Left atrial appendage closure guided by fusion of 3D computational modelling on real-time fluoroscopy: A multicenter experience.

Artificial intelligence Computational modelling Digital twin Image fusion Left atrial appendage closure

Journal

International journal of cardiology
ISSN: 1874-1754
Titre abrégé: Int J Cardiol
Pays: Netherlands
ID NLM: 8200291

Informations de publication

Date de publication:
10 Oct 2024
Historique:
received: 12 08 2024
revised: 25 09 2024
accepted: 02 10 2024
medline: 13 10 2024
pubmed: 13 10 2024
entrez: 12 10 2024
Statut: aheadofprint

Résumé

Patient-specific 3-dimensional (3D) computational modelling offers a tailored approach with promising results, but experience using digital-twin fusion on real-time fluoroscopy to guide left atrial appendage closure (LAAC) is unreported. To assess whether LAAC guided by fusion of a 3D computational model on real-time fluoroscopy is safe and effective. We included retrospectively through a multicenter registry all consecutive patients with non-valvular atrial fibrillation (AF) who underwent LAAC guided by artificial intelligence (AI)-enabled computer simulations (FEops, Gent, Belgium) fusion with real-time fluoroscopy. Operators selected the appropriate device size and position in relation to the LAA using FEops HEARTguide™, and a digital twin was provided for image fusion. The primary efficacy endpoint was successful LAAC with the use of a single device, without moderate or greater peri-device leak and/or device related thrombus (DRT) on follow-up imaging. The primary safety endpoint was a composite of major procedural complications including tamponade, stroke, systemic embolism, major bleeding, and device embolization. A total of 106 patients underwent LAAC with an Amulet™ or Watchman FLX™ device using CT-model-fluoroscopy fusion imaging. Device implantation was successful in 100 % of cases. The primary efficacy endpoint was met in 82 patients (89 %). A single-device deployment LAAC procedure was observed in 49 cases (46 %). The primary safety endpoint occurred in 2 patients (1.9 %). After a median follow-up of 405 days, two patients suffered an ischemic stroke and four expired. Fusion of a CT-based 3D computational model on real-time fluoroscopy is a safe and effective approach that may optimize transcatheter LAAC outcomes.

Sections du résumé

BACKGROUND BACKGROUND
Patient-specific 3-dimensional (3D) computational modelling offers a tailored approach with promising results, but experience using digital-twin fusion on real-time fluoroscopy to guide left atrial appendage closure (LAAC) is unreported.
OBJECTIVES OBJECTIVE
To assess whether LAAC guided by fusion of a 3D computational model on real-time fluoroscopy is safe and effective.
METHODS METHODS
We included retrospectively through a multicenter registry all consecutive patients with non-valvular atrial fibrillation (AF) who underwent LAAC guided by artificial intelligence (AI)-enabled computer simulations (FEops, Gent, Belgium) fusion with real-time fluoroscopy. Operators selected the appropriate device size and position in relation to the LAA using FEops HEARTguide™, and a digital twin was provided for image fusion. The primary efficacy endpoint was successful LAAC with the use of a single device, without moderate or greater peri-device leak and/or device related thrombus (DRT) on follow-up imaging. The primary safety endpoint was a composite of major procedural complications including tamponade, stroke, systemic embolism, major bleeding, and device embolization.
RESULTS RESULTS
A total of 106 patients underwent LAAC with an Amulet™ or Watchman FLX™ device using CT-model-fluoroscopy fusion imaging. Device implantation was successful in 100 % of cases. The primary efficacy endpoint was met in 82 patients (89 %). A single-device deployment LAAC procedure was observed in 49 cases (46 %). The primary safety endpoint occurred in 2 patients (1.9 %). After a median follow-up of 405 days, two patients suffered an ischemic stroke and four expired.
CONCLUSIONS CONCLUSIONS
Fusion of a CT-based 3D computational model on real-time fluoroscopy is a safe and effective approach that may optimize transcatheter LAAC outcomes.

Identifiants

pubmed: 39395724
pii: S0167-5273(24)01236-1
doi: 10.1016/j.ijcard.2024.132614
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

132614

Informations de copyright

Copyright © 2024. Published by Elsevier B.V.

Déclaration de conflit d'intérêts

Declaration of competing interest P. Garot is medical director and shareholder of CERC, a CRO dedicated to cardiovascular research. He is proctor for Abbott and has received Advisory/speaker's fees from Abbott, Biosensors, Boston Scientific, Cordis, GE Healthcare, and Terumo outside the submitted work. C. Skurk has received speakers fees from Abiomed and Boston Scientific. A. Gautier has received consulting fees from Abbott, Boston Scientific, GE HealthCare, Medtronic and Terumo outside the submitted work. A.M. Bavo is an employee of FEops. R. Vaillant is an employee of General Electric HealthCare. J. Horvilleur is proctor for Abbott. X. Freixa is proctor for Abbott, Boston Scientific and Lifetech Medical. J. Saw is Consultant and Proctor for Abbott and Boston Scientific. O. De Backer has received institutional research grants and consulting fees from Abbott and Boston Scientific. The other co-authors have nothing to disclose.

Auteurs

Philippe Garot (P)

Institut Cardiovasculaire Paris Sud (ICPS), Hôpital Jacques Cartier, Ramsay-Santé, Massy, France. Electronic address: p.garot@angio-icps.com.

Emmanuel Gall (E)

Institut Cardiovasculaire Paris Sud (ICPS), Hôpital Jacques Cartier, Ramsay-Santé, Massy, France; Université Paris-Cité, Department of Cardiology, University Hospital of Lariboisiere, (Assistance Publique des Hôpitaux de Paris, AP-HP), 75010 Paris, France; Inserm MASCOT - UMRS 942, University Hospital of Lariboisiere, 75010 Paris, France; MIRACL.ai laboratory, Multimodality Imaging for Research and Artificial Intelligence Core Laboratory, University Hospital of Lariboisiere (AP-HP), 75010 Paris, France.

Sandra Zendjebil (S)

Institut Cardiovasculaire Paris Sud (ICPS), Hôpital Jacques Cartier, Ramsay-Santé, Massy, France.

Pedro Cepas-Guillén (P)

Institut Clínic Cardiovascular, Hospital Clínic, Barcelona, Spain.

Xavier Iriart (X)

Department of Pediatric and Adult Congenital Cardiology, Hôpital Cardiologique du Haut-Lévêque, CHU de Bordeaux, Bordeaux-Pessac, France.

Bruno Farah (B)

Clinique Pasteur, Toulouse, France.

Carsten Skurk (C)

Deutches Herzzentrum des Charite (DHZC), Department of Cardiology, Angiology and Intensive Care Medicine, Campus Benjamin Franklin, Berlin, Germany.

Alexandre Gautier (A)

Institut Cardiovasculaire Paris Sud (ICPS), Hôpital Jacques Cartier, Ramsay-Santé, Massy, France.

Cheuk Bong Ho (CB)

Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.

Alessandra M Bavo (AM)

FEops NV, Ghent, Belgium.

Régis Vaillant (R)

General Electric Healthcare, Buc, France.

Jérôme Horvilleur (J)

Institut Cardiovasculaire Paris Sud (ICPS), Hôpital Jacques Cartier, Ramsay-Santé, Massy, France.

Xavier Freixa (X)

Institut Clínic Cardiovascular, Hospital Clínic, Barcelona, Spain.

Jacqueline Saw (J)

Division of Cardiology, Vancouver General Hospital, Vancouver, British Columbia, Canada.

Ole de Backer (O)

Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.

Classifications MeSH