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A Paced-ECG Detector and Delineator for Automatic Multi-Parametric Catheter Mapping of Ventricular Tachycardia
- Source :
- IEEE Access, Vol 8, Pp 223952-223960 (2020), IEEE Access, IEEE Access, IEEE, 2020, 8, pp.223952-223960. ⟨10.1109/ACCESS.2020.3043542⟩
- Publication Year :
- 2020
- Publisher :
- IEEE, 2020.
-
Abstract
- International audience; Ventricular tachycardia (VT) is a life-threatening arrhythmia, which can be treated by catheter intervention. Accurate identification of the underlying reentrant circuit is often challenging, yet it is key to successful ablation of the VT. In practice, the cardiologist often uses electrocardiography (ECG) data provided by various catheter mapping techniques, including parameters acquired during sinus rhythm (voltage maps, presence of fragmented/late potentials) and during controlled pacing from different sites of the ventricle, so-called pace-mapping. A novel method is presented here to automatically extract the key information from pace-mapping data with automated detection of paced heartbeats from the surface ECG signals, using wavelet detection of pacing spikes and combined time/energy criteria, and automated delineation of paced beats, QRS peak, and QRS onset. This allows the generation of correlation gradient maps (indicating QRS morphology changes as the catheter is moved) and stimulus-to-QRS maps (sQRS, indicating the delay between pacing and activation of the healthy myocardium). The delineator is shown to be in good agreement with manual annotations from experts in a retrospective study of 18 VT ablation procedures. Paced-QRS detection had 95.2% sensitivity and 98.4% positive predictive value. Resulting sQRS maps had a mean absolute error of 11.1 ms, which was in the same range as the inter-observer errors (9.7 ms). The automatic processing drastically reduces the need for manual annotations. Therefore it makes it feasible to process and visualize, during the procedure, all the relevant parametric maps, which can be analyzed jointly to identify VT circuits and corresponding ablation targets.
- Subjects :
- General Computer Science
Computer science
medicine.medical_treatment
electrocardiography
0206 medical engineering
radiofrequency catheter ablation
02 engineering and technology
030204 cardiovascular system & hematology
Ventricular tachycardia
03 medical and health sciences
QRS complex
0302 clinical medicine
Wavelet
[SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system
medicine
General Materials Science
Sinus rhythm
cardiovascular diseases
Parametric statistics
[SDV.IB] Life Sciences [q-bio]/Bioengineering
medicine.diagnostic_test
business.industry
General Engineering
Pattern recognition
Ablation
medicine.disease
020601 biomedical engineering
[SDV.MHEP.CSC] Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular system
Catheter
cardiac interventional electrophysiology
medicine.anatomical_structure
Ventricle
cardiovascular system
[SDV.IB]Life Sciences [q-bio]/Bioengineering
Artificial intelligence
lcsh:Electrical engineering. Electronics. Nuclear engineering
business
Electrocardiography
lcsh:TK1-9971
Arrhythmia
Subjects
Details
- Language :
- English
- ISSN :
- 21693536
- Volume :
- 8
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....85b10e907d96bb44aa84794ce023eb03