Angiographic quantitative flow ratio-guided coronary intervention (FAVOR III China): a multicentre, randomised, sham-controlled trial

Xu, Bo; Tu, Shengxian; Song, Lei; Jin, Zening; Yu, Bo; Fu, Guosheng; Zhou, Yujie; Wang, Jianan; Chen, Yundai; Pu, Jun; Chen, Lianglong; Qu, Xinkai; Yang, Jian; Liu, Xuebo; Guo, Lijun; Shen, Chengxing; Zhang, Yaojun; Zhang, Qi; Pan, Hongwei; Fu, Xiaogang; Liu, Jian; Zhao, Yanyan; Escaned, Javier; Wang, Yan; Fearon, William F.; Dou, Kefei; Kirtane, Ajay J.; Wu, Yongjian; Serruys, Patrick W.; Yang, Wei; Wijns, William; Guan, Changdong; Leon, Martin B.; Qiao, Shubin; Stone, Gregg W.

doi:10.1016/s0140-6736(21)02248-0

Cited by 196 publications

(151 citation statements)

References 22 publications

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“…However, myocardial ischemia is the root cause of coronary artery disease and its complications which is regarded unobservable. 1 It is diagnosed through various observable pathological artery structures, symptoms such as stenosis, chest pain etc. However, the challenge is that none of them is demonstrated to be a necessary condition of myocardial ischemia and thus not suitable to act as an indicator of Ischemia.…”

Section: Methodsmentioning

confidence: 99%

“…), blood viscosity and density etc. 1 Recent studies have demonstrated that myocardial ischemia is not sufficiently indicated merely by artery anatomic structure, conventionally mapped to artery stenosis, but rather comprehensively on a functional perspective intrinsically rooted in hemodynamics. 2 However, before FFR being regarded as a standard and effective approach to discriminate stenosis causing pathological myocardial ischemia while exclude stenosis with “wolf clothing but sheep inside”, CAG is recognized as the gold rule to diagnose coronary artery disease in an anatomic perspective.…”

Section: Introductionmentioning

confidence: 99%

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When Diagnosis Is Made By Playing “Shuffled Cards”: A Non-Invasive, Real-Time, Adaptive Method to Functionally Evaluate Coronary Artery Based on Coronary Angiography

Dai¹,

Zhu

Xue

et al. 2022

Preprint

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Aims The great value concealed in the sequence of coronary angiography frames is not discovered in the world. We discovered and demonstrated the Sequence Value concealed in the coronary angiography and proposed DZL (Disarranged Zone Learning) to realize the sequence value in functional evaluation of coronary artery disease. Furthermore, we automated the DZL using a deep learning model to release huge medical resources. Methods and Results We gave a novel definition of TIMI flow grade using the term temporal and spatial coupling tightness (TSCT) of the antegrade contrast agent. We used the TSCT to model the myocardial ischemia in a functional perspective and used the PCI conduction after CAG as the outcome event of myocardial ischemia. We proposed a novel method (Disarranged Zone Learning) to measure TSCT and we designed an experiment to validate its effectiveness. We further automated the novel method using an unsupervised deep learning model. The prediction accuracy of the model was applied as a proxy of myocardial ischemia. We further proposed Difference DZL to quantify the functional capability of any specific vessel segment. DZL overall AUC reaches 0.92. DZL automation reveals an AUC of 0.84 (95%CI, 0.81-0.87). Conclusion We unprecedentedly discovered the Sequence Value concealed in coronary angiography. We then proposed a novel method termed DZL to functionally evaluate the coronary artery in a non-invasive, real-time and adaptive manner.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

When Diagnosis Is Made By Playing “Shuffled Cards”: A Non-Invasive, Real-Time, Adaptive Method to Functionally Evaluate Coronary Artery Based on Coronary Angiography

Dai¹,

Zhu

Xue

et al. 2022

Preprint

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“…(2) taking into account the flow velocity estimated by the time needed for the contrast agent to fill the segment, which is known as contrast-flow QFR (cQFR) (4)(5)(6)(7)(8)(9). Then, angiographyderived microcirculatory resistance (MR) was computed by Angioplus System, as shown in Figure 3.…”

Section: Qfr and Mr Analysismentioning

confidence: 99%

“…Quantitative flow ratio (QFR), as a novel angiography-based approach, has been recently reported to provide the physiological value of the accuracy of detection of vessel dysfunction and risk from cardiovascular events ( 3 ). In the latest results of the FAVOR III China study, a QFR-guided PCI strategy was proved to be able to reduce major cardiac events compared with standard angiography guidance PCI strategy ( 4 ). By focusing on geometric and functional outcomes of stenting in STEMI, we aimed to explore the optimal criteria for adequate stent expansion for post-pPCI prognosis by IVUS and QFR.…”

Section: Introductionmentioning

confidence: 99%

Microvascular and Prognostic Effect in Lesions With Different Stent Expansion During Primary PCI for STEMI: Insights From Coronary Physiology and Intravascular Ultrasound

Sun

Luo

et al. 2022

Front. Cardiovasc. Med.

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BackgroundWhile coronary stent implantation in ST-elevation myocardial infarction (STEMI) can mechanically revascularize culprit epicardial vessels, it might also cause distal embolization. The relationship between geometrical and functional results of stent expansion during the primary percutaneous coronary intervention (pPCI) is unclear.ObjectiveWe sought to determine the optimal stent expansion strategy in pPCI using novel angiography-based approaches including angiography-derived quantitative flow ratio (QFR)/microcirculatory resistance (MR) and intravascular ultrasound (IVUS).MethodsPost-hoc analysis was performed in patients with acute STEMI and high thrombus burden from our prior multicenter, prospective cohort study (ChiCTR1800019923). Patients aged 18 years or older with STEMI were eligible. IVUS imaging, QFR, and MR were performed during pPCI, while stent expansion was quantified on IVUS images. The patients were divided into three subgroups depending on the degree of stent expansion as follows: overexpansion (>100%), optimal expansion (80%−100%), and underexpansion (<80%). The patients were followed up for 12 months after PCI. The primary endpoint included sudden cardiac death, myocardial infarction, stroke, unexpected hospitalization or unplanned revascularization, and all-cause death.ResultsA total of 87 patients were enrolled. The average stent expansion degree was 82% (in all patients), 117% (in overexpansion group), 88% (in optimal expansion), and 75% (in under-expansion). QFR, MR, and flow speed increased in all groups after stenting. The overall stent expansion did not affect the final QFR (p = 0.08) or MR (p = 0.09), but it reduced the final flow speed (−0.14 cm/s per 1%, p = 0.02). Under- and overexpansion did not affect final QFR (p = 0.17), MR (p = 0.16), and flow speed (p = 0.10). Multivariable Cox analysis showed that stent expansion was not the risk factor for MACE (hazard ratio, HR = 0.97, p = 0.13); however, stent expansion reduced the risk of MACE (HR = 0.95, p = 0.03) after excluding overexpansion patients. Overexpansion was an independent risk factor for no-reflow (HR = 1.27, p = 0.02) and MACE (HR = 1.45, p = 0.007). Subgroup analysis shows that mild underexpansion of 70%−80% was not a risk factor for MACE (HR = 1.11, p = 0.08) and no-reflow (HR = 1.4, p = 0.08); however, stent expansion <70% increased the risk of MACE (HR = 1.36, p = 0.04).ConclusionsStent expansion does not affect final QFR and MR, but it reduces flow speed in STEMI. Appropriate stent underexpansion of 70–80% does not seem to be associated with short-term prognosis, so it may be tolerable as noninferior compared with optimal expansion. Meanwhile, overexpansion and underexpansion of <70% should be avoided due to the independent risk of MACEs and no-reflow events.

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“…Quantitative flow ratio (QFR) was calculated based on combined geometrical data and hemodynamic boundary conditions derived from coronary angiography (Tu et al, 2016(Tu et al, , 2019Xu et al, 2017). QFR has been widely validated showing a significant diagnostic performance and prognostic value for coronary artery stenosis (Westra et al, 2018;Biscaglia et al, 2019;Tang et al, 2021), validated in the latest multicenter randomized controlled trial (Xu et al, 2021). Recently, a new method for computing QFR from a single angiographic view, based on artificial intelligence and the Murray bifurcation fractal law, exhibited high feasibility and excellent diagnostic accuracy (Tu et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Functional Assessment of Cerebral Artery Stenosis by Angiography-Based Quantitative Flow Ratio: A Pilot Study

Huang

Yao

et al. 2022

Front. Aging Neurosci.

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BackgroundIncreasing attention has been paid to the hemodynamic evaluation of cerebral arterial stenosis. We aimed to demonstrate the performance of angiography-based quantitative flow ratio (QFR) to assess hemodynamic alterations caused by luminal stenoses, using invasive fractional pressure ratios (FPRs) as a reference standard.MethodsBetween March 2013 and December 2019, 29 patients undergoing the pressure gradient measurement of cerebral atherosclerosis were retrospectively enrolled. Wire-based FPR was defined by the arterial pressure distal to the stenotic lesion (Pd) to proximal (Pa) pressure ratios (Pd/Pa). FPR < 0.70 or FPR < 0.75 was assumed as hemodynamically significant stenosis. The new method of computing QFR from a single angiographic view, i.e., the Murray law-based QFR, was applied to the interrogated vessel. An artificial intelligence algorithm was developed to realize the automatic delineation of vascular contour.ResultsFractional pressure ratio and QFR were assessed in 38 vessels from 29 patients. Excellent correlation and agreement were observed between QFR and FPR [r = 0.879, P < 0.001; mean difference (bias): −0.006, 95% limits of agreement: −0.198 to 0.209, respectively). Intra-observer and inter-observer reliability in QFR were excellent (intra-class correlation coefficients, 0.996 and 0.973, respectively). For predicting FPR < 0.70, the area under the receiver-operating characteristic curves (AUC) of QFR was 0.946 (95% CI, 0.820 to 0.993%). The sensitivity and specificity of QFR < 0.70 for identifying FPR < 0.70 was 88.9% (95% CI, 65.3 to 98.6%) and 85.0% (95% CI, 62.1 to 96.8%). For predicting FPR < 0.75, QFR showed similar performance with an AUC equal to 0.926.ConclusionComputational QFR from a single angiographic view achieved comparable results to the wire-based FPR. The excellent diagnostic performance and repeatability empower QFR with high feasibility in the functional assessment of cerebral arterial stenosis.

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Angiographic quantitative flow ratio-guided coronary intervention (FAVOR III China): a multicentre, randomised, sham-controlled trial

Cited by 196 publications

References 22 publications

When Diagnosis Is Made By Playing “Shuffled Cards”: A Non-Invasive, Real-Time, Adaptive Method to Functionally Evaluate Coronary Artery Based on Coronary Angiography

When Diagnosis Is Made By Playing “Shuffled Cards”: A Non-Invasive, Real-Time, Adaptive Method to Functionally Evaluate Coronary Artery Based on Coronary Angiography

Microvascular and Prognostic Effect in Lesions With Different Stent Expansion During Primary PCI for STEMI: Insights From Coronary Physiology and Intravascular Ultrasound

Functional Assessment of Cerebral Artery Stenosis by Angiography-Based Quantitative Flow Ratio: A Pilot Study

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