The DOI matches its Crossref record; 61 of the 61 references it cites were found in a registry or an index.
Computationally guided personalized targeted ablation of persistent atrial fibrillation
Open accessAbstract
Atrial fibrillation (AF)—the most common arrhythmia—significantly increases the risk of stroke and heart failure. Although catheter ablation can restore normal heart rhythms, patients with persistent AF who develop atrial fibrosis often undergo multiple failed ablations, and thus increased procedural risks. Here, we present personalized computational modelling for the reliable predetermination of ablation targets, which are then used to guide the ablation procedure in patients with persistent AF and atrial fibrosis. First, we show that a computational model of the atria of patients identifies fibrotic tissue that, if ablated, will not sustain AF. Then, we report the results of integrating the target ablation sites in a clinical mapping system and testing its feasibility in ten patients with persistent AF. The computational prediction of ablation targets avoids lengthy electrical mapping and could improve the accuracy and efficacy of targeted AF ablation in patients while eliminating the need for repeat procedures. Personalized computational modelling can reliably predetermine ablation targets in patients with persistent atrial fibrillation and atrial fibrosis.
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Self-citationCalkins, H., Kuck, K. H., Cappato, R., Brugada, J., Camm, A. J., Chen, S.-A., Crijns, H. J. G., Damiano, R. J., Davies, D. W., DiMarco, J., et al. (2012) · Europace · doi:10.1093/europace/eus027 · Cited by 2,722
Self-citationApproaches to catheter ablation for persistent atrial fibrillation
Verma, A., Jiang, C.-Y., Betts, T. R., Chen, J., Deisenhofer, I., Mantovan, R., Macle, L., Morillo, C. A., Haverkamp, W., Weerasooriya, R., et al. (2015) · New England Journal of Medicine · doi:10.1056/nejmoa1408288 · Cited by 2,339
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Promotion of Atrial Fibrillation by Heart Failure in Dogs: Atrial Remodeling of a Different Sort
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Atrial Remodeling and Atrial Fibrillation: Mechanisms and Implications
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Cited by
Next-generation tissue-engineered heart valves with repair, remodelling and regeneration capacity
Fioretta, E. S., Motta, S. E., Lintas, V., Loerakker, S., Parker, K. K., Baaijens, F. P. T., Falk, V., Hoerstrup, S. P., & Emmert, M. Y. (2021) · Nature Reviews Cardiology · doi:10.1038/s41569-020-0422-8 · Cited by 262
How will machine learning inform the clinical care of atrial fibrillation?
Siontis, K. C., Yao, X., Pirruccello, J. P., Philippakis, A. A., & Noseworthy, P. A. (2020) · Circulation Research · doi:10.1161/circresaha.120.316401 · Cited by 61
Galappaththige, S., Gray, R. A., Costa, C. M., Niederer, S., & Pathmanathan, P. (2022) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1010541 · Cited by 45
Metadata
- Authors
- Boyle, P. M., Zghaib, T., Zahid, S., Ali, R. L., Deng, D., Franceschi, W. H., Hakim, J. B., Murphy, M. J., Prakosa, A., Zimmerman, S. L., Ashikaga, H., Marine, J. E., Kolandaivelu, A., Nazarian, S., Spragg, D. D., Calkins, H., & Trayanova, N. A.
- Venue
- Nature Biomedical Engineering
- Published
- 2019-08-19
- Volume
- 3
- Issue
- 11
- Pages
- 870-879
- ISSN
- 2157-846X (ISSN-L)
- OpenAlex
- W2969852609
- Cited by
- 312
- References
- 61
- FWCI
- 21.03
- Type
- journal article
- Language
- en
- Open access
- green
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- Boyle, P. M., Zghaib, T., Zahid, S., Ali, R. L., Deng, D., Franceschi, W. H., Hakim, J. B., Murphy, M. J., Prakosa, A., Zimmerman, S. L., Ashikaga, H., Marine, J. E., Kolandaivelu, A., Nazarian, S., Spragg, D. D., Calkins, H., & Trayanova, N. A. (2019). Computationally guided personalized targeted ablation of persistent atrial fibrillation. Nature Biomedical Engineering. https://doi.org/10.1038/s41551-019-0437-9
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