scholarly journals 197 Angio-based index of microcirculatory resistance for the assessment of the coronary resistance: a proof of concept study

2021 ◽  
Vol 23 (Supplement_G) ◽  
Author(s):  
Andrea Marrone ◽  
Federico Gibiino ◽  
Ennio Scollo ◽  
Matteo Tebaldi ◽  
Simone Biscaglia ◽  
...  
Keyword(s):  
Pearson Correlation ◽  
University Hospital ◽  
Fractional Flow ◽  
Flow Reserve ◽  
Coronary Artery Angiography ◽  
Index Of Microcirculatory Resistance ◽  
Quantitative Flow Ratio ◽  
Sensitivity Specificity ◽  
The University ◽  
First Time

Abstract Aims The study of coronary microcirculation has gained increasing consideration and importance in cath-lab. Despite the increase of evidence its use still remains very limited. QFR is a novel angio-based approach for the evaluation of coronary stenosis. The aim of our study was to use the QFR assessment in stable patients to recreate the IMR formula and to correlate the result of the two techniques. Methods and results From 1 June 2019 to 29 February 2019, 200 patients with CCS and indication of coronary artery angiography and referred to the cath-lab of the University Hospital of Ferrara (Italy) were enrolled. After baseline coronary angiogram, quantitative flow ratio, fractional flow reserve and index of microcirculatory resistance evaluation were performed. Pearson correlation (r) between Angio-based index of microcirculatory resistance (A-IMR) and IMR 0.32 with R2 = 0.098, P = 0.03: McNemar test showed a difference between the two test of 6.82% with 95% CI from −12.05% to 22.89%, which is not significant (P = 0.60). Bland and Altman plot showed a mean difference of 23.3 (from −26.5 to 73.1). Sensitivity, specificity, NPV and PPV were 70%, 83.3%, 75% and 70% for A-IMR value > 44.2. The area under the ROC curve for A-IMR was 0.76 (95% CI: 0.61–0.88, P = 0.0003). Conclusions We have validated for the first time the formula of the A-IMR, a tool for the calculation of microvascular resistance which does not require the use of pressure guides and the induction of hyperemia

scholarly journals Angio-Based Index of Microcirculatory Resistance for the Assessment of the Coronary Resistance: A Proof of Concept Study

2020 ◽  
Vol 2020 ◽  
pp. 1-4
Author(s):  
Matteo Tebaldi ◽  
Simone Biscaglia ◽  
Domenico Di Girolamo ◽  
Andrea Erriquez ◽  
Carlo Penzo ◽  
...  
Keyword(s):  
Pearson Correlation ◽  
University Hospital ◽  
Fractional Flow ◽  
Flow Reserve ◽  
Coronary Artery Angiography ◽  
Index Of Microcirculatory Resistance ◽  
Quantitative Flow Ratio ◽  
Sensitivity Specificity ◽  
The University ◽  
First Time

Background. The study of coronary microcirculation has gained increasing consideration and importance in cath lab. Despite the increase of evidence, its use still remains very limited. QFR is a novel angio-based approach for the evaluation of coronary stenosis. The aim of our study was to use the QFR assessment in stable patients to recreate the IMR formula and to correlate the result of the two techniques. Methods. From June 1, 2019, to February 29, 2019, 200 patients with CCS and indication of coronary artery angiography and referred to the cath lab of the University Hospital of Ferrara (Italy) were enrolled. After baseline coronary angiogram, quantitative flow ratio, fractional flow reserve, and index of microcirculatory resistance evaluation were performed. Results. Pearson correlation (r) between angio-based index of microcirculatory resistance (A-IMR) and IMR 0.32 with R2 = 0.098, P = 0.03 : McNemar test showed a difference between the two tests of 6.82% with 95% CI from –12.05% to 22.89%, which is not significant ( P = 0.60 ). Bland and Altman plot showed a mean difference of 23.3 (from −26.5 to 73.1). Sensitivity, specificity, NPV, and PPV were 70%, 83.3%, 75%, and 70% for A-IMR value >44.2. The area under the ROC curve for A-IMR was 0.76 (95% CI 0.61–0.88, P = 0.0003 ). Conclusion. We have validated for the first time the formula of the A-IMR, a tool for the calculation of microvascular resistance which does not require the use of pressure guides and the induction of hyperemia.

Additional value of deep learning computed tomographic angiography-based fractional flow reserve in detecting coronary stenosis and predicting outcomes

2021 ◽  
pp. 028418512098397
Author(s):  
Yang Li ◽  
Hong Qiu ◽  
Zhihui Hou ◽  
Jianfeng Zheng ◽  
Jianan Li ◽  
...  
Keyword(s):  
Deep Learning ◽  
Unstable Angina ◽  
Fractional Flow Reserve ◽  
Predictive Value ◽  
Computed Tomographic Angiography ◽  
Fractional Flow ◽  
Computed Tomographic ◽  
Flow Reserve ◽  
Sensitivity Specificity ◽  
Tomographic Angiography

Background Deep learning (DL) has achieved great success in medical imaging and could be utilized for the non-invasive calculation of fractional flow reserve (FFR) from coronary computed tomographic angiography (CCTA) (CT-FFR). Purpose To examine the ability of a DL-based CT-FFR in detecting hemodynamic changes of stenosis. Material and Methods This study included 73 patients (85 vessels) who were suspected of coronary artery disease (CAD) and received CCTA followed by invasive FFR measurements within 90 days. The diagnostic accuracy, sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), and area under the receiver operating characteristics curve (AUC) were compared between CT-FFR and CCTA. Thirty-nine patients who received drug therapy instead of revascularization were followed for up to 31 months. Major adverse cardiac events (MACE), unstable angina, and rehospitalization were evaluated and compared between the study groups. Results At the patient level, CT-FFR achieved 90.4%, 93.6%, 88.1%, 85.3%, and 94.9% in accuracy, sensitivity, specificity, PPV, and NPV, respectively. At the vessel level, CT-FFR achieved 91.8%, 93.9%, 90.4%, 86.1%, and 95.9%, respectively. CT-FFR exceeded CCTA in these measurements at both levels. The vessel-level AUC for CT-FFR also outperformed that for CCTA (0.957 vs. 0.599, P < 0.0001). Patients with CT-FFR ≤0.8 had higher rates of rehospitalization (hazard ratio [HR] 4.51, 95% confidence interval [CI] 1.08–18.9) and MACE (HR 7.26, 95% CI 0.88–59.8), as well as a lower rate of unstable angina (HR 0.46, 95% CI 0.07–2.91). Conclusion CT-FFR is superior to conventional CCTA in differentiating functional myocardial ischemia. In addition, it has the potential to differentiate prognoses of patients with CAD.

Diagnostic performance and clinical implications for enhancing a hybrid quantitative flow ratio and fractional flow reserve revascularization decision making strategy

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
J Peper ◽  
R.W Van Hamersvelt ◽  
B.J.M.W Rensing ◽  
J.P Van Kuijk ◽  
M Voskuil ◽  
...  
Keyword(s):  
Diagnostic Performance ◽  
Hybrid Approach ◽  
High Accuracy ◽  
Intermediate Zone ◽  
Flow Ratio ◽  
Fractional Flow ◽  
Hybrid Strategy ◽  
Flow Reserve ◽  
Quantitative Flow Ratio ◽  
Quantitative Flow

Abstract Background Fractional flow reserve (FFR) adoption persists low mainly due to procedural and operator related factors as well as costs. An alternative for FFR, quantitative flow ratio (QFR) achieves a high accuracy mainly outside the intermediate zone without the need for hyperemia and wire-use. Currently, no outcome trials assess the role of QFR in the guidance of revascularization. Therefore, we evaluate a QFR-FFR hybrid strategy in which FFR is measured inside of the intermediate zone. Methods This retrospective multi-center study included consecutive patients who underwent both invasive coronary angiography and FFR in the participating centers. QFR was calculated for all vessels in which FFR was measured. Diagnostic performance of QFR was assessed using an FFR cut-off of 0.80 as reference standard. The QFR-FFR hybrid approach was modeled using the intermediate zone of 0.77 to 0.87 assuming that lesions within the intermediate zone follow the FFR binary cutoff. Results In total, 381 vessels in 289 patients were analyzed. The sensitivity, specificity and accuracy on a per vessel-based analysis were 84.6%, 86.3% and 85.6% for QFR and 91.1%, 95.3% and 93.4% for the QFR-FFR hybrid approach. The diagnostic accuracy of QFR-FFR hybrid strategy with invasive FFR measurement is 93.4% and results in a FFR reduction of 56.7%. Conclusion QFR has a good correlation and agreement with invasive FFR and a high diagnostic accuracy. A hybrid QFR-FFR approach could extend the use of QFR and reduces the proportion of invasive FFR-measurements needed while maintaining a high accuracy. Hybrid QFR-FFR strategy Funding Acknowledgement Type of funding source: None

scholarly journals Diagnostic performance and clinical implications for enhancing a hybrid quantitative flow ratio–FFR revascularization decision-making strategy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Joyce Peper ◽  
Robbert W. van Hamersvelt ◽  
Benno J. W. M. Rensing ◽  
Jan-Peter van Kuijk ◽  
Michiel Voskuil ◽  
...  
Keyword(s):  
Diagnostic Performance ◽  
Invasive Coronary Angiography ◽  
Hybrid Approach ◽  
Intermediate Zone ◽  
Flow Ratio ◽  
Fractional Flow ◽  
Hybrid Strategy ◽  
Flow Reserve ◽  
Quantitative Flow Ratio ◽  
Quantitative Flow

AbstractInvasive fractional flow reserve (FFR) adoption remains low mainly due to procedural and operator related factors as well as costs. Alternatively, quantitative flow ratio (QFR) achieves a high accuracy mainly outside the intermediate zone without the need for hyperaemia and wire-use. We aimed to determine the diagnostic performance of QFR and to evaluate a QFR–FFR hybrid strategy in which FFR is measured only in the intermediate zone. This retrospective study included 289 consecutive patients who underwent invasive coronary angiography and FFR. QFR was calculated for all vessels in which FFR was measured. The QFR–FFR hybrid approach was modelled using the intermediate zone of 0.77–0.87 in which FFR-measurements are recommended. The sensitivity, specificity, and accuracy on a per vessel-based analysis were 84.6%, 86.3% and 85.6% for QFR and 88.0%, 92.9% and 90.3% for the QFR–FFR hybrid approach. The diagnostic accuracy of QFR–FFR hybrid strategy with invasive FFR measurement was 93.4% and resulted in a 56.7% reduction in the need for FFR. QFR has a good correlation and agreement with invasive FFR. A hybrid QFR–FFR approach could extend the use of QFR and reduces the proportion of invasive FFR-measurements needed while improving accuracy.

Abstract 14743: Usefulness of Estimated Coronary Flow Velocity Using Quantitative Flow Ratio for Intermediate Coronary Stenosis

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Eiji Ichimoto ◽  
Nao Konagai ◽  
Sawako Horie ◽  
Atsushi Hasegawa ◽  
Hirofumi Miyahara ◽  
...  
Keyword(s):  
Flow Velocity ◽  
Coronary Stenosis ◽  
Coronary Flow ◽  
Flow Ratio ◽  
Operating Characteristics ◽  
Fractional Flow ◽  
Coronary Flow Velocity ◽  
Flow Reserve ◽  
Quantitative Flow Ratio ◽  
Quantitative Flow

Introduction: Quantitative flow ratio (QFR) is a diagnostic modality for functional assessment for intermediate coronary stenosis without the use of pressure wire. QFR is calculated from 3-dimensional quantitative CAG (3D-QCA) using an advanced algorithm that enables fast computation of the pressure drop caused by coronary stenosis. Hypothesis: We assessed the usefulness of QFR and the association with an estimated coronary flow velocity (eCFV) for intermediate coronary stenosis. Methods: A total of 100 lesions in 80 consecutive patients were assessed Fractional Flow Reserve (FFR) for intermediate coronary stenosis between January 2011 and April 2019. Of these, 97 lesions in 77 patients who underwent QFR were included in this study. Patients were classified into two groups (FFR ≤ 0.80 or FFR > 0.80). QFR and eCFV using contrast were measured by Thrombolysis in Myocardial Infarction (TIMI) frame counts. Results: There was no significant differences in target vessels (p = 0.90) and diffuse lesions (p = 0.06) between the two groups (FFR ≤ 0.80 or FFR > 0.80). Mean FFR and QFR values were 0.78 ± 0.12 and 0.77 ± 0.11, respectively. QFR had a good correlation with FFR values (r = 0.86, p < 0.0001). The diagnostic accuracy, sensitivity, and specificity on QFR ≤ 0.80 were 91.8%, 92.7% and 90.5%, respectively. The eCFV of FFR ≤ 0.80 was greater than that of FFR > 0.80 (0.19 ± 0.08 m/s vs. 0.14 ± 0.06 m/s, p<0.001). Figure showed that the eCFV correlated with FFR values (r = -0.29, p < 0.01). Moreover, the eCFV had a high area under the curve (AUC = 0.71, p < 0.01) on Receiver operating characteristics curve (ROC) analysis with FFR ≤ 0.80. Conclusions: QFR was useful for the assessment of functional stenosis severity. As eCFV was faster, FFR was lower for intermediate coronary stenosis. The eCFV had a good correlation with FFR and may become one of the evaluations for ischemia.

scholarly journals Feasibility and Validity of Computed Tomography-Derived Fractional Flow Reserve in Patients With Severe Aortic Stenosis

2020 ◽  
Author(s):  
Michael Michail ◽  
Abdul-Rahman Ihdayhid ◽  
Andrea Comella ◽  
Udit Thakur ◽  
James D. Cameron ◽  
...  
Keyword(s):  
Aortic Stenosis ◽  
Diagnostic Accuracy ◽  
Operating Characteristic ◽  
Severe Aortic Stenosis ◽  
Characteristic Curve ◽  
Fractional Flow ◽  
Predictive Values ◽  
Flow Reserve ◽  
Artery Disease ◽  
Sensitivity Specificity

Background: Coronary artery disease is common in patients with severe aortic stenosis. Computed tomography-derived fractional flow reserve (CT-FFR) is a clinically used modality for assessing coronary artery disease, however, its use has not been validated in patients with severe aortic stenosis. This study assesses the safety, feasibility, and validity of CT-FFR in patients with severe aortic stenosis. Methods: Prospectively recruited patients underwent standard-protocol invasive FFR and coronary CT angiography (CTA). CTA images were analyzed by central core laboratory (HeartFlow, Inc) for independent evaluation of CT-FFR. CT-FFR data were compared with FFR (ischemia defined as FFR ≤0.80). Results: Forty-two patients (68 vessels) underwent FFR and CTA; 39 patients (92.3%) and 60 vessels (88.2%) had interpretable CTA enabling CT-FFR computation. Mean age was 76.2±6.7 years (71.8% male). No patients incurred complications relating to premedication, CTA, or FFR protocol. Mean FFR and CT-FFR were 0.83±0.10 and 0.77±0.14, respectively. CT calcium score was 1373.3±1392.9 Agatston units. On per vessel analysis, there was positive correlation between FFR and CT-FFR (Pearson correlation coefficient, R =0.64, P <0.0001). Sensitivity, specificity, positive predictive value, and negative predictive values were 73.9%, 78.4%, 68.0%, and 82.9%, respectively, with 76.7% diagnostic accuracy. The area under the receiver-operating characteristic curve for CT-FFR was 0.83 (0.72–0.93, P <0.0001), which was higher than that of CTA and quantitative coronary angiography ( P =0.01 and P <0.001, respectively). Bland-Altman plot showed mean bias between FFR and CT-FFR as 0.059±0.110. On per patient analysis, the sensitivity, specificity, positive predictive, and negative predictive values were 76.5%, 77.3%, 72.2%, and 81.0% with 76.9% diagnostic accuracy. The per patient area under the receiver-operating characteristic curve analysis was 0.81 (0.67–0.95, P <0.0001). Conclusions: CT-FFR is safe and feasible in patients with severe aortic stenosis. Our data suggests that the diagnostic accuracy of CT-FFR in this cohort potentially enables its use in clinical practice and provides the foundation for future research into the use of CT-FFR for coronary evaluation pre-aortic valve replacement.

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
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