Key result
Perturbed pacing analysis accurately predicts the site of conduction block in ~95% of experimental models.
Why the study?
Does principal components analysis of conduction time variations during perturbed pacing identify and predict unstable sites prone to conduction block in heterogeneous cardiac tissue?
Does principal components analysis of conduction time variations during perturbed pacing identify and predict unstable sites prone to conduction block in heterogeneous cardiac tissue?
Analyzing conduction time variations during perturbed pacing via principal components analysis can predict sites of impending conduction block in heterogeneous cardiac tissue, offering potential translational utility for electrophysiology mapping and ablation.
Answers are grounded in this paper and cite their sources.
May enable early block prediction in tissue models; leaves open clinical translation for arrhythmia mapping.
Safe and stable action potential propagation is crucial for the proper function of the heart. Altered propagation safety can lead to slow conduction and conduction block, the key ingredients of reentrant and potentially life-threatening arrhythmias. Hence, it is important to develop metrics to quantify the stability of conduction. The previously proposed safety factor, useful in computer simulations, is difficult to determine in real cardiac tissue. We hypothesized that unstable conduction, potentially prone to block, is sensitive to small perturbations of pacing and tested this in co-cultured strands of homozygous connexin 43 knock-out and heterozygous knock-out or wild-type murine ventricular cardiomyocytes grown on microelectrode arrays, and in corresponding computer simulations. The tissues were stimulated at a progressively increasing rate in the presence vs absence of stochastic or alternating variations of pacing cycle length. Variations of conduction times between adjacent electrodes were analyzed using principal components analysis. In 18 out of 19 cultured strands and in 10 out of 10 simulations, our approach correctly identified and predicted the location at which conduction block ultimately occurred already hundreds of beats and tens of seconds in advance. Interestingly, prediction was already possible in the absence of pacing variations, albeit with lower reliability. Finally, the site of slowest conduction was not necessarily the site of block. By permitting to identify sites of unstable conduction most prone to block occurs, our work may find translational applications in clinical cardiac electrophysiology during mapping and ablation procedures and open new avenues to explore innovative markers of conduction stability.
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Ostini et al. (2026) studied Unstable conduction prone to conduction block in heterogeneous cardiac tissue (n=19). Principal components analysis of conduction time variations during progressively increasing pacing rates with stochastic or alternating cycle length variations vs. Pacing in the absence of stochastic or alternating variations of pacing cycle length was evaluated on Correct identification and prediction of the location of ultimate conduction block. Principal components analysis of conduction time variations under perturbed pacing predicted the site of conduction block in 18 of 19 (94.7%) cultured strands and 10 of 10 (100%) simulations.
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