Artificial Intelligence-Based Fully Automated Quantitative Coronary Angiography vs Optical Coherence Tomography-Guided PCI (FLASH Trial).

Background: Recently developed artificial intelligence-based coronary angiography (AI-QCA, fully automated) provides real-time, objective, and reproducible quantitative analysis of coronary angiography without requiring additional time or labor.
Objectives: This study aimed to evaluate the efficacy of AI-QCA-assisted percutaneous coronary intervention (PCI) compared to optical coherence tomography (OCT)-guided PCI in terms of post-PCI results.
Methods: This trial enrolled 400 patients with significant coronary artery disease undergoing PCI from 13 participating centers in South Korea. Patients were randomized in a 1:1 ratio to either AI-QCA-assisted or OCT-guided PCI. The primary endpoint was the post-PCI minimal stent area (MSA) assessed by OCT. The noninferiority of AI-QCA-assisted PCI to OCT-guided PCI regarding the post-PCI MSA was tested with a noninferiority margin of 0.8 mm ² .
Results: A total of 395 patients (199 in the AI-QCA group and 196 in the OCT group) were included in the primary endpoint analysis. The post-PCI MSA was 6.3 ± 2.2 mm ² in the AI-QCA group and 6.2 ± 2.2 mm ² in the OCT group (difference, -0.16; 95% CI: -0.59 to 0.28; P for noninferiority < 0.001). Other OCT-defined endpoints, such as stent underexpansion (50.8% [101/199] vs 54.6% [107/196]; P = 0.48), dissection (15.6% [31/199] vs 12.8% [25/196]; P = 0.42), and untreated reference segment disease (15.1% [30/199] vs 13.3% [26/196]; P = 0.61), were not significantly different between groups, except for a higher incidence of stent malapposition in the AI-QCA group (13.6% [27/199] vs 5.6 [11/196]; P = 0.007).
Conclusions: This study demonstrated the noninferiority of AI-QCA-assisted PCI to OCT-guided PCI in achieving MSA with comparable OCT-defined endpoints. (Fully Automated Quantitative Coronary Angiography Versus Optical Coherence Tomography Guidance for Coronary Stent Implantation [FLASH]; NCT05388357).
Competing Interests: Funding Support and Author Disclosures This work was supported by the Korea Medical Device Development Fund grant funded by the Korean government (the Ministry of Science and ICT, the Ministry of Trade, Industry and Energy, the Ministry of Health and Welfare, and the Ministry of Food and Drug Safety) (Project Number: 1711179379, RS-2022-00141289) and Medipixel, Inc. Dr Kang has received consulting fees from Medipixel, Inc; and owns stock options of Medipixel, Inc. Dr Kweon has received consulting fees and research grant support from Medipixel, Inc. Dr Y-H Kim has received consulting fees from Medipixel, Inc. Dr Ahn has received consulting fees from Medipixel, Inc. All other authors have reported that they have no relationships relevant to the contents of this paper to disclose.
(Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)