Search

Background: Quantitative flow ratio (QFR) is a novel approach to derive fractional flow reserve (FFR) from coronary angiography. This study sought to evaluate the reproducibility of QFR when analyzed in independent core laboratories., Methods: All interrogated vessels in the FAVOR II China Study were separately analyzed using the AngioPlus system (Pulse medical imaging technology, Shanghai) by two independent core laboratories, following the same standard operation procedures. The analysts were blinded to the FFR values and online QFR values. For each interrogated vessel, two identical angiographic image runs were used by two core laboratories for QFR computation. In both core laboratories QFR was successfully obtained in 330 of 332 vessels, in which FFR was available in 328 vessels. Thus, 328 vessels ended in the present statistical analysis., Results: The mean difference in contrast-flow QFR between the two core laboratories was 0.004 ± 0.03 (p = 0.040), which was slightly smaller than that between the online analysis and the two core laboratories (0.01 ± 0.05, p < 0.001 and 0.01 ± 0.05, p = 0.038). The mean difference of QFR with re-spect to FFR were comparable between the two core laboratories (0.002 ± 0.06, p = 0.609, and 0.002 ± 0.06, p = 0.531). Receiver operating characteristic curve analysis showed that diagnostic accuracies of QFR analyzed by the two core laboratories were both excellent (area under the curve: 0.970 vs. 0.963, p = 0.142), when using FFR as the reference standard., Conclusions: The present study showed good inter-core laboratory reproducibility of QFR in assessing functionally-significant stenosis. It suggests that QFR analyses can be carried out in different core labo-ratories if, and only if, highly standardized conditions are maintained.

To assess a novel approach for automatic flow velocity computation in deriving quantitative flow ratio (QFR) from coronary angiography. QFR is a novel approach for assessment of functional significance of coronary artery stenosis without using pressure wire and induced hyperemia. Patient-specific coronary flow is estimated semi-automatically by frame count method, which is subjective and inconvenient in the workflow of QFR analysis. The vascular structures were automatically delineated from coronary angiogram. Subsequently, the centerline of the interrogated vessel was extracted from the delineated lumen on each image frame and the change in the length of centerline was used to compute the flow velocity, which provided patient-specific flow for computation of QFR (QFR auto ). A parameter derived from the increase in centerline length was used to automatically quantify the stability of contrast flow. From the two angiographic image runs used for three-dimensional angiographic reconstruction, the one with better stability was used to compute QFR auto . QFR auto was assessed in all patients enrolled in the FAVOR II China study, and compared with the commercialized QFR computational method based on frame count (QFR count ), using pressure wire-based fractional flow reserve (FFR) as the reference standard. Out of 328 vessels with paired FFR data, QFR auto was successfully computed on 325 (99%) vessels with acceptable stability in filling of contrast flow. The flow velocity computed by the proposed approach had a weak to moderate correlation with the frame count method (r = 0.37, p < 0.001), with mean differences of - 0.02 ± 0.07 m/s (p < 0.001). QFR auto had good correlation (r = 0.96, p < 0.001) and agreement (mean difference: - 0.01 ± 0.04, p < 0.001) with QFR count . Good correlation (r = 0.83, p < 0.001) and agreement (mean difference: 0.01 ± 0.06, p = 0.016) were also observed between QFR auto and FFR. Using FFR ≤ 0.80 to define functional significance of coronary stenosis, the overall diagnostic accuracy for QFR auto was 93.2% (95% CI 90.5-96.0%). The area under the receiver-operating characteristic curve did not differ significantly between QFR count and QFR auto (difference: 0.00; 95% CI - 0.01 to 0.01; p = 0.529). Sensitivity, specificity, positive likelihood ratio, and negative likelihood ratio for QFR auto were 92.4% (95% CI 86.0-96.5%), 93.7% (95% CI 89.5-96.6%), 14.7 (95% CI 8.7-25.0), and 0.1 (95% CI 0.0-0.2), respectively. Automatic computation of patient-specific coronary flow velocity based on coronary angiography is feasible. Assessment of QFR based on this novel approach had good diagnostic accuracy in determining the functional significance of coronary stenosis.

Background: Quantitative flow ratio (QFR) is a novel modality for physiological lesion assessment based on 3-dimensional vessel reconstructions and contrast flow velocity estimates. We evaluated the value of online QFR during routine invasive coronary angiography for procedural feasibility, diagnostic performance, and agreement with pressure-wire-derived fractional flow reserve (FFR) as a gold standard in an international multicenter study., Methods and Results: FAVOR II E-J (Functional Assessment by Various Flow Reconstructions II Europe-Japan) was a prospective, observational, investigator-initiated study. Patients with stable angina pectoris were enrolled in 11 international centers. FFR and online QFR computation were performed in all eligible lesions. An independent core lab performed 2-dimensional quantitative coronary angiography (2D-QCA) analysis of all lesions assessed with QFR and FFR. The primary comparison was sensitivity and specificity of QFR compared with 2D-QCA using FFR as a reference standard. A total of 329 patients were enrolled. Paired assessment of FFR, QFR, and 2D-QCA was available for 317 lesions. Mean FFR, QFR, and percent diameter stenosis were 0.83±0.09, 0.82±10, and 45±10%, respectively. FFR was ≤0.80 in 104 (33%) lesions. Sensitivity and specificity by QFR was significantly higher than by 2D-QCA (sensitivity, 86.5% (78.4-92.4) versus 44.2% (34.5-54.3); P <0.001; specificity, 86.9% (81.6-91.1) versus 76.5% (70.3-82.0); P =0.002). Area under the receiver curve was significantly higher for QFR compared with 2D-QCA (area under the receiver curve, 0.92 [0.89-0.96] versus 0.64 [0.57-0.70]; P <0.001). Median time to QFR was significantly lower than median time to FFR (time to QFR, 5.0 minutes [interquartile range, -6.1] versus time to FFR, 7.0 minutes [interquartile range, 5.0-10.0]; P <0.001)., Conclusions: Online computation of QFR in the catheterization laboratory is clinically feasible and is superior to angiographic assessment for evaluation of intermediary coronary artery stenosis using FFR as a reference standard., Clinical Trial Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT02959814., (© 2018 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley.)

Background: Quantitative flow ratio (QFR) is a novel diagnostic modality for functional testing of coronary artery stenosis without the use of pressure wires and induction of hyperemia. QFR is based on computation of standard invasive coronary angiographic imaging. The purpose of WIFI II (Wire-Free Functional Imaging II) was to evaluate the feasibility and diagnostic performance of QFR in unselected consecutive patients., Methods and Results: WIFI II was a predefined substudy to the Dan-NICAD study (Danish Study of Non-Invasive Diagnostic Testing in Coronary Artery Disease), referring 362 consecutive patients with suspected coronary artery disease on coronary computed tomographic angiography for diagnostic invasive coronary angiography. Fractional flow reserve (FFR) was measured in all segments with 30% to 90% diameter stenosis. Blinded observers calculated QFR (Medis Medical Imaging bv, The Netherlands) for comparison with FFR. FFR was measured in 292 lesions from 191 patients. Ten (5%) and 9 patients (5%) were excluded because of FFR and angiographic core laboratory criteria, respectively. QFR was successfully computed in 240 out of 255 lesions (94%) with a mean diameter stenosis of 50±12%. Mean difference between FFR and QFR was 0.01±0.08. QFR correctly classified 83% of the lesions using FFR with cutoff at 0.80 as reference standard. The area under the receiver operating characteristic curve was 0.86 (95% confidence interval, 0.81-0.91) with a sensitivity, specificity, negative predictive value, and positive predictive value of 77%, 86%, 75%, and 87%, respectively. A QFR-FFR hybrid approach based on the present results enables wire-free and adenosine-free procedures in 68% of cases., Conclusions: Functional lesion evaluation by QFR assessment showed good agreement and diagnostic accuracy compared with FFR. Studies comparing clinical outcome after QFR- and FFR-based diagnostic strategies are required., Clinical Trial Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT02264717., (© 2018 The Authors.)

Background: The nonculprit lesion (NCL) management in ST-segment-elevation myocardial infarction patients with multivessel disease is debated. We sought to assess whether quantitative flow ratio (QFR), a noninvasive tool to identify potentially flow-limiting lesions, may be reliable in this scenario., Methods and Results: The present proof-of-concept study is based on a 3-step process: (1) identification of the QFR reproducibility in NCLs assessment (cohort A, n=31); (2) prospective validation of QFR diagnostic accuracy in respect to fractional flow reserve (cohort B, n=45); and (3) investigation of long-term clinical outcomes of NCLs stratified according to QFR (cohort C, n=110). A blinded core laboratory computed QFR values for all NCLs. Cohort A showed a good correlation and agreement between QFR values at index (acute) and at staged (subacute, 3-4 days later) procedures ( r =0.98; 95% confidence interval, 0.96-0.99; mean difference, 0.004 [-0.027 to 0.34]). The inter-rater agreement was κ=0.9. In cohort B, fractional flow reserve and QFR identified 16 (33%) and 17 (35%) NCLs potentially flow limiting. Sensitivity, specificity, negative, and positive predictive values were 88%, 97%, 94%, and 94%. The area under the receiver operating characteristics curve was 0.96 (95% confidence interval, 0.89-0.99). Finally, in cohort C, we identified 110 ST-segment-elevation myocardial infarction patients where at least 1 NCL was left untreated. Patients with NCLs showing a QFR value ≤0.80 were at higher risk of adverse events (hazard ratio, 2.3; 95% confidence interval, 1.2-4.5; P =0.01)., Conclusions: In a limited and selected study population, our study showed that QFR computation may be a safe and reliable tool to guide coronary revascularization of NCLs in ST-segment-elevation myocardial infarction patients., (© 2018 American Heart Association, Inc.)

Fractional flow reserve (FFR) is the current gold standard to assess the physiological significance of coronary stenoses. With the development of coronary imaging techniques, several anatomic parameters have been investigated in vivo and their associations with FFR have been studied. The aim of this review is to summarize the accuracy of anatomic parameters derived by the present coronary imaging techniques including invasive coronary angiography, coronary computed tomography angiography, intravascular ultrasound and optical coherence tomography, in predicting a significant FFR. The impact of patient characteristics, lesion locations, variability of FFR and imaging resolution on the predictive ability are discussed.

Objectives: The aim of this prospective multicenter study was to identify the optimal approach for simple and fast fractional flow reserve (FFR) computation from radiographic coronary angiography, called quantitative flow ratio (QFR)., Background: A novel, rapid computation of QFR pullbacks from 3-dimensional quantitative coronary angiography was developed recently., Methods: QFR was derived from 3 flow models with: 1) fixed empiric hyperemic flow velocity (fixed-flow QFR [fQFR]); 2) modeled hyperemic flow velocity derived from angiography without drug-induced hyperemia (contrast-flow QFR [cQFR]); and 3) measured hyperemic flow velocity derived from angiography during adenosine-induced hyperemia (adenosine-flow QFR [aQFR]). Pressure wire-derived FFR, measured during maximal hyperemia, served as the reference. Separate independent core laboratories analyzed angiographic images and pressure tracings from 8 centers in 7 countries., Results: The QFR and FFR from 84 vessels in 73 patients with intermediate coronary lesions were compared. Mean angiographic percent diameter stenosis (DS%) was 46.1 ± 8.9%; 27 vessels (32%) had FFR ≤ 0.80. Good agreement with FFR was observed for fQFR, cQFR, and aQFR, with mean differences of 0.003 ± 0.068 (p = 0.66), 0.001 ± 0.059 (p = 0.90), and -0.001 ± 0.065 (p = 0.90), respectively. The overall diagnostic accuracy for identifying an FFR of ≤0.80 was 80% (95% confidence interval [CI]: 71% to 89%), 86% (95% CI: 78% to 93%), and 87% (95% CI: 80% to 94%). The area under the receiver-operating characteristic curve was higher for cQFR than fQFR (difference: 0.04; 95% CI: 0.01 to 0.08; p < 0.01), but did not differ significantly between cQFR and aQFR (difference: 0.01; 95% CI: -0.04 to 0.06; p = 0.65). Compared with DS%, both cQFR and aQFR increased the area under the receiver-operating characteristic curve by 0.20 (p < 0.01) and 0.19 (p < 0.01). The positive likelihood ratio was 4.8, 8.4, and 8.9 for fQFR, cQFR, and aQFR, with negative likelihood ratio of 0.4, 0.3, and 0.2, respectively., Conclusions: The QFR computation improved the diagnostic accuracy of 3-dimensional quantitative coronary angiography-based identification of stenosis significance. The favorable results of cQFR that does not require pharmacologic hyperemia induction bears the potential of a wider adoption of FFR-based lesion assessment through a reduction in procedure time, risk, and costs., (Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.)