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与压力导丝衍生的血流储备分数相比,血管造影衍生的血流储备分数的诊断性能:MPFFR关键试验的原理与设计

Diagnostic performance of angiography-derived fractional flow reserve compared to pressure wire-derived fractional flow reserve: Rationale and design of MPFFR pivotal trial.

作者信息

Chu Hyun-Wook, Yoon Chang-Hwan, Han Donghoon, Seo Won-Woo, Park Sang-Don, Doh Joon Hyung, Nam Chang-Wook, Shin Eun-Seok, Koo Bon-Kwon, Chae In-Ho, Youn Tae-Jin

机构信息

Department of Internal Medicine, Seoul National University College of Medicine and Cardiovascular Center, Seoul National University Bundang Hospital, Seongnam, South Korea; Department of Internal Medicine, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul, South Korea.

Department of Internal Medicine, Seoul National University College of Medicine and Cardiovascular Center, Seoul National University Bundang Hospital, Seongnam, South Korea.

出版信息

Cardiovasc Revasc Med. 2025 Aug;77:56-60. doi: 10.1016/j.carrev.2024.09.015. Epub 2024 Sep 24.

Abstract

BACKGROUND

Cardiovascular disease remains the leading cause of death and the use of percutaneous coronary intervention (PCI) is steadily increasing. Current guidelines advocate the use of the fractional flow reserve (FFR) to assess coronary stenosis and treatment strategies; however, invasive FFR has some limitations. Angiography-derived FFR is a potential alternative for calculating FFR from two-dimensional (2D) angiographic images, thereby reducing invasiveness and complications. A novel artificial intelligence (AI)-based angiography-derived FFR, named "MPFFR," offers automated operator-independent hemodynamic calculations; this phase 3 trial aims to validate its diagnostic performance against 2D-quantitative coronary angiography (QCA).

METHODS AND ANALYSIS

This pivotal MPFFR trial is a prospective, multicenter, single-blind study. This trial involves patients with coronary artery disease (CAD) from eight cardiovascular centers. Invasive FFR will be performed according to standard guidelines and defined as the reference standard. Angiography-derived FFR will be computed using a proprietary method and 2D-QCA will be performed using validated software. The primary endpoint is the area under the curve for identifying physiologically significant coronary stenosis (FFR ≤0.80), with secondary endpoints including diagnostic accuracy, sensitivity, specificity, positive predictive value, negative predictive value, and correlations between angiography-derived and invasive FFR. This study is designed to demonstrate the superiority of angiography-derived FFR over 2D-QCA and is powered to achieve this with a sample size of 240 patients. Medipixel Inc. supports the trial and is not involved in the data analysis or management.

摘要

背景

心血管疾病仍然是主要的死亡原因,经皮冠状动脉介入治疗(PCI)的使用正在稳步增加。当前指南提倡使用血流储备分数(FFR)来评估冠状动脉狭窄和治疗策略;然而,有创FFR存在一些局限性。基于血管造影的FFR是一种从二维(2D)血管造影图像计算FFR的潜在替代方法,从而减少侵入性和并发症。一种名为“MPFFR”的基于人工智能(AI)的新型血管造影衍生FFR提供了独立于操作者的自动血流动力学计算;这项3期试验旨在验证其相对于二维定量冠状动脉造影(QCA)的诊断性能。

方法与分析

这项关键的MPFFR试验是一项前瞻性、多中心、单盲研究。该试验纳入了来自八个心血管中心的冠状动脉疾病(CAD)患者。有创FFR将根据标准指南进行,并被定义为参考标准。基于血管造影的FFR将使用专有方法计算,2D-QCA将使用经过验证的软件进行。主要终点是识别具有生理意义的冠状动脉狭窄(FFR≤0.80)的曲线下面积,次要终点包括诊断准确性、敏感性、特异性、阳性预测值、阴性预测值以及基于血管造影的FFR与有创FFR之间的相关性。本研究旨在证明基于血管造影的FFR优于2D-QCA,并通过240例患者的样本量来实现这一目标。Medipixel公司支持该试验,但不参与数据分析或管理。

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