Electrical imaging of the heart

Brooks, Dana H.; MacLeod, Rob S.

doi:10.1109/79.560322

Cited by 59 publications

(10 citation statements)

References 86 publications

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“…The measurement of the electrical activity of the heart can be accomplished with numerous techniques including intracavity electrodes (1), multi-electrode baskets, optical techniques (2), monophasic action potentials (3) and body surface potential mapping (4)(5)(6).…”

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confidence: 99%

Electromechanical mapping with MRI tagging and epicardial sock electrodes

McVeigh

Faris²,

Ennis³

et al. 2002

Journal of Electrocardiology

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Methods currently exist for the precise measurement of local three-dimensional myocardial motion noninvasivly with magnetic resonace imaging tagging. From these motion estimates, strain images representing the local deformation of the myocardium can be formed to show local myocardial contraction. These images clearly show the sequence of mechanical events during the activation and relaxation of the heart, making them ideal to visualize abnormalities caused by asynchronous electrical activation or ischemia. Coupled with the near simultaneous mapping of electrical depolarization with a sock electrode array, we can investigate the relationship between electical activity and mechanical function on a local level in the in vivo heart. Registered fiber angle maps can be also be obtained in the same heart with diffusion magnetic resonance imaging to assist in the construction of the electromechanical model of the whole heart. The ability to measure the precise mechanical function, the electrical function, and the underlying fiber architecture in the same heart in vivo may uncover the interactions of these constituents in normal and abnormal cardiac function. The detailed relationship between local muscle shortening, electrical activation, and myocardial fiber angle has been difficult to appreciate due to the inability to measure these features of the heart in the same preparation.The measurement of the electrical activity of the heart can be accomplished with numerous techniques including intracavity electrodes (1), multi-electrode baskets, optical techniques (2), monophasic action potentials (3) and body surface potential mapping (4-6).MRI has made contributions to the understanding of myocardial mechanics by providing methods for measuring local three dimensional myocardial motion non-invasively using presaturation tagging patterns (7-9). Recently, methods for measuring the diffusion tensor with MRI have led to a method for measuring the myocardial fiber angle in soft tissue (10,11).We have developed an experimental protocol in which electrical mapping, myocardial strain mapping, and fiber angle mapping can be achieved in the same heart (12). The data are registered so that local correlations can be made among these 3 features.In MRI tagging a set of saturation pulses placed in the tissue provides a spatially varying signal intensity pattern in the tissue; the change in shape of the intensity pattern in the image reflects the change in shape of the underlying body containing the intensity pattern. Originally demonstrated by Zerhouni et. al. (7) with saturation pulses, and by Axel (8) with SPAMM pulses, these techniques have become a mainstay for imaging myocardial function (13). Figure Reprint 1 shows a short axis slice of the heart at two time points in the heart cycle; just prior to pacing the right ventricle (RV) apex, and just after pacing. The ability to measure local mechanics from the deformation of the tagging pattern is very clear.The objective of the analysis of tagged images is to track the three...

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Electromechanical mapping with MRI tagging and epicardial sock electrodes

McVeigh

Faris²,

Ennis³

et al. 2002

Journal of Electrocardiology

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“…In the interpretation of ECG signals, the relative timing of the P-wave, QRS-complex, and T-wave is important. These features are relatively easily picked up by a trained eye, even when the data is noisy, yet automatic detection and segmentation is difficult due to changes in heart rate, noise, and other considerations [36]. Consider Fig.…”

Section: B Piecewise Monotonic Ls Regression Inmentioning

confidence: 99%

Mathematical programming algorithms for regression-based nonlinear filtering in R/sup N/

Sidiropoulos

Bro²

1999

IEEE Trans. Signal Process.

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This paper is concerned with regression under a "sum" of partial order constraints. Examples include locally monotonic, piecewise monotonic, runlength constrained, and unimodal and oligomodal regression. These are of interest not only in nonlinear filtering but also in density estimation and chromatographic analysis. It is shown that under a least absolute error criterion, these problems can be transformed into appropriate finite problems, which can then be efficiently solved via dynamic programming techniques. Although the result does not carry over to least squares regression, hybrid programming algorithms can be developed to solve least squares counterparts of certain problems in the class.

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“…Due to the spatio-temporal limitations of classical ECG, electrocardiographic imaging (ECGI) allows to effectively reconstruct the electrophysiological activity on the heart surface from non-invasive-recorded body surface potentials (BSP) [7,8]. However, the inverse problem in ECGI is ill-posed, and it is necessary to apply regularization methods to obtain realistic solutions [9,10].…”

Section: Introductionmentioning

confidence: 99%

Including a Priori Knowledge in the Solution of the Inverse Problem During Atrial Fibrillation

Suárez-Gutiérrez

Cámara

Barquero-Pérez

et al. 2017

Computing in Cardiology Conference (CinC)

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Regularization methods for the inverse problem face important challenges during atrial fibrillation (AF), so any a priori information available during the electrophysiological study may improve the solution. We propose a Tikhonov-based inverse problem formulation that incorporates extra information provided by noisy intracavitary measurements near the endocardium. Since we introduced two different sources of information (Tikhonov estimation and a priori measurements), two regularization parameters must be tuned using a generalized L-Curve method. Performance of this method is studied using several timebased metrics proposed in previous works. The method proposed improved estimations accuracy in sinus rhythm, simple and complex AF models.

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Electrical imaging of the heart

Cited by 59 publications

References 86 publications

Electromechanical mapping with MRI tagging and epicardial sock electrodes

Electromechanical mapping with MRI tagging and epicardial sock electrodes

Mathematical programming algorithms for regression-based nonlinear filtering in R/sup N/

Including a Priori Knowledge in the Solution of the Inverse Problem During Atrial Fibrillation

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