基于人工智能的全自动定量冠状动脉造影与光学相干断层扫描引导的经皮冠状动脉介入治疗：FLASH试验
Artificial Intelligence-Based Fully Automated Quantitative Coronary Angiography vs Optical Coherence Tomography-Guided PCI: The FLASH Trial.
作者信息
Kim Yongcheol, Yoon Hyuck-Jun, Suh Jon, Kang Si-Hyuck, Lim Young-Hyo, Jang Duck Hyun, Park Jae Hyoung, Shin Eun-Seok, Bae Jang-Whan, Lee Jang Hoon, Oh Jun-Hyok, Kang Do-Yoon, Kweon Jihoon, Jo Min-Woo, Yun Sung-Cheol, Park Duk-Woo, Kim Young-Hak, Park Seung-Jung, Park Hanbit, Ahn Jung-Min
机构信息
Yonsei University College of Medicine and Cardiovascular Center, Yongin Severance Hospital, Yongin, Korea.
Division of Cardiology, Department of Internal Medicine, Keimyung University Dongsan Hospital, Daegu, Korea.
出版信息
JACC Cardiovasc Interv. 2025 Jan 27;18(2):187-197. doi: 10.1016/j.jcin.2024.10.025. Epub 2024 Oct 30.
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.
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 in the AI-QCA group and 6.2 ± 2.2 mm 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).
背景
最近开发的基于人工智能的冠状动脉造影（AI-QCA，全自动）可对冠状动脉造影进行实时、客观且可重复的定量分析，无需额外的时间或人力。
目的
本研究旨在比较AI-QCA辅助的经皮冠状动脉介入治疗（PCI）与光学相干断层扫描（OCT）引导的PCI在PCI术后结果方面的疗效。
方法
本试验纳入了来自韩国13个参与中心的400例接受PCI的严重冠状动脉疾病患者。患者按1:1比例随机分为AI-QCA辅助PCI组或OCT引导PCI组。主要终点是通过OCT评估的PCI术后最小支架面积（MSA）。以0.8mm的非劣效界值检验AI-QCA辅助PCI在PCI术后MSA方面相对于OCT引导PCI的非劣效性。
结果
共有395例患者（AI-QCA组199例，OCT组196例）纳入主要终点分析。AI-QCA组PCI术后MSA为6.3±2.2mm，OCT组为6.2±2.2mm（差异为-0.16；95%CI：-0.59至0.28；非劣效性P<0.001）。其他OCT定义的终点，如支架扩张不足（50.8%[101/199]对54.6%[107/196]；P=0.48）、夹层（15.6%[31/199]对12.8%[25/196]；P=0.42）和未治疗的参考节段病变（15.1%[30/199]对13.3%[26/196]；P=0.61），两组间无显著差异，但AI-QCA组支架贴壁不良的发生率较高（13.6%[27/199]对5.6%[11/196]；P=0.007）。
结论
本研究表明，在实现MSA以及具有可比的OCT定义终点方面，AI-QCA辅助PCI不劣于OCT引导PCI。（冠状动脉支架植入的全自动定量冠状动脉造影与光学相干断层扫描引导[FLASH]；NCT05388357）
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