Key result
Patient-specific atrial anatomy influences AF reentry dynamics but fails to alter AF initiation rates.
Why the study?
AF is influenced by and contributes to atrial structural remodelling, but how differences in atrial anatomy affect AF inducibility and dynamics, with and without fibrosis, remains incompletely understood.
Does anatomical variability and fibrosis affect AF inducibility and reentry dynamics in personalized in silico models?
Does anatomical variability and fibrosis affect AF inducibility and reentry dynamics in personalized in silico models?
Absolute Event Rate: 53.5% vs 54%
p-value: p=0.37
Patient-specific anatomical variability significantly influences AF reentry dynamics in computational models, whereas fibrosis plays a limited modifying role in low-fibrotic atria.
Anatomical variability does not alter AF initiation in models; extends computational reentry insights but leaves clinical relevance open.
Purpose Atrial fibrillation (AF) is both influenced by and contributes to atrial structural remodelling, including atrial enlargement and fibrosis. In this work, we aimed to understand how differences in atrial anatomy affect AF inducibility and dynamics, both without and with fibrosis, through in silico models. Methods Atrial wall anatomies from late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) were used to generate personalised models. Detailed intra- and inter-atrial structures (pectinate muscles, Bachmann’s bundle, fossa ovalis, coronary sinus, and fibre orientations) were mapped onto patient-specific atrial anatomies through a novel strategy using universal atrial coordinates and a highly detailed reference model. Patient-specific endomysial fibrosis was incorporated based on LGE-MRI. We quantified AF and macro-reentrant atrial tachycardia (MRAT) initiation rates in models with and without fibrosis, comparing reentry dynamics using renewal theory. Results We generated personalised models of 10 patients, all but one with low-fibrotic content (Utah stages ≤ 2). Anatomical variability did not significantly affect AF initiation rates in both non-fibrotic (54.0 ± 13.7%, p = 0.43) and fibrotic models (53.5 ± 15.3%, p = 0.37). For AF + MRAT, initiation rates varied significantly among fibrotic models ( p = 0.04) but not among non-fibrotic ones ( p = 0.14). Reentry formation rates varied significantly across anatomies both with and without fibrosis ( p < 0.04). With fibrosis, reentry destruction rates also varied significantly ( p < 0.02). The number of simultaneous reentries varied significantly across patient anatomies ( p < 0.001 without fibrosis, p < 0.05 with fibrosis), with fibrosis altering reentry counts in 2 patients ( p < 0.02). Conclusion Atrial anatomy influenced patient-specific variability in AF reentry dynamics, while fibrosis played a limited modifying role in this low-fibrotic cohort.
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Marques et al. (2026) studied Atrial fibrillation (n=10). Patient-specific anatomical variability and fibrosis vs. Non-fibrotic models was evaluated on Atrial fibrillation (AF) initiation rates (p=0.37). Patient-specific anatomical variability influenced AF reentry dynamics but did not significantly affect AF initiation rates in non-fibrotic (54.0%, p=0.43) or fibrotic (53.5%, p=0.37) models.
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