Arrhythmogenic vulnerability of re-entrant pathways in post-infarct ventricular tachycardia assessed by advanced computational modelling.


Journal

Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology
ISSN: 1532-2092
Titre abrégé: Europace
Pays: England
ID NLM: 100883649

Informations de publication

Date de publication:
02 08 2023
Historique:
received: 10 03 2023
accepted: 21 06 2023
medline: 7 9 2023
pubmed: 8 7 2023
entrez: 8 7 2023
Statut: ppublish

Résumé

Substrate assessment of scar-mediated ventricular tachycardia (VT) is frequently performed using late gadolinium enhancement (LGE) images. Although this provides structural information about critical pathways through the scar, assessing the vulnerability of these pathways for sustaining VT is not possible with imaging alone.This study evaluated the performance of a novel automated re-entrant pathway finding algorithm to non-invasively predict VT circuit and inducibility. Twenty post-infarct VT-ablation patients were included for retrospective analysis. Commercially available software (ADAS3D left ventricular) was used to generate scar maps from 2D-LGE images using the default 40-60 pixel-signal-intensity (PSI) threshold. In addition, algorithm sensitivity for altered thresholds was explored using PSI 45-55, 35-65, and 30-70. Simulations were performed on the Virtual Induction and Treatment of Arrhythmias (VITA) framework to identify potential sites of block and assess their vulnerability depending on the automatically computed round-trip-time (RTT). Metrics, indicative of substrate complexity, were correlated with VT-recurrence during follow-up. Total VTs (85 ± 43 vs. 42 ± 27) and unique VTs (9 ± 4 vs. 5 ± 4) were significantly higher in patients with- compared to patients without recurrence, and were predictive of recurrence with area under the curve of 0.820 and 0.770, respectively. VITA was robust to scar threshold variations with no significant impact on total and unique VTs, and mean RTT between the four models. Simulation metrics derived from PSI 45-55 model had the highest number of parameters predictive for post-ablation VT-recurrence. Advanced computational metrics can non-invasively and robustly assess VT substrate complexity, which may aid personalized clinical planning and decision-making in the treatment of post-infarction VT.

Identifiants

pubmed: 37421339
pii: 7221521
doi: 10.1093/europace/euad198
pmc: PMC10481251
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : British Heart Foundation
ID : PG/18/74/34077
Pays : United Kingdom

Commentaires et corrections

Type : CommentIn

Informations de copyright

© The Author(s) 2023. Published by Oxford University Press on behalf of the European Society of Cardiology.

Déclaration de conflit d'intérêts

Conflict of interest: None declared.

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Auteurs

Pranav Bhagirath (P)

School of Biomedical Engineering and Imaging Sciences, King's College London, 4th Floor, Lambeth Wing, St. Thomas' Hospital, London SE1 7EH, UK.
Department of Cardiology, St Thomas' Hospital, London SE1 7EH, UK.

Fernando O Campos (FO)

School of Biomedical Engineering and Imaging Sciences, King's College London, 4th Floor, Lambeth Wing, St. Thomas' Hospital, London SE1 7EH, UK.

Pieter Postema (P)

Department of Cardiology, Amsterdam University Medical Center, Amsterdam, the Netherlands.

Michiel J B Kemme (MJB)

Department of Cardiology, Amsterdam University Medical Center, Amsterdam, the Netherlands.

Arthur A M Wilde (AAM)

Department of Cardiology, Amsterdam University Medical Center, Amsterdam, the Netherlands.

Anton J Prassl (AJ)

Gottfried Schatz Research Center, Division of Biophysics, Medical University of Graz, Graz, Austria.

Aurel Neic (A)

Gottfried Schatz Research Center, Division of Biophysics, Medical University of Graz, Graz, Austria.

Christopher A Rinaldi (CA)

Department of Cardiology, St Thomas' Hospital, London SE1 7EH, UK.

Marco J W Götte (MJW)

Department of Cardiology, Amsterdam University Medical Center, Amsterdam, the Netherlands.

Gernot Plank (G)

Gottfried Schatz Research Center, Division of Biophysics, Medical University of Graz, Graz, Austria.

Martin J Bishop (MJ)

School of Biomedical Engineering and Imaging Sciences, King's College London, 4th Floor, Lambeth Wing, St. Thomas' Hospital, London SE1 7EH, UK.

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Classifications MeSH