Electrocardiographic Imaging: II. Effect of Torso Inhomogeneities on Noninvasive Reconstruction of Epicardial Potentials, Electrograms, and Isochrones

Ramanathan, Charulatha; Rudy, Yoram

doi:10.1046/j.1540-8167.2001.00241.x

Cited by 85 publications

(64 citation statements)

References 3 publications

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“…The Tikhonov regularization method 76 with CRESO-determined regularization parameter 24 is used to stabilize the inverse procedure and obtain , similar to our previous ECGI inverse computations using mesh-based BEM. 15,16,32,33,47,56,61,62,[65][66][67][68][69][70][71] Once the coefficient vector is obtained, u(x) can be computed at any location in the domain using: (5) The epicardial potential can then be calculated using: (6) Epicardial potentials are calculated using (6) on many epicardial nodes; numbers are provided for each dataset in the Results section. An epicardial potential map, reflecting the spatial distribution of potentials on the epicardial surface, is computed every millisecond during the cardiac cycle.…”

Section: Formulating the Methods Of Fundamental Solutions For Ecgimentioning

confidence: 99%

Application of the Method of Fundamental Solutions to Potential-based Inverse Electrocardiography

2006

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Potential-based inverse electrocardiography is a method for the noninvasive computation of epicardial potentials from measured body surface electrocardiographic data. From the computed epicardial potentials, epicardial electrograms and isochrones (activation sequences), as well as repolarization patterns can be constructed. We term this noninvasive procedure Electrocardiographic Imaging (ECGI). The method of choice for computing epicardial potentials has been the Boundary Element Method (BEM) which requires meshing the heart and torso surfaces and optimizing the mesh, a very time-consuming operation that requires manual editing. Moreover, it can introduce mesh-related artifacts in the reconstructed epicardial images. Here we introduce the application of a meshless method, the Method of Fundamental Solutions (MFS) to ECGI. This new approach that does not require meshing is evaluated on data from animal experiments and human studies, and compared to BEM. Results demonstrate similar accuracy, with the following advantages: 1. Elimination of meshing and manual mesh optimization processes, thereby enhancing automation and speeding the ECGI procedure. 2. Elimination of mesh-induced artifacts. 3. Elimination of complex singular integrals that must be carefully computed in BEM. 4. Simpler implementation. These properties of MFS enhance the practical application of ECGI as a clinical diagnostic tool.

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Section: Formulating the Methods Of Fundamental Solutions For Ecgimentioning

confidence: 99%

Application of the Method of Fundamental Solutions to Potential-based Inverse Electrocardiography

2006

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“…As in previous studies, [12][13][14] recorded potentials were placed on a digitized 3D canine heart model and aligned on the basis of the positions of coronary arteries. The heart was then placed in the correct anatomic position inside a computer model of the human torso that contained lungs, spine, sternum, and skeletal muscle.…”

Section: Methodsmentioning

confidence: 99%

“…The heart was then placed in the correct anatomic position inside a computer model of the human torso that contained lungs, spine, sternum, and skeletal muscle. 14 The measured epicardial potentials were used to compute ECG potentials at 458 nodes on the body surface. Gaussian noise (50 V peak-topeak) was added to the computed torso potentials to simulate measurement noise.…”

Section: Methodsmentioning

confidence: 99%

Imaging Dispersion of Myocardial Repolarization, II

et al. 2001

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Background-Dispersion of myocardial repolarization supports the development and maintenance of life-threatening arrhythmias. Current noninvasive approaches for detecting substrates with increased dispersion based on ECG measures (eg, QT dispersion) have shown limited success and inconsistencies. The companion article shows that, in contrast, epicardial potentials and derived measures reflect local dispersion of repolarization. Here, using a recently developed ECG imaging method, we evaluate the feasibility of noninvasive reconstruction of such epicardial measures from body-surface ECG data. Methods and Results-Epicardial potentials were recorded with a 224-electrode sock from an open-chest dog during control, regional warming, cooling, and simultaneous adjacent warming and cooling to induce localized changes in myocardial repolarization and regions of increased dispersion. Body-surface potentials were generated from these epicardial potentials in a human torso model. Realistic geometric errors and measurement noise were added to the torso data, which were then used to noninvasively reconstruct epicardial measures of repolarization dispersion (activation recovery intervals [ARIs] and QRST integrals). Repolarization properties were accurately depicted by ECG imaging, including (1) shortened ARIs and increased QRST integrals over the warmed region, (2) prolonged ARIs and decreased QRST integrals over the cooled region, and (3) high gradients of ARIs and QRST integrals over the adjacent warmed and cooled regions. Conclusions-ECG imaging can reconstruct repolarization properties accurately and localize areas of increased dispersion of repolarization in the heart noninvasively. Its clinical significance lies in the possibility of noninvasive risk stratification and in guidance and evaluation of therapy.

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“…On the one hand, it has been shown that inhomogeneous inverse solutions correspond more closely with epicardial potential maps in the absence of noise. [25][26][27] On the other hand, it is argued that this correspondence is degraded by geometric error and noise because transfer matrices for the inverse problem are ill conditioned and are less robust for inhomogeneous than for homogeneous torso models. 26 These analyses are based on numeric experiments, in which forward models are used to construct the BSPMs that provide the input for the inverse solution tests.…”

Section: Why Does the Forward Problem Of Electrocardiography Matter?mentioning

confidence: 99%

Forward Problem of Electrocardiography

Bear

Cheng

LeGrice

et al. 2015

Circ: Arrhythmia and Electrophysiology

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Background-The relationship between epicardial and body surface potentials defines the forward problem of electrocardiography. A robust formulation of the forward problem is instrumental to solving the inverse problem, in which epicardial potentials are computed from known body surface potentials. Here, the accuracy of different forward models has been evaluated experimentally. Methods and Results-Body surface and epicardial potentials were recorded simultaneously in anesthetized closed-chest pigs (n=5) during sinus rhythm, and epicardial and endocardial ventricular pacing (65 records in total). Body surface potentials were simulated from epicardial recordings using experiment-specific volume conductor models constructed from magnetic resonance imaging. Results for homogeneous (isotropic electric properties) and inhomogeneous (incorporating lungs, anisotropic skeletal muscle, and subcutaneous fat) forward models were compared with measured body surface potentials. Correlation coefficients were 0.85±0.08 across all animals and activation sequences with no significant difference between homogeneous and inhomogeneous solutions (P=0.85). Despite this, there was considerable variance between simulated and measured body surface potential distributions. Differences between the body surface potential extrema predicted with homogeneous forward models were 55% to 78% greater than observed (P<0.05) and attenuation of potentials adjacent to extrema were 10% to 171% greater (P<0.03). The length and orientation of the vector between potential extrema were also significantly different. Inclusion of inhomogeneous electric properties in the forward model reduced, but did not eliminate these differences. Conclusions-These results demonstrate that homogeneous volume conductor models introduce substantial spatial inaccuracies in forward problem solutions. This probably affects the precision of inverse reconstructions of cardiac potentials, in which this assumption is made. (Circ Arrhythm Electrophysiol. 2015;8:677-684.

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Electrocardiographic Imaging: II. Effect of Torso Inhomogeneities on Noninvasive Reconstruction of Epicardial Potentials, Electrograms, and Isochrones

Abstract: The results demonstrate that, in the clinical application, it is not necessary to include torso inhomogeneities for noninvasive reconstructions of epicardial potentials, EGMs, and activation sequences.

Cited by 85 publications

References 3 publications

Application of the Method of Fundamental Solutions to Potential-based Inverse Electrocardiography

Application of the Method of Fundamental Solutions to Potential-based Inverse Electrocardiography

Imaging Dispersion of Myocardial Repolarization, II

Forward Problem of Electrocardiography

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