Wavelet-promoted sparsity for non-invasive reconstruction of electrical activity of the heart.
We investigated a novel sparsity-based regularization method in the wavelet domain of the inverse problem of electrocardiography that aims at preserving the spatiotemporal characteristics of heart-surface potentials. In three normal, anesthetized dogs, electrodes were implanted around the epicardium...
| Publicado en: | Medical & Biological Engineering & Computing Vol. 56; no. 11; pp. 2039 - 2051 |
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| Autores principales: | , , , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
Nov2018
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=132461117&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 132461117 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 01400118 PO0 jtl: Medical & Biological Engineering & Computing issn: 01400118 maglogo: N pubinfo: dt: Nov2018 vid: 56 iid: 11 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 132461117 132461117 NLM29752679 10.1007/s11517-018-1831-2 NLM29752679 132461117 ppf: 2039 ppct: 12 formats: fmt: @attributes: type: P tig: atl: Wavelet-promoted sparsity for non-invasive reconstruction of electrical activity of the heart. aug: au: Cluitmans, Matthijs Karel, Joël Bonizzi, Pietro Volders, Paul Westra, Ronald Peeters, Ralf affil: Department of Data Science and Knowledge Engineering, Maastricht University, Maastricht, The Netherlands sug: subj: Electrocardiography Methods Signal Processing, Computer Assisted Electrodes, Implanted Algorithms Tomography, X-Ray Computed Pericardium Pericardium Physiology Dogs Body Surface Potential Mapping Methods Animals Arthritis Impact Measurement Scales Ferrans and Powers Quality of Life Index Scales ab: We investigated a novel sparsity-based regularization method in the wavelet domain of the inverse problem of electrocardiography that aims at preserving the spatiotemporal characteristics of heart-surface potentials. In three normal, anesthetized dogs, electrodes were implanted around the epicardium and body-surface electrodes were attached to the torso. Potential recordings were obtained simultaneously on the body surface and on the epicardium. A CT scan was used to digitize a homogeneous geometry which consisted of the body-surface electrodes and the epicardial surface. A novel multitask elastic-net-based method was introduced to regularize the ill-posed inverse problem. The method simultaneously pursues a sparse wavelet representation in time-frequency and exploits correlations in space. Performance was assessed in terms of quality of reconstructed epicardial potentials, estimated activation and recovery time, and estimated locations of pacing, and compared with performance of Tikhonov zeroth-order regularization. Results in the wavelet domain obtained higher sparsity than those in the time domain. Epicardial potentials were non-invasively reconstructed with higher accuracy than with Tikhonov zeroth-order regularization (p < 0.05), and recovery times were improved (p < 0.05). No significant improvement was found in terms of activation times and localization of origin of pacing. Next to improved estimation of recovery isochrones, which is important when assessing substrate for cardiac arrhythmias, this novel technique opens potentially powerful opportunities for clinical application, by allowing to choose wavelet bases that are optimized for specific clinical questions. Graphical Abstract The inverse problem of electrocardiography is to reconstruct heart-surface potentials from recorded bodysurface electrocardiograms (ECGs) and a torso-heart geometry. However, it is ill-posed and solving it requires additional constraints for regularization. We introduce a regularization method that simultaneously pursues a sparse wavelet representation in time-frequency and exploits correlations in space. Our approach reconstructs epicardial (heart-surface) potentials with higher accuracy than common methods. It also improves the reconstruction of recovery isochrones, which is important when assessing substrate for cardiac arrhythmias. This novel technique opens potentially powerful opportunities for clinical application, by allowing to choose wavelet bases that are optimized for specific clinical questions. pubtype: Academic Journal doctype: Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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