Literature DB >> 19266284

Application of L1-norm regularization to epicardial potential solution of the inverse electrocardiography problem.

Subham Ghosh1, Yoram Rudy.   

Abstract

The electrocardiographic inverse problem of computing epicardial potentials from multi-electrode body-surface ECG measurements, is an ill-posed problem. Tikhonov regularization is commonly employed, which imposes penalty on the L2-norm of the potentials (zero-order) or their derivatives. Previous work has indicated superior results using L2-norm of the normal derivative of the solution (a first order regularization). However, L2-norm penalty function can cause considerable smoothing of the solution. Here, we use the L1-norm of the normal derivative of the potential as a penalty function. L1-norm solutions were compared to zero-order and first-order L2-norm Tikhonov solutions and to measured 'gold standards' in previous experiments with isolated canine hearts. Solutions with L1-norm penalty function (average relative error [RE] = 0.36) were more accurate than L2-norm (average RE = 0.62). In addition, the L1-norm method localized epicardial pacing sites with better accuracy (3.8 +/- 1.5 mm) compared to L2-norm (9.2 +/- 2.6 mm) during pacing in five pediatric patients with congenital heart disease. In a pediatric patient with Wolff-Parkinson-White syndrome, the L1-norm method also detected and localized two distinct areas of early activation around the mitral valve annulus, indicating the presence of two left-sided pathways which were not distinguished using L2 regularization.

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Mesh:

Year:  2009        PMID: 19266284      PMCID: PMC2958169          DOI: 10.1007/s10439-009-9665-6

Source DB:  PubMed          Journal:  Ann Biomed Eng        ISSN: 0090-6964            Impact factor:   3.934


  31 in total

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2.  Ventricular intramural and epicardial potential distributions during ventricular activation and repolarization in the intact dog.

Authors:  M S Spach; R C Barr
Journal:  Circ Res       Date:  1975-08       Impact factor: 17.367

3.  An admissible solution approach to inverse electrocardiography.

Authors:  G F Ahmad; D H Brooks; R S MacLeod
Journal:  Ann Biomed Eng       Date:  1998 Mar-Apr       Impact factor: 3.934

4.  An improved method for estimating epicardial potentials from the body surface.

Authors:  F Greensite; G Huiskamp
Journal:  IEEE Trans Biomed Eng       Date:  1998-01       Impact factor: 4.538

5.  Noninvasive electrocardiographic imaging: reconstruction of epicardial potentials, electrograms, and isochrones and localization of single and multiple electrocardiac events.

Authors:  H S Oster; B Taccardi; R L Lux; P R Ershler; Y Rudy
Journal:  Circulation       Date:  1997-08-05       Impact factor: 29.690

Review 6.  The inverse problem in electrocardiography: solutions in terms of epicardial potentials.

Authors:  Y Rudy; B J Messinger-Rapport
Journal:  Crit Rev Biomed Eng       Date:  1988

7.  Electrocardiographic imaging (ECGI), a novel diagnostic modality used for mapping of focal left ventricular tachycardia in a young athlete.

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8.  Electrocardiographic imaging of cardiac resynchronization therapy in heart failure: observation of variable electrophysiologic responses.

Authors:  Ping Jia; Charulatha Ramanathan; Raja N Ghanem; Kyungmoo Ryu; Niraj Varma; Yoram Rudy
Journal:  Heart Rhythm       Date:  2006-03       Impact factor: 6.343

9.  Inverse calculation of QRS-T epicardial potentials from body surface potential distributions for normal and ectopic beats in the intact dog.

Authors:  R C Barr; M S Spach
Journal:  Circ Res       Date:  1978-05       Impact factor: 17.367

10.  Noninvasive electrocardiographic imaging for cardiac electrophysiology and arrhythmia.

Authors:  Charulatha Ramanathan; Raja N Ghanem; Ping Jia; Kyungmoo Ryu; Yoram Rudy
Journal:  Nat Med       Date:  2004-03-14       Impact factor: 53.440

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  17 in total

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2.  Non-invasive imaging of cardiac activation and recovery.

Authors:  Peter M van Dam; Thom F Oostendorp; André C Linnenbank; Adriaan van Oosterom
Journal:  Ann Biomed Eng       Date:  2009-06-27       Impact factor: 3.934

3.  ML and MAP estimation of parameters for the Kalman filter and smoother applied to electrocardiographic imaging.

Authors:  Taha Erenler; Yesim Serinagaoglu Dogrusoz
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4.  Evaluation of multivariate adaptive non-parametric reduced-order model for solving the inverse electrocardiography problem: a simulation study.

Authors:  Önder Nazım Onak; Yesim Serinagaoglu Dogrusoz; Gerhard Wilhelm Weber
Journal:  Med Biol Eng Comput       Date:  2018-12-01       Impact factor: 2.602

5.  Finite-element-based discretization and regularization strategies for 3-D inverse electrocardiography.

Authors:  Dafang Wang; Robert M Kirby; Chris R Johnson
Journal:  IEEE Trans Biomed Eng       Date:  2011-03-03       Impact factor: 4.538

6.  Noninvasive Reconstruction of Transmural Transmembrane Potential With Simultaneous Estimation of Prior Model Error.

Authors:  Sandesh Ghimire; John L Sapp; B Milan Horacek; Linwei Wang
Journal:  IEEE Trans Med Imaging       Date:  2019-03-20       Impact factor: 10.048

7.  Examining the Impact of Prior Models in Transmural Electrophysiological Imaging: A Hierarchical Multiple-Model Bayesian Approach.

Authors:  Azar Rahimi; John Sapp; Jingjia Xu; Peter Bajorski; Milan Horacek; Linwei Wang
Journal:  IEEE Trans Med Imaging       Date:  2015-08-04       Impact factor: 10.048

8.  Assessment of regularization techniques for electrocardiographic imaging.

Authors:  Matija Milanič; Vojko Jazbinšek; Robert S Macleod; Dana H Brooks; Rok Hren
Journal:  J Electrocardiol       Date:  2013-10-17       Impact factor: 1.438

9.  Binary optimization for source localization in the inverse problem of ECG.

Authors:  Danila Potyagaylo; Elisenda Gil Cortés; Walther H W Schulze; Olaf Dössel
Journal:  Med Biol Eng Comput       Date:  2014-07-10       Impact factor: 2.602

10.  Noninvasive Imaging of Epicardial and Endocardial Potentials With Low Rank and Sparsity Constraints.

Authors:  Lin Fang; Jingjia Xu; Hongjie Hu; Yunmei Chen; Pengcheng Shi; Linwei Wang; Huafeng Liu
Journal:  IEEE Trans Biomed Eng       Date:  2019-01-21       Impact factor: 4.538

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