TCT-706: New Perspective on the Fractional Flow Reserve: High Predictive Value of Baseline Pd/Pa during Intracoronary Pressure Wire Study

Abstract Background Non-invasive fractional flow reserve (NiFFR) is an emerging method for evaluating the functional significance of a coronary lesion during diagnostic coronary angiography (CAG). The method relies on the computational flow dynamics and the 3D reconstruction of the vessel extracted from CAG. In the present study, we sought to evaluate the diagnostic performance and applicability of 2D-based NiFFR. Methods In this prospective observational study, we evaluated 2D-based NiFFR in 279 candidates for invasive CAG and invasive FFR. NiFFR was calculated via 2 methods: variable NiFFR, in which the contrast transport time was extracted from the angiographic view, and fixed NiFFR, in which a prespecified frame count was applied. Results The final analysis was performed on 245 patients (250 lesions). Variable NiFFR had an area under the receiver operating characteristic curve of 81.5%, an accuracy of 80.0%, a sensitivity of 82.2%, a specificity of 82.2%, a negative predictive value of 91.4%, and a positive predictive value of 63.6%. The mean difference between FFR and NiFFR was −0.0244 ±0.0616 (P≤0.0001). A pressure wire-free hybrid strategy was possible in 68.8% of our population with variable NiFFR. Conclusions Our 2D-based NiFFR yielded results comparable to those derived from 3D-based software. Our findings should, however, be confirmed in larger trials. Pressure wire-free hybrid strategy Funding Acknowledgement Type of funding source: None

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

Acta Radiologica ◽

10.1177/0284185120983977 ◽

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.

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P6175Prediction of coronary revascularization by coronary computed tomography angiography derived fractional flow reserve - different algorithms for interpretation

European Heart Journal ◽

10.1093/eurheartj/ehz746.0781 ◽

2019 ◽

Vol 40 (Supplement_1) ◽

Author(s):

K T Madsen ◽

K T Veien ◽

B L Noergaard ◽

P Larsen ◽

L Deibjerg ◽

...

Keyword(s):

Chest Pain ◽

Fractional Flow Reserve ◽

Predictive Value ◽

Diagnostic Performance ◽

Coronary Revascularization ◽

Standard Of Care ◽

Fractional Flow ◽

Coronary Cta ◽

Flow Reserve ◽

Stable Chest Pain

Abstract Introduction Coronary CT angiography (CTA) derived fractional flow reserve (FFRct) is increasingly used for guiding referral to invasive procedures in patients with stable chest pain. However, optimal interpretation of FFRct-analysis in terms of location and threshold of applied FFRct-values is unclear. Purpose To evaluate the clinical performance of various vessel-specific physiological FFRct derived measures of ischemia for prediction of standard of care guided coronary revascularization in patients with stable chest pain and coronary artery disease as determined by coronary CTA. Methods Retrospective study in patients with stable chest pain referred for coronary angiography based on coronary CTA. Standard acquired coronary CTA data sets were transmitted for core-laboratory analysis at HeartFlow. Any FFRct value in the major coronary arteries ≥1.8 mm in diameter, including side branches, were registered. Lesions were categorized as positive for ischemia using 6 different algorithms: Lowest in vessel FFRct-value (1) ≤0.75 or (2) ≤0.80; 2 cm distal-to-lesion FFRct-value (3) ≤0.75 or (4) ≤0.80; ΔFFRct (5) ≥0.06 or a combination of 2 and 5. The personnel responsible for downstream patient management had no information regarding FFRct test results. Results A total of 172 patients were included. Revascularization was performed in 62 (35%) patients. The diagnostic performance of different FFRct algorithms for predicting standard of care guided coronary revascularization is shown in the Table. Revascularization Predictions by FFRct N=172 Diagnostic performance FFRCT false negative FFRCT false positive Values given as (%) No. of revasc vessels No. of abnormal vessels FFRCT Algorithm Sens Spec PPV NPV Acc 1 2 3 1 2 3 Distal FFRCT ≤0.75 77 68 58 84 72 12 2 0 29 5 1 Distal FFRCT ≤0.80 92 43 48 90 61 5 0 0 40 20 3 Lesion-specific FFRCT ≤0.75 68 86 74 83 80 17 3 0 12 3 0 Lesion-specific FFRCT ≤0.80 82 78 68 89 80 10 2 0 21 3 1 ΔFFRCT ≥0.06 98 36 47 98 59 1 0 0 51 19 0 Combinationa 92 54 53 92 67 5 0 0 39 12 0 aDistal FFRCT ≤0.80 and ΔFFRCT ≥0.06. Sens = sensitivity; Spec = specificity; PPV = positive predictive value; NPV = negative predictive value; Acc = accuracy; FFRCT = fractional flow reserve derived from coronary CTA; ΔFFRCT = difference between FFRCT-value immediately proximal and distal to lesion; Revasc = revascularized. Conclusion The diagnostic performance of FFRct in terms of predicting standard of care guided coronary revascularization is dependent on the applied algorithm for interpretation of the FFRct-analysis.

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Fractional flow reserve in clinical practice: from wire-based invasive measurement to image-based computation

European Heart Journal ◽

10.1093/eurheartj/ehz918 ◽

2019 ◽

Vol 41 (34) ◽

pp. 3271-3279 ◽

Cited By ~ 8

Author(s):

Shengxian Tu ◽

Jelmer Westra ◽

Julien Adjedj ◽

Daixin Ding ◽

Fuyou Liang ◽

...

Keyword(s):

Fractional Flow Reserve ◽

Diagnostic Methods ◽

Functional Evaluation ◽

Fractional Flow ◽

Catheterization Laboratory ◽

Flow Reserve ◽

Pressure Wire ◽

Stenosis Severity ◽

Procedural Guidance ◽

Invasive Measurement

Abstract Fractional flow reserve (FFR) and instantaneous wave-free ratio are the present standard diagnostic methods for invasive assessment of the functional significance of epicardial coronary stenosis. Despite the overall trend towards more physiology-guided revascularization, there remains a gap between guideline recommendations and the clinical adoption of functional evaluation of stenosis severity. A number of image-based approaches have been proposed to compute FFR without the use of pressure wire and induced hyperaemia. In order to better understand these emerging technologies, we sought to highlight the principles, diagnostic performance, clinical applications, practical aspects, and current challenges of computational physiology in the catheterization laboratory. Computational FFR has the potential to expand and facilitate the use of physiology for diagnosis, procedural guidance, and evaluation of therapies, with anticipated impact on resource utilization and patient outcomes.

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Accuracy of computational pressure-fluid dynamics applied to coronary angiography to derive fractional flow reserve: FLASH FFR

Cardiovascular Research ◽

10.1093/cvr/cvz289 ◽

2019 ◽

Vol 116 (7) ◽

pp. 1349-1356 ◽

Cited By ~ 5

Author(s):

Jianping Li ◽

Yanjun Gong ◽

Weimin Wang ◽

Qing Yang ◽

Bin Liu ◽

...

Keyword(s):

Fluid Dynamics ◽

Coronary Artery ◽

Coronary Angiography ◽

Fractional Flow Reserve ◽

Predictive Value ◽

Diagnostic Performance ◽

Characteristic Curve ◽

Fractional Flow ◽

Performance Goal ◽

Flow Reserve

Abstract Aims Conventional fractional flow reserve (FFR) is measured invasively using a coronary guidewire equipped with a pressure sensor. A non-invasive derived FFR would eliminate risk of coronary injury, minimize technical limitations, and potentially increase adoption. We aimed to evaluate the diagnostic performance of a computational pressure-flow dynamics derived FFR (caFFR), applied to coronary angiography, compared to invasive FFR. Methods and results The FLASH FFR study was a prospective, multicentre, single-arm study conducted at six centres in China. Eligible patients had native coronary artery target lesions with visually estimated diameter stenosis of 30–90% and diagnosis of stable or unstable angina pectoris. Using computational pressure-fluid dynamics, in conjunction with thrombolysis in myocardial infarction (TIMI) frame count, applied to coronary angiography, caFFR was measured online in real-time and compared blind to conventional invasive FFR by an independent core laboratory. The primary endpoint was the agreement between caFFR and FFR, with a pre-specified performance goal of 84%. Between June and December 2018, matched caFFR and FFR measurements were performed in 328 coronary arteries. Total operational time for caFFR was 4.54 ± 1.48 min. caFFR was highly correlated to FFR (R = 0.89, P = 0.76) with a mean bias of −0.002 ± 0.049 (95% limits of agreement −0.098 to 0.093). The diagnostic performance of caFFR vs. FFR was diagnostic accuracy 95.7%, sensitivity 90.4%, specificity 98.6%, positive predictive value 97.2%, negative predictive value 95.0%, and area under the receiver operating characteristic curve of 0.979. Conclusions Using wire-based FFR as the reference, caFFR has high accuracy, sensitivity, and specificity. caFFR could eliminate the need of a pressure wire, technical error and potentially increase adoption of physiological assessment of coronary artery stenosis severity. Clinical Trial Registration URL: http://www.chictr.org.cn Unique Identifier: ChiCTR1800019522.

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P2238Prognostic value and incremental benefit of ischaemic myocardial burden subtended by non-invasive CT-derived fractional flow reserve (FFRCT) significant stenoses

European Heart Journal ◽

10.1093/eurheartj/ehz748.0716 ◽

2019 ◽

Vol 40 (Supplement_1) ◽

Author(s):

A R Ihdayhid ◽

B L Norgaard ◽

N Khav ◽

S Gaur ◽

J Leipsic ◽

...

Keyword(s):

Myocardial Infarction ◽

Fractional Flow Reserve ◽

Primary Endpoint ◽

Predictive Value ◽

Grey Zone ◽

Fractional Flow ◽

Ischaemic Myocardium ◽

Incremental Benefit ◽

Flow Reserve ◽

Fatal Myocardial Infarction

Abstract Background Fractional flow reserve derived from CT-coronary angiography (FFRCT) accurately identifies ischaemic vessels which may be associated with clinical outcomes. Its predictive value in grey zone FFRCT values between 0.7–0.8 is not defined. The technique permits estimation of burden of ischaemic myocardium subtended by FFRCT significant vessels. Purpose To evaluate the prognostic value and incremental benefit of FFRCT defined ischaemic myocardial burden when compared to FFRCT alone. Methods This is a subanalysis of NXT (Analysis of Coronary Blood-Flow Using CTA:Next-Steps), a prospective study of stable coronary artery disease (CAD) patients referred for invasive angiography (ICA) undergoing invasive FFR, CTA and FFRCT in whom treating physicians had been blinded to FFRCT results. Primary endpoint, defined as a composite of non-fatal myocardial infarction and any revascularisation, was determined in 206 patients (age 64±9.5 years, 64% male) and 618 vessels. Burden of ischaemic myocardium was defined as percentage of myocardium subtended beyond the point at which a vessel's FFRCT becomes ≤0.8 as estimated by APPROACH score (FFRCT-APPROACH). In significant FFRCT vessels, the predictive value and incremental benefit of FFRCT-APPROACH was compared with significant FFRCT (≤0.8) for primary endpoint as measured by area under the receiver operator characteristic curve (AUC). Significant ischaemic myocardial burden was defined as >10%. The incidence and relationship between the primary endpoint with each 10% increase in FFRCT-APPROACH and 0.05-unit decrease in FFRCT values ≤0.8 was determined. Results Significant FFRCT was identified in 52.9% of patients (109/206) and 29.3% of vessels (181/618). At 4.7 years median follow-up the incidence of the primary endpoint in vessels with significant FFRCT-APPROACH was 58.9% (96/163) which was comparable with vessels with significant FFRCT (55.2%,100/181; P=0.50). The predictive value of FFRCT-APPROACH for the primary endpoint was comparable with FFRCT (AUC 0.72 [95% CI 0.65–0.79] vs 0.71 [0.63–0.78], P=0.79). When combined, there was significant predictive improvement compared with FFRCT alone (AUC 0.77 [0.70–0.84]; P=0.01). The largest incremental benefit upon FFRCT was observed in vessels with FFRCT values in the grey zone between 0.70–0.80 (AUC 0.76 [0.65–0.86] vs 0.62 [0.48–0.74]; P<0.01). Each 10% increase in FFRCT-APPROACH (Adjusted-HR 1.36; 95% CI 1.16–1.60; P<0.001) and each 0.05-unit FFRCT decrease (Adjusted-HR 1.42; 1.19–1.70; P<0.001) were independently associated with significant increase in the incidence of the primary-endpoint. Conclusion In patients with stable CAD referred for ICA, the burden of ischaemic myocardium subtended by FFRCT significant vessels predicted non-fatal myocardial infarction and future revascularisation. This provided significant incremental benefit when used in combination with FFRCT particularly at FFRCT values in the grey zone between 0.7 to 0.8.

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Fractional Flow Reserve: Who Needs the Pressure Wire?

Journal of Interventional Cardiology ◽

10.1111/j.1540-8183.1999.tb00670.x ◽

1999 ◽

Vol 12 (6) ◽

pp. 425-430

Author(s):

JOZEF BARTUNEK ◽

NICO H. J. PIJLS ◽

G. JAN WILLEM BECH ◽

BERNARD BRUYNE

Keyword(s):

Fractional Flow Reserve ◽

Fractional Flow ◽

Flow Reserve ◽

Pressure Wire

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Usefulness of the Hybrid RFR-FFR Approach: Results of a Prospective and Multicenter Analysis of Diagnostic Agreement between RFR and FFR—The RECOPA (REsting Full-Cycle Ratio Comparation versus Fractional Flow Reserve (A Prospective Validation)) Study

Journal of Interventional Cardiology ◽

10.1155/2021/5522707 ◽

2021 ◽

Vol 2021 ◽

pp. 1-8

Author(s):

Juan Casanova-Sandoval ◽

Diego Fernández-Rodríguez ◽

Imanol Otaegui ◽

Teresa Gil Jiménez ◽

Marcos Rodríguez-Esteban ◽

...

Keyword(s):

Positive Predictive Value ◽

Negative Predictive Value ◽

Fractional Flow Reserve ◽

Predictive Value ◽

Primary Objective ◽

Grey Zone ◽

Fractional Flow ◽

Predictive Values ◽

Hybrid Strategy ◽

Flow Reserve

Background. The resting full‐cycle ratio (RFR) is a novel resting index which in contrast to the gold standard (fractional flow reserve (FFR)) does not require maximum hyperemia induction. The objectives of this study were to evaluate the agreement between RFR and FFR with the currently recommended thresholds and to design a hybrid RFR-FFR ischemia detection strategy, allowing a reduction of coronary vasodilator use. Materials and Methods. Patients subjected to invasive physiological study in 9 Spanish centers were prospectively recruited between April 2019 and March 2020. Sensitivity and specificity studies were made to assess diagnostic accuracy between the recommended levels of RFR ≤0.89 and FFR ≤0.80 (primary objective) and to determine the RFR “grey zone” in order to define a hybrid strategy with FFR affording 95% global agreement compared with FFR alone (secondary objective). Results. A total of 380 lesions were evaluated in 311 patients. Significant correlation was observed (R2 = 0.81; P < 0.001 ) between the two techniques, with 79% agreement between RFR ≤ 0.89 and FFR ≤ 0.80 (positive predictive value, 68%, and negative predictive value, 80%). The hybrid RFR-FFR strategy, administering only adenosine in the “grey zone” (RFR: 0.86 to 0.92), exhibited an agreement of over 95% with FFR, with high predictive values (positive predictive value, 91%, and negative predictive value, 92%), reducing the need for vasodilators by 58%. Conclusions. Dichotomous agreement between RFR and FFR with the recommended thresholds is significant but limited. The adoption of a hybrid RFR-FFR strategy affords very high agreement, with minimization of vasodilator use.

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P1250Validation of quantitative flow reserve and residual quantitative flow reserve to predict fractional flow reserve post stenting from the DOCTORS study population

European Heart Journal ◽

10.1093/eurheartj/ehz748.0208 ◽

2019 ◽

Vol 40 (Supplement_1) ◽

Author(s):

B G Guillon ◽

V R Rubimbura ◽

S F Fournier ◽

N A Amabile ◽

C C P Chi Pan ◽

...

Keyword(s):

Fractional Flow Reserve ◽

Pearson Correlation ◽

Correlation Coefficients ◽

Mean Value ◽

Fractional Flow ◽

Mean Values ◽

Flow Reserve ◽

Pressure Wire ◽

Study Population ◽

Quantitative Flow

Abstract Background Quantitative flow reserve (QFR) is a computation of fractional flow reserve (FFR) based on angiography without use of a pressure wire. The ability to predict post-PCI FFR using residual QFR after virtual stenting (pre-PCI), and using QFR (post-PCI) remains unknown. We sought to evaluate the correlation and diagnosis accuracy of residual QFR and post-PCI QFR to predict post-PCI FFR. Methods From the DOCTORS (Does Optical Coherence Tomography Optimize Results of Stenting) study population, we blindly analyzed the following from angiography, and compared them to post-PCI FFR: pre-PCI residual contrast QFR (cQFR) and fixed QFR (fQFR), and post-PCI cQFR and fQFR. Results 93 post-PCI QFR measurements and 84 residual QFR measurements were compared to post-PCI FFR measurements in 93 patients. Compared to the post-PCI FFR mean value of 0.92±0.05, mean values of residual cQFR, residual fQFR, post-PCI cQFR and post-PCI fQFR were, respectively: 0.94±0.05, 0.93±0.05, 0.93±0.06 and 0.93±0.05 (p values >0.05 for all pairs except for residual cQFR versus FFR (p=0.01)). Pearson correlation coefficients of residual cQFR, residual fQFR, post-PCI cQFR and post-PCI fQFR compared with post-PCI FFR were, respectively: 0.62, (95% CI: 0.46–0.73); 0.61, (95% CI: 0.45–0.73); 0.75, (95% CI: 0.64–0.83) and 0.73, (95% CI: 0.62–0.81). Area under the curves for these indices with a post-PCI FFR cutoff value of 0.90 were, respectively: 0.79, 0.78, 0.85 and 0.84. Conclusions cQFR and fQFR correlated well and had similar diagnostic performance. Pre-PCI QFR analysis with virtual PCI, and post-PCI QFR analysis, correlated well with post-PCI FFR, and had similar diagnostic accuracy. Further studies are needed to prospectively validate a QFR-guided PCI strategy.

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