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dc.contributor.advisor2023 Computing in Cardiology (CinC)
dc.contributor.authorJaffery, OAen_US
dc.contributor.authorHorrach, CVen_US
dc.contributor.authorLagalante, DJen_US
dc.contributor.authorThomas, Gen_US
dc.contributor.authorSlabaugh, Gen_US
dc.contributor.authorMelki, Len_US
dc.contributor.authorGood, WWen_US
dc.contributor.authorRoney, CHen_US
dc.date.accessioned2024-02-02T12:00:56Z
dc.date.issued2023-01-01en_US
dc.identifier.isbn9798350382525en_US
dc.identifier.issn2325-8861en_US
dc.identifier.urihttps://qmro.qmul.ac.uk/xmlui/handle/123456789/94421
dc.description.abstractImproving patient outcomes with ablation of non-paroxysmal AF (PsAF) has proved challenging using a population-based treatment approach due to large interindividual variability in the underlying electroanatomical substrate. Ablation of pathologic conduction patterns outside of pulmonary vein isolation (PVI) has recently shown encouraging results in PsAF patients returning for their first or second retreatment (76% freedom from AF recorded in the RECOVER AF trial). However, the optimal targets and best sequence of ablation lesions are still unknown, and testing different sequences, types, and methods of ablation cannot be performed clinically on a single patient or patient cohort. Considering the predictive potential of computational modelling, a small exploratory subset of patients (N=4) enrolled in the ongoing DISCOVER trial was used to create patient-specific models of left atrial electrophysiology. The subject-specific models displayed a high correlation between simulated targets and clinical targets. AF complexity was highest in all patients prior to therapy. PVI caused a marginal decrease in complexity across the cohort whereas PVI+PCP showed an extensive decrease in the AF complexity across the patients and resulted in AF termination in all patients.en_US
dc.rights© 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
dc.titleSubject-Specific Ablation of Pathologic Conduction Patterns Beyond the Pulmonary Veins: A Personalised Modelling Approachen_US
dc.typeConference Proceeding
dc.identifier.doi10.22489/CinC.2023.400en_US
pubs.notesNot knownen_US
pubs.publication-statusPublisheden_US
rioxxterms.funderDefault funderen_US
rioxxterms.identifier.projectDefault projecten_US
qmul.funderMapping populations to patients: designing optimal ablation therapy for atrial fibrillation through simulation and deep learning of digital twins::UK Research and Innovationen_US


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