Advances in Clinical Medicine
Vol. 13  No. 11 ( 2023 ), Article ID: 75734 , 7 pages
10.12677/ACM.2023.13112551

冠状动脉CT血流储备分数研究进展

韩千程,温生宝*,王雪燕,王宇

青海大学附属医院影像中心,青海 西宁

收稿日期:2023年10月23日;录用日期:2023年11月15日;发布日期:2023年11月22日

摘要

血流储备分数值(Fractional flow reserve, FFR)是评价冠状动脉生理功能的金标准,但介入性有创操作限制了其在临床实践中的广泛应用。近些年来,已经开发出从冠状动脉CT血管成像(Coronary CT angiography, CCTA)中获取功能信息的新方法,即利用CCTA提供的解剖学信息与流体动力学算法相结合,从CCTA图像数据集中计算FFR。计算机断层扫描衍生的血流储备分数值(CT derived fractional flow reserve, CT-FFR)能够无创地识别病变生理特性,CT-FFR建模技术提供了整个冠状动脉树的FFR,同时CT-FFR与FFR的良好相关性有助于引导冠心病(Coronary artery disease, CAD)患者选择最佳治疗策略,并提高治疗预期。本文对国内外有关FFR检测方法及临床进展进行综述,旨在为相关人员提供参考借鉴。

关键词

冠心病,血流储备分数,冠状动脉CT血管成像,CT-FFR

Advances in Coronary CT Flow Reserve Fraction Studies

Qiancheng Han, Shengbao Wen*, Xueyan Wang, Yu Wang

Imaging Center of Qinghai University Affiliated Hospital, Xining Qinghai

Received: Oct. 23rd, 2023; accepted: Nov. 15th, 2023; published: Nov. 22nd, 2023

ABSTRACT

Fractional flow reserve (FFR) is the gold standard for evaluating the physiological function of coronary vessels, but its widespread use in clinical practice is limited by the invasive nature of the intervention. In recent years, new methods have been developed to obtain functional information from coronary CT angiography (CCTA). That is, the anatomical information provided by CCTA is used in combination with computational fluid dynamics to calculate FFR values from CCTA image datasets. Computed tomography-derived fractional flow reserve (CT-FFR) can identify the physiological characteristics of the lesion noninvasively, and CT-FFR modeling provides FFR values of the entire coronary tree, while the good correlation between CT-FFR and FFR can help guide the selection of patients with coronary artery disease (CAD) patients to choose the best treatment strategy and improve treatment expectations. In this paper, we review the FFR detection methods and clinical advances at home and abroad, aiming to provide reference for relevant personnel.

Keywords:Coronary Artery Disease, Fractional Flow Reserve, Coronary CT Angiography, CT-FFR

Copyright © 2023 by author(s) and Hans Publishers Inc.

This work is licensed under the Creative Commons Attribution International License (CC BY 4.0).

http://creativecommons.org/licenses/by/4.0/

1. 引言

在全球范围内,冠心病每年导致700多万人死亡,在235种单一死因中排名第一 [1] ,是世界上心血管疾病死亡的主要原因 [2] 。临床实践中常用的诊断冠心病的影像学方法包括:有创冠状动脉造影(Invasive coronary angiography, ICA)、CCTA、心肌灌注成像(CT myocardial perfusion, CTP)、正电子发射断层成像术(Positron emission tomography, PET)、单光子发射计算机断层成像术(Single-photon emission computed tomography, SPECT)等。CCTA可以识别冠状动脉狭窄,但对冠脉狭窄引起的功能性心肌缺血意义不大。CT-FFR可以无创地评估冠状动脉病变的血流动力学意义,并将冠状动脉狭窄的严重程度与其生理影响结合起来。自2011年首次证明在人类中使用的可行性以来,已经有大量的临床证据来评估冠状动脉CT-FFR与有创FFR参考标准的诊断效能 [3] 。利用ICA进行解剖与生理联合评估的FFR是目前确定冠状动脉狭窄是否导致缺血的金标准 [4] 。欧洲心脏病学会(ESC)指南强烈建议对冠状动脉功能病变的严重程度进行评估 [5] 。根据美国心脏病学会(ACC)/美国心脏协会(AHA)/心血管造影与介入学会(SCAI)关于冠状动脉血运重建的最新指南,生理评估对于评价冠脉严重程度的病变是必要的,并有助于指导血运重建决策(IIa级,A级) [6] 。FFR被认为是指导临床决策的诊断方法之一,用来确定哪些患者将受益于血运重建 [6] [7] 。FFR的侵入性、高成本以及使用血管扩张药物可能给患者带来不适,限制了其在常规临床诊断中的应用。通过CCTA获得的CT-FFR是血管成像领域的一项新技术,近年来已成为对冠状动脉病变进行无创性功能评估的有效方法 [8] ,CT-FFR基于CCTA数据与计算流体动力学(Computational fluid dynamics, CFD)相结合,是一种无创的、与FFR高度相关的、对冠状动脉解剖结构和功能变化的“一站式”评估。冠状动脉狭窄和心肌缺血之间的关系很复杂,在CAD患者中,冠状动脉造影识别狭窄程度与FFR检测到的缺血程度不匹配 [9] ,故评估冠状动脉的功能学及解剖学指标非常必要;CT-FFR是一种新兴的无创评估冠状动脉疾病的工具,它为临床医生提供了进一步的功能评价,为冠心病患者的决策提供有价值的信息。本文的目的是通过对CT-FFR现状进行回顾,并介绍其原理及应用。

2. 血流储备分数介绍

2.1. 有创血流储备分数

ICA时进行的FFR用于联合评估解剖病变与生理功能,是目前确定冠状动脉狭窄是否导致缺血的金标准 [4] 。1976年,Gould和Lipscomb描述了冠状动脉管腔直径与血流动力学之间的关系 [10] ,即从缺血角度分析病变,使用FFR诊断冠心病。FFR作为冠状动脉狭窄生理意义的精确指标,定义为狭窄动脉的最大血流量与正常静息血流的比值。结果表明,在怀疑有冠脉狭窄的病人中,FFR所提供的信息对于决定是否进行血运重建具有很高的参考价值。为了确定冠状动脉狭窄的功能意义,临床指南强调有创性FFR的作用,并认为它是一种可靠的诊断手段。根据2014 ESC/EACTS心肌血运重建指南 [7] ,有创性 FFR可以帮助医生确定冠状动脉狭窄的功能意义,以便制定更有效的治疗方案。FFR是在有创血管造影术中评估冠状动脉狭窄的生理意义的一种公认的工具。FFR测量在药物诱导的最大充血状态下,近端主动脉平均压力和狭窄远端冠状动脉平均压力的比值 [11] ,无冠状动脉狭窄时的压力应相等(FFR = 1.0)。

2.2. 无创血流储备分数

CT-FFR是一项由Taylor等 [3] 学者于2015年提出的新技术,可以无创评估冠状动脉狭窄导致血流动力学变化,可以提示狭窄的管腔是否会影响心肌异常灌注。CT-FFR为冠心病血流动力学研究提供了新的切入点。与侵入性FFR比较,CT-FFR属于无创技术,其不需要静脉注射腺苷,且有助于补充临床上CCTA发现的冠脉狭窄的血流动力学意义。CT-FFR一旦计算完成,就生成整个冠状动脉树到远端血管的血流储备分数值的3D图 [12] 。使用来自CCTA的解剖数据来估计整个冠状动脉狭窄的FFR,它基于心脏CT数据的流体动力学建模,使用先进的后处理和3D Navier-Stokes方程求解整个冠脉血管床的流量和压力测量,因此病变所导致的管腔两端的血流动力学变化能够以数值的形式表现出来。在多项研究中 [13] ,冠状动脉狭窄功能学意义的CT-FFR阈值均在0.75~0.80 [9] [14] [15] 。CT-FFR ≤ 0.75通常提示心肌缺血可能性大,而CT-FFR > 0.80一般不会导致心肌缺血,0.76~0.80之间的CT-FFR为“灰区” [16] [17] 。以血流储备分数作为参考标准,从标准冠状动脉CTA图像数据集中提取的血流储备分数在冠心病患者中显示出高诊断性能,为CAD的解剖评估提供高诊断灵敏度,为缺血提供高特异性 [18] 。因此,CT-FFR可以增强冠状动脉CTA作为导管介入术实验室看门人的潜力。

3. 血流储备分数的临床应用

3.1. CT-FFR的算法

CT-FFR的分析软件有几种类型:基于3D-CFD、降维CFD、机器学习算法和示踪剂动力学算法。在欧洲、亚洲和美国的5个中心,纳入了351例患者,包括525条血管进行有创FFR测量,对CTA数据进行机器学习算法和CFD算法。基于机器学习算法的CT-FFR通过正确地重新分类血流动力学上不显著的狭窄,提高了CTA的性能,并且与基于CFD的CT-FFR表现相同 [19] 。为了验证机器学习方法,在87名患者的研究中,机器学习方法模型与CFD进行了比较。这两种方法之间的相关性为0.9994 (P < 0.001) [20] 。在同一项研究中,机器学习方法与有创FFR进行了比较,使用有创性方法发现了总共38个有血流动力学意义的病变,定义为FFR ≤ 0.80,以此为金标准,基于机器学习的FFR的敏感性为81%,特异性为84%,准确性为83%。相关性也较强,为0.729 (P < 0.001) [20] 。杨琳等 [21] 基于动力学示踪算法的CT-FFR软件诊断冠脉心肌缺血的敏感性为92.4%,特异性为82.1%,阳性预测值为87.6%,阴性预测值为88.7%,ROC曲线下面积(Area under curve, AUC)为0.94。不同算法的CT-FFR软件在评估冠状动脉心肌缺血方面均有较高的诊断价值。

3.2. CT-FFR与其他检查方法对比

静息全周期比率(Resting Full-Cycle Ratio, RFR)是在冠脉狭窄功能性评价“金标准”的血流储备分数(FFR)基础上衍生而来。有研究 [22] 在验证基于流体结构相互作用的CT-FFR的总体可靠性,并评估其与CT-FFR、有创FFR和RFR的临床应用价值。计算了308例临床疑似冠状动脉疾病接受CCTA的924条冠状血管的CT-FFR,这些数据表明CT-FFR与侵袭性FFR和RFR密切相关,具有高度一致性。采用混合RFR-FFR策略提供了非常高的诊断率 [23] 。

与PET相比 [24] ,CT-FFR在血管水平上具有更好的诊断性能。与静态和动态腺苷应力灌注CT相比 [24] ,CT-FFR具有相当的诊断准确性 [25] [26] 。在CT-FFR与CCTA、SPECT和PET诊断缺血的对比研究中,CT-FFR在血管特异性缺血诊断方面的表现优于CCTA、SPECT和PET,此外CT-FFR还可以提供冠状动脉病变的解剖学和血流动力学价值 [24] 。

利用计算流体力学技术对CCTA数据进行CT-FFR分析。评估单光子发射计算机化断层显像心肌灌注显像(SPECT-MPI)缺血与CT-FFR的相关性(FFR ≤ 0.80)。在62例患者中,对186条血管进行了评估。在单血管分析中,SPECT-MPI预测CT-FFR ≤ 0.80的准确性、敏感性和特异性分别为74.2%、45.0%和77.7%。通过特征曲线分析SPECT-MPI的曲线下面积(AUC)对CT-FFR ≤ 0.80 (AUC 0.56)的预测表现中等。在非侵入性功能评估的疑似CAD患者中,SPECT-MPI显示与CT-FFR有一定的一致性 [27] 。

CT-FFR在冠状动脉钙化病变中的表现,这项前瞻性多中心试验CT-FFR中国试验结果支持CT-FFR作为评估冠状动脉钙化病变的可行工具。在所有钙化积分评分组中,以FFR < 0.80为临界值,CT-FFR基于患者和基于血管的诊断效能没有统计学意义上的差异,冠状动脉钙化对CT-FFR诊断效能没有显著影响 [28] 。

3.3. 冠心病患者临床应用结局的预测

CT-FFR显著提高了CCTA的诊断准确性,不需要额外的检查,同时减少了ICA患者的比例,用于诊断需要治疗的稳定的CAD [29] 。FAME试验发现,使用FFR < 0.8来指导经皮冠状动脉介入治疗与单纯血管造影术相比,在1年内,非致命性心肌梗塞、死亡及重复血管重构的发生率降低。心肌梗死和死亡率通过FFR策略显著减少 [30] [31] 。在FAME 2中,FFR < 0.80的患者有明显预后不良的趋势。因此,FFR现在被广泛用于检测心肌缺血并指导是否需要血管重建 [7] 。

已经使用CT-FFR进行了几项具有良好准确性的研究 [32] [33] [34] [35] [36] [37] 。使用HeartFlow平台进行的DISCOVER-FLOW、DEFACTO和NXT等试验表明,与传统CTA相比,CT-FFR的特异性显著提高(82% vs. 25%、54% vs. 42%、79% vs. 34%) [32] [33] [35] 。还有研究表明,CT-FFR的特异性优于单独的CTA (85% vs.32% 和 65% vs.38%) [34] 。CT-FFR分析提供了冠状动脉树所有位置的功能信息,增加了对临床决策有用的丰富信息。在临床实践中应用时,CT-FFR可以对所有适合血运重建的血管提供完整的解剖学和病变特异性缺血评估。当根据其预期用途进行评估时,CT-FFR的诊断准确性和鉴别能力有了显著提高。

支架置入和优化后,重新检查血流储备分数可确保血运重建的血流动力学指标。支架术后血流储备分数的提高(通常>0.90)带来了有利的长期结果,而支架术后持续的血流储备分数降低可能表明支架置入效果不理想,这正好可以进一步优化支架。血流储备分数的降低,可能提示支架扩张不足、支架贴壁不良、斑块脱落或血栓等临床问题 [38] [39] 。

3.4. CT-FFR在临床应用的局限性

尽管CT-FFR在CAD的诊断、治疗决策中具有重要作用,但在某些方面还有局限性。1) 对于有心肌梗死或冠状动脉旁路移植术(Coronary artery bypass grafting, CABG)病史的患者,CT-FFR诊断效能仍不清楚 [40] 。2) 由于CT-FFR来源于冠状动脉CTA成像数据,显著的CT成像伪影,如运动、低对比度或冠状动脉钙化引起的晕染,可能会降低其诊断性能。通过遵守冠状动脉CTA图像采集指南,特别是在图像采集前服用降心率药物和舌下硝酸盐,可以将这些问题发生率降至最低,此外,随着CT技术和CT-FFR分析过程的进一步改进可能会减少CT成像伪影的影响。3) 由于冠脉解剖变异导致心肌缺血的相互作用复杂,并且普通人群发病率低,目前缺少CT-FFR对于冠脉解剖变异之间相互关系的证据。4) 在发现有多发冠状动脉狭窄的CAD患者中,CT-FFR指导下的血运重建是安全的,研究表明 [41] ,尽管支撑文献较少,但稳定型CAD患者(多发狭窄及分叉处病变) CT-FFR可以指导临床的血运重建。CT-FFR技术的初步验证研究包括CCTA的中度狭窄患者(50%~70%),并且显示出良好的准确性和灵敏度,到目前为止,还没有一项试验专门评估CT-FFR在重度狭窄CAD中的诊断能力 [42] 。

4. 小结与展望

CT-FFR通过测量冠脉血管的血流动力学信息,从而可以在整体上了解每一处冠状动脉的病变及血管的生理信息,在使用CT-FFR时,应充分利用其所提供的信息,使其在临床上发挥更大的作用。目前现有的多中心临床试验证实了CT-FFR诊断能力,与有创FFR相比具有较高的一致性,以CT-FFR指导的治疗策略较常规治疗方案进一步改善了冠心病患者的预后。目前国内血流储备分数与心肌灌注相关方面研究较少,两者之间的相关性需要进一步探讨及研究。另外国内大部分CT-FFR的研究仅探讨了诊断效能,对于临床及预后的数据相对缺乏,所以需要进行相关高质量前瞻性临床研究,为临床应用提供更多的证据支撑。

基金项目

青海省卫健委医药卫生科技项目指导性计划课题(2021-wjzdx-40)。

文章引用

韩千程,温生宝,王雪燕,王 宇. 冠状动脉CT血流储备分数研究进展
Advances in Coronary CT Flow Reserve Frac-tion Studies[J]. 临床医学进展, 2023, 13(11): 18182-18188. https://doi.org/10.12677/ACM.2023.13112551

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  43. NOTES

    *通讯作者。

期刊菜单