Coronary Fractional Flow Reserve Research Articles

Functional stress imaging to predict abnormal coronary fractional flow reserve: the PACIFIC 2 study.

AimsThe diagnostic performance of non-invasive imaging in patients with prior coronary artery disease (CAD) has not been tested in prospective head-to-head comparative studies. The aim of this study was to compare the diagnostic performance of qualitative single-photon emission computed tomography (SPECT), quantitative positron emission tomography (PET), and qualitative magnetic resonance imaging (MRI) in patients with a prior myocardial infarction (MI) or percutaneous coronary intervention (PCI).Methods and resultsIn this prospective clinical study, all patients with prior MI and/or PCI and new symptoms of ischaemic CAD underwent 99mTc-tetrofosmin SPECT, [15O]H2O PET, and MRI, followed by invasive coronary angiography with fractional flow reserve (FFR) in all coronary arteries. All modalities were interpreted by core laboratories. Haemodynamically significant CAD was defined by at least one coronary artery with an FFR ≤0.80. Among the 189 enrolled patients, 63% had significant CAD. Sensitivity was 67% (95% confidence interval 58–76%) for SPECT, 81% (72–87%) for PET, and 66% (56–75%) for MRI. Specificity was 61% (48–72%) for SPECT, 65% (53–76%) for PET, and 62% (49–74%) for MRI. Sensitivity of PET was higher than SPECT (P = 0.016) and MRI (P = 0.014), whereas specificity did not differ among the modalities. Diagnostic accuracy for PET (75%, 68–81%) did not statistically differ from SPECT (65%, 58–72%, P = 0.03) and MRI (64%, 57–72%, P = 0.052). Using FFR < 0.75 as a reference, accuracies increased to 69% (SPECT), 79% (PET), and 71% (MRI).ConclusionIn this prospective head-to-head comparative study, SPECT, PET, and MRI did not show a significantly different accuracy for diagnosing FFR defined significant CAD in patients with prior PCI and/or MI. Overall diagnostic performances, however, were discouraging and the additive value of non-invasive imaging in this high-risk population is questionable.

The impact of deep learning reconstruction on image quality and coronary CT angiography-derived fractional flow reserve values.

To explore the impact of deep learning reconstruction (DLR) on image quality and machine learning-based coronary CT angiography (CTA)-derived fractional flow reserve (CT-FFRML) values. Thirty-three consecutive patients with known or suspected coronary artery disease who underwent coronary CTA and subsequent invasive coronary angiography were enrolled. DLR was compared with filtered back projection (FBP), statistical-based iterative reconstruction (SBIR), model-based iterative reconstruction (MBIR) Cardiac, and MBIR Cardiac sharp for objective image qualities of coronary CTA. Invasive fractional flow reserve (FFR) and quantitative flow ratio (QFR) were used as the reference standards. The diagnostic performances of different reconstruction approach-based CT-FFRML were calculated. A total of 182 lesions in 33 patients were enrolled for analysis. The image quality of DLR was superior to the others. There were no significant differences in the CT-FFRML values among these five approaches (all p > 0.05). Of the 182 lesions, 17 had invasive FFR results, and 70 had QFR results. Using FFR as a reference, MBIR Cardiac, MBIR Cardiac sharp, and DLR achieved equal diagnostic performance, slightly higher than the other reconstruction approaches (MBIR Cardiac, MBIR Cardiac sharp, and DLR: AUC = 0.82, FBP and AIDR: AUC = 0.78, all p > 0.05). Using QFR as a reference, the AUCs of FBP, SBIR, MBIR Cardiac, MBIR Cardiac sharp, and DLR were 0.83, 0.81, 0.86, 0.84, and 0.83, respectively (all p > 0.05). Our study showed that the DLR algorithm improved image quality, but there were no significant differences in the CT-FFRML values and diagnostic performance among different reconstruction approaches. • Deep learning-based image reconstruction (DLR) improves the image quality of coronary CTA. • CT-FFRML values and diagnostic performance of DLR revealed no significant differences compared to other reconstruction approaches.

Synergistic prognostic value of coronary distensibility index and fractional flow reserve based cCTA for major adverse cardiac events in patients with Coronary artery disease

BackgroundCoronary distensibility index (CDI), as an early predictor of cardiovascular diseases, has the potential to complement coronary computed tomography angiography (cCTA)-derived fractional flow reserve (CT-FFR) for predicting major adverse cardiac events (MACEs). Thus, the prognostic value of CT-FFR combined with CDI for MACEs is worth exploring.MethodsPatients with a moderate or severe single left anterior descending coronary artery stenosis were included and underwent FFR and CDI analysis based on cCTA, followed up at least 1 year, and recorded MACEs. Multivariate logistic regression analysis was performed to determine independent predictors of MACEs. The area under of receiver operating characteristic (ROC) curve was used to evaluated evaluate the diagnostic performance of CT-FFR, CDI, and a combination of the two.ResultsAll the vessel-specific data were from LAD. 150 patients were analysed. 55 (37%) patients experienced MACEs during follow-up. Patients with CT-FFR ≤ 0.8 had higher percentage of MACEs compared with CT-FFR > 0.8 (56.3% vs.7.3%, p < 0.05). Patients’ CDI was significantly decreased in MACEs group compared with non-MACEs group (p < 0.05). Multivariate analysis revealed that diabetes (p = 0.025), triglyceride (p = 0.015), CT-FFR ≤ 0.80 (p = 0.038), and CDI (p < 0.001) are independent predictors of MACEs. According to ROC curve analysis, CT-FFR combined CDI showed incremental diagnostic performance over CT-FFR alone for prediction of MACEs (AUC = 0.831 vs. 0.656, p = 0.0002).ConclusionOur study provides initial evidence that combining CDI with CT-FFR shows incremental discriminatory power for MACEs over CT-FFR alone, independent of clinical risk factors. Diabetes and triglyceride are also associated with MACEs.

Fractal Analysis of Dynamic Stress CT-Perfusion Imaging for Detection of Hemodynamically Relevant Coronary Artery Disease

BackgroundCombined computed tomography–derived myocardial blood flow (CTP-MBF) and computed tomography angiography (CTA) has shown good diagnostic performance for detection of coronary artery disease (CAD). However, fractal analysis might provide additional insight into ischemia pathophysiology by characterizing multiscale perfusion patterns and, therefore, may be useful in diagnosing hemodynamically significant CAD. ObjectivesThe purpose of this study was to investigate, in a multicenter setting, whether fractal analysis of perfusion improves detection of hemodynamically relevant CAD over myocardial blood flow quantification (CTP-MBF) using dynamic, 4-dimensional, dynamic stress myocardial computed tomography perfusion (CTP) imaging. MethodsIn total, 7 centers participating in the prospective AMPLIFiED (Assessment of Myocardial Perfusion Linked to Infarction and Fibrosis Explored with Dual-source CT) study acquired CTP and CTA data in patients with suspected or known CAD. Hemodynamically relevant CAD was defined as ≥90% stenosis on invasive coronary angiography or fractional flow reserve <0.80. Both fractal analysis and CTP-MBF quantification were performed on CTP images and were combined with CTA results. ResultsThis study population included 127 participants, among them 61 patients, or 79 vessels, with CAD as per invasive reference standard. Compared with the combination of CTP-MBF and CTA, combined fractal analysis and CTA improved sensitivity on the per-patient level from 84% (95% CI: 72%-92%) to 95% (95% CI: 86%-99%; P = 0.01) and specificity from 70% (95% CI: 57%-82%) to 89% (95% CI: 78%-96%; P = 0.02). The area under the receiver-operating characteristic curve improved from 0.83 (95% CI: 0.75-0.90) to 0.92 (95% CI: 0.86-0.98; P = 0.01). ConclusionsFractal analysis constitutes a quantitative and pathophysiologically meaningful approach to myocardial perfusion analysis using dynamic stress CTP, which improved diagnostic performance over CTP-MBF when combined with anatomical information from CTA.

D-14 | Efficacy of contrast Diastolic Hyperemia-Free Ratio (Contrast - DFR) in comparison to coronary Fractional Flow Reserve with adenosine and Diastolic Hyperemia-Free Ratio (DFR)

BackgroundCoronary fractional flow reserve (FFR) is recommended as the gold standard method in evaluating intermediate coronary stenosis. Various methodologies have been reported using Diastolic Hyperemia – Free Ratio (DFR) and Instantaneous wave - free ratio.AimTo compare the contrast induced Pd/Pa ratio (DFR) with DFR and FFR.MethodsWe enrolled 19 consecutive patients with 20 intermediate lesions who underwent Diastolic pressure ratio measurement using DFR baseline Pd/Pa was calculated. A single contrast medium injection of 6 ml (3 ml/s) was performed manually and a Contrast DFR was measured within 10 seconds of injection.Following which coronary FFR measurement was performed using intravenous injection of adenosine to induce maximal hyperemia using 140 mcg/kg/min for 2 minutes and when it was ≤ 0.80, the intermediate lesion was considered as significant.Abnormal DFR was defined as cut off value 0.89, Contrast DFR as cut off value 0.80, FFR as cut off value 0.80.ResultsDiastolic pressure ratio was identified as significant in 10 lesions of 20 (50%) with a mean of 0.89 (range:0.66-1). The Contrast DFR was identified significant in 9 lesions of 20 (45%) with a mean of 0.80 (range of 0.67-0.97). FFR was abnormal in 9 lesions of 20 (45%) with a mean of 0.82 (range 0.63-0.97). A substantial positive correlation between FFR and contrast DFR values was detected (0.76) versus comparing correlation of DFR versus FFR (0.59).ConclusionsDisclosuresT. Raxwal Nothing to disclose. D. Parekh Nothing to disclose. R. M. Akel Nothing to disclose. BackgroundCoronary fractional flow reserve (FFR) is recommended as the gold standard method in evaluating intermediate coronary stenosis. Various methodologies have been reported using Diastolic Hyperemia – Free Ratio (DFR) and Instantaneous wave - free ratio. Coronary fractional flow reserve (FFR) is recommended as the gold standard method in evaluating intermediate coronary stenosis. Various methodologies have been reported using Diastolic Hyperemia – Free Ratio (DFR) and Instantaneous wave - free ratio. AimTo compare the contrast induced Pd/Pa ratio (DFR) with DFR and FFR. To compare the contrast induced Pd/Pa ratio (DFR) with DFR and FFR. MethodsWe enrolled 19 consecutive patients with 20 intermediate lesions who underwent Diastolic pressure ratio measurement using DFR baseline Pd/Pa was calculated. A single contrast medium injection of 6 ml (3 ml/s) was performed manually and a Contrast DFR was measured within 10 seconds of injection.Following which coronary FFR measurement was performed using intravenous injection of adenosine to induce maximal hyperemia using 140 mcg/kg/min for 2 minutes and when it was ≤ 0.80, the intermediate lesion was considered as significant.Abnormal DFR was defined as cut off value 0.89, Contrast DFR as cut off value 0.80, FFR as cut off value 0.80. We enrolled 19 consecutive patients with 20 intermediate lesions who underwent Diastolic pressure ratio measurement using DFR baseline Pd/Pa was calculated. A single contrast medium injection of 6 ml (3 ml/s) was performed manually and a Contrast DFR was measured within 10 seconds of injection. Following which coronary FFR measurement was performed using intravenous injection of adenosine to induce maximal hyperemia using 140 mcg/kg/min for 2 minutes and when it was ≤ 0.80, the intermediate lesion was considered as significant. Abnormal DFR was defined as cut off value 0.89, Contrast DFR as cut off value 0.80, FFR as cut off value 0.80. ResultsDiastolic pressure ratio was identified as significant in 10 lesions of 20 (50%) with a mean of 0.89 (range:0.66-1). The Contrast DFR was identified significant in 9 lesions of 20 (45%) with a mean of 0.80 (range of 0.67-0.97). FFR was abnormal in 9 lesions of 20 (45%) with a mean of 0.82 (range 0.63-0.97). A substantial positive correlation between FFR and contrast DFR values was detected (0.76) versus comparing correlation of DFR versus FFR (0.59). Diastolic pressure ratio was identified as significant in 10 lesions of 20 (50%) with a mean of 0.89 (range:0.66-1). The Contrast DFR was identified significant in 9 lesions of 20 (45%) with a mean of 0.80 (range of 0.67-0.97). FFR was abnormal in 9 lesions of 20 (45%) with a mean of 0.82 (range 0.63-0.97). A substantial positive correlation between FFR and contrast DFR values was detected (0.76) versus comparing correlation of DFR versus FFR (0.59). Conclusions DisclosuresT. Raxwal Nothing to disclose. D. Parekh Nothing to disclose. R. M. Akel Nothing to disclose. T. Raxwal Nothing to disclose. D. Parekh Nothing to disclose. R. M. Akel Nothing to disclose.

Structure (Epicardial Stenosis) and Function (Microvascular Dysfunction) That Influence Coronary Fractional Flow Reserve Estimation

Background. The treatment of coronary stenosis is decided by performing high risk invasive surgery to generate the fractional flow reserve diagnostics index, a ratio of distal to proximal pressures in respect of coronary atherosclerotic plaques. Non-invasive methods are a need of the times that necessitate the use of mathematical models of coronary hemodynamic physiology. This study proposes an extensible mathematical description of the coronary vasculature that provides an estimate of coronary fractional flow reserve. Methods. By adapting an existing computational model of human coronary blood flow, the effects of large vessel stenosis and microvascular disease on fractional flow reserve were quantified. Several simulations generated flow and pressure information, which was used to compute fractional flow reserve under several conditions including focal stenosis, diffuse stenosis, and microvascular disease. Sensitivity analysis was used to uncover the influence of model parameters on fractional flow reserve. The model was simulated as coupled non-linear ordinary differential equations and numerically solved using our implicit higher order method. Results. Large vessel stenosis affected fractional flow reserve. The model predicts that the presence, rather than severity, of microvascular disease affects coronary flow deleteriously. Conclusions. The model provides a computationally inexpensive instrument for future in silico coronary blood flow investigations as well as clinical-imaging decision making. A combination of focal and diffuse stenosis appears to be essential to limit coronary flow. In addition to pressure measurements in the large epicardial vessels, diagnosis of microvascular disease is essential. The independence of the index with respect to heart rate suggests that computationally inexpensive steady state simulations may provide sufficient information to reliably compute the index.

Cost-effectiveness in diagnosis of stable angina patients: a decision-analytical modelling approach

ObjectiveGiven recent data on published diagnostic accuracies, this study sought to determine the most cost-effective diagnostic strategy for detection of significant coronary artery disease (CAD) in stable angina patients using...

Impact of machine-learning-based coronary computed tomography angiography-derived fractional flow reserve on decision-making in patients with severe aortic stenosis undergoing transcatheter aortic valve replacement.

To evaluate feasibility and diagnostic performance of coronary CT angiography (CCTA)-derived fractional flow reserve (CT-FFR) for detection of significant coronary artery disease (CAD) and decision-making in patients with severe aortic stenosis (AS) undergoing transcatheter aortic valve replacement (TAVR) to potentially avoid additional pre-TAVR invasive coronary angiography (ICA). Consecutive patients with severe AS (n = 95, 78.6 ± 8.8 years, 53% female) undergoing pre-procedural TAVR-CT followed by ICA with quantitative coronary angiography were retrospectively analyzed. CCTA datasets were evaluated using CAD Reporting and Data System (CAD-RADS) classification. CT-FFR measurements were computed using an on-site machine-learning algorithm. A combined algorithm was developed for decision-making to determine if ICA is needed based on pre-TAVR CCTA: [1] all patients with CAD-RADS ≥ 4 are referred for ICA; [2] patients with CAD-RADS 2 and 3 are evaluated utilizing CT-FFR and sent to ICA if CT-FFR ≤ 0.80; [3] patients with CAD-RADS < 2 or CAD-RADS 2-3 and normal CT-FFR are not referred for ICA. Twelve patients (13%) had significant CAD (≥ 70% stenosis) on ICA and were treated with PCI. Twenty-eight patients (30%) showed CT-FFR ≤ 0.80 and 24 (86%) of those were reported to have a maximum stenosis ≥ 50% during ICA. Using the proposed algorithm, significant CAD could be identified with a sensitivity, specificity, and positive and negative predictive value of 100%, 78%, 40%, and 100%, respectively, potentially decreasing the number of necessary ICAs by 65 (68%). Combination of CT-FFR and CAD-RADS is able to identify significant CAD pre-TAVR and bears potential to significantly reduce the number of needed ICAs. • Coronary CT angiography-derived fractional flow reserve (CT-FFR) using machine learning together with the CAD Reporting and Data System (CAD-RADS) classification safely identifies significant coronary artery disease based on quantitative coronary angiography in patients prior to transcatheter aortic valve replacement. • The combination of CT-FFR and CAD-RADS enables decision-making and bears the potential to significantly reduce the number of needed invasive coronary angiographies.

The role of coronary flow reserve (CFR) and fractional flow reserve (FFR) in acute coronary syndrome - systematic review

The methods used to appreciate the degree of coronary stenosis such as CFR and FFR, come to complement the coronary angiography and help the interventional physician during PCI. Furthermore, CFR and FFR measured immediately after reperfusion, in patients with ACS, may act as a prognosis factor for myocardial infarction.Changes in coronary microcirculation in patients with ACS and NSTEMI correlate to the degree and extent of tissue lysis processes.So far, there are few data revealing the degree of microvascular bed injury and vasodilator capacity in patients with acute myocardial infarction. In this article, we will refer to some studies in the field.

Fractal analysis of 4D dynamic myocardial stress-CT perfusion imaging differentiates micro- and macrovascular ischemia in a multi-center proof-of-concept study

Fractal analysis of dynamic, four-dimensional computed tomography myocardial perfusion (4D-CTP) imaging might have potential for noninvasive differentiation of microvascular ischemia and macrovascular coronary artery disease (CAD) using fractal dimension (FD) as quantitative parameter for perfusion complexity. This multi-center proof-of-concept study included 30 rigorously characterized patients from the AMPLIFiED trial with nonoverlapping and confirmed microvascular ischemia (nmicro = 10), macrovascular CAD (nmacro = 10), or normal myocardial perfusion (nnormal = 10) with invasive coronary angiography and fractional flow reserve (FFR) measurements as reference standard. Perfusion complexity was comparatively high in normal perfusion (FDnormal = 4.49, interquartile range [IQR]:4.46–4.53), moderately reduced in microvascular ischemia (FDmicro = 4.37, IQR:4.36–4.37), and strongly reduced in macrovascular CAD (FDmacro = 4.26, IQR:4.24–4.27), which allowed to differentiate both ischemia types, p < 0.001. Fractal analysis agreed excellently with perfusion state (κ = 0.96, AUC = 0.98), whereas myocardial blood flow (MBF) showed moderate agreement (κ = 0.77, AUC = 0.78). For detecting CAD patients, fractal analysis outperformed MBF estimation with sensitivity and specificity of 100% and 85% versus 100% and 25%, p = 0.02. In conclusion, fractal analysis of 4D-CTP allows to differentiate microvascular from macrovascular ischemia and improves detection of hemodynamically significant CAD in comparison to MBF estimation.

Prognostic Value of Coronary Angiography-Derived Fractional Flow Reserve Immediately After Stenting.

ObjectivesThe aim of this study was to investigate the potential prognostic value of post-percutaneous coronary intervention (PCI) angiography-derived fractional flow reserve (FFR) and its gradient across the stent.BackgroundPost-PCI FFR and its gradient across the stent have been proved to be associated with clinical outcomes. However, little is known about the prognostic value of post-PCI coronary angiography-derived FFR and its gradient across the stent.MethodsPatients diagnosed with coronary heart disease and participated in drug-eluting stent (DES) clinical trials for stent implantation in a single center were included for this retrospective analysis. A novel coronary angiography-derived FFR (caFFR) and its gradient across the stent were calculated offline using two projections from coronary angiography performed after PCI. Clinical follow-up was completed at 9 months after the index procedure and the primary outcome was target vessel failure (TVF), defined as a composite of target vessel-related myocardial infarction (MI), target vessel-related revascularization (TVR), and cardiac death. Coronary angiography was also performed at the 9 months follow-up time to get data of late lumen loss (LLL) and percent diameter stenosis (%DS).ResultsA total of 159 vessels in 136 patients were analyzed. The mean value of post-PCI caFFR was 0.90 ± 0.06. The median value of trans-stent caFFR gradient (ΔcaFFRstent) was 0.04 (interquartile range 0.02–0.08). ΔcaFFRstent>0 was demonstrated in 147 vessels (92.45%). The TVF rate was significantly higher in patients with post-PCI caFFR < 0.90 (4 [8.16%] vs. 1 [1.15%], P = 0.037), which was mainly achieved by the difference between the TVR rate. In the subgroup with lesions located in the left anterior descending coronary artery (LAD), post-PCI caFFR was an independent predictor of LLL (β = −1.07, 95% CI: −1.74 to −0.39, P = 0.002) and %DS at follow-up (β = −30.24, 95% CI: −56.44 to −4.04, P = 0.025), ΔcaFFRstent was an independent predictor of LLL (β=0.98, 95% CI:0.13–1.83, P = 0.026).ConclusionSuboptimal post-PCI caFFR and trans-stent caFFR gradient were common among vessels immediately after stenting. Lower post-PCI caFFR was associated with a higher rate of 9-month TVF. After LAD PCI, both post-PCI caFFR and its gradient across stent were independent predictors of the neointimal proliferation of the target vessel evaluated by LLL and %DS at follow-up.

Diagnostic efficacy of CCTA and CT-FFR based on risk factors for myocardial ischemia

BackgroundCoronary artery coronary computed tomography angiography (CCTA) can observe the degree of coronary artery stenosis and fractional flow reserve (FFR) can diagnose hemodynamic abnormalities caused by coronary artery stenosis. However, noninvasive imaging examination that can both observe the above two methods at the same time has not yet been elucidated.ObjectiveTo investigate the diagnostic efficacy of CCTA and computed tomography-derived fractional flow reserve (CT-FFR) based on different risk factors for myocardial ischemia.MethodsPatients undergoing CCTA in our hospital from August 18, 2020 to April 28, 2021 were randomly selected, and the data were subjected to CT-FFR analysis. Vascular characteristics were measured, including total plaque volume, calcified plaque volume, non-calcified plaque volume, plaque length, and lumen stenosis, and the patients were categorized into a non-ischemia group (FFR > 0.8) and an ischemia group (FFR ≤ 0.8). Plaque characteristics were compared between the two groups, and logistic regression analysis was employed to explore the correlations between plaque characteristics and ischemic lesions.ResultsFrom a total of 122 patients enrolled in the study, there were 218 vascular branches with FFR > 0.8 and 174 vascular branches with FFR ≤ 0.8. There were significant group differences in total plaque volume, calcified plaque volume, plaque length, and lumen stenosis > 50% (n). The obtained data were as follows: non-ischemic group 10.57 (4.80, 259.65), ischemic group 14.87 (3.39, 424.45), Z = 9.772, p = 0.002, non-ischemic group 10.57 (0, 168.77), ischemic group 14.87 (0, 191.00), Z = 2.503, p ≤ 0.001), non-ischemic group 8.17 (37.05, 40.53), ischemic group 8.38 (56.66, 86.47), Z = 5.923, p = 0.016, and lumen stenosis > 50%, non-ischemic group 46, ischemic group 90, x2 = 14.77, p ≤ 0.001. The regression analysis results indicated that total plaque volume, calcified plaque volume, plaque length and lumen stenosis > 50% were risk factors for myocardial ischemia, with ORs and p values of (2.311, p = 0.002), (1.021, p = 0.004), (2.159, p < 0.001), and (0.181, p < 0.001), respectively.ConclusionTotal plaque volume, calcified plaque volume, plaque length and lumen stenosis > 50% are predictors for myocardial ischemia. Coronary artery CCTA combined with CT-FFR could simultaneously observe the anatomical stenosis and evaluate myocardial blood supply at the functional level. Thus, myocardial ischemia could be better diagnosed.

Diagnostic Accuracy of Coronary Angiography-Based Vessel Fractional Flow Reserve (vFFR) Virtual Stenting.

3D coronary angiography-based vessel fractional flow reserve (vFFR) proved to be an accurate diagnostic alternative to invasively measured pressure wire based fractional flow reserve (FFR). The ability to compute post-PCI vFFR using pre-PCI vFFR virtual stent analysis is unknown. We aimed to assess the feasibility and diagnostic accuracy of pre-PCI vFFR virtual stenting analysis (residual vFFR) with post-PCI FFR as a reference. This is an observational, single-center retrospective cohort study including consecutive patients from the FFR-SEARCH registry. We blindly calculated residual vFFR from pre-PCI angiograms and compared them to invasive pressure-wire based post-PCI FFR. Inclusion criteria involved presentation with either stable or unstable angina or non-ST elevation myocardial infarction (NSTEMI), ≥1 significant stenosis in one of the epicardial coronary arteries (percentage diameter stenosis of >70% by QCA or hemodynamically relevant stenosis with FFR ≤0.80) and pre procedural angiograms eligible for vFFR analysis. Exclusion criteria comprised patients with ST elevation myocardial infarction (STEMI), coronary bypass grafts, cardiogenic shock or severe hemodynamic instability. Eighty-one pre-PCI residual vFFR measurements were compared to post-PCI FFR and post-PCI vFFR measurements. Mean residual vFFR was 0.91 ± 0.06, mean post-PCI FFR 0.91 ± 0.06 and mean post-PCI vFFR was 0.92 ± 0.05. Residual vFFR showed a high linear correlation (r = 0.84) and good agreement (mean difference (95% confidence interval): 0.005 (−0.002–0.012)) with post-PCI FFR, as well as with post-PCI-vFFR (r = 0.77, mean difference −0.007 (−0.015–0.0003)). Residual vFFR showed good accuracy in the identification of lesions with post-PCI FFR < 0.90 (sensitivity 94%, specificity 71%, area under the curve (AUC) 0.93 (95% CI: 0.86–0.99), p < 0.001). Virtual stenting using vFFR provided an accurate estimation of post-PCI FFR and post-PCI vFFR. Further studies are needed to prospectively validate a vFFR-guided PCI strategy.

AI Evaluation of Stenosis on Coronary CTA, Comparison With Quantitative Coronary Angiography and Fractional Flow Reserve: A CREDENCE Trial Substudy

BackgroundClinical reads of coronary computed tomography angiography (CTA), especially by less experienced readers, may result in overestimation of coronary artery disease stenosis severity compared with expert interpretation. Artificial intelligence (AI)-based solutions applied to coronary CTA may overcome these limitations. ObjectivesThis study compared the performance for detection and grading of coronary stenoses using artificial intelligence–enabled quantitative coronary computed tomography (AI-QCT) angiography analyses to core lab–interpreted coronary CTA, core lab quantitative coronary angiography (QCA), and invasive fractional flow reserve (FFR). MethodsCoronary CTA, FFR, and QCA data from 303 stable patients (64 ± 10 years of age, 71% male) from the CREDENCE (Computed TomogRaphic Evaluation of Atherosclerotic DEtermiNants of Myocardial IsChEmia) trial were retrospectively analyzed using an Food and Drug Administration–cleared cloud-based software that performs AI-enabled coronary segmentation, lumen and vessel wall determination, plaque quantification and characterization, and stenosis determination. ResultsDisease prevalence was high, with 32.0%, 35.0%, 21.0%, and 13.0% demonstrating ≥50% stenosis in 0, 1, 2, and 3 coronary vessel territories, respectively. Average AI-QCT analysis time was 10.3 ± 2.7 minutes. AI-QCT evaluation demonstrated per-patient sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of 94%, 68%, 81%, 90%, and 84%, respectively, for ≥50% stenosis, and of 94%, 82%, 69%, 97%, and 86%, respectively, for detection of ≥70% stenosis. There was high correlation between stenosis detected on AI-QCT evaluation vs QCA on a per-vessel and per-patient basis (intraclass correlation coefficient = 0.73 and 0.73, respectively; P < 0.001 for both). False positive AI-QCT findings were noted in in 62 of 848 (7.3%) vessels (stenosis of ≥70% by AI-QCT and QCA of <70%); however, 41 (66.1%) of these had an FFR of <0.8. ConclusionsA novel AI-based evaluation of coronary CTA enables rapid and accurate identification and exclusion of high-grade stenosis and with close agreement to blinded, core lab–interpreted quantitative coronary angiography. (Computed TomogRaphic Evaluation of Atherosclerotic DEtermiNants of Myocardial IsChEmia [CREDENCE]; NCT02173275)

Prognostic Value of Coronary CT Angiography-Derived Fractional Flow Reserve in Non-obstructive Coronary Artery Disease: A Prospective Multicenter Observational Study

Coronary artery disease (CAD) is a major contributor to morbidity and mortality worldwide. Myocardial ischemia may occur in patients with normal or non-obstructive CAD on invasive coronary angiography (ICA). The comprehensive evaluation of coronary CT angiography (CCTA) integrated with fractional flow reserve derived from CCTA (CT-FFR) to CAD may be essential to improve the outcomes of patients with non-obstructive CAD. China CT-FFR Study-2 (ChiCTR2000031410) is a large-scale prospective, observational study in 29 medical centers in China. The primary purpose is to uncover the relationship between the CCTA findings (including CT-FFR) and the outcome of patients with non-obstructive CAD. At least 10,000 patients with non-obstructive CAD but without previous revascularization will be enrolled. A 5-year follow-up will be performed. The primary endpoint is the occurrence of major adverse cardiovascular events (MACE), including all-cause mortality, non-fatal myocardial infarct, unplanned revascularization, and hospitalization for unstable angina. Clinical characteristics, laboratory and imaging examination results will be collected to analyze their prognostic value.

Influence of diabetes mellitus on the diagnostic performance of machine learning-based coronary CT angiography-derived fractional flow reserve: a multicenter study.

To examine the diagnostic accuracy of machine learning-based coronary CT angiography-derived fractional flow reserve (FFRCT) in diabetes mellitus (DM) patients. In total, 484 patients with suspected or known coronary artery disease from 11 Chinese medical centers were retrospectively analyzed. All patients underwent CCTA, FFRCT, and invasive FFR. The patients were further grouped into mild (25~49 %), moderate (50~69 %), and severe (≥ 70 %) according to CCTA stenosis degree and Agatston score < 400 and Agatston score ≥ 400 groups according to coronary artery calcium severity. Propensity score matching (PSM) was used to match DM (n =112) and non-DM (n =214) groups. Sensitivity, specificity, accuracy, and area under the curve (AUC) with 95 % confidence interval (CI) were calculated and compared. Sensitivity, specificity, accuracy, and AUC of FFRCT were 0.79, 0.96, 0.87, and 0.91 in DM patients and 0.82, 0.93, 0.89, and 0.89 in non-DM patients without significant difference (all p > 0.05) on a per-patient level. The accuracies of FFRCT had no significant difference among different coronary stenosis subgroups and between two coronary calcium subgroups (all p > 0.05) in the DM and non-DM groups. After PSM grouping, the accuracies of FFRCT were 0.88 in the DM group and 0.87 in the non-DM group without a statistical difference (p > 0.05). DM has no negative impact on the diagnostic accuracy of machine learning-based FFRCT. • ML-based FFRCT has a high discriminative accuracy of hemodynamic ischemia, which is not affected by DM. • FFRCT was superior to the CCTA alone for the detection of ischemia relevance of coronary artery stenosis in both DM and non-DM patients. • Coronary calcification had no significant effect on the diagnostic accuracy of FFRCT to detect ischemia in DM patients.

Hemodynamic characteristics expose the atherosclerotic severity in coronary main arteries: One-dimensional and three-dimensional approaches

Computed tomography coronary angiography image-based noninvasive virtual fractional flow reserve (vFFR) is a promising clinical practice to determine the physiological condition of coronary lesions. vFFR is the key factor in the diagnosis of coronary plaque. The purpose of this study is to detect the coronary main arteries lesion severity by using 1D (one-dimensional) hemodynamic factors compared to 3D (three-dimensional) heart flow computational models. The results provide the hemodynamic properties of the intraluminal condition by evaluating the vFFR. The computational burden of 3D hemodynamic simulations is one of the important drawbacks in most clinical cases. At first, we have established comparative results between vFFR3D (vFFR in 3D) and published results in the maximal hyperemic flow conditions. Then, we have employed statistical analysis including Pearson correlation test, Bland–Altman test, and computation time test for vFFR3D compared with the vFFR1D (vFFR in 1D) results. We have observed that the vFFR3D and vFFR1D results do not significantly differ as a function of stenosis length, type (concentric or eccentric), or location in the coronary artery. Pearson's product moment was found as r=0.9661,p&amp;lt;0.0001 illustrating a strong correlation between vFFR1D and vFFR3D. In both 3D and 1D cases, the results suggest that proximal stenosis is more severe compared to a distal one, even if they provide the same reduction in lumen (80% or 90% area of stenosis). The 1D inexpensive computational results vFFR1D can be used to predict the severity of atherosclerotic plaque in clinical procedures.

Research progress in derivative indicators of coronary fractional flow reserve

冠心病严重影响我国居民健康。冠状动脉造影可以明确是否存在冠状动脉粥样硬化狭窄，但无法准确地判定狭窄是否引起心肌缺血。血流储备分数是目前使用最广泛的冠状动脉生理学评价指标，能识别引起心肌缺血的冠状动脉狭窄病变。血流储备分数的相关衍生指标相继出现，简化了血流储备分数的测量过程，有助于推广冠状动脉生理功能评价指标在临床中的应用。本文将对冠状动脉血流储备分数衍生指标的原理、研究证据及优缺点做出总结梳理。.

Coronary CT angiography-derived fractional flow reserve in-stable angina: association with recurrent chest pain.

AimsThe aim of this study was to evaluate the association between coronary computed tomography angiography (CCTA)-derived fractional flow reserve (FFRCT) and recurrent chest pain (CP) at 1-year follow-up in patients with stable angina pectoris (SAP).Methods and resultsStudy of patients (n = 267) with SAP who underwent CCTA and FFRCT testing; 236 (88%) underwent invasive coronary angiography; and 87 (33%) were revascularized. Symptomatic status at 1-year follow-up was gathered by a structured interview. Three different FFRCT algorithms were applied using the following criteria for abnormality: (i) 2 cm-FFRCT ≤0.80; (ii) d-FFRCT ≤0.80; and (iii) a combination in which both a d-FFRCT ≤0.80 and a ΔFFRCT ≥0.06 must be present in the same vessel (c-FFRCT). Patients were classified into two groups based on the FFRCT test result and revascularization: completely revascularized/normal (CRN), patients in whom all coronary arteries with an abnormal FFRCT test result were revascularized or patients with completely normal FFRCT test results, and incompletely revascularized (IR), patients in whom ≥1 coronary artery with an abnormal FFRCT test result was not revascularized. Recurrent CP was present in 62 (23%) patients. Classification of patients (CRN or IR) was significantly associated with recurrent CP for all applied FFRCT interpretation algorithms. When applying the c-FFRCT algorithm, the association with recurrent CP was found, irrespective of the extent of coronary calcification and the degree of coronary stenosis. A negative association between per-patient minimal d-FFRCT and recurrent CP was demonstrated, P < 0.005.ConclusionAn abnormal FFRCT test result is associated with an increased risk of recurrent CP in patients with new-onset SAP.

Positive predictive value of CT coronary angiography vs. CT fractional flow reserve in a real-world population

Abstract Background Computerised tomography coronary angiography and fractional flow reserve (CTCA and CT-FFR) are non-invasive diagnostic tools for the detection of flow limiting coronary artery stenoses. Although their negative predictive values are well established, there is a concern that the high sensitivity of these tests may lead to overestimation of coronary artery disease (CAD) and unnecessary invasive coronary angiography (ICA). We compared the positive predictive value (PPV) of CT-FFR with computerised tomography coronary angiography (CTCA) against the gold standard of ICA in different real-world patient groups. Methods We conducted a retrospective study of 477 patients referred for CTCA or CT-FFR for investigation of possible coronary ischaemia. Patients were excluded if the image quality was poor or inconclusive. Patient-based PPV was calculated to detect or rule out significant CAD, defined as more than 70% stenosis on ICA. A sub-analysis of PPV by indication for scan was also performed. Patients that underwent invasive non-hyperaemic pressure wire measurements had their iFR or RFR compared with their CT-FFR values. Results In a patient-based analysis, the overall PPV was 59.3% for CTCA and 76.2% for CT-FFR. This increased to 81.0% and 86.7% respectively for patients with stable angina symptoms. In patients with atypical angina symptoms, CT-FFR considerably outperformed CTCA with a PPV of 61.3% vs. 37.5%. There was not a linear relationship between invasive pressure wire measurement and CT-FFR value (r=0.23, p=0.265). Conclusion The PPV of CTCA and CT-FFR is lower in the real-world than in previously published trials, partly due to the heterogeneity of indication for the scan. However, in patients with typical angina symptoms, both are reliable diagnostic tools to determine the presence of clinically significant coronary stenoses. CT-FFR significantly outperforms CTCA in patients with more atypical symptoms and the targeted use of CT-FFR in this group may help to avoid unnecessary invasive procedures. Funding Acknowledgement Type of funding sources: None.