Wire-based Fractional Flow Reserve Research Articles

VERMONT non-optimised: can baseline diagnostic catheter images be used to measure angiography based CAAS-vFFR?

Abstract Background We have previously reported strong diagnostic accuracy and validity of angiography-based vessel Fractional Flow Reserve (CAAS-vFFR) compared to conventional wire based Fractional Flow Reserve (FFR)(1). The CAAS-vFFR system requires at least two additional optimised angiographic cine images taken after intracoronary glyceryl trinitrate administration, separated by ≥ 30 degrees at a frame-rate of ≥ 15 frames/seconds with minimal overlap and foreshortening, no table movement and adequate contrast opacification. At present, there is a paucity of data regarding the validity of using baseline non-optimised diagnostic cine images in the assessment of CAAS-vFFR. Purpose To assess the concordance and validity of using baseline non-optimised diagnostic cine images in measuring angiography based CAAS-vFFR. Methods We conducted an investigator-initiated, single centre, blinded, prospective observational study performing wire based FFR and CAAS-vFFR conducted simultaneously in patients undergoing routine wire-based FFR for intermediate coronary stenoses. All eligible patients had baseline diagnostic and optimised guide-catheter based angiographic images acquired. Results 195 consecutive patients with 205 lesions were recruited over 19 months; 56 (27.3%) lesions were excluded due to inadequate baseline cine angiogram images (Picture 1). 102 (68.5%) had stable symptoms and 107 (71.8%) were male. The median age was 65.0 years (interquartile range 59.0 – 73.0) and mean body-mass-index was 29.2 kg/m2 (± 5.8). There were 117 (78.5%) lesions in the left anterior descending artery/diagonal branches, 20 (13.4%) in the right coronary artery and 12 (8.1%) in the left circumflex artery/marginal branches. There were 93 (62.4%) diffuse (≥ 20 cm), 23 (15.4%) bifurcation and 15 (10.1%) ostial lesions. The mean optimised vFFR and non-optimised vFFR were 0.80 (± 0.1) and 0.79 (± 0.1) respectively with a Pearson correlation of 0.87 (p<0.001). Overall, 52 lesions (34.9%) and 73 lesions (49.0%) had a wire-based FFR and non-optimised vFFR value of ≤ 80 respectively. The mean wire-based FFR and non-optimised vFFR were 0.82 (± 0.1) and 0.79 (± 0.1) respectively. Receiver operating characteristic (ROC) curve analysis revealed excellent diagnostic accuracy of non-optimised vFFR in predicting a wire based FFR of ≤ 80 (AUC 0.91; 95% CI; 0.87-0.96) (Picture 2). Baseline non-optimised diagnostic vFFR images produced a sensitivity of 94.2%, specificity of 75.3%, positive-predictive-value (PPV) of 67.1% and negative-predictive-value (NPV) of 96.1% compared with wire-based FFR. Conclusions CAAS-vFFR derived values from baseline non-optimised diagnostic cine images were strongly concordant with those derived from optimised images and displayed a high sensitivity and NPV compared to wire-based FFR. This reflects the potential for CAAS-vFFR to have broader clinical applications and be utilised as a retrospective screening tool for intermediate lesions.Excluded baseline angiogram lesionsROC Curve

Non-invasive physiological assessment of intermediate coronary stenoses from plain angiography through artificial intelligence: the STARFLOW system.

Despite evidence supporting use of fractional flow reserve (FFR) and instantaneous waves-free ratio (iFR) to improve outcome of patients undergoing coronary angiography (CA) and percutaneous coronary intervention, such techniques are still underused in clinical practice due to economic and logistic issues. We aimed to develop an artificial intelligence (AI)-based application to compute FFR and iFR from plain CA. Consecutive patients performing FFR or iFR or both were enrolled. A specific multi-task deep network exploiting 2 projections of the coronary of interest from standard CA was appraised. Accuracy of prediction of FFR/iFR of the AI model was the primary endpoint, along with sensitivity and specificity. Prediction was tested both for continuous values and for dichotomous classification (positive/negative) for FFR or iFR. Subgroup analyses were performed for FFR and iFR.A total of 389 patients from 5 centers were enrolled. Mean age was 67.9±9.6 and 39.2% of patients were admitted for acute coronary syndrome. Overall, the accuracy was 87.3% (81.2-93.4%), with a sensitivity of 82.4% (71.9-96.4%) and a specificity of 92.2% (90.4-93.9%). For FFR, accuracy was 84.8% (77.8-91.8%), with a sensitivity of 81.9% (69.4-94.4%) and a specificity of 87.7% (85.5-89.9%), while for iFR accuracy was 90.2% (86.0-94.6%), with a sensitivity of 87.2% (76.6-97.8%) and a specificity of 93.2% (91.7-94.7%, all confidence intervals 95%). The presented machine-learning based tool showed high accuracy in prediction of wire-based FFR and iFR.

Changes in donor vessel physiology following coronary computed tomography angiography guided chronic total occlusion percutaneous coronary intervention: insights from computed tomography fractional flow reserve and artificial intelligence-guided ischemia model.

Donor vessel fractional flow reserve (FFR) usually increases following successful chronic total occlusion (CTO) percutaneous coronary intervention, as documented by pressure wires. In this case, donor vessel physiology changes were assessed using FFR derived from coronary computed tomography angiography (CCTA) and an artificial Intelligence-guided quantitative CCTA ischemia model in combination with pressure wire-based FFR.

Diagnostic Performance of Coronary Angiography Derived Computational Fractional Flow Reserve.

Computational fluid dynamics can compute fractional flow reserve (FFR) accurately. However, existing models are limited by either the intravascular hemodynamic phenomarkers that can be captured or the fidelity of geometries that can be modeled. This study aimed to validate a new coronary angiography-based FFR framework, FFRHARVEY, and examine intravascular hemodynamics to identify new biomarkers that could augment FFR in discerning unrevascularized patients requiring intervention. A 2-center cohort was used to examine diagnostic performance of FFRHARVEY compared with reference wire-based FFR (FFRINVASIVE). Additional biomarkers, longitudinal vorticity, velocity, and wall shear stress, were evaluated for their ability to augment FFR and indicate major adverse cardiac events. A total of 160 patients with 166 lesions were investigated. FFRHARVEY was compared with FFRINVASIVE by investigators blinded to the invasive FFR results with a per-stenosis area under the curve of 0.91, positive predictive value of 90.2%, negative predictive value of 89.6%, sensitivity of 79.3%, and specificity of 95.4%. The percentage ofdiscrepancy for continuous values of FFR was 6.63%. We identified a hemodynamic phenomarker, longitudinal vorticity, as a metric indicative of major adverse cardiac events in unrevascularized gray-zone cases. FFRHARVEY had high performance (area under the curve: 0.91, positive predictive value: 90.2%, negative predictive value: 89.6%) compared with FFRINVASIVE. The proposed framework provides a robust and accurate way to compute a complete set of intravascular phenomarkers, in which longitudinal vorticity was specifically shown to differentiate vessels predisposed to major adverse cardiac events.

Diagnostic performance of intravascular ultrasound-based fractional flow reserve in evaluating of intermediate left main stenosis.

The recently introduced ultrasonic flow ratio (UFR), is a novel fast computational method to derive fractional flow reserve (FFR) from intravascular ultrasound (IVUS) images. In the present study, we evaluate the diagnostic performance of UFR in patients with intermediate left main (LM) stenosis. This is a prospective, single center study enrolling consecutive patients with presence of intermediated LM lesions (diameter stenosis of 30%-80% by visual estimation) underwent IVUS and FFR measurement. An independent core laboratory assessed offline UFR and IVUS-derived minimal lumen area (MLA) in a blinded fashion. Both UFR and FFR were successfully achieved in 41 LM patients (mean age, 62.0 ± 9.9 years, 46.3% diabetes). An acceptable correlation between UFR and FFR was identified (r = 0.688, P < 0.0001), with an absolute numerical difference of 0.03 (standard difference: 0.01). The area under the curve (AUC) in diagnosis of physiologically significant coronary stenosis for UFR was 0.94 (95% CI: 0.87-1.01), which was significantly higher than angiographic identified stenosis > 50% (AUC = 0.66, P < 0.001) and numerically higher than IVUS-derived MLA (AUC = 0.82; P = 0.09). Patient level diagnostic accuracy, sensitivity and specificity for UFR to identify FFR ≤ 0.80 was 82.9% (95% CI: 70.2-95.7), 93.1% (95% CI: 82.2-100.0), 58.3% (95% CI: 26.3-90.4), respectively. In patients with intermediate LM diseases, UFR was proved to be associated with acceptable correlation and high accuracy with pressure wire-based FFR as standard reference. The present study supports the use of UFR for functional evaluation of intermediate LM stenosis.

Combined Assessment of Fractional Flow Reserve and Coronary Flow Velocity Reserve after Drug-Eluting Stent Implantation

Coronary flow velocity reserve (CFVR) can be measured noninvasively using stress transthoracic Doppler echocardiography (S-TDE). The prognostic significance of S-TDE-derived CFVR after percutaneous coronary intervention (PCI) remains unknown. The aim of this study was to investigate the prognostic value of post-PCI CFVR and its additional efficacy to fractional flow reserve (FFR) in patients undergoing elective PCI. A retrospective study was conducted involving 187 consecutive patients with chronic coronary syndrome who underwent elective PCI guided by FFR for the left anterior descending coronary artery. Pre- and post-PCI wire-based FFR and CFVR assessments of the left anterior descending coronary artery using S-TDE were performed in all patients. The association between post-PCI clinical and physiologic parameters and major adverse cardiac events (MACE), defined as a composite of cardiac death, myocardial infarction, heart failure, and unplanned remote target vessel revascularization, was evaluated. Three-quarters of patients exhibited CFVR increase after PCI, while all patients showed FFR improvement. During a median follow-up period of 1.5years, MACE occurred in 21 patients (11.2%). Among clinical demographics, patients with MACE had higher levels of N-terminal pro-brain natriuretic peptide compared with those without MACE (median, 615pg/mL [interquartile range, 245-1,500pg/mL] vs 180pg/mL [interquartile range, 70-559pg/mL]; P=.010). Post-PCI S-TDE-derived CFVR was lower in patients with MACE, while post-PCI FFR showed a nonsignificant tendency to be lower in patients with MACE. In a multivariable analysis, higher NT-proBNP (adjusted hazard ratio, 1.33; 95% CI, 1.02-1.74; P=.038), post-PCI CFVR ≤ 2.0 (adjusted hazard ratio, 2.93; 95% CI, 1.16-7.40; P=.023), and post-PCI FFR ≤ 0.82 (adjusted hazard ratio, 3.93; 95% CI, 1.52-10.18; P=.005) were independently associated with MACE. In patients with chronic coronary syndrome who underwent successful elective PCI for left anterior descending coronary artery, the combined assessment of S-TDE-derived post-PCI CFVR and post-PCI FFR provided a significant association with the occurrence of MACE.

Diagnostic performances of Nonhyperemic Pressure Ratios and Coronary Angiography-Based Fractional Flow Reserve against conventional Wire-Based Fractional Flow Reserve.

Nonhyperemic pressure ratios (NHPRs) have been proposed as alternatives to fractional flow reserve (FFR) without induction of hyperemia. More recently, imaging based-FFR estimation, especially coronary angiography-derived FFR (Angio-FFR) measurement, is proposed to estimate wire-based FFR. However, little is known about the diagnostic performance of these indices against conventional FFR. We aimed to assess and compare the diagnostic performance of both NHPRs and coronary Angio-FFR against wire-based conventional FFR. PubMed and Embase databases were systematically searched for peer-reviewed original articles up to 08/2022. The primary outcomes were the pooled sensitivity and specificity as well as the area under the curve (AUC) of the summary receiver-operating characteristic curve of those indices. A total of 6693 records were identified after a literature search, including 37 reports for NHPRs and 34 for Angio-FFR. Overall, NHPRs have a lower diagnostic performance in estimating wire-based FFR with an AUC of 0.85 (0.81, 0.88) when compared with Angio-FFR of 0.95 (0.93, 0.97). When all four modalities of NHPRs (iFR, Pd/Pa, DPR, RFR) were compared, those had overlapping AUCs without major differences among each other. Similarly, when the two most commonly used Angio-FFR (QFR, FFR angio ) were compared, those had overlapping AUCs without major differences among each other. Angio-FFR may offer a better estimation of wire-based FFR than NHPRs. Our results support a wider use of Angio-FFR in the cardiac catheterization laboratory to streamline our workflow for coronary physiologic assessment. FFR,, stable ischemic disease and non-ST elevation acute coronary syndrome.

Diagnostic accuracy of vessel fractional flow reserve compared to conventional diagnostic tools in patients with coronary artery stenosis

Abstract Background Wire-based fractional flow reserve (FFR) is currently the golden standard in a physiological assessment for intermediate coronary artery stenosis (CAS). However, the clinical advantage of FFR has been limited by its invasiveness. In the previous study with a small number of participants (334 patients), three-dimensional quantitative coronary angiography (3D-QCA)-based vessel FFR (vFFR) has shown non-inferiority to wire-based FFR in diagnostic accuracy. There has been no reports regarding the relationship between vFFR and other conventional physiological assessment tools. Methods The present study was a retrospective registry designed to evaluate the diagnostic accuracy of vFFR compared to the conventional reference standard (wire-based FFR ≤0.80). Between January 2019 and February 2022, patients with stable or unstable angina, and non-ST-elevation acute coronary syndrome who had undergone physiological assessments [wire-based FFR, instantaneous wave-free ratio (iFR), resting full-cycle ratio (RFR), and/or coronary computed tomography angiography-derived FFR (FFRCT)] before percutaneous coronary intervention were included for the present analysis. The exclusion criteria were ST-elevation myocardial infarction, previous coronary artery bypass grafting, cardiogenic shock, and adenosine intolerance. In the present study, we investigate the relationship between vFFR and conventional tools such as wire-based FFR, iFR, RFR, and/or FFRCT in patients with intermediate CAS, including multi-vessel disease, severe coronary calcium, in-stent restenosis, and hemodialysis. Results The study included 722 patients (mean age, 70±10 years; male, 80%) who underwent vFFR in 698 patients (97%), wire-based FFR in 711 (98%), iFR in 523 (72%), RFR in 109 (15%), and FFRCT in 48 (7%). Most patients presented stable angina (93%). In the present study, multi-vessel disease was identified only 20% of all. A total of 1108 target vessels were LAD in 549 (50%), LCx in 287 (26%), and RCA in 272 (24%), respectively. Bifurcation lesions and in-stent restenosis were present in 12% and 13%, respectively. The subjects were diagnosed several comorbidities, such as hypertension (77%), dyslipidemia (57%), diabetes mellitus (40%), and hemodialysis (12%). Overall, vFFR showed good correlations with wire-based FFR (r=0.70; p&amp;lt;0.001), IFR (r=0.57; p&amp;lt;0.001), and RFR (r=0.69; p&amp;lt;0.001). However, the correlation between vFFR and FFRCT was weak (r=0.36; p&amp;lt;0.001). Furthermore, vFFR had a good diagnostic accuracy (sensitivity, specificity, negative predictive value and positive predictive value; 81%, 88%, 82% and 87%, respectively) to identify the lesions with wire-based FFR≤0.80 (AUC, 0.87; 95% CI, 0.84-0.90; p&amp;lt;0.001). Conclusion In this large number cohort, the 3D-QCA based vFFR has a good correlation with wire-based FFR, and a high diagnostic accuracy to detect the lesion with FFR ≤ 0.80 even in patients with severe coronary calcification, in-stent restenosis, and hemodialysis.Scatter plotsBland-Altman plots

Are baseline conditions of coronary arteries sufficient for calculating angio-based index of microcirculatory resistance and fractional flow reserve?

Angio-based index of microcirculatory resistance (IMR) and fractional flow reserve (FFR) have been developed, however, the differences between baseline and hyperemic data and their effects on their computation have not yet been discussed. This study aimed to compare the diagnostic performance of a novel method for calculating IMR and FFR from coronary angiography under baseline and hyperemic conditions. We performed a retrospective study to investigate the diagnostic performance of angiography-derived IMR (AccuIMR) and FFR (AccuFFRangio) computed from the hyperemic condition (AccuIMRhyp, AccuFFRangiohyp) and baseline condition (AccuIMRbase, AccuFFRangiobase) in 101 consecutive patients with chronic coronary syndrome (CCS) who underwent measurements of IMR and FFR at a single center, using wire-based IMR and FFR as the reference standard. AccuIMRhyp showed much better correlation with IMR than AccuIMRbase (r=0.77 vs. 0.47, P<0.001). The diagnostic accuracy and area under the curve (AUC) for identifying significant microvascular dysfunction was higher for AccuIMRhyp than AccuIMRbase [92.1% (95% CI: 85.0-96.5%) vs. 83.2% (95% CI: 74.4-89.9%), P=0.012; 0.942 (95% CI: 0.877-0.979) vs. 0.815 (95% CI: 0.726-0.886), P=0.003]. The computed AccuFFRangio showed good correlations with FFR and good diagnostic performance under both hyperemic and baseline conditions [r=0.68 vs. 0.68, P>0.99; diagnostic accuracy =95.9% (95% CI: 89.8-98.9%) vs. 94.9% (95% CI: 88.4-98.3%), P=0.728; AUC =0.989 (95% CI: 0.942-1.000) vs. 0.973 (95% CI: 0.919-0.995), P=0.381]. The net reclassification index (NRI) demonstrated that hyperemic group had improved reclassification ability compared to the baseline group in identification of IMR >25 (NRI =0.20, P<0.001) and FFR ≤0.8 (NRI =0.11, P<0.001). By comparing the calculated angio-derived IMR and FFR under the baseline and hyperemic conditions, this study demonstrates that AccuIMR calculation is more accurate using the hyperemic condition, while AccuFFRangio calculation is accurate under both conditions.

Diagnostic accuracy of optical flow ratio: an individual patient-data meta-analysis.

Optical flow ratio (OFR) is a novel method for the fast computation of fractional flow reserve (FFR) from optical coherence tomography. We aimed to evaluate the diagnostic accuracy of OFR in assessing intermediate coronary stenosis using wire-based FFR as the reference. We performed an individual patient-level meta-analysis of all available studies with paired OFR and FFR assessments. The primary outcome was vessel-level diagnostic concordance of the OFR and FFR, using a cut-off of ≤0.80 to define ischaemia and ≤0.90 to define suboptimal post-percutaneous coronary intervention (PCI) physiology. This meta-analysis was registered in PROSPERO (CRD42021287726). Five studies were finally included, providing 574 patients and 626 vessels (404 pre-PCI and 222 post-PCI) with paired OFR and FFR from 9 international centres. Vessel-level diagnostic concordance of the OFR and FFR was 91% (95% confidence interval [CI]: 88%-94%), 87% (95% CI: 82%-91%), and 90% (95% CI: 87%-92%) in pre-PCI, post-PCI, and overall, respectively. The overall sensitivity, specificity, and positive and negative predictive values were 84% (95% CI: 79%-88%), 94% (95% CI: 92%-96%), 90% (95% CI: 86%-93%), and 89% (95% CI: 86%-92%), respectively. Multivariate logistic regression indicated that a low pullback speed (odds ratio [OR] 7.02, 95% CI: 1.68-29.43; p=0.008) was associated with a higher risk of obtaining OFR values at least 0.10 higher than FFR. Increasing the minimal lumen area was associated with a lower risk of obtaining an OFR at least 0.10 lower than FFR (OR 0.39, 95% CI: 0.18-0.82; p=0.013). This individual patient data meta-analysis demonstrated a high diagnostic accuracy of OFR. OFR has the potential to provide an improved integration of intracoronary imaging and physiological assessment for the accurate evaluation of coronary artery disease.

Diagnostic Accuracy of Artificial Intelligence-Based Angiography-Derived Fractional Flow Reserve Using Pressure Wire-Based Fractional Flow Reserve as a Reference.

Angiographic fractional flow reserve (angioFFR) is a novel artificial intelligence (AI)-based angiography-derived fractional flow reserve (FFR) application. We investigated the diagnostic accuracy of angioFFR to detect hemodynamically relevant coronary artery disease. Consecutive patients with 30-90% angiographic stenoses and invasive FFR measurements were included in this prospective, single-center study conducted between November 2018 and February 2020. Diagnostic accuracy was assessed using invasive FFR as the reference standard. In patients undergoing percutaneous coronary intervention, gradients of invasive FFR and angioFFR in the pre-senting segments were compared. We assessed 253 vessels (200 patients). The accuracy of angioFFR was 87.7% (95% confidence interval [CI] 83.1-91.5%), with a sensitivity of 76.8% (95% CI 67.1-84.9%), specificity of 94.3% (95% CI 89.5-97.4%), and area under the curve of 0.90 (95% CI 0.86-0.93%). AngioFFR was well correlated with invasive FFR (r=0.76; 95% CI 0.71-0.81; P<0.001). The agreement was 0.003 (limits of agreement: -0.13, 0.14). The FFR gradients of angioFFR and invasive FFR were comparable (n=51; mean [±SD] 0.22±0.10 vs. 0.22±0.11, respectively; P=0.87). AI-based angioFFR showed good diagnostic accuracy for detecting hemodynamically relevant stenosis using invasive FFR as the reference standard. The gradients of invasive FFR and angioFFR in the pre-stenting segments were comparable.

Accuracy of the angiography-based quantitative flow ratio in intermediate left main coronary artery lesions and comparison with visual estimation

BackgroundRevascularization of left main coronary artery (LMCA) stenosis is mostly based on angiography. Indices based on angiography might increase accuracy of the decision, although they have been scarcely used in LMCA. The objective of this study is to study the diagnostic agreement of QFR (quantitative flow ratio) with wire-based fractional flow reserve (FFR) in LMCA lesions and to compare with visual severity assessment. MethodsIn a series of patients with invasive FFR assessment of intermediate LMCA stenoses we retrospectively compared the measured value of QFR with that of FFR and the estimate of significance from angiography. Results107 QFR studies were included. The QFR intra-observer and inter-observer agreement was 87% and 82% respectively. The mean QFR-FFR difference was 0.047 ± 0.05 with a concordance of 90.7%, sensitivity 88.1%, specificity 92.3%, positive predictive value 88.1% and negative predictive value 92.3%. All these values were superior to those observed with the visual estimation which showed an intra- and inter-observer agreement of 73% and 72% respectively, besides 78% with the FFR value. The low diagnostic performance of the visual estimation and the acceptable performance of the QFR index measurement were observed in all subgroups analysed. ConclusionsQFR allows an acceptable estimate of the FFR obtained with intracoronary pressure guidewire in intermediate LMCA lesions, and clearly superior to the assessment based on angiography alone. The decision to revascularize patients with moderate LMCA lesions should not be based solely on the degree of angiographic stenosis.

The diagnostic performance of AccuFFRangio for evaluating coronary artery stenosis under different computational conditions.

A computational method (AccuFFrangio) based on invasive coronary angiography (ICA) and computational fluid dynamics (CFD) to calculate fractional flow reserve (FFR) without a pressure wire has been devised to clarify the physiological significance of coronary stenosis. This study aimed to evaluate the diagnostic performance of AccuFFRangio computation under different boundary conditions and vessel reconstruction approaches. Consecutive patients with stable angina pectoris who underwent ICA and FFR assessment from 2 centers were analyzed retrospectively. Using wire-based FFR as the reference standard, the diagnostic performances of AccuFFRangio and its variations were evaluated and compared. The calculation of AccuFFRangio involves several key boundary conditions, including patient-specific aortic pressure, contrast flow velocity derived from the thrombolysis in myocardial infarction (TIMI) frame count method, and vessel reconstruction based on 2 angiographic views. We considered the following 3 variations: (I) a fixed aortic pressure [fixed pressure AccuFFRangio (pAccuFFRangio)], (II) an empirical hyperemic velocity [fixed velocity AccuFFRangio (vAccuFFRangio)], and (III) vessel reconstruction using a single angiographic view [single view AccuFFRangio (sAccuFFRangio)]. A total of 230 patients with 230 vessels were included in the final analysis. The accuracy for standard AccuFFRangio, pAccuFFRangio, vAccuFFRangio, and sAccuFFRangio was 93.91%, 86.52%, 81.74%, and 83.48%, respectively; the sensitivity was 90.74%, 51.85%, 83.33%, and 46.30%, respectively; the specificity was 94.89%, 97.16%, 81.25%, and 94.89%, respectively; and the area under the receiver operating characteristic curve was 0.971, 0.928, 0.892, and 0.870, respectively. The comparison suggested that the overall performance of the standard AccuFFRangio was superior to other variations and had the highest accuracy among all the cases.

TCTAP A-066 Agreement Between Different Angiography-Derived Modalities With Wire-Based Fractional Flow Reserve Systems and 30 Month Clinical Outcomes in Evaluation of Non-Hemodynamically Significant Obstructive Coronary Artery Disease, a Single Centre Experience

TCTAP A-066 Agreement Between Different Angiography-Derived Modalities With Wire-Based Fractional Flow Reserve Systems and 30 Month Clinical Outcomes in Evaluation of Non-Hemodynamically Significant Obstructive Coronary Artery Disease, a Single Centre Experience

Assessment of fractional flow reserve in intermediate coronary stenosis using optical coherence tomography-based machine learning.

This study aimed to evaluate and compare the diagnostic accuracy of machine learning (ML)- fractional flow reserve (FFR) based on optical coherence tomography (OCT) with wire-based FFR irrespective of the coronary territory. ML techniques for assessing hemodynamics features including FFR in coronary artery disease have been developed based on various imaging modalities. However, there is no study using OCT-based ML models for all coronary artery territories. OCT and FFR data were obtained for 356 individual coronary lesions in 130 patients. The training and testing groups were divided in a ratio of 4:1. The ML-FFR was derived for the testing group and compared with the wire-based FFR in terms of the diagnosis of ischemia (FFR ≤ 0.80). The mean age of the subjects was 62.6 years. The numbers of the left anterior descending, left circumflex, and right coronary arteries were 130 (36.5%), 110 (30.9%), and 116 (32.6%), respectively. Using seven major features, the ML-FFR showed strong correlation (r = 0.8782, P < 0.001) with the wire-based FFR. The ML-FFR predicted wire-based FFR ≤ 0.80 in the test set with sensitivity of 98.3%, specificity of 61.5%, and overall accuracy of 91.7% (area under the curve: 0.948). External validation showed good correlation (r = 0.7884, P < 0.001) and accuracy of 83.2% (area under the curve: 0.912). OCT-based ML-FFR showed good diagnostic performance in predicting FFR irrespective of the coronary territory. Because the study was a small-size study, the results should be warranted the performance in further large-scale research.

Angiographic quantitative flow ratio in acute coronary syndrome: beyond a tool to define ischemia-causing stenosis-a literature review.

Numerous studies have demonstrated the safety and effectiveness of physiology-guided coronary revascularization in chronic coronary syndrome, resulting in a high level of guideline recommendation for these patients. However, the application of coronary physiology in acute coronary syndrome (ACS), especially in the acute phase of myocardial infarction, remains challenging. Over the last decade, the number of novel physiological indices derived from the computation of angiography have been developed as alternatives to pressure wire-based fractional flow reserve. Among these angiography-based indices, the quantitative flow ratio (QFR) is undoubtedly the one with the largest amount of data cumulated so far. In this article, we aim to review the related studies that describe efforts to investigate the diagnostic role of QFR and discuss perspectives for its current and future applications in the setting of the ACS. A literature search was performed on the electronic databases, including PubMed, Google Scholar and Web of Science covering publications in English up to May 2022. An emerging body of evidence has validated the diagnostic accuracy of angiography-derived QFR for the assessment of functional severity of coronary stenosis in both acute and chronic coronary syndromes. In parallel, multiple technologies, i.e., QFR-based pullback pressure gradient index, angiography-derived index of microcirculatory resistance and intravascular imaging-based morphofunctional evaluation methods, have been proposed, allowing operators to easily obtained physiological data of micro and macro-circulation, together with atherosclerotic lesion characteristics in catheterization laboratories. More recently, promising results supporting the clinical value of QFR in guiding revascularization and predicting outcomes for ACS patients have been published. Angiography-based QFR bears the potential of a wider adoption of coronary physiology assessment in the ACS setting due to its quicker and less-invasive nature. However, the current evidence mainly derived from retrospective studies or post-hoc analyses of prospective trials. Future studies are needed to further explore the benefits of QFR-guided revascularization on outcomes in ACS.

Performance and 12-month Outcomes of a Wire-free Fractional Flow Reserve System for Assessment of Coronary Artery Disease

Background: Fractional flow reserve (FFR) using an invasive pressure wire is recommended to guide coronary revascularisation in stable coronary artery disease. Coronary angiography-based wire-free FFR (CAFFR) determines the significance of a coronary lesion without the requirement of a pressure wire. Deferral of revascularisation of coronary lesions with an FFR &gt;0.8 has been shown to have similar outcomes to patients managed with optimal medical therapy. Objective: The aim of our study was to assess the performance and 12-month clinical outcomes in patients with CAFFR-guided percutaneous coronary intervention (PCI) deferral. Methods: This was a prospective study involving 69 patients (93 vessels) with angiographic stenosis of 30–90%. Patients with CAFFR ≤0.80 or poor image quality were excluded, leaving 29 patients (31 vessels) for analysis. All recruited patients had a CAFFR &gt;0.80 and thus, PCI deferral. This cohort was followed up for 12 months. The primary endpoint was a composite of death from any cause, MI or target vessel revascularisation. Wired FFR was done for comparison on 14 patients (48%) at the operator’s discretion. Results: The mean age was 59.9 (±12.6) years. The majority of patients were men (83%; n=24), 41% (n=12) had diabetes, 62% (n=18) had hypertension, 59% (n=17) had dyslipidaemia, 62% (n=18) had a history of smoking. The mean left ventricular ejection fraction (LVEF) was 52 (±11.4)% and 76% of the patients had a recent acute coronary syndrome. We assessed the left anterior descending artery and 52% (n=16) of vessels had a mean CAFFR was 0.87. At 12 months, all patients were alive, 89.7% remained in chronic coronary syndrome (CCS) class 1 and 3.4% (n=1) of the study population met the primary outcome of target vessel revascularisation. Conclusion: CAFFR showed good agreement with wire-based FFR and 12-month outcomes showed that CAFFR-guided deferral of PCI was safe and comparable to wired-based FFR guidance.

Quantitative Flow Ratio Based on Murray Fractal Law: Accuracy of Single Versus Two Angiographic Views.

Murray bifurcation fractal law-based quantitative flow ratio (QFR), namely, μQFR, is a novel method for the fast computation of fractional flow reserve (FFR) from a single angiographic view. We aimed to compare the diagnostic accuracy of computational QFR based on single vs 2 angiographic views in patients with intermediate coronary stenosis. The algorithm of μQFR was extended to develop a Murray law-based 3-dimensional (3D) μQFR from 2 angiographic projections. Patients with both angiographic views acquired according to the protocol-specified recommended views in the FAVOR (Functional Diagnostic Accuracy of Quantitative Flow Ratio in Online Assessment of Coronary Stenosis) II China study were included. μQFR was computed separately from the first (μQFR1) and second (μQFR2) angiographic projections, whereas the 3D-μQFR was computed based on both projections, all blinded to FFR data. Hemodynamically significant coronary stenosis was defined by wire-based FFR of ≤0.80. Altogether, 280 vessels from 262 patients had 2 protocol-specified recommended angiographic views; μQFR1, μQFR2, and 3D-μQFR were successfully computed in all these vessels. The mean FFR was 0.82 ± 0.12. The vessel-level diagnostic accuracy for μQFR1, μQFR2, and 3D-μQFR to identify hemodynamically significant stenosis was 92.1% (95% CI, 89.0%-95.3%), 92.5% (95% CI, 89.4%-95.6%), and 93.2% (95% CI, 90.3%-96.2%), respectively, with similar areas under the receiver operating characteristic curve for μQFR1 (0.96, P < .001), μQFR2 (0.95, P < .001), and 3D-μQFR (0.95, P < .001). μQFR1 and μQFR2 had excellent correlation (r = 0.95) and agreement (mean difference = 0.00 ± 0.03). Computation of μQFR from a single angiographic view had comparably good diagnostic performance as 2-view 3D-μQFR in identifying hemodynamically significant coronary stenosis.

Comparison of coronary CT angiography-based and invasive coronary angiography-based quantitative flow ratio for functional assessment of coronary stenosis: A multicenter retrospective analysis

BackgroundThe aim of this study was to evaluate the diagnostic performance of coronary CT angiography (CTA)-based quantitative flow ratio (QFR), namely CT-QFR, and compare it with invasive coronary angiography (ICA)-based Murray law QFR (μQFR), using fractional flow reserve (FFR) as the reference standard. MethodsPatients who underwent coronary CTA, ICA and pressure wire-based FFR assessment within two months were retrospectively analyzed. CT-QFR and μQFR were computed in blinded fashion and compared with FFR, all applying the same cut-off value of ≤0.80 to identify hemodynamically significant stenosis. ResultsPaired comparison between CT-QFR and μQFR was performed in 191 vessels from 167 patients. Average FFR was 0.81 ​± ​0.10 and 42.4% vessels had an FFR ≤0.80. CT-QFR had a slightly lower correlation with FFR compared with μQFR, although statistically non-significant (r ​= ​0.87 versus 0.90, p ​= ​0.110). The vessel-level diagnostic performance of CT-QFR was slightly lower but without statistical significance than μQFR (AUC ​= ​0.94 versus 0.97, difference: −0.03 [95%CI: −0.00-0.06], p ​= ​0.095), and substantially higher than diameter stenosis by CTA (AUC difference: 0.17 [95%CI: −0.10-0.23], p ​< ​0.001). The patient-level diagnostic accuracy, sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio and negative likelihood ratio for CT-QFR to identify FFR value ​≤ ​0.80 was 88%, 90%, 86%, 86%, 91%, 6.59 and 0.12, respectively. The diagnostic accuracy of CT-QFR was 84% in extensively calcified lesions, while in vessels with no or less calcification, CT-QFR showed a comparable diagnostic accuracy with μQFR (91% versus 92%, p ​= ​0.595). Intra- and inter-observer variability in CT-QFR analysis was −0.00 ​± ​0.04 and 0.00 ​± ​0.04, respectively. ConclusionsPerformance in diagnosis of hemodynamically significant coronary stenosis by CT-QFR was slightly lower but without statistical significance than μQFR, and substantially higher than CTA-derived diameter stenosis. Extensively calcified lesions reduced the diagnostic accuracy of CT-QFR.

Computational Fractional Flow Reserve From Coronary Computed Tomography Angiography-Optical Coherence Tomography Fusion Images in Assessing Functionally Significant Coronary Stenosis.

BackgroundCoronary computed tomography angiography (CTA) and optical coherence tomography (OCT) provide additional functional information beyond the anatomy by applying computational fluid dynamics (CFD). This study sought to evaluate a novel approach for estimating computational fractional flow reserve (FFR) from coronary CTA-OCT fusion images.MethodsAmong patients who underwent coronary CTA, 148 patients who underwent both pressure wire-based FFR measurement and OCT during angiography to evaluate intermediate stenosis in the left anterior descending artery were included from the prospective registry. Coronary CTA-OCT fusion images were created, and CFD was applied to estimate computational FFR. Based on pressure wire-based FFR as a reference, the diagnostic performance of Fusion-FFR was compared with that of CT-FFR and OCT-FFR.ResultsFusion-FFR was strongly correlated with FFR (r = 0.836, P < 0.001). Correlation between FFR and Fusion-FFR was stronger than that between FFR and CT-FFR (r = 0.682, P < 0.001; z statistic, 5.42, P < 0.001) and between FFR and OCT-FFR (r = 0.705, P < 0.001; z statistic, 4.38, P < 0.001). Area under the receiver operating characteristics curve to assess functionally significant stenosis was higher for Fusion-FFR than for CT-FFR (0.90 vs. 0.83, P = 0.024) and OCT-FFR (0.90 vs. 0.83, P = 0.043). Fusion-FFR exhibited 84.5% accuracy, 84.6% sensitivity, 84.3% specificity, 80.9% positive predictive value, and 87.5% negative predictive value. Especially accuracy, specificity, and positive predictive value were superior for Fusion-FFR than for CT-FFR (73.0%, P = 0.007; 61.4%, P < 0.001; 64.0%, P < 0.001) and OCT-FFR (75.7%, P = 0.021; 73.5%, P = 0.020; 69.9%, P = 0.012).ConclusionCFD-based computational FFR from coronary CTA-OCT fusion images provided more accurate functional information than coronary CTA or OCT alone.Clinical Trial Registration[www.ClinicalTrials.gov], identifier [NCT03298282].