Identifying locations susceptible to micro-anatomical reentry using a spatial network representation of atrial fibre maps.
Micro-anatomical reentry has been identified as a potential driver of atrial fibrillation (AF). In this paper, we introduce a novel computational method which aims to identify which atrial regions are most susceptible to micro-reentry. The approach, which considers the structural basis for micro-ree...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2022-01-01
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| Series: | PLoS ONE |
| Online Access: | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0267166&type=printable |
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| author | Max Falkenberg James A Coleman Sam Dobson David J Hickey Louie Terrill Alberto Ciacci Belvin Thomas Arunashis Sau Fu Siong Ng Jichao Zhao Nicholas S Peters Kim Christensen |
| author_facet | Max Falkenberg James A Coleman Sam Dobson David J Hickey Louie Terrill Alberto Ciacci Belvin Thomas Arunashis Sau Fu Siong Ng Jichao Zhao Nicholas S Peters Kim Christensen |
| author_sort | Max Falkenberg |
| collection | DOAJ |
| description | Micro-anatomical reentry has been identified as a potential driver of atrial fibrillation (AF). In this paper, we introduce a novel computational method which aims to identify which atrial regions are most susceptible to micro-reentry. The approach, which considers the structural basis for micro-reentry only, is based on the premise that the accumulation of electrically insulating interstitial fibrosis can be modelled by simulating percolation-like phenomena on spatial networks. Our results suggest that at high coupling, where micro-reentry is rare, the micro-reentrant substrate is highly clustered in areas where the atrial walls are thin and have convex wall morphology, likely facilitating localised treatment via ablation. However, as transverse connections between fibres are removed, mimicking the accumulation of interstitial fibrosis, the substrate becomes less spatially clustered, and the bias to forming in thin, convex regions of the atria is reduced, possibly restricting the efficacy of localised ablation. Comparing our algorithm on image-based models with and without atrial fibre structure, we find that strong longitudinal fibre coupling can suppress the micro-reentrant substrate, whereas regions with disordered fibre orientations have an enhanced risk of micro-reentry. With further development, these methods may be useful for modelling the temporal development of the fibrotic substrate on an individualised basis. |
| format | Article |
| id | doaj-art-fd6fc27dec4648d6a4af524501e6cbf4 |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-fd6fc27dec4648d6a4af524501e6cbf42025-08-20T03:46:21ZengPublic Library of Science (PLoS)PLoS ONE1932-62032022-01-01176e026716610.1371/journal.pone.0267166Identifying locations susceptible to micro-anatomical reentry using a spatial network representation of atrial fibre maps.Max FalkenbergJames A ColemanSam DobsonDavid J HickeyLouie TerrillAlberto CiacciBelvin ThomasArunashis SauFu Siong NgJichao ZhaoNicholas S PetersKim ChristensenMicro-anatomical reentry has been identified as a potential driver of atrial fibrillation (AF). In this paper, we introduce a novel computational method which aims to identify which atrial regions are most susceptible to micro-reentry. The approach, which considers the structural basis for micro-reentry only, is based on the premise that the accumulation of electrically insulating interstitial fibrosis can be modelled by simulating percolation-like phenomena on spatial networks. Our results suggest that at high coupling, where micro-reentry is rare, the micro-reentrant substrate is highly clustered in areas where the atrial walls are thin and have convex wall morphology, likely facilitating localised treatment via ablation. However, as transverse connections between fibres are removed, mimicking the accumulation of interstitial fibrosis, the substrate becomes less spatially clustered, and the bias to forming in thin, convex regions of the atria is reduced, possibly restricting the efficacy of localised ablation. Comparing our algorithm on image-based models with and without atrial fibre structure, we find that strong longitudinal fibre coupling can suppress the micro-reentrant substrate, whereas regions with disordered fibre orientations have an enhanced risk of micro-reentry. With further development, these methods may be useful for modelling the temporal development of the fibrotic substrate on an individualised basis.https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0267166&type=printable |
| spellingShingle | Max Falkenberg James A Coleman Sam Dobson David J Hickey Louie Terrill Alberto Ciacci Belvin Thomas Arunashis Sau Fu Siong Ng Jichao Zhao Nicholas S Peters Kim Christensen Identifying locations susceptible to micro-anatomical reentry using a spatial network representation of atrial fibre maps. PLoS ONE |
| title | Identifying locations susceptible to micro-anatomical reentry using a spatial network representation of atrial fibre maps. |
| title_full | Identifying locations susceptible to micro-anatomical reentry using a spatial network representation of atrial fibre maps. |
| title_fullStr | Identifying locations susceptible to micro-anatomical reentry using a spatial network representation of atrial fibre maps. |
| title_full_unstemmed | Identifying locations susceptible to micro-anatomical reentry using a spatial network representation of atrial fibre maps. |
| title_short | Identifying locations susceptible to micro-anatomical reentry using a spatial network representation of atrial fibre maps. |
| title_sort | identifying locations susceptible to micro anatomical reentry using a spatial network representation of atrial fibre maps |
| url | https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0267166&type=printable |
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