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D M Auslander

Publications and source records attributed to D M Auslander.

8 recordsLinked to original sources
PubMed1996

Deconvolution: a novel signal processing approach for determining activation time from fractionated electrograms and detecting infarcted tissue.

BACKGROUND: Two important signal processing applications in electrophysiology are activation mapping and characterization of the tissue substrate from which electrograms are recorded. We hypothesize that a novel signal-processing method that uses deconvolution is more accurate than amplitude, derivative, and manual activation time estimates. We further hypothesize that deconvolution quantifies changes in morphology that detect electrograms recorded from regions of myocardial infarction. METHODS AND RESULTS: To determine the accuracy of activation time estimation, 600 unipolar electrograms were calculated with a detailed computer model using various degrees of coupling heterogeneity to model infarction. Local activation time was defined as the time of peak inward sodium current in the modeled myocyte closest to the electrode. Deconvolution, minimum derivative, and maximum amplitude were calculated. Two experienced electrophysiologists blinded to the computer-determined activation times marked their estimates of activation time. F tests compared the variance of activation time estimation for each method. To evaluate the performance of deconvolution to detect infarction, 380 unipolar electrograms were recorded from 10 dogs with infarcts resulting from ligation of the left anterior descending coronary artery. The amplitude, duration, number of inflections, peak frequency, bandwidth, minimum derivative, and deconvolution were calculated. Metrics were compared by Mann-Whitney rank-sum tests, and receiver operating curves were plotted. CONCLUSIONS: Deconvolution estimated local activation time more accurately than the other metrics (P < .0001). Furthermore, the algorithm quantified changes in morphology (P < .0001) with superior performance, detecting electrograms recorded from regions of myocardial infarction. Thus, deconvolution, which incorporates a priori knowledge of electrogram morphology, shows promise to improve present clinical metrics.

Algorithms↗
PubMed1995

Fractionated electrograms from a computer model of heterogeneously uncoupled anisotropic ventricular myocardium.

BACKGROUND: The relation between heterogeneously coupled myocardium and fractionated electrograms is incompletely understood. The purpose of this study was to use a detailed computer model of nonuniformly anisotropic myocardium to test the hypothesis that spatial variation of morphology of electrograms recorded simultaneously from multiple sites increases with increasing heterogeneity of intercellular coupling. METHODS AND RESULTS: A sheet of elements with Beeler-Reuter ionic kinetics was coupled with cytoplasmic resistivity to model cells. Gap junctional resistance values were assigned by recursive randomization to produce a fractal pattern of heterogeneous coupling, simulating damage resulting from infarction. The correlation dimension of the pattern, D, measured heterogeneity of intercellular coupling. The peak-to-peak amplitude, duration, minimum derivative (steepest downslope), number of inflections, frequency of peak power, and bandwidth of unfiltered unipolar electrograms were calculated. Linear regressions indicate (P < .001) that the coefficient of variation of five electrogram metrics increases with increasing substrate heterogeneity and that the distance over which electrogram morphology decorrelates decreases with increasing heterogeneity of intercellular coupling. CONCLUSIONS: These findings confirm our hypothesis that the spatial variation of morphology of electrograms recorded simultaneously from multiple sites increases with increasing heterogeneity of intercellular coupling.

Anisotropy↗
PubMed1994

Effects of coupling heterogeneity on fractionated electrograms in a model of nonuniformly anisotropic ventricular myocardium.

To further understand the relation between heterogeneously infarcted myocardium and fractionated electrograms, a computer model was used to test the hypothesis that the way electrogram metrics change with electrode location relates to statistical properties of the underlying myocardium. A sheet of Beeler-Reuter elements was coupled with cytoplasmic resistance to form cells. Junctional resistance values were assigned using a recursive randomization to produce a fractal pattern, simulating damage from disrupted blood supply. The pattern's correlation dimension, D, was a statistical measure of heterogeneity. Unipolar electrogram's amplitude, duration, number of inflections, peak frequency, bandwidth, and the rate of change of metrics with height were calculated. Analysis of variance indicated (P < .0001) that peak-to-peak amplitude and bandwidth decreased at a slower rate when height was increased above heterogeneous tissue as compared with homogeneous tissue. These findings could be useful during clinical mapping procedures as statistical estimates of tissue structure.

Anisotropy↗
PubMed1994

Adaptive classification of myocardial electrogram waveforms.

The shape of myocardial electrogram complexes can change gradually in response to electrical and physiological transients. These changes could affect the reliability of morphologic-based electrogram classifiers proposed for use in implantable cardioverters. In this report, we present a method of detecting gradual changes in the shape of electrogram complexes and evaluate the method by incorporating it into a simple adaptive classification scheme. Of the six subjects recruited to take part in a previous comparative study of myocardial electrogram features, we observed extensive morphologic drift of normal sinus beats in two subjects. Our results indicate that the adaptive classification scheme proposed here can reduce observed classification error rates compared to rates obtained without adaptation.

Algorithms↗
PubMed1994

Benzene toxicokinetics in humans: exposure of bone marrow to metabolites.

A three compartment physiologically based toxicokinetic model was fitted to human data on benzene disposition. Two separate groups of model parameter derivations were obtained, depending on which data sets were being fitted. The model was then used to simulate five environmental or occupational exposures. Predicted values of the total bone marrow exposure to benzene and cumulative quantity of metabolites produced by the bone marrow were generated for each scenario. The relation between cumulative quantity of metabolites produced by the bone marrow and continuous benzene exposure was also investigated in detail for simulated inhalation exposure concentrations ranging from 0.0039 ppm to 150 ppm. At the level of environmental exposures, no dose rate effect was found for either model. The occupational exposures led to only slight dose rate effects. A 32 ppm exposure for 15 minutes predicted consistently higher values than a 1 ppm exposure for eight hours for the total exposure of bone marrow to benzene and the cumulative quantity of metabolites produced by the bone marrow. The general relation between the cumulative quantity of metabolites produced by the bone marrow and the inhalation concentration of benzene is not linear. An inflection point exists in some cases leading to a slightly S shaped curve. At environmental levels (0.0039-10 ppm) the curve bends upward, and it saturates at high experimental exposures (greater than 100 ppm).

Air↗
PubMed1993

Selection of myocardial electrogram features for use by implantable devices.

Implantable devices that terminate ventricular tachycardia must be capable of correctly classifying heart rhythms to a high degree of reliability. We evaluated the relative discriminating power of several myocardial electrogram (ME) features in six human subjects by reducing the order of their corresponding feature spaces using three different optimization methods: 1) minimizing univariate Bayes error rates (univariate parametric), 2) maximizing the Kullback divergence (multivariate parametric), and 3) pruning classification trees (nonparametric). We found that although the composition of the optimal subspaces varied considerably from one subject to another, one frequency domain feature was common to most of the optimal subspaces.

Bayes Theorem↗
PubMed1988

Identification of ventricular tachycardia with use of the morphology of the endocardial electrogram.

Currently available antitachycardia devices rely primarily on timing information to define abnormal rhythms. It would be useful to have more specific means of automatically identifying pathologic tachycardias. Using unfiltered (0.04 to 500 Hz bandpass) recordings made during electrophysiologic testing in 10 patients with ventricular tachycardia (VT), we studied the differences in electrogram morphology during sinus rhythm and VT. Signals were digitized at 1 kHz. A template of a normal sinus rhythm electrogram was created for each patient by averaging five sinus complexes from the beginning of each study. Ten sinus electrograms just before the onset of VT and 10 electrograms during stable monomorphic VT were compared with this template. The difference in morphology between a given electrogram and its template was quantitated by superimposing the two signals and measuring the area between the curves. There was no overlap in the ranges of these "area of the difference" measurements between sinus and VT electrograms from any of the 10 patients studied, including four with intraventricular conduction disturbances. In contrast, discrete features of the signal, including peak amplitude and maximum dV/dt, did not reliably differentiate sinus from VT electrograms. Bandpass filtering, sample window size, and digitizing rate were manipulated to determine the minimal signal content necessary for the area of difference method to reliably identify VT. These interventions suggest that the low-frequency far-field portion of the signal is primarily responsible for the morphologic differences between sinus and VT electrograms. In conclusion, the morphology of VT electrograms in man is consistently and distinctly different from the morphology of sinus electrograms.(ABSTRACT TRUNCATED AT 250 WORDS)

Electrocardiography↗