| Autor: |
Bifulco, Savannah F, Sarairah, Sakher, Birjandian, Zeinab, Roney, Caroline H, Niederer, Steven A, Mahnkopf, Christian, K?hnlein, Peter, Mitlacher, Marcel, Tirschwell, David, Akoum, Nazem W, Boyle, Patrick M |
| Zdroj: |
Circulation (Ovid); November 2019, Vol. 140 Issue: Supplement 1 pA16280-A16280, 1p |
| Abstrakt: |
Introduction:Sub-clinical atrial fibrillation (AFib) is suspected as the cause of embolic stroke of unknown source (ESUS, i.e., cryptogenic stroke). However, AFib is only detected in ~30% of ESUS patients in follow-up. Early prediction of AFib vulnerability will enable better outcomes for ESUS patients.Hypothesis:Simulations conducted in computational models reconstructed from late gadolinium enhanced (LGE)-MRI scans of ESUS patients can stratify AFib risk by determining whether the fibrotic substrate for AFib exists.Methods:ESUS was defined per standard criteria and verified by a neurologist. 18 patients had LGE-MRI for fibrosis assessment within 3 months of stroke. Left atrial (LA) models including fibrotic tissue were reconstructed from LGE-MRI scans segmented by Merisight (Marrek Inc). Fiber orientations were mapped into models using the universal atrial coordinates approach. The LA was modeled as a bilayer with endo-epicardial dissociation in fibrotic areas. The fibrotic substrate for AFib was deemed present in models in which burst pacing from the pulmonary veins induced stable reentry.Results:Simulations predicted AFib vulnerability in 6/18 models (33%). Examples of fibrotic tissue distribution (Fig A) and reentry (Fig B) are shown. Fibrotic tissue volume was not significantly different between inducible/non-inducible models (23.9?10.5 vs 16.5?6.8; Fig C). Our findings suggest the AFib substrate existed in 1/3 of patients at the time of ESUS; however, fibrosis burden alone is insufficient to predict AFib risk.Conclusion:This pilot study shows that it may be possible to stratify AFib risk in ESUS patients via computational modeling. Long term follow-up in this small cohort is ongoing and will determine whether the models? predictions are correct. If successful, this work will lead to a higher proportion of at-risk ESUS patients receiving prophylactic treatment for AFib, which is a dramatic shift away from the current ?wait-and-see? paradigm. |
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