ArticleIEEE transactions on medical imaging2019
Noninvasive Activation Imaging of Ventricular Arrhythmias by Spatial Gradient Sparse in Frequency Domain-Application to Mapping Reentrant Ventricular Tachycardia.
Article in IEEE transactions on medical imaging, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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4 citing papers in PubMed, 10 citations in OpenAlex.
- ECG Localization Method Based on Volume Conductor Model and Kalman Filtering.Sensors (Basel, Switzerland) · 2021Article
- Cardiac Activation Maps Reconstruction: A Comparative Study Between Data-Driven and Physics-Based Methods.Frontiers in physiology · 2021Article
- Non-invasive reconstruction of dynamic myocardial transmembrane potential with graph-based total variation constraints.Healthcare technology letters · 2019Article
- Noninvasive Imaging of Epicardial and Endocardial Potentials With Low Rank and Sparsity Constraints.IEEE transactions on bio-medical engineering · 2019Article
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
The aim of this paper is to develop and evaluate a novel imaging method [spatial gradient sparse in frequency domain (SSF)] for the reconstruction of activation sequences of ventricular arrhythmia from noninvasive body surface potential map (BSPM) measurements. We formulated and solved the electrocardiographic inverse problem in the frequency domain, and the activation time was encoded in the phase information of the imaging solution. A cellular automaton heart model was used to generate focal ventricular tachycardia (VT). Different levels of Gaussian white noise were added to simulate noise-contaminated BSPM. The performance of SSF was compared with that of weighted minimum norm inverse solution. We also evaluated the method in a swine model with simultaneous intracardiac and body surface recordings. Four reentrant VTs were observed in pigs with myocardial infarction generated by left anterior descending artery occlusion. The imaged activation sequences of reentrant VTs were compared with those obtained from intracardiac electrograms. In focal VT simulation, SSF has increased the correlation coefficient (CC) by 5% and decreased localization errors (LEs) by 2.7 mm on average under different noise levels. In the animal validation with reentrant VT, SSF has achieved an average CC of 88% and an average LE of 6.3 mm in localizing the earliest and latest activation site in the reentry circuit. Our promising results suggest that the SSF provides noninvasive imaging capability of detecting and mapping macro-reentrant circuits in 3-D ventricular space. The SSF may become a useful imaging tool of identifying and localizing the potential targets for ablation of focal and reentrant VT.
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