Unraveling the Influence of Right Ventricle Presence on Paced ECGs

Background: In-silico pace-mapping uses personalized computational models and patient ECGs to create virtual pace maps, aiding in ventricular arrhythmias (VT) ablation. Due to challenges in accurately defining the right ventricle (RV) boundaries, most computational studies focus only on left ventricle (LV) anatomy. The impact of the RV's presence on simulated ECGs during pacing remains unexplored.Objective: To compare ECGs during pacing with and without the RV.Methods: Twenty biventricular (BiV) computational models were created from computer tomography (CT) data, and a LV-only version was derived.Stimuli were delivered at 17 LV locations (AHA segments).ECGs from pacing BiV and LV models were correlated.The top 10 ECG lead correlations (ccm10) were averaged.Results: The mean ccm10 across all models was 0.970.02,with the lowest and highest values in segments 8 (0.92) and 15 (0.99), respectively.Conclusion: In-silico pacing showed strong ECG correlation (ccm10 > 0.90) between BiV and LV models, suggesting that RV inclusion may not be necessary for simple pace-mapping applications.

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Publication Details

Journal
Computing in cardiology
Published
2024-12-01
DOI
https://doi.org/10.22489/cinc.2024.329
Primary Topic
Cardiac pacing and defibrillation studies
Type
article
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article

Unraveling the Influence of Right Ventricle Presence on Paced ECGs

Steven Niederer, Cristóbal Rodero, Gernot Plank, Christopher A. Rinaldi et al.
Computing in cardiology
Cardiac pacing and defibrillation studies
article

Unraveling the Influence of Right Ventricle Presence on Paced ECGs

Steven Niederer, Cristóbal Rodero, Gernot Plank, Christopher A. Rinaldi, Fernando O. Campos, Martin Bishop, John Whitaker
article en

Abstract

Background: In-silico pace-mapping uses personalized computational models and patient ECGs to create virtual pace maps, aiding in ventricular arrhythmias (VT) ablation. Due to challenges in accurately defining the right ventricle (RV) boundaries, most computational studies focus only on left ventricle (LV) anatomy. The impact of the RV's presence on simulated ECGs during pacing remains unexplored.Objective: To compare ECGs during pacing with and without the RV.Methods: Twenty biventricular (BiV) computational models were created from computer tomography (CT) data, and a LV-only version was derived.Stimuli were delivered at 17 LV locations (AHA segments).ECGs from pacing BiV and LV models were correlated.The top 10 ECG lead correlations (ccm10) were averaged.Results: The mean ccm10 across all models was 0.970.02,with the lowest and highest values in segments 8 (0.92) and 15 (0.99), respectively.Conclusion: In-silico pacing showed strong ECG correlation (ccm10 > 0.90) between BiV and LV models, suggesting that RV inclusion may not be necessary for simple pace-mapping applications.

Computing in cardiologyVol. 51
Openalex Percentile: Top 57%
Cardiac pacing and defibrillation studies
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