection of a radioactive tracer, can be quantified using the deconvolution method. Essentially all the inherent information in the renogram, the estimated relative renal uptake function and transit time spectrum through the kidney, can be derived from the computed renal retention function. This study shows how statistical and physiological noise and different backgrounds affect the accuracy of the derived parameters. Confidence intervals for the estimated relative renal function and mean transit time (MTT) are presented. The principal source of error in relative renal function was due to extrarenal background. It was found that the error in mean transit time due to statistical noise was proportional to MTT, that the presence of extrarenal background strongly affected the accuracy of the MTT, whereas the vascular background in the renogram was of minor importance. Physiological noise, interpreted as periodic changes in transit times does, strictly speaking, invalidate the deconvolution principle, but it was possible to calculate a valid mean value of the different actual transit times. The transit time spectrum, measured by differentiation of the computed retention function, was found to be of no practical value with use of the unconstrained matrix method. The signal to noise ratio and consequently the need for smoothing can be estimated from the sum of the squared second derivatives of the renogram itself. The plateau levels in the renal retention function provide a more reliable estimate for the relative function ratio than the relative amplitude of a renogram in which extrarenal background only has been subtracted.

Algorithms↗

PubMed1992

Constrained least-squares restoration and renogram deconvolution: a comparison by simulation.

Before deconvolution can be used in renography, it is necessary to decide whether the renal function is sufficiently good to allow it. To see if this decision can be circumvented, an iterative constrained least-squares restoration (CLSR) method was implemented in which the point of termination of the iteration occurs when a residual vector has a value less than an estimate of the noise in the original renogram curve. The technique was compared with the matrix algorithm and with direct FFT division. The comparison was achieved by deconvolving simulated renogram data with differing transit time spectra and statistics. As expected, the FFT technique produced results of little value whereas the CLSR and matrix methods produced values of mean transit time (MTT) that differed slightly from the expected results. Analysis indicated that the matrix approach was superior when the percentage noise component was less than 6% and vice versa. No technique produced useful transit time spectra. As the CLSR technique produced better results than the matrix method in simulations with relatively long MTTs and high noise, it seems reasonable to suggest that it might be used for renogram deconvolution without the need for previous inspection of the curves.

Humans↗

PubMed1993

Constrained least-squares restoration and renogram deconvolution: a comparison with other techniques.

It has previously been shown that an iterative constrained least-squares (CLSR) technique using a noise-based constraint may be superior to other methods of renogram deconvolution analysis. To test this hypothesis on real data, renography was performed on 70 patients with established diagnoses of normal, insufficient or acutely obstructed kidneys. Standard renography parameters were obtained from the time activity curves which were then deconvolved using three techniques. One kidney per patient was chosen at random for analysis resulting in a total of 43 normal and 27 diseased kidneys. The ability of each of the analytical techniques to discriminate between normal and diseased kidneys was assessed using logistic regression. CLSR proved to be robust and provide the best discrimination of the deconvolution techniques. However, the best overall discrimination was provided by a model based on the renography parameters excretion ratio, rate of uptake and time to peak activity which correctly classified 86% of the kidneys. It is possible that the renogram parameters could be used to produce notional probabilities of renal dysfunction which the physician could use as an aid in the interpretation of gamma-camera renography.

Acute Kidney Injury↗

PubMed1994

3D reconstruction for a multi-ring PET scanner by single-slice rebinning and axial deconvolution.

A three-dimensional (3D) image reconstruction method, which was originally developed for a positron emission tomography (PET) system consisting of two rotating scintillation cameras, has now been implemented for a multi-ring PET scanner with retractable septa. The method is called 'single-slice rebinning with axial deconvolution' (SSAD), and can be described as follows. The projection data are sorted into transaxial 2D sinograms. Correction for the axial blurring is made by deconvolution in the sinograms. To obtain the axial spread functions, which depend on the activity distribution, 2D reconstruction is first made using a limited axial acceptance angle. The final 3D image is obtained by 2D reconstruction of transaxial planes. The method is simple but not approximate, has a modest memory requirement, and can be combined with different 2D techniques. Evaluations by Monte Carlo simulations and phantom studies have been made.

Algorithms↗

PubMed2006

Relative extents of preformation and neoformation in tree shoots: Analysis by a deconvolution method.

BACKGROUND AND AIMS: Neoformation is the process by which organs not preformed in a bud are developed on a growing shoot, generally after preformation extension. The study of neoformation in trees has been hindered due to methodological reasons. The present report is aimed at assessing the relative importance of preformation and neoformation in the development of shoots of woody species. METHODS: A deconvolution method was applied to estimate the distribution of the number of neoformed organs for eight data sets corresponding to four Nothofagus species and a Juglans hybrid. KEY RESULTS: The number of preformed organs was higher and less variable than the number of neoformed organs. Neoformation contributed more than preformation to explain full-size differences between shoots developed in different positions within the architecture of each tree species. CONCLUSIONS: Differences between the distributions of the numbers of preformed and neoformed organs may be explained by alluding to the duration of differentiation and extension for each of these groups of organs. The deconvolution of distributions is a useful tool for the analysis of neoformation and shoot structure in trees.

Logistic Models↗

PubMed2000

Deconvolution of composite chromatographic peaks by simultaneous dual detections.

Composite chromatographic peaks are deconvoluted by a method that uses ratio formation from signals of simultaneous double detection. The method is generally suitable if two detector signals can simultaneously be acquired and their uses do not need any a priori assumption or mathematical shape analysis. A simple deduction makes the compound- and detector-specific intensive parameters explicit, which allows for the digital construction of directly invisible component peaks. The simultaneous double detection is shown to be superior to coupled detectors, sequentially fixed chromatograms, and subsequently synchronized peaks. The combination of circular dichroism and ultraviolet (UV) detection is shown to be especially advantageous in the analysis of enantiomers for which the other ratio-forming peak-deconvolution techniques have inherently been insensitive. The double chiroptical UV detection can be of further use to decompose overlapping peaks of nonenantiomeric compounds that are highly similar. The capacity of the method is exemplified by the analysis of morphine alkaloids, steroid oximes, and synthetic heterocycles.

Chromatography, Liquid↗

PubMedDate not supplied

Deconvolution of chemical shift spectra in two- or three-dimensional [19F] MR imaging.

The chemical shift spectra of 19F in perfluorinated compounds (PFCs) present a nontrivial impulse response function for magnetic resonance (MR) imaging. The 19F images of organs containing PFCs can be degraded by blurring and ghost image artifacts. Two methods (noise masked deconvolution and maximum entropy deconvolution) are presented that allow the chemical shift spectra of 19F in PFCs to be used to extract high quality MR images free of chemical shift artifact. Both techniques rely on postprocessing of either the raw data or the original image to produce images that are not degraded by the chemical shift spectra of the compound being imaged and that exhibit a signal-to-noise ratio equal to or better than that observed in the original image. The techniques are general in that they can be used with many PFC spectra. Using MR imaging data obtained from phantoms filled with cis/transperfluorodecalin and perfluorotributylamine (FC-43), the methods are compared in terms of their (a) ability to eliminate the chemical shift artifact associated with the PFC spectrum; (b) signal-to-noise performance; and (c) ability to preserve information related to the density and the longitudinal relaxation rate of the resonant nuclei. The utility of these techniques is demonstrated by a series of three-dimensional Fourier transform in vivo images of FC-43 emulsion in a mouse liver.

Algorithms↗

PubMed1985

The individual kidney function. A comparison between frame summation and deconvolution.

A variety of methods have been developed to estimate the individual kidney function. Many methods use a scintillation camera the data from which are processed in a computer system. To compare two of these methods, the principles of which are completely different, such as the 'Oberhausen' method of frame summation and background subtraction and a method that uses deconvolution, the scintillation camera data of 121 patients have been collected. A computer program was written to calculate the individual kidney function by which both methods were used. It is often asserted that specific techniques of frame summation and background subtraction are not suitable to define the individual kidney function. To see if this assertion is true, two different methods have been compared using the contribution of the left kidney to the individual kidney function. An excellent correlation between the two methods was found (R = 0.9808, n = 121) which proves the ability of both the 'Oberhausen' method and the method that uses deconvolution. However, it is also seen that the 'Oberhausen' method may give false results, caused by an increasing background count outside the kidneys in patients with a large difference in function between the two kidneys.

Humans↗

PubMed2001

Is deconvolution applicable to renography?

The feasibility of deconvolution depends on many factors, but the technique cannot provide accurate results if the maximal transit time (MaxTT) is longer than the duration of the acquisition. This study evaluated whether, on the basis of a 20 min renogram, it is possible to predict in which cases the MaxTT will exceed 20 min. Renograms of various shapes were simulated by convolution of a plasma disappearance curve and various created retention functions with a mean transit time (MTT) ranging from 3 to 23 min. The values of MaxTT were then derived from the created curves and compared to three parameters of transit measured on the renograms: the time to reach the maximum of the curve (Tmax), the output efficiency at 20 min (OE20), and the normalized residual activity at 20 min (NORA20). The proportion of retention functions (n=390) with MaxTT>20 min increased with increasing Tmax (e.g. 9% for 6< or =Tmax<10 min, and 34% for 11< or =Tmax<15 min), increasing NORA20 (e.g. 20% for 1.4< or =NORA20<3.0, and 84% for 3.0< or =NORA20<5.0) and decreasing OE20 (19% for 50% <OE20< or =75%, and 76% for 25% <OE20< or =50%). Use of Tmax, OE20 and NORA20 doesn't allow the differentiation of cases with a MaxTT longer or shorter than 20 min. Deconvolution can paradoxically only be used in cases of normal transit.

Humans↗

PubMed2003

Calculation of renal retention function without deconvolution.

The aim of this study was to evaluate Rutland's method for the recovery of renal retention function without deconvolution. Renograms (n=5800) were generated by convolving 10 real input functions with 580 artificially created retention functions. Their ratios of minimal to mean transit time ranged from 0.1 to 1.0, and for mean transit time ranged from 3 to 60 min. The retention function was recovered from each renogram and its associated input function by calculating the first derivative of the residence time of the tracer in the kidney. Minimal, mean, and maximal transit time of the recovered retention function were calculated and compared with the original values. Qualitatively, the recovered retention function differed little from the original one. Quantitatively, values for recovered minimal transit time equalled original minimal transit time in all cases, whilst recovered mean transit time and maximal transit time equalled, respectively, the original mean transit time and maximal transit time if the original minimal to mean transit time ratio equalled 1. If this ratio was less than 1, recovered mean transit time was higher than original mean transit time and recovered maximal transit time was lower than original maximal transit time. For values of mean and maximal transit time, the differences from the original value increased with increasing original mean and maximal transit time, respectively, and with increasing renal clearance and decreasing minimal to mean transit time ratio. It is confirmed that Rutland's method is a particularly interesting alternative to deconvolution analysis. The errors that occur when recovering the retention function are relatively small.

Algorithms↗

PubMed2003

Comparison of quantification of histochemical staining by hue-saturation-intensity (HSI) transformation and color-deconvolution.

We tested a recently developed flexible method of separation and quantification of immunohistochemical staining by means of color image analysis. An algorithm was recently developed to deconvolve the color information acquired with RGB cameras, to calculate the contribution of each of the applied stains, based on the stain-specific RGB absorption. The algorithm was tested using a set of lung-tumor samples labeled for the detection of Ki-67, an antigen expressed in proliferating cells, covering a wide range of staining levels. Quantification of the labeling was compared with HSI-based segmentation and manual analysis of the same samples. The recently developed deconvolution method performed significantly better than the HSI based system when compared to manual counting as gold standard. The deconvolution system showed significantly reduced variability in the LI determination, especially of highly labeled control samples. This resulted in significant increase in sensitivity of classification of samples with increased KI-67 labeling without changing the specificity, when compared to the HSI based method.

Algorithms↗

PubMedDate not supplied

Measurement of tumor blood flow using dynamic contrast-enhanced magnetic resonance imaging and deconvolution analysis: a preliminary study in musculoskeletal tumors.

OBJECTIVE: To measure tumor blood flow (TBF) using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI). METHODS: A DCE-MRI was performed using inversion recovery-preparation fast-field echo sequences. Dynamic data were obtained every 3.2 seconds for 2 minutes, immediately after gadolinium injection. In 14 patients with malignant musculoskeletal tumors, TBF maps were generated pixel-by-pixel by deconvolution analysis. For preclinical studies, muscle blood flow in 5 volunteers and signal intensities of different gadolinium concentrations were measured. RESULTS: There was a good linear relationship between signal intensities and gadolinium concentrations (r = 0.989, P < 0.001, at gadolinium concentrations <or=2 mmol/L). The average value of muscle blood flow in volunteers was 11.1 +/- 2.7 mL.100 mL.min. In 14 patients with musculoskeletal tumors, TBF showed wide variances: the lowest of 9.6 mL.100 mL.min in liposarcoma and the highest of 182.0 mL.100 mL.min in osteosarcoma. After chemotherapy, the TBF values (7.9, 11.0, and 11.7 mL. 100 mL.min) in the good responders were lower than those (26.8, 31.0, and 62.4 mL.100 mL.min) in the poor responders. CONCLUSIONS: A functional map of TBF generated by DCE-MRI and deconvolution analysis would be a promising tool for evaluating tumor blood flow in vivo.

Adolescent↗

PubMed2006

Importance of parametric mapping and deconvolution in analyzing magnetic resonance myocardial perfusion images.

AIM: : We sought to improve the clinical interpretation of first-pass myocardial magnetic resonance perfusion. Parametric analyses of the myocardial distribution of the contrast agent have been proposed. The objective of the present study was to compare the effectiveness of visual analysis and of a parametric approach in an animal model under acquisition conditions as close as possible to clinical reality. METHOD: : Experiments were conducted in vivo with various kinds of pharmacological stimulation in normal pigs and in pigs with stenosis of the left circumflex coronary artery. First-pass MR images and parametric maps were first assessed by medical experts. MR parameters, the myocardial signal intensity variation DeltaSI, ascending up-slope, and rMBF (blood flow calculated by fast discrete ARMA deconvolution) were then compared with blood flow measurements using radioactive microspheres. RESULTS AND CONCLUSIONS: : Interobserver agreement was 57% and 81% and accuracy 53% and 81%, for visual and for parametric map analysis, respectively. For deconvolution parameters, a linear relationship y = 371 + 1.27x, r = 0.78 was obtained between rMBF calculated by ARMA and the radioactive microsphere blood flow. Moreover, the fast and robust parametric mapping of rMBF by the discrete ARMA method allows MR evaluation of myocardial perfusion independently of hemodynamic conditions.

Animals↗

PubMed2006

Equivalence of the virtual-source method and wave-field deconvolution in seismic interferometry.

Seismic interferometry and the virtual-source method are related approaches for extracting the Green's function that accounts for wave propagation between receivers by making suitable combinations of the waves recorded at these two receivers. These waves can either be excited by active, controlled, sources, or by natural incoherent sources. We compare this technique with the deconvolution of the wave field recorded at different receivers. We show that the deconvolved wave field is a solution of the same wave equation as that for the physical system, but that the deconvolved wave forms may satisfy different boundary conditions than those of the original system. We apply this deconvolution approach to the wave motion recorded at various levels in a building after an earthquake, and show how to extract the building response for different boundary conditions. Extracting the response of the system with different boundary conditions can be used to enhance, or suppress, the normal-mode response. In seismic exploration this principle can be used for the suppression of surface-related multiples.

Journal Article↗

PubMed2001

Software based digital signal processing and spectrum deconvolution in X-ray spectroscopy.

Approaches for software based digital signal processing and numerical deconvolution of measured signals which overcome limitations of state-of-the-art systems are described. The basic technical equipment for digital signal processing consists of an energy resolving detector with a preamplifier followed by a fast sampling analogue-to-digital converter (ADC). The main idea is the numerical decomposition of the measured signal into contributions caused by single photon absorption using standard pulses. The latter can be obtained by measurements under definite conditions. The maximum pulse rate is then limited only by the ratio of sampling time to the time between two pulses which should be attributed to single events. Thus pulse overlaps do not require pulse rejection. At sampling rates of 10(8) samples per second theoretically a comparable photon rate can be detected at throughputs of 100%. Beyond that it is outlined that in a comparable manner a numerical deconvolution of measured energy spectra (statistic distribution functions of single events) into combinations of standard spectra, which can likewise be determined by measurement, offers outstanding possibilities, too. On the one hand the energy resolution attainable for individual events for a given detector can be improved drastically by the statistical treatment of spectra. On the other hand an energy resolving work principle becomes possible for certain detectors, which do not permit this conventionally due to their poor signal to noise ratio.

Journal Article↗

PubMed1996

A stochastic deconvolution method to reconstruct insulin secretion rate after a glucose stimulus.

Insulin secretion rate (ISR) is not directly measurable in man but it can be reconstructed from C-peptide (CP) concentration measurements by solving an input estimation problem by deconvolution. The major difficulties posed by the estimation of ISR after a glucose stimulus, e.g., during an intravenous glucose tolerance test (IVGTT), are the ill-conditioning of the problem, the nonstationary pattern of the secretion rate, and the nonuniform/infrequent sampling schedule. In this work, a nonparametric method based on the classic Phillips-Tikhonov regularization approach is presented. The problem of nonuniform/infrequent sampling is addressed by a novel formulation of the regularization method which allows the estimation of quasi time-continuous input profiles. The input estimation problem is stated into a Bayesian context, where the a priori known nonstationary characteristics of ISR after the glucose stimulus are described by a stochastic model. Deconvolution is tackled by linear minimum variance estimation, thus allowing the derivation of new statistically based regularization criteria. Finally, a Monte-Carlo strategy is implemented to assess the uncertainty of the estimated ISR arising from CP measurement error and impulse response parameters uncertainty.

C-Peptide↗