Noninvasive Imaging of Cardiac Electrophysiology (NICE)

Seger, Michael; Pfeifer, Bernhard; Berger, Thomas

doi:10.5772/30019

Cited by 2 publications

(2 citation statements)

References 52 publications

(82 reference statements)

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“…Another motivation for BSPMs is to utilize it together with torso and heart geometries and conductivities to estimate the epicardial potentials on the heart surface. In other words, BSPM is an essential part of ECG Imaging (ECGI) system which has demonstrated feasibility in estimating potentials, electrograms, isochrones and repolarization patterns on the heart surface [3].…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Laplacian Based Interpolation Algorithm for Noise Reduction in Body Surface Potential Maps

Rababah¹,

Finlay²,

Guldenring³

et al. 2018

2018 Computing in Cardiology Conference (CinC)

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Body surface potential maps (BSPMs) are typically recorded from a large number of ECG leads that cover the entire thorax. This improves diagnostic accuracy and is required in Electrocardiographic imaging (ECGi). BSPMs recorded in the clinical setting may have some leads that are noisy due to poor skin electrode contact. We analyzed 117 lead BSPMs recorded from 360 subjects. We successively simulated the removal of ECG leads at various locations and tested the ability of our algorithm to accurately reconstruct the missing information. When seven electrodes were removed, the algorithm could reconstruct BSPM patterns from QRS segments with median RMSE of 6.24µV and 12.15µV and CC of 0.999 and 0.997 when Laplacian method and PCA based method were used respectively. This work shows that noisy BSPM leads, which often manifest in the clinical setting, can be more accurately reconstructed using our Laplacian based interpolation algorithm, when low number of missed electrodes in regions where electrodes are organised in a well distributed and tight mesh.

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Section: Introductionmentioning

confidence: 99%

An Adaptive Laplacian Based Interpolation Algorithm for Noise Reduction in Body Surface Potential Maps

Rababah¹,

Finlay²,

Guldenring³

et al. 2018

2018 Computing in Cardiology Conference (CinC)

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show abstract

“…Through the years, various noninvasive electrocardiographic imaging techniques have emerged that estimate epicardial potentials or myocardial activation times from potentials recorded on the thorax. [1][2][3][4][5][6][7][8] The recording of potentials from a large number of torso electrodes is referred to as body surface potential mapping (BSPM). 9 The BSPM data can later be used in mathematical inverse procedures to calculate local epicardial potentials or myocardial activation times.…”

mentioning

confidence: 99%

Noninvasive Imaging of Cardiac Excitation: Current Status and Future Perspective

Graaf

Bhagirath

Ramanna

et al. 2014

Noninvasive Electrocardiol

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Noninvasive imaging of cardiac excitation using body surface potential mapping (BSPM) data and inverse procedures is an emerging technique that enables estimation of myocardial depolarization and repolarization. Despite numerous reports on the possible advantages of this imaging technique, it has not yet advanced into daily clinical practice. This is mainly due to the time consuming nature of data acquisition and the complexity of the mathematics underlying the used inverse procedures. However, the popularity of this field of research has increased and noninvasive imaging of cardiac electrophysiology is considered a promising tool to complement conventional invasive electrophysiological studies. Furthermore, the use of appropriately designed electrode vests and more advanced computers has greatly reduced the procedural time. This review provides descriptive overview of the research performed thus far and the possible future directions. The general challenges in routine application of BSPM and inverse procedures are discussed. In addition, individual properties of the biophysical models underlying the inverse procedures are illustrated.

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Noninvasive Imaging of Cardiac Electrophysiology (NICE)

Cited by 2 publications

References 52 publications

An Adaptive Laplacian Based Interpolation Algorithm for Noise Reduction in Body Surface Potential Maps

An Adaptive Laplacian Based Interpolation Algorithm for Noise Reduction in Body Surface Potential Maps

Noninvasive Imaging of Cardiac Excitation: Current Status and Future Perspective

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