Biomedical subjects

Dana H Brooks

Publications and source records attributed to Dana H Brooks.

14 recordsLinked to original sources

PubMed2006

Wavefront-based models for inverse electrocardiography.

We introduce two wavefront-based methods for the inverse problem of electrocardiography, which we term wavefront-based curve reconstruction (WBCR) and wavefront-based potential reconstruction (WBPR). In the WBCR approach, the epicardial activation wavefront is modeled as a curve evolving on the heart surface, with the evolution governed by factors derived phenomenologically from prior measured data. The body surface potential/wavefront relationship is modeled via an intermediate mapping of wavefront to epicardial potentials, again derived phenomenologically. In the WBPR approach, we iteratively construct an estimate of epicardial potentials from an estimated wavefront curve according to a simplified model and use it as an initial solution in a Tikhonov regularization scheme. Initial simulation results using measured canine epicardial data show considerable improvement in reconstructing activation wavefronts and epicardial potentials with respect to standard Tikhonov solutions. In particular the WBCR method accurately finds the anisotropic propagation early after epicardial pacing, and the WBPR method finds the wavefront (regions of sharp gradient of the potential) both accurately and with minimal smoothing.

Action Potentials↗

PubMed2006

Improved performance of bayesian solutions for inverse electrocardiography using multiple information sources.

The usual goal in inverse electrocardiography (ECG) is to reconstruct cardiac electrical sources from body surface potentials and a mathematical model that relates the sources to the measurements. Due to attenuation and smoothing that occurs in the thorax, the inverse ECG problem is ill-posed and imposition of a priori constraints is needed to combat this ill-posedness. When the problem is posed in terms of reconstructing heart surface potentials, solutions have not yet achieved clinical utility; limitations include the limited availability of good a priori information about the solution and the lack of a "good" error metric. We describe an approach that combines body surface measurements and standard forward models with two additional information sources: statistical prior information about epicardial potential distributions and sparse simultaneous measurements of epicardial potentials made with multielectrode coronary venous catheters. We employ a Bayesian methodology which offers a general way to incorporate these information sources and additionally provides statistical performance analysis tools. In a simulation study, we first compare solutions using one or more of these information sources. Then, we study the effects of varying the number of sparse epicardial potential measurements on reconstruction accuracy. To evaluate accuracy, we used the Bayesian error covariance as well as traditional error metrics such as relative error. Our results show that including even sparsely sampled information from coronary venous catheters can substantially improve the reconstruction of epicardial potential distributions and that a Bayesian framework provides a feasible approach to using this information. Moreover, computing the Bayesian error standard deviations offers a means to indicate confidence in the results even in the absence of validation data.

Action Potentials↗

PubMed2006

Electrode boundary conditions and experimental validation for BEM-based EIT forward and inverse solutions.

In this paper, we present theoretical developments and experimental results for the problem of estimating the conductivity map inside a volume using electrical impedance tomography (EIT) when the boundary locations of any internal inhomogeneities are known. We describe boundary element method (BEM) implementations of advanced electrode models for the forward problem of EIT. We then use them in the inverse problem with known internal boundaries and derive the associated Jacobians. We report on the results of two EIT phantom studies, one using a homogeneous cubical tank, and one using a cylindrical tank with agar conductivity inhomogeneities. We test both the accuracy of our BEM forward model, including the electrode models, as well as our inverse solution, against the measured data. Results show good agreement between measured values and both forward-computed tank voltages and inverse-computed conductivities; for instance, in a phantom experiment, we reconstructed the conductivities of three agar objects inside a cylindrical tank with an error less than 2% of their true value.

Algorithms↗

PubMed2005

A haemodynamic response function model in spatio-temporal diffuse optical tomography.

Diffuse optical tomography (DOT) is a new and effective technique for functional brain imaging. It can detect local changes in both oxygenated and deoxygenated haemoglobin concentrations in tissue based on differential absorption at multiple wavelengths. Traditional methods in spatio-temporal analysis of haemoglobin concentrations in diffuse optical tomography first reconstruct the spatial distribution at different time instants independently, then look at the temporal dynamics on each pixel, without incorporating any temporal information as a prior in the image reconstruction. In this work, we present a temporal haemodynamic response function model described by a basis function expansion, in a joint spatio-temporal DOT reconstruction of haemoglobin concentration changes during simulated brain activation. In this joint framework, we simultaneously employ spatial regularization, spectral information and temporal assumptions. We also present an efficient algorithm for solving the associated large-scale systems. The expected improvements in spatial resolution and contrast-to-noise ratio are illustrated with simulations of human brain activation.

Algorithms↗

PubMed2005

Quantitative spectroscopic diffuse optical tomography of the breast guided by imperfect a priori structural information.

Spectroscopic diffuse optical tomography (DOT) can directly image the concentrations of physiologically significant chromophores in the body. This information may be of importance in characterizing breast tumours and distinguishing them from benign structures. This paper studies the accuracy with which lesions can be characterized given a physiologically realistic situation in which the background architecture of the breast is heterogeneous yet highly structured. Specifically, in simulation studies, we assume that the breast is segmented into distinct glandular and adipose regions. Imaging with a high-resolution imaging modality, such as magnetic resonance imaging, in conjunction with a segmentation by a clinical expert, allows the glandular/adipose boundary to be determined. We then apply a two-step approach in which the background chromophore concentrations of each region are estimated in a nonlinear fashion, and a more localized lesion is subsequently estimated using a linear perturbational approach. In addition, we examine the consequences which errors in the breast segmentation have on estimating both the background and inhomogeneity chromophore concentrations.

Algorithms↗

PubMed2005

Identification of cardiac rhythm features by mathematical analysis of vector fields.

Automated techniques for locating cardiac arrhythmia features are limited, and cardiologists generally rely on isochronal maps to infer patterns in the cardiac activation sequence during an ablation procedure. Velocity vector mapping has been proposed as an alternative method to study cardiac activation in both clinical and research environments. In addition to the visual cues that vector maps can provide, vector fields can be analyzed using mathematical operators such as the divergence and curl. In the current study, conduction features were extracted from velocity vector fields computed from cardiac mapping data. The divergence was used to locate ectopic foci and wavefront collisions, and the curl to identify central obstacles in reentrant circuits. Both operators were applied to simulated rhythms created from a two-dimensional cellular automaton model, to measured data from an in situ experimental canine model, and to complex three-dimensional human cardiac mapping data sets. Analysis of simulated vector fields indicated that the divergence is useful in identifying ectopic foci, with a relatively small number of vectors and with errors of up to 30 degrees in the angle measurements. The curl was useful for identifying central obstacles in reentrant circuits, and the number of velocity vectors needed increased as the rhythm became more complex. The divergence was able to accurately identify canine in situ pacing sites, areas of breakthrough activation, and wavefront collisions. In data from human arrhythmias, the divergence reliably estimated origins of electrical activity and wavefront collisions, but the curl was less reliable at locating central obstacles in reentrant circuits, possibly due to the retrospective nature of data collection. The results indicate that the curl and divergence operators applied to velocity vector maps have the potential to add valuable information in cardiac mapping and can be used to supplement human pattern recognition.

Algorithms↗

PubMed2005

Bayesian solutions and performance analysis in bioelectric inverse problems.

In bioelectric inverse problems, one seeks to recover bioelectric sources from remote measurements using a mathematical model that relates the sources to the measurements. Due to attenuation and spatial smoothing in the medium between the sources and the measurements, bioelectric inverse problems are generally ill-posed. Bayesian methodology has received increasing attention recently to combat this ill-posedness, since it offers a general formulation of regularization constraints and additionally provides statistical performance analysis tools. These tools include the estimation error covariance and the marginal probability density of the measurements (known as the "evidence") that allow one to predictively quantify and compare experimental designs. These performance analysis tools have been previously applied in inverse electroencephalography and magnetoencephalography, but only in relatively simple scenarios. The main motivation here was to extend the utility of Bayesian estimation techniques and performance analysis tools in bioelectric inverse problems, with a particular focus on electrocardiography. In a simulation study we first investigated whether Bayesian error covariance, computed without knowledge of the true sources and based on instead statistical assumptions, accurately predicted the actual reconstruction error. Our study showed that error variance was a reasonably reliable qualitative and quantitative predictor of estimation performance even when there was error in the prior model. We also examined whether the evidence statistic accurately predicted relative estimation performance when distinct priors were used. In a simple scenario our results support the hypothesis that the prior model that maximizes the evidence is a good choice for inverse reconstructions.

Algorithms↗

PubMed2005

Venous catheter based mapping of ectopic epicardial activation: training data set selection for statistical estimation.

A source of error in most of the existing catheter cardiac mapping approaches is that they are not capable of acquiring epicardial potentials even though arrhythmic substrates involving epicardial and subepicardial layers account for about 15% of the ventricular tachycardias. In this subgroup of patients, mapping techniques that are limited to the endocardium result in localization errors and failure in subsequent ablation procedures. In addition, catheter-based electrophysiological studies of the epicardium are limited to regions near the coronary vessels or require transthoracic access. We have developed a statistical approach by which to estimate high-resolution maps of epicardial activation from very low-resolution multi-electrode venous catheter measurements. A training set of previously recorded maps is necessary for this technique so that composition of the database becomes an important determinant of accuracy. The specific hypothesis of the study was that estimation accuracy would be best when the training data set matches that of the test beat(s), whereby the matching was according to the site of initiation of the beats. This hypothesis suggests approaches to optimized selection of the training set, three of which we have developed and evaluated. One of these methods, the high-CC refinement method, was able to estimate the earliest activation site of left ventricularly paced maps within an average of 4.67 mm of the true site; in 89% of the cases (a total of 231 cases) the error was smaller than 10 mm. In another method, MHC-Spatial activation, right ventricularly paced maps (239 maps) were estimated with an error of 7.15 mm. The average correlation coefficient between the original and the estimated maps was also very high (0.97), which shows the ability of the training data set refinement methods to estimate the epicardial activation sequence. The results of these tests support the hypothesis and, moreover, suggest that such an approach is feasible for providing accurate reconstruction of complete epicardial activation-time maps in a clinical setting.

Algorithms↗

PubMed2004

Comparative psychometric analysis of vector and isochrone cardiac activation maps.

Isochronal cardiac activation maps can be constructed from local activation times associated with spatial locations, and are frequently used to study cardiac arrhythmias. Cardiac velocity vector mapping has been proposed as an alternative method to study cardiac activation in both clinical and research environments. Velocity vectors inherently contain more information than scalar measures of latency, but it is unknown how vector maps and isochronal maps compare when they are used to identify patterns and features associated with arrhythmias. In order to quantitatively compare these two visualization methods, eight cardiologists were asked to complete forced-choice tasks in which they selected ablation sites based on synthetic vector or isochronal maps. Maps varied in arrhythmia complexity, number of vectors or activation times included, and errors in magnitude or angle for maps of velocity vectors. Quantitative comparison was achieved by using psychometric functions to characterize the learning curve and the total number of measurements needed in order to choose a correct ablation site. For simple arrhythmias, performance with vector maps was superior to isochronal maps. Subjects required fewer measurements, and learned more rapidly by studying vector maps. For more complex arrhythmias, there was no significant difference in performance between vector and isochronal maps. However, arrhythmia features were clearer with vector maps, even though this clarity did not necessarily change the ablation site choice. When errors were added to vector maps, performance was satisfactory for angle errors < 55 degrees, and speed errors did not affect performance.

Arrhythmias, Cardiac↗

PubMed2003

Estimation of entrainment response using electrograms from remote sites: validation in animal and computer models of reentrant tachycardia.

INTRODUCTION: Studies suggest that entrainment response (ER) of reentrant tachycardia to overdrive pacing can be estimated using signals from sites other than the paced site. METHODS AND RESULTS: A formula for estimation of ER using remote sites against the difference between the postpacing interval (PPI) and tachycardia cycle length (TCL) determined solely from the paced site signal was validated in experimental data and using a simple two-dimensional cellular automata model of reentry. The model also was used to study the behavior and features of entrained surfaces, including the resetting of tachycardia phase by single premature paced stimuli. Experimental results from 1,484 remote sites in 115 pacing sequences showed the average of the median ER estimate error at each pacing site was -2 +/- 5 msec, and the median ER estimate was within 10 msec of PPI-TCL for 94% of pacing sites. From simulation results, ER at the paced site was accurately estimated from >99.8% of 20,764 remote sites during pacing at 24 sites and three paced cycle lengths. Intervals measured from remote electrograms revealed whether the site was activated orthodromically or nonorthodromically during pacing, and results of simulations illustrated that the portion of the surface activated nonorthodromically during pacing increased with distance from the pacing site to the circuit. The phenomenon of nonorthodromic activation of reentrant circuits predicted by modeling was discernible in measurements taken from the animal model of reentrant tachycardia. Results also showed that, for single premature stimuli that penetrated the tachycardia circuit, phase reset of the tachycardia was linearly related to distance between the central obstacle and the paced site. CONCLUSION: The ER is a complex but predictable perturbation of the global activation sequence of reentrant tachycardias. This predictability allows calculations of the response from anywhere on the perturbed surface. These findings suggest new techniques for measurement of the ER, which may lend themselves to computer-based methods for accurate and rapid mapping of reentrant circuits.

Animals↗

PubMed2003

Improved alignment method for noisy high-resolution ECG and Holter records using multiscale cross-correlation.

The coherent signal averaging process requires accurate estimation of a fiducial point in all beats to be averaged. The temporal cross-correlation between each detected beat and a template beat is the typical alignment method used with high-resolution electrocardiogram (HRECG) records. However, this technique does not produce a precise fiducial mark in records with high noise levels, like those found in Holter HRECG systems. In this study, we propose a new alignment method based on the multiscale cross-correlation between the template and each detected beat. We report the results of tests comparing multiscale and temporal methods for 3000 beats of simulated HRECG records corrupted separately with white noise, electromyographic noise and power line interference (50 Hz) of different root mean square levels. A second study with simulated records constructed from real Holter HRECG records is also presented. The results indicate that the multiscale alignment method produces a lower trigger jitter than the temporal method in all tests. We conclude that the proposed alignment method can be used in HRECG records with high noise levels.

Algorithms↗

PubMed2003

Estimation of cardiac conduction velocities using small data sets.

Cardiac surface conduction velocities could provide valuable information about the speed and angle of a propagating electrical wave front. It would be advantageous to develop catheter-based velocity mapping devices to improve the visualization of cardiac arrhythmias. However, catheter tip size is limited to < or = 2.5 mm in diameter, restricting the number and size of electrodes that can be placed on a catheter tip. We address the feasibility of estimating conduction speed and angle from small data sets suitable for recording from a catheter device in a standard clinical environment. We estimated cardiac conduction velocities from data subsets of 4-7 closely spaced electrograms, and then compared these estimates to velocities estimated from a larger reference grid. We studied 137 ventricular beats and 17,756 velocity vectors from six swine hearts. Average differences in angle between the two estimates were 0.4 degrees +/- 16 degrees while average differences in speed were 5% +/- 33%. These angle and speed differences provide an initial quantitative assessment of velocity accuracy for the purposes of catheter-based vector mapping.

Animals↗

PubMed2002

Multielectrode venous catheter mapping as a high quality constraint for electrocardiographic inverse solution.

A persistent challenge in solving inverse problems in electrocardiography is the application of suitable constraints to the calculation of cardiac sources. Whether one formulates the inverse problem in terms of epicardial potentials or activation wavefronts, the problem is physically ill-posed and hence results in numerically unstable computations. Suitable physiological constraints applied with appropriate weighting can recover useful inverse solutions. However, it is often difficult to determine the best possible constraints and their optimal weighting. We have recently begun to use multielectrode catheters as a means of mapping epicardial signals in animal models. To accommodate the sparse sampling of this venous catheter based approach, we have applied statistical signal processing methods to estimate complete epicardial maps of activation time and epicardial potentials. Such measurements--and the estimated maps from them--also have the potential to provide high quality constraints for electrocardiographic inverse problems because they provide direct--albeit sparse--access to the desired solution. In this presentation we describe several approaches we have applied to extract useful constraints from sparsely sampled epicardial signals as well as a training set of epicardial maps, and use them to improve the quality of computed inverse solutions. Results suggest that combining various information sources provides valuable constraint information. Such a multimodal approach to cardiac mapping is clinically and technically viable and offers a possible means to overcome a major remaining limitation of inverse electrocardiography.

Animals↗

PubMedDate not supplied

Eigenvector-based spatial filtering for reduction of physiological interference in diffuse optical imaging.

Diffuse optical imaging is an effective technique for noninvasive functional brain imaging. However, the measurements respond to systemic hemodynamic fluctuations caused by the cardiac cycle, respiration, and blood pressure, which may obscure or overwhelm the desired stimulus-evoked response. Previous work on this problem employed temporal filtering, estimation of systemic effects from background pixels, or modeling of interference signals with predefined basis functions, with some success. However, weak signals are still lost in the interference, and other complementary methods are desirable. We use the spatial behavior of measured baseline signals to identify the interference subspaces. We then project signals components in this subspace out of the stimulation data. In doing so, we assume that systemic interference components will be more global spatially, with higher energy, than the stimulus-evoked signals of interest. Thus, the eigenvectors corresponding to the largest eigenvalues of an appropriate correlation matrix form the basis for an interference subspace. By projecting the data onto the orthogonal nullspace of these eigenvectors, we can obtain more localized response, as reflected in improved contrast-to-noise ratio and correlation coefficient maps.

Artifacts↗