Impact of Computational Modeling on Transcatheter Left Atrial Appendage Closure Efficiency and Outcomes

Ole De Backer; Xavier Iriart; Joelle Kefer; Jens Erik Nielsen-Kudsk; Adel Aminian; Liesbeth Rosseel; Klaus Fuglsang Kofoed; Jacob Odenstedt; Sergio Berti; Jacqueline Saw; Lars Søndergaard; Philippe Garot

doi:10.1016/j.jcin.2023.01.008

Impact of Computational Modeling on Transcatheter Left Atrial Appendage Closure Efficiency and Outcomes

JACC Cardiovasc Interv. 2023 Mar 27;16(6):655-666. doi: 10.1016/j.jcin.2023.01.008. Epub 2023 Feb 22.

Authors

Affiliations

¹ Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark. Electronic address: ole.debacker@gmail.com.
² Bordeaux University Hospital, Fondation Bordeaux Université, Bordeaux, France.
³ Cliniques Universitaires Saint-Luc, Brussels, Belgium.
⁴ Aarhus University Hospital, Aarhus, Denmark.
⁵ Centre Hospitalier Universitaire de Charleroi, Charleroi, Belgium.
⁶ Algemeen Stedelijk Ziekenhuis, Aalst, Belgium.
⁷ Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark.
⁸ Sahlgrenska University Hospital, Gothenburg, Sweden.
⁹ Fondazione CNR Regione Toscana, Massa, Italy.
¹⁰ Vancouver General Hospital, Vancouver, British Columbia, Canada.
¹¹ Hôpital Jacques Cartier, Institut Cardiovasculaire Paris Sud, Ramsay-Santé, Massy, France.

PMID: 36990554
DOI: 10.1016/j.jcin.2023.01.008

Abstract

Background: When performing transcatheter left atrial appendage (LAA) closure, peridevice leaks and device-related thrombus (DRT) have been associated with worse clinical outcomes-hence, their risk should be mitigated.

Objectives: The authors sought to assess whether use of preprocedural computational modeling impacts procedural efficiency and outcomes of transcatheter LAA closure.

Methods: The PREDICT-LAA trial (NCT04180605) is a prospective, multicenter, randomized trial in which 200 patients were 1:1 randomized to standard planning vs cardiac computed tomography (CT) simulation-based planning of LAA closure with Amplatzer Amulet. The artificial intelligence-enabled CT-based anatomical analyses and computer simulations were provided by FEops (Belgium).

Results: All patients had a preprocedural cardiac CT, 197 patients underwent LAA closure, and 181 of these patients had a postprocedural CT scan (standard, n = 91; CT + simulation, n = 90). The composite primary endpoint, defined as contrast leakage distal of the Amulet lobe and/or presence of DRT, was observed in 41.8% in the standard group vs 28.9% in the CT + simulation group (relative risk [RR]: 0.69; 95% CI: 0.46-1.04; P = 0.08). Complete LAA closure with no residual leak and no disc retraction into the LAA was observed in 44.0% vs 61.1%, respectively (RR: 1.44; 95% CI: 1.05-1.98; P = 0.03). In addition, use of computer simulations resulted in improved procedural efficiency with use of fewer Amulet devices (103 vs 118; P < 0.001) and fewer device repositionings (104 vs 195; P < 0.001) in the CT + simulation group.

Conclusions: The PREDICT-LAA trial demonstrates the possible added value of artificial intelligence-enabled, CT-based computational modeling when planning for transcatheter LAA closure, leading to improved procedural efficiency and a trend toward better procedural outcomes.

Keywords: cardiac computed tomography; computational modeling; left atrial appendage closure; randomized controlled trial; simulations.

Publication types

Randomized Controlled Trial
Multicenter Study
Research Support, Non-U.S. Gov't

MeSH terms

Artificial Intelligence
Atrial Appendage* / diagnostic imaging
Atrial Fibrillation*
Cardiac Catheterization / adverse effects
Computer Simulation
Echocardiography, Transesophageal
Humans
Prospective Studies
Treatment Outcome

Associated data

ClinicalTrials.gov/NCT04180605