Post-PCI outcomes predicted by pre-intervention simulation of residual quantitative flow ratio using augmented reality

Abstract

Background: The simulated residual quantitative flow ratio (QFR) computed from pre-intervention three-dimensional (3-D) coronary angiograms, which could theoretically predict actual post-percutaneous coronary intervention (PCI) QFR value, can be used for enhanced PCI via augmented reality. The study sought to investigate the concordance between simulated residual QFR and actual post-PCI QFR, and the prognostic value of simulated residual QFR.

Methods: QFR assessment was retrospectively performed in treated vessels from the all-comers PANDA III trial. Three-step analysis was performed: 1) concordance between simulated residual QFR and post-PCI QFR; 2) prognostic value of simulated residual QFR; and 3) forecast of outcomes by virtual randomized controlled trials (RCTs) between residual QFR and angiographic guidance.

Results: Of 2989 treated vessels, 2146 (71.8%) with paired analyzable simulated residual QFR and post-PCI QFR were included. The simulated residual QFR and post-PCI QFR were strongly correlated (r = 0.976). Low simulated residual QFR (≤0.92) was independently associated with higher risk of 2-year vessel-oriented composite endpoint (adjusted hazard ratio: 5.50; 95% confidence interval: 3.03 to 10.0). Based upon 5000 iterations of virtual RCTs, simulated residual QFR-guided strategy was anticipated to have a 2.6% absolute reduction of 2-year incidence of target vessel failure compared with the angiography-guided strategy.

Conclusions: With high consistency to actual post-PCI QFR, the simulated residual QFR computed from pre-PCI 3-D coronary angiograms and augmented reality could predict functional outcome of the procedure and 2-year prognosis. Using data from PANDA III trial, the present study forecasted superiority of residual QFR-guided PCI strategy over angiographic guidance. Clinical Trial Registration Information URL: https://www.clinicaltrials.gov; Unique identifier: NCT02017275.

Keywords: Augmented reality; Clinical outcomes; Coronary artery disease; Percutaneous coronary intervention; Physiology assessment.