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

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