Optical coherence tomography‐defined plaque vulnerability in relation to functional stenosis severity stratified by fractional flow reserve and quantitative flow ratio

2020 ◽  
Vol 96 (3) ◽  
Author(s):  
Yoshinori Kanno ◽  
Tomoyo Sugiyama ◽  
Masahiro Hoshino ◽  
Eisuke Usui ◽  
Rikuta Hamaya ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Fractional Flow Reserve ◽  
Optical Coherence ◽  
Flow Ratio ◽  
Plaque Vulnerability ◽  
Fractional Flow ◽  
Flow Reserve ◽  
Stenosis Severity ◽  
Quantitative Flow Ratio ◽  
Quantitative Flow

scholarly journals Quantitative Flow Ratio Is Related to Intraluminal Coronary Stenosis Parameters as Assessed with Optical Coherence Tomography

2021 ◽  
Vol 10 (9) ◽  
pp. 1856
Author(s):  
Andrea Milzi ◽  
Rosalia Dettori ◽  
Kathrin Burgmaier ◽  
Nikolaus Marx ◽  
Sebastian Reith ◽  
...  
Keyword(s):  
Optical Coherence Tomography ◽  
Optical Coherence ◽  
Flow Ratio ◽  
Fractional Flow ◽  
Luminal Diameter ◽  
Flow Reserve ◽  
Pressure Wire ◽  
Minimal Lumen Area ◽  
Quantitative Flow Ratio ◽  
Quantitative Flow

Background: Quantitative flow ratio (QFR) is a novel method for assessing hemodynamic relevance of a coronary lesion based on angiographic projections without the need of a pressure wire. Various studies demonstrated that QFR consistently related to fractional flow reserve (FFR); however, it is still unclear to what extent QFR reflects intraluminal stenosis parameters. Given that optical coherence tomography (OCT) is currently the gold standard to assess intraluminal stenosis parameters, we investigated the relationship between OCT-derived lesion geometry and QFR. Methods: We determined QFR in 97 lesions from 87 patients who underwent coronary angiography and OCT due to stable angina. QFR was measured with proprietary software and compared with OCT-based assessment of intraluminal stenosis parameters as well as lesion morphology. Results: Mean QFR was 0.79 ± 0.10. QFR demonstrated a consistent association with FFR (R = 0.834, p < 0.001). Interestingly, QFR was associated with OCT-derived parameters such as minimal lumen area (MLA, R = 0.390, p = 0.015), percent area stenosis (R = 0.412, p < 0.001), minimal lumen diameter (MLD, R = 0.395, p < 0.001), and percent diameter stenosis (R = 0.400, p < 0.001). Both minimal luminal area (ROC = 0.734, optimal cut-off 1.75 mm2) and minimal luminal diameter (ROC = 0.714, optimal cut-off 1.59 mm) presented a good diagnostic accuracy in diagnosing hemodynamic relevance (QFR ≤ 0.80). There was no significant association between QFR and anatomic features of plaque vulnerability. Conclusion: OCT-derived intraluminal stenosis parameters are related to QFR values and predict hemodynamic lesion relevance. The data supports the validity of QFR as 3D-vessel reconstruction method to assess coronary physiology without the need of a pressure wire.

scholarly journals P4635Referral of patients for fractional flow reserve using quantitative flow ratio

2018 ◽  
Vol 39 (suppl_1) ◽  
Author(s):  
J M Smit ◽  
G Koning ◽  
A R Van Rosendael ◽  
M El Mahdiui ◽  
B J Mertens ◽  
...  
Keyword(s):  
Fractional Flow Reserve ◽  
Flow Ratio ◽  
Fractional Flow ◽  
Flow Reserve ◽  
Quantitative Flow Ratio ◽  
Quantitative Flow

scholarly journals Meta-Analysis of Diagnostic Performance of Contrast-Fractional Flow Reserve versus Quantitative Flow Ratio for Functional Assessment of Coronary Stenoses

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Ruitao Zhang ◽  
Jianwei Zhang ◽  
Lijun Guo
Keyword(s):  
Sensitivity And Specificity ◽  
Fractional Flow Reserve ◽  
Coronary Stenosis ◽  
Diagnostic Performance ◽  
Meta Analysis ◽  
Flow Ratio ◽  
Fractional Flow ◽  
Flow Reserve ◽  
Quantitative Flow Ratio ◽  
Quantitative Flow

Background. Use of the fractional flow reserve (FFR) technique is recommended to evaluate coronary stenosis severity and guide revascularization. However, its high cost, time to administer, and the side effects of adenosine reduce its clinical utility. Two novel adenosine-free indices, contrast-FFR (cFFR) and quantitative flow ratio (QFR), can simplify the functional evaluation of coronary stenosis. This study aimed to analyze the diagnostic performance of cFFR and QFR using FFR as a reference index. Methods. We conducted a systematic review and meta-analysis of observational studies in which cFFR or QFR was compared to FFR. A bivariate model was applied to pool diagnostic parameters. Cochran’s Q test and the I2 index were used to assess heterogeneity and identify the potential source of heterogeneity by metaregression and sensitivity analysis. Results. Overall, 2220 and 3000 coronary lesions from 20 studies were evaluated by cFFR and QFR, respectively. The pooled sensitivity and specificity were 0.87 (95% CI: 0.81, 0.91) and 0.92 (95% CI: 0.88, 0.94) for cFFR and 0.87 (95% CI: 0.82, 0.91) and 0.91 (95% CI: 0.87, 0.93) for QFR, respectively. No statistical significance of sensitivity and specificity for cFFR and QFR were observed in the bivariate analysis (P=0.8406 and 0.4397, resp.). The area under summary receiver-operating curve of cFFR and QFR was 0.95 (95% CI: 0.93, 0.97) for cFFR and 0.95 (95% CI: 0.93, 0.97). Conclusion. Both cFFR and QFR have good diagnostic performance in detecting functional severity of coronary arteries and showed similar diagnostic parameters.

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