Diagnostic accuracy of intracoronary optical coherence tomography-derived fractional flow reserve for assessment of coronary stenosis severity

Simulation of coronary fractional flow reserve and whole-cycle flow based on optical coherence tomography in individual patients with coronary artery disease

Computer simulations of coronary fractional flow reserve (FFR) based on coronary imaging have emerged as an attractive alternative to invasive measurements. However, most methods are proprietary and employ non-physiological assumptions. Our aims were to develop and validate a physiologically realistic open-source simulation model for coronary flow, and to use this model to predict FFR based on intracoronary optical coherence tomography (OCT) data in individual patients. We included patients undergoing elective coronary angiography with angiographic borderline coronary stenosis. Invasive measurements of coronary hyperemic pressure and absolute flow and OCT imaging were performed. A computer model of coronary flow incorporating pulsatile flow and the effect of left ventricular contraction was developed and calibrated, and patient-specific flow simulation was performed. Forty-eight coronary arteries from 41 patients were included in the analysis. Average FFR was 0.79 ± 0.14, and 50% had FFR ≤ 0.80. Correlation between simulated and measured FFR was high (r = 0.83, p < 0.001). Average difference between simulated FFR and observed FFR in individual patients was - 0.009 ± 0.076. Overall diagnostic accuracy for simulated FFR ≤ 0.80 in predicting observed FFR ≤ 0.80 was 0.88 (0.75-0.95) with sensitivity 0.79 (0.58-0.93) and specificity 0.96 (0.79-1.00). The positive predictive value was 0.95 (0.75-1.00) and the negative predictive value was 0.82 (0.63-0.94). In conclusion, realistic simulations of whole-cycle coronary flow can be produced based on intracoronary OCT data with a new, computationally simple simulation model. Simulated FFR had moderate numerical agreement with observed FFR and a good diagnostic accuracy for predicting hemodynamic significance of coronary stenoses.

Renal Dysfunction Increases Risk of Adverse Cardiovascular Events in 5-Year Follow-Up Study of Intermediate Coronary Artery Lesions

BACKGROUND Progression of chronic coronary syndrome (CCS) is influenced by chronic kidney disease (CKD). This 5-year follow-up study aimed to assess 100 patients with 118 intermediate coronary artery lesions evaluated by fractional flow reserve (FFR) and intravascular imaging stratified according to renal function. MATERIAL AND METHODS This prospective study enrolled patients with intermediate coronary stenosis identified by coronary angiogram. Patients with severe renal dysfunction (estimated glomerular filtration rate (eGFR) <45 ml/min/1.73 m²) were excluded from the study. The remaining were divided into 2 groups according to eGFR: 45-60 ml/min/1.73 m² for mild-to-moderate renal dysfunction and >60 ml/min/1.73 m² for no renal dysfunction. We analyzed intermediate-grade stenoses (40-80% as assessed in coronary angiography) with the use of optical coherence tomography (OCT), FFR, and intravascular ultrasound (IVUS). RESULTS Renal dysfunction patients were older (67.7±8.1 vs 63.6±9.7 years, P=0.044). Lesion characteristics, including plaque type and minimal lumen area in OCT, showed no significant differences between the renal dysfunction and no renal dysfunction groups. Thin-cap fibroatheroma, calcific plaques, lipidic plaques, and fibrous plaques had similar prevalence. FFR values and IVUS parameters did not significantly differ between the groups. Over a 5-year follow-up, individuals with mild-to-moderate renal dysfunction had an elevated risk of all-cause mortality and major adverse cardiovascular events in multivariate analyses adjusted for age and sex. CONCLUSIONS Mild-to-moderate renal dysfunction was not associated with significant differences in OCT- and IVUS-derived plaque morphology nor with functional indices characterizing intermediate-grade coronary stenoses. Renal dysfunction was related to a higher risk of all-cause mortality and major adverse cardiovascular events prevalence in 5-year follow-up.

Illusion of revascularization: does anyone achieve optimal revascularization during percutaneous coronary intervention?

This Perspective article is a form of 'pastiche', inspired by the 1993 review by Lincoff and Topol entitled 'Illusion of reperfusion', and explores how their concept continues to apply to percutaneous revascularization in patients with coronary artery disease and ischaemia. Just as Lincoff and Topol argued that reperfusion of acute myocardial infarction was facing unresolved obstacles that hampered clinical success in 1993, we propose that challenging issues are similarly jeopardizing the potential benefits of stent-based angioplasty today. By analysing the appropriateness and efficacy of percutaneous coronary intervention (PCI), we emphasize the limitations of relying solely on visual angiographic guidance, which frequently leads to inappropriate stenting and overtreatment in up to one-third of patients and the associated increased risk of periprocedural myocardial infarction. The lack of optimal revascularization observed in half of patients undergoing PCI confers risks such as suboptimal physiology after PCI, residual angina and long-term stent-related events, leaving an estimated 76% of patients with an 'illusion of revascularization'. These outcomes highlight the need to refine our diagnostic tools by integrating physiological assessments with targeted intracoronary imaging and emerging strategies, such as co-registration systems and angiography-based computational methods enhanced by artificial intelligence, to achieve optimal revascularization outcomes.

Co-registered optical coherence tomography and X-ray angiography for the prediction of fractional flow reserve

Cardiovascular disease (CVD) stands as the leading global cause of mortality, and coronary artery disease (CAD) has the highest prevalence, contributing to 42% of these fatalities. Recognizing the constraints inherent in the anatomical assessment of CAD, Fractional Flow Reserve (FFR) has emerged as a pivotal functional diagnostic metric. Herein, we assess the potential of employing an ensemble approach with deep neural networks (DNN) to predict invasively measured Fractional Flow Reserve (FFR) using raw anatomical data extracted from both optical coherence tomography (OCT) and X-ray coronary angiography (XA). In this study, we used a challenging dataset, with 46% of the lesions falling within the FFR range of 0.75 to 0.85. Despite this complexity, our model achieved an accuracy of 84.3%, demonstrating a sensitivity of 87.5% and a specificity of 81.4%. Our results demonstrate that incorporating both OCT and XA signals, co-registered, as inputs for the DNN model leads to an important increase in overall accuracy.

Virtual Hemodynamic Assessment of Coronary Lesions: The Advent of Functional Angiography and Coronary Imaging

The fractional flow reserve (FFR) is well recognized as a gold standard measure for the estimation of functional coronary stenosis. Technological progressions in image processing have empowered the reconstruction of three-dimensional models of the coronary arteries via both non-invasive and invasive imaging modalities. The application of computational fluid dynamics (CFD) techniques to coronary 3D anatomical models allows the virtual evaluation of the hemodynamic significance of a coronary lesion with high diagnostic accuracy.

METHODS

Search of the bibliographic database for articles published from 2011 to 2023 using the following search terms: invasive FFR and non-invasive FFR. Pooled analysis of the sensitivity and specificity, with the corresponding confidence intervals from 32% to 94%. In addition, the summary processing times were determined.

RESULTS

In total, 24 studies published between 2011 and 2023 were included, with a total of 13,591 patients and 3345 vessels. The diagnostic accuracy of the invasive and non-invasive techniques at the per-patient level was 89% (95% CI, 85-92%) and 76% (95% CI, 61-80%), respectively, while on the per-vessel basis, it was 92% (95% CI, 82-88%) and 81% (95% CI, 75-87%), respectively.

CONCLUSION

These opportunities providing hemodynamic information based on anatomy have given rise to a new era of functional angiography and coronary imaging. However, further validations are needed to overcome several scientific and computational challenges before these methods are applied in everyday clinical practice.

Artificial Intelligence for the Interventional Cardiologist: Powering and Enabling OCT Image Interpretation

Intravascular optical coherence tomography (IVOCT) is a form of intra-coronary imaging that uses near-infrared light to generate high-resolution, cross-sectional, and 3D volumetric images of the vessel. Given its high spatial resolution, IVOCT is well-placed to characterise coronary plaques and aid with decision-making during percutaneous coronary intervention. IVOCT requires significant interpretation skills, which themselves require extensive education and training for effective utilisation, and this would appear to be the biggest barrier to its widespread adoption. Various artificial intelligence-based tools have been utilised in the most contemporary clinical IVOCT systems to facilitate better human interaction, interpretation and decision-making. The purpose of this article is to review the existing and future technological developments in IVOCT and demonstrate how they could aid the operator.

Optimal diagnostic approach for using CT-derived quantitative flow ratio in patients with stenosis on coronary computed tomography angiography

BACKGROUND

Coronary computed tomography angiography (CCTA)-derived quantitative flow ratio (CT-QFR) is an on-site non-invasive technique estimating invasive fractional flow reserve (FFR). This study assesses the diagnostic performance of using most distal CT-QFR versus lesion-specific CT-QFR approach for identifying hemodynamically obstructive coronary artery disease (CAD).

METHODS

Prospectively enrolled de novo chest pain patients (n ​= ​445) with ≥50 ​% visual diameter stenosis on CCTA were referred for invasive evaluation. On-site CT-QFR was analyzed post-hoc blinded to angiographic data and obtained as both most distal (MD-QFR) and lesion-specific CT-QFR (LS-QFR). Abnormal CT-QFR was defined as ≤0.80. Hemodynamically obstructive CAD was defined as invasive FFR ≤0.80 or ≥70 ​% diameter stenosis by 3D-quantitative coronary angiography.

RESULTS

In total 404/445 patients had paired CT-QFR and invasive analyses of whom 149/404 (37 ​%) had hemodynamically obstructive CAD. MD-QFR and LS-QFR classified 188 (47 ​%) and 165 (41 ​%) patients as abnormal, respectively. Areas under the receiver-operating characteristic curve for MD-QFR was 0.83 vs. 0.85 for LS-QFR, p ​= ​0.01. Sensitivities for MD-QFR and LS-QFR were 80 ​% (95%CI: 73-86) vs. 77 ​% (95%CI: 69-83), p ​= ​0.03, respectively, and specificities were 73 ​% (95%CI: 67-78) vs. 80 ​% (95%CI: 75-85), p ​< ​0.01, respectively. Positive predictive values for MD-QFR and LS-QFR were 63 ​% vs. 69 ​%, p ​< ​0.01, respectively, and negative predictive values for MD-QFR and LS-QFR were 86 ​% vs. 85 ​%, p ​= ​0.39, respectively).

CONCLUSION

Using a lesion-specific CT-QFR approach has superior discrimination of hemodynamically obstructive CAD compared to a most distal CT-QFR approach. CT-QFR identified most cases of hemodynamically obstructive CAD while a normal CT-QFR excluded hemodynamically obstructive CAD in the majority of patients.

Diagnostic performance of angiography-derived fractional flow reserve and CT-derived fractional flow reserve: A systematic review and Bayesian network meta-analysis

OBJECTIVE

Accumulating evidence has demonstrated that fractional flow reserves (FFRs) derived from invasive coronary angiograms (CA-FFRs) and coronary computed tomography angiography-derived FFRs (CT-FFRs) are promising alternatives to wire-based FFRs. However, it remains unclear which method has better diagnostic performance. This systematic review and meta-analysis aimed to compare the diagnostic performances of the two approaches.

METHODS

The Cochrane Library, PubMed, Embase, Medline (Ovid), the Chinese China National Knowledge Infrastructure Database (CNKI), VIP, and WanFang Data databases were searched for relevant studies that included comparisons between CA-FFR and CT-FFR, from their respective database inceptions until January 1, 2023. Studies where both noninvasive FFR (including CA-FFR and CT-FFR) and invasive FFR (as a reference standard) were performed for the diagnosis of ischemic coronary artery disease and were designed as prospective, paired diagnostic studies, were pulled. The diagnostic test accuracy method and Bayesian hierarchical summary receiver operating characteristic (ROC) model for network meta-analysis (NMA) of diagnostic tests (HSROC-NMADT) were both used to perform a meta-analysis on the data.

RESULTS

Twenty-six studies were included in this NMA. The results from both the diagnostic test accuracy and HSROC-NMADT methods revealed that the diagnostic accuracy of CA-FFR was higher than that of CT-FFR, in terms of sensitivity (Se; 0.86 vs. 0.84), specificity (Sp; 0.90 vs. 0.78), positive predictive value (PPV; 0.83 vs. 0.70), and negative predictive value (NPV; 0.91 vs. 0.89) for the detection of myocardial ischemia. A cumulative ranking curve analysis indicated that CA-FFR had a higher diagnostic accuracy than CT-FFR in the context of this study, with a higher area under the ROC curve (AUC; 0.94 vs. 0.87).

CONCLUSIONS

Although both of these two commonly used virtual FFR methods showed high levels of diagnostic accuracy, we demonstrated that CA-FFR had a better Se, Sp, PPV, NPV, and AUC than CT-FFR. However, this study provided only indirect comparisions; therefore, larger studies are warranted to directly compare the diagnostic performances of these two approaches.

Intravascular Imaging-Derived Physiology-Basic Principles and Clinical Application

Intravascular imaging-derived physiology is emerging as a promising tool allowing simultaneous anatomic and functional lesion assessment. Recently, several optical coherence tomography-based and intravascular ultrasound-based fractional flow reserve (FFR) indices have been developed that compute FFR through computational fluid dynamics, fluid dynamics equations, or machine-learning methods. This review aims to provide an overview of the currently available intravascular imaging-based physiologic indices, their diagnostic performance, and clinical application.

Assessment of the functional severity of coronary lesions from optical coherence tomography based on ensembled learning

BACKGROUND

Atherosclerosis is one of the most frequent cardiovascular diseases. The dilemma faced by physicians is whether to treat or postpone the revascularization of lesions that fall within the intermediate range given by an invasive fractional flow reserve (FFR) measurement. The paper presents a monocentric study for lesions significance assessment that can potentially cause ischemia on the large coronary arteries.

METHODS

A new dataset is acquired, comprising the optical coherence tomography (OCT) images, clinical parameters, echocardiography and FFR measurements collected from 80 patients with 102 lesions, with stable multivessel coronary artery disease. Having the ground truth given by the invasive FFR measurement, the dataset is challenging because almost 40% of the lesions are in the gray zone, having an FFR value between 0.75 and 0.85. Twenty-six features are extracted from OCT images, clinical characteristics, and echocardiography and the most relevant are identified by examining the models' accuracy. An ensembled learning is performed for solving the binary classification problem of lesion significance considering the leave-one-out cross-validation approach.

RESULTS

Ensemble models are designed from the multi-features voting from 5 features models by prediction aggregation with a maximum accuracy of 81.37% and a maximum area under the curve score (AUC) of 0.856.

CONCLUSIONS

The proposed explainable supervised learning-based lesion classification is a new method that can be improved by training with a larger multicenter dataset for further designing a tool for guiding the decision making of the clinician for the cases outside the gray zone and for the other situation extra clinical information about the lesion is needed.

Prognostic value of optical flow ratio for cardiovascular outcomes in patients after percutaneous coronary stent implantation

Background

The relationship between the optical flow ratio (OFR) and clinical outcomes in patients with coronary artery disease (CAD) after percutaneous coronary stent implantation (PCI) remains unknown.

Objective

To examine the correlation between post-PCI OFR and clinical outcomes in patients with CAD following PCI.

Methods

Patients who underwent optical coherence tomography (OCT) guided PCI at Guangdong Provincial People's Hospital were retrospectively and continuously enrolled. Clinical data, post-PCI OCT characteristics, and OFR measurements were collected and analyzed to identify predictors of target vessel failure (TVF) after PCI.

Results

Among 354 enrolled patients, 26 suffered TVF during a median follow-up of 484 (IQR: 400-774) days. Post-PCI OFR was significantly lower in the TVF group than in the non-TVF group (0.89 vs. 0.93; P = 0.001). In multivariable Cox regression analysis, post-PCI OFR (HR per 0.1 increase: 0.60; 95% CI: 0.41-0.89; P = 0.011), large stent edge dissection (HR: 3.85; 95% CI: 1.51-9.84; P = 0.005) and thin-cap fibroatheroma (TCFA) (HR: 2.95; 95% CI: 1.19-7.35; P = 0.020) in the non-stented segment were independently associated with TVF. In addition, the inclusion of post-PCI OFR to baseline characteristics and post-PCI OCT findings improved the predictive power of the model to distinguish subsequent TVF after PCI (0.838 vs. 0.796; P = 0.028).

Conclusion

The post-PCI OFR serves as an independent determinant of risk for TVF in individuals with CAD after PCI. The inclusion of post-PCI OFR assessments, alongside baseline characteristics and post-PCI OCT findings, substantially enhances the capacity to differentiate the subsequent manifestation of TVF in CAD patients following PCI.

Diagnostic accuracy of a novel optical coherence tomography-based fractional flow reserve algorithm for assessment of coronary stenosis significance

BACKGROUND

This study aimed to introduce a novel optical coherence tomography-derived fractional flow reserve (FFR) computational approach and assess the diagnostic performance of the algorithm for assessing physiological function.

METHODS

The fusion of coronary optical coherence tomography and angiography was used to generate a novel FFR algorithm (AccuFFRoct) to evaluate functional ischemia of coronary stenosis. In the current study, a total of 34 consecutive patients were included, and AccuFFRoct was used to calculate the FFR for these patients. With the wire-measured FFR as the reference standard, we evaluated the performance of our approach by accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).

RESULTS

Per vessel accuracy, sensitivity, specificity, PPV, and NPV for AccuFFRoct in identifying hemodynamically significant coronary stenosis were 93.8%, 94.7%, 92.3%, 94.7%, and 92.3%, respectively, were found. Good correlation (Pearson's correlation coefficient r = 0.80, p < 0.001) between AccuFFRoct and FFR was observed. The Bland-Altman analysis showed a mean difference value of -0.037 (limits of agreement: -0.189 to 0.115). The area under the receiver-operating characteristic curve (AUC) of AccuFFRoct in identifying physiologically significant stenosis was 0.94, which was higher than the minimum lumen area (MLA, AUC = 0.91) and significantly higher than the diameter stenosis (%DS, AUC = 0.78).

CONCLUSIONS

This clinical study shows the efficiency and accuracy of AccuFFRoct for clinical implementation when using invasive FFR measurement as a reference. It could provide important insights into coronary imaging superior to current methods based on the degree of coronary artery stenosis.

Clinical quantitative coronary artery stenosis and coronary atherosclerosis imaging: a Consensus Statement from the Quantitative Cardiovascular Imaging Study Group

The detection and characterization of coronary artery stenosis and atherosclerosis using imaging tools are key for clinical decision-making in patients with known or suspected coronary artery disease. In this regard, imaging-based quantification can be improved by choosing the most appropriate imaging modality for diagnosis, treatment and procedural planning. In this Consensus Statement, we provide clinical consensus recommendations on the optimal use of different imaging techniques in various patient populations and describe the advances in imaging technology. Clinical consensus recommendations on the appropriateness of each imaging technique for direct coronary artery visualization were derived through a three-step, real-time Delphi process that took place before, during and after the Second International Quantitative Cardiovascular Imaging Meeting in September 2022. According to the Delphi survey answers, CT is the method of choice to rule out obstructive stenosis in patients with an intermediate pre-test probability of coronary artery disease and enables quantitative assessment of coronary plaque with respect to dimensions, composition, location and related risk of future cardiovascular events, whereas MRI facilitates the visualization of coronary plaque and can be used in experienced centres as a radiation-free, second-line option for non-invasive coronary angiography. PET has the greatest potential for quantifying inflammation in coronary plaque but SPECT currently has a limited role in clinical coronary artery stenosis and atherosclerosis imaging. Invasive coronary angiography is the reference standard for stenosis assessment but cannot characterize coronary plaques. Finally, intravascular ultrasonography and optical coherence tomography are the most important invasive imaging modalities for the identification of plaques at high risk of rupture. The recommendations made in this Consensus Statement will help clinicians to choose the most appropriate imaging modality on the basis of the specific clinical scenario, individual patient characteristics and the availability of each imaging modality.

Practical Application of Coronary Physiologic Assessment: Asia-Pacific Expert Consensus Document: Part 1

Coronary physiologic assessment is performed to measure coronary pressure, flow, and resistance or their surrogates to enable the selection of appropriate management strategy and its optimization for patients with coronary artery disease. The value of physiologic assessment is supported by a large body of evidence that has led to major recommendations in clinical practice guidelines. This expert consensus document aims to convey practical and balanced recommendations and future perspectives for coronary physiologic assessment for physicians and patients in the Asia-Pacific region based on updated information in the field that including both wire- and image-based physiologic assessment. This is Part 1 of the whole consensus document, which describes the general concept of coronary physiology, as well as practical information on the clinical application of physiologic indices and novel image-based physiologic assessment.

Fast Computational Approaches to Derive Fractional Pressure Ratio in Patients with Extracranial or Intracranial Symptomatic Stenosis

OBJECTIVE

We aimed to evaluate the performance of fast and straightforward Murray law-based quantitative flow ratio (μQFR) computation in cerebrovascular stenosis.

METHODS

A total of 30 patients with symptomatic stenosis of 50%-70% luminal stenosis and underwent fractional pressure ratio (FPR) assessment at our hospital were included in the present study. μQFR was applied to the interrogated vessel. An artificial intelligence algorithm was proposed for automatic delineation of lumen contours of cerebrovascular stenosis. We used invasive FPRs as a reference standard. Pearson's correlation coefficient (r) was used to assess the correlation strength between the μQFR and FPR, and Bland-Altman plots were used to evaluate the agreement between the μQFR and FPR. An analysis of the receiver operating characteristic was used to evaluate the performance of μQFR.

RESULTS

Our results displayed a strong positive correlations (r = 0.92; P < 0.001) between the μQFR and pressure wire FPR. Excellent agreement was observed between the μQFR and FPR with a mean difference of 0.01 ± 0.08 (range, -0.16 to 0.14; P = 0.263). The overall accuracy for identifying an FPR of ≤0.7 was 92% (95% confidence interval [CI], 85%-100%). The area under the receiver operating characteristic curve was higher for the μQFR (0.92; 95% CI, 0.81-0.98) than for diameter stenosis (0.88; 95% CI, 0.75-0.95). The positive likelihood ratio was 3.9 for the μQFR with a negative likelihood ratio of 0.

CONCLUSIONS

The μQFR computation has a strong correlation and agrees with the FPR calculated from the pressure wire. Therefore, the μQFR might provide an essential therapeutic aid for patients with symptomatic stenosis.

Intravascular Imaging versus Physiological Assessment versus Biomechanics-Which Is a Better Guide for Coronary Revascularization

Today, coronary artery disease (CAD) continues to be a prominent cause of death worldwide. A reliable assessment of coronary stenosis represents a prerequisite for the appropriate management of CAD. Nevertheless, there are still major challenges pertaining to some limitations of current imaging and functional diagnostic modalities. The present review summarizes the current data on invasive functional and intracoronary imaging assessment using optical coherence tomography (OCT), and intravascular ultrasound (IVUS). Amongst the functional parameters-on top of fractional flow reserve (FFR) and instantaneous wave-free ratio (iFR)-we point to novel angiography-based measures such as quantitative flow ratio (QFR), vessel fractional flow reserve (vFFR), angiography-derived fractional flow reserve (FFRangio), and computed tomography-derived flow fractional reserve (FFR-CT), as well as hybrid approaches focusing on optical flow ratio (OFR), computational fluid dynamics and attempts to quantify the forces exaggerated by blood on the coronary plaque and vessel wall.

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

BACKGROUND

Optical flow ratio (OFR) is a novel method for the fast computation of fractional flow reserve (FFR) from optical coherence tomography.

AIMS

We aimed to evaluate the diagnostic accuracy of OFR in assessing intermediate coronary stenosis using wire-based FFR as the reference.

METHODS

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).

RESULTS

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).

CONCLUSIONS

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.

Quantitative flow ratio modulated by intracoronary optical coherence tomography for predicting physiological efficacy of percutaneous coronary intervention

BACKGROUND

The combination of coronary imaging assessment and blood flow perturbation estimation has the potential to improve percutaneous coronary intervention (PCI) guidance.

OBJECTIVES

We aimed to evaluate a novel method for fast computation of Murray law-based quantitative flow ratio (μQFR) from coregistered optical coherence tomography (OCT) and angiography (OCT-modulated μQFR, OCT-μQFR) in predicting physiological efficacy of PCI.

METHODS

Patients treated by OCT-guided PCI in the OCT-arm of the Fractional Flow Reserve versus Optical Coherence Tomography to Guide RevasculariZAtion of Intermediate Coronary Stenoses trial (FORZA, NCT01824030) were included. Based on angiography and OCT before PCI, simulated residual OCT-μQFR was computed by assuming full stent expansion to the intended-to-treat segment. Plaque composition was automatically characterized using a validated artificial intelligence algorithm. Actual post-PCI OCT-μQFR pullback was computed based on coregistration of angiography and OCT acquired immediately after PCI. Suboptimal functional stenting result was defined as OCT-μQFR ≤ 0.90.

RESULTS

Paired simulated residual OCT-μQFR and actual post-PCI OCT-μQFR were obtained in 76 vessels from 74 patients. Simulated residual OCT-μQFR showed good correlation (r = 0.80, p < 0.001), agreement (mean difference = -0.02 ± 0.02, p < 0.001), and diagnostic concordance (79%, 95% confidence interval: 70%-88%) with actual post-PCI OCT-μQFR. Actual post-PCI in-stent OCT-μQFR had a median value of 0.02 and was associated with left anterior descending artery lesion location (β = 0.38, p < 0.001), higher baseline total plaque burden (β = 0.25, p = 0.031), and fibrous plaque volume (β = 0.24, p = 0.026).

CONCLUSIONS

This study based on patients enrolled in a prospective OCT-guidance PCI trial shows that simulated residual OCT-μQFR had good correlation, agreement, and diagnostic concordance with actual post-PCI OCT-μQFR. In OCT-guided procedures, OCT-μQFR in-stent pressure drop was low and was significantly predicted by pre-PCI vessel/plaque characteristics.

Intravascular Imaging-Based Physiologic Assessment

Intravascular imaging (IVI), including intravascular ultrasound (IVUS) and optical coherence tomography (OCT), is clinically useful for assessing the luminal size, lesion length, and plaque characteristics, as well as for evaluating stent deployment; however, it is not designed to estimate myocardial ischemia accurately. Thus, several types of IVI-derived fractional flow reserve (FFR) (IVI-derived FFR) have been developed and reported. In general, the algorithms of virtual FFR are based on basic fluid dynamics equations (mainly Poiseuille and Borda-Carnot equations) and original microvascular models (fixed velocity or calculating coronary flow reserve). Although the models and assumptions used in the past reports were mostly based on the standard population (not independent patient data), the developed software calculated FFR with high accuracy (88% to 94%) with strong correlations between IVI-derived FFR and wire-based FFR (0.69 to 0.89). Given several other less invasive virtual FFR methods currently available for clinical use, IVI-derived FFR would be limited for the sole use of pre-percutaneous coronary intervention (PCI) physiological evaluation; however, it may play a unique role at PCI guidance and optimization, potentially allowing comprehensive and time/cost-saving assessment of both anatomical and physiological lesion properties using a single diagnostic device.

Coronary Physiologic Assessment Based on Angiography and Intracoronary Imaging

Intracoronary physiology testing has evolved as a promising diagnostic approach in the management of patients with coronary artery disease. The value of hyperemic translesional pressure ratios to estimate the functional relevance of coronary stenoses is supported by a wealth of outcomes data. The continuing drive to further simplify this approach led to the development of non-hyperemic pressure-based indices. Recent attention has focused on estimating functional significance without invasively measuring coronary pressure through the measurement of virtual indices derived from the coronary angiogram. By offering a routine assessment of the physiology of all the major epicardial coronary vessels, angiogram-derived physiology has the potential to modify current practice by facilitating more accurate patient-level, vessel-level, and even lesion-level decision making. This article reviews the current state of angiogram-derived physiology and speculates on its potential impact on clinical practice, in continuation to the previously published article on coronary physiology in this journal.

Advances in Diagnosis, Therapy, and Prognosis of Coronary Artery Disease Powered by Deep Learning Algorithms

Percutaneous coronary intervention has been a standard treatment strategy for patients with coronary artery disease with continuous ebullient progress in technology and techniques. The application of artificial intelligence and deep learning in particular is currently boosting the development of interventional solutions, improving the efficiency and objectivity of diagnosis and treatment. The ever-growing amount of data and computing power together with cutting-edge algorithms pave the way for the integration of deep learning into clinical practice, which has revolutionized the interventional workflow in imaging processing, interpretation, and navigation. This review discusses the development of deep learning algorithms and their corresponding evaluation metrics together with their clinical applications. Advanced deep learning algorithms create new opportunities for precise diagnosis and tailored treatment with a high degree of automation, reduced radiation, and enhanced risk stratification. Generalization, interpretability, and regulatory issues are remaining challenges that need to be addressed through joint efforts from multidisciplinary community.

Optical coherence tomography and coronary revascularization: from indication to procedural optimization

Angiography alone is the most commonly used imaging modality for guidance of percutaneous coronary interventions. Angiography is limited, however, by several factors, including that it only portrays a low resolution, two-dimensional outline of the lumen and does not inform on plaque composition and functional stenosis severity. Optical coherence tomography (OCT) is an intracoronary imaging technique that has superior spatial resolution compared to all other imaging modalities. High-resolution imaging of the vascular wall enables precise measurement of vessel wall and luminal dimensions, more accurately informing about the anatomic severity of epicardial stenoses, and also provides input for computational models to assess functional severity. The very high-resolution images also permit plaque characterization that may be informative for prognostication. Moreover, periprocedural imaging provides valuable information to guide lesion preparation, stent implantation and to evaluate acute stent complications for which iterative treatment might reduce the occurrence of major adverse stent events. As such, OCT represent a potential future all-in-one tool that provides the data necessary to establish the indications, procedural planning and optimization, and final evaluation of percutaneous coronary revascularization.

In-Hospital Heart Failure in Patients With Takotsubo Cardiomyopathy Due to Coronary Artery Disease: An Artificial Intelligence and Optical Coherence Tomography Study

BACKGROUND

Takotsubo syndrome (TTS) is often associated with symptoms of heart failure (HF) during the acute phase of the disease. 3-dimensional optical coherence tomography (OCT) may be used to assess the extent of angiographically silent underlying coronary artery disease (CAD). This study aims to use an artificial intelligence algorithm to analyze OCT findings and to determine whether the presence of pre-existing CAD predisposes TTS patients to present HF at admission.

METHODS

This is an observational and retrospective study that enrolled TTS patients who underwent coronary angiography and OCT examination of left anterior descending (LAD) coronary artery. Plaque characterization was automatically analyzed via an artificial intelligence model from OCT images. An angiography-derived index of microcirculatory resistance (IMRangio) using the optic flow ratio (OFR) was calculated to assess its correlation with plaque volumes.

RESULTS

Thirty-seven patients were included (94.6 % women) with a median age of 82.0 years. Ten patients (27 %) showed some degree of HF at admission. Sixty-seven coronary non-obstructive plaques were analyzed. Tissue compositional analysis showed that patients with HF had an increased overall plaque volume (79.0 mm³ vs 28.6 mm³; p = 0.011) and longer plaque lesion length (12.8 mm vs 7.2 mm; p = 0.006). Patients with HF also showed an increased percentage of lipidic and calcified plaque tissue (26.4 % vs 13.4 %; p = 0.019 and 4.5 % vs 0.0 %; p = 0.001, respectively). A moderate positive correlation was found between global overall plaque volume and IMRangio.

CONCLUSION

Increased overall plaque volume was associated with the development of HF during the acute phase of TTS, suggesting that the presence of angiographically silent underlying CAD may play a prognostic role in these patients.

Diagnostic efficacy of the optical flow ratio in patients with coronary heart disease: A meta-analysis

BACKGROUND

Coronary atherosclerotic heart disease (CAD) remains one of the most serious diseases threatening human health and life. PCI (Percutaneous Coronary Intervention) is the most common treatment for patients with CAD. A rigorous and comprehensive assessment of coronary artery lesions is now needed before PCI, however, there is no consensus on how best evaluate the combination of various intracavitary imaging techniques. By merging the benefits of physiological assessment and high-definition imaging, the optical flow ratio (OFR) has emerged as a novel technology with promising prospects for application.

METHODS

A systematic review of the literature was conducted. Studies that met the criteria of the meta-analysis were considered to assess OFR and FFR (fractional flow reserve). And the summary values of sensitivity and specificity of diagnostic tests and summary receiver operating curves (SROC) were calculated.

RESULTS

A total of 5 studies were included. The sensitivity and specificity of OFR in the diagnosis of coronary artery lesions were 0.83 (95% CI: 0.75-0.88) and 0.94 (95% CI: 0.91-0.96), respectively; the positive likelihood ratio and the negative likelihood ratio were 14 (95% CI: 9.3, 21.3) and 0.18 (95% CI:0.13, 0.27), respectively. OFR showed good correlation and consistency with FFR.

CONCLUSION

The new OFR technique achieve an encouraging diagnostic performance, which also showed good correlation and consistency with FFR.

Intravascular Imaging-Derived Physiology-Basic Principles and Clinical Application

Intravascular imaging-derived physiology is emerging as a promising tool allowing simultaneous anatomic and functional lesion assessment. Recently, several optical coherence tomography-based and intravascular ultrasound-based fractional flow reserve (FFR) indices have been developed that compute FFR through computational fluid dynamics, fluid dynamics equations, or machine-learning methods. This review aims to provide an overview of the currently available intravascular imaging-based physiologic indices, their diagnostic performance, and clinical application.

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

Background and Objective

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.

Methods

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.

Key Content and Findings

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.

Conclusions

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.

Numerical vs analytical comparison with experimental fractional flow reserve values of right coronary artery stenosis

BACKGROUND: The fractional flow reserve (FFR) index has been widely accepted as a standard diagnostic method for identifying functional relevance of coronary stenosis. Since the invasive techniques used for its determination are associated with a certain risk of vascular injury, as well as with an increased cost, several non-invasive procedures have been developed. OBJECTIVE: The aim of this study was to compare FFR values for the coronary artery obtained by computational fluid dynamics (CFD) and coronary computed tomography angiography (CCTA). METHODS: Computation of FFR has been performed using both numerical and the analytical method. The numerical method employs CFD to solve the governing equations which relate to mass and momentum conservation (the continuity equation and the Navier-Stokes equations) as well as CCTA to generate the three-dimensional computational domain. After imposing the appropriate boundary conditions, the values of the pressure change are calculated and the FFR index is determined. Based on Bernoulli’s law, the analytical method calculates the overall pressure drop across the stenosis in the coronary artery, enabling FFR determination. RESULTS: The clinical data for twenty patients who underwent invasive coronary angiography are used to validate the results obtained by using CFD (together with CCTA) simulation and analytical solution. The medically measured FFR compared to the analytical one differs by about 4%, while, the difference is about 2.6% when compared to the numerical FFR. For FFR values below 0.8 (which are considered to be associated with myocardial ischemia) the standard error has a value of 0.01201, while the standard deviation is 0.02081. For FFR values above 0.80, these values are slightly higher. Bland-Altman analysis showed that medical measurement and numerical FFR were in good agreement (SD = 0.0292, p< 0.0001). CONCLUSIONS: The analytically calculated FFR has a slightly lower coefficient of determination than the numerically computed FFR when compared with experimental one. However, it can still give a reliable answer to the question of whether patients need a stent, bypass surgery or only drug treatment and it requires a significantly lower computation time.

Coronary physiology in the catheterisation laboratory: an A to Z practical guide

Coronary revascularisation, either percutaneous or surgical, aims to improve coronary flow and relieve myocardial ischaemia. The decision-making process in patients with coronary artery disease (CAD) remains largely based on invasive coronary angiography (ICA), even though until recently ICA could not assess the functional significance of coronary artery stenoses. Invasive wire-based approaches for physiological evaluations were developed to properly assess the ischaemic relevance of epicardial CAD. Fractional flow reserve (FFR) and later, instantaneous wave-free ratio (iFR), were shown to improve clinical outcomes in several patient subsets when used for coronary revascularisation guidance or deferral and for procedural optimisation of percutaneous coronary intervention (PCI) results. Despite accumulating evidence and positive guideline recommendations, the adoption of invasive physiology has remained quite low, mainly due to technical and economic issues as well as to operator-resistance to change. Coronary image-based computational physiology has been recently developed, with promising results in terms of accuracy and a reduction in computational time, costs, radiation exposure and risks for the patient. Lastly, the integration of intracoronary imaging and physiology allows for individualised PCI treatment, aiming at complete relief of ischaemia through optimised morpho-functional immediate procedural results. Instead of a conventional state-of-the-art review, this A to Z dictionary attempts to provide a practical guide for the application of coronary physiology in the catheterisation laboratory, exploring several methods, their pitfalls, and useful tips and tricks.

Radial wall strain: a novel angiographic measure of plaque composition and vulnerability

BACKGROUND

The lipid-to-cap ratio (LCR) and thin-cap fibroatheroma (TCFA) derived from optical coherence tomography (OCT) are indicative of plaque vulnerability.

AIMS

We aimed to explore the association of a novel method to estimate radial wall strain (RWS) from angiography with plaque composition and features of vulnerability assessed by OCT.

METHODS

Anonymised data from patients with intermediate stenosis who underwent coronary angiography (CAG) and OCT were analysed in a core laboratory. Angiography-derived RWSmax was computed as the maximum deformation of lumen diameter throughout the cardiac cycle, expressed as a percentage of the largest lumen diameter. The LCR and TCFA were automatically determined on OCT images by a recently validated algorithm based on artificial intelligence.

RESULTS

OCT and CAG images from 114 patients (124 vessels) were analysed. The average time for the analysis of RWSmax was 57 (39-82) seconds. The RWSmax in the interrogated plaques was 12% (10-15%) and correlated positively with the LCR (r=0.584; p<0.001) and lipidic plaque burden (r=0.411; p<0.001), and negatively with fibrous cap thickness (r= -0.439; p<0.001). An RWSmax >12% was an angiographic predictor for an LCR >0.33 (area under the curve [AUC]=0.86, 95% confidence interval [CI]: 0.78-0.91; p<0.001) and TCFA (AUC=0.72, 95% CI: 0.63-0.80; p<0.001). Lesions with RWSmax >12% had a higher prevalence of TCFA (22.0% versus 1.5%; p<0.001), thinner fibrous cap thickness (71 μm versus 101 μm; p<0.001), larger lipidic plaque burden (23.3% versus 15.4%; p<0.001), and higher maximum LCR (0.41 versus 0.18; p<0.001) compared to lesions with RWSmax ≤12%.

CONCLUSIONS

Angiography-derived RWS was significantly correlated with plaque composition and known OCT features of plaque vulnerability in patients with intermediate coronary stenosis.

Morphometric Assessment for Functional Evaluation of Coronary Stenosis with Optical Coherence Tomography and the Optical Flow Ratio in a Vessel with Single Stenosis

Objectives: The study aimed to evaluate the diagnostic performance of optical coherence tomography (OCT) in identifying functionally significant coronary stenosis in a vessel with single stenosis. Background: The OCT-based morphofunctional computational method for deriving the optical flow ratio (OFR) has diagnostic value, as it can identify the functional severity of coronary stenosis, but the ability of the OFR to aid the OCT in determining coronary stenosis hemodynamics in single-stenosis lesion remains unclear. Methods: 74 vessels with single stenosis were studied in 69 patients; all cases were performed through OCT and quantitative flow ratio (QFR), and OCT images were used to perform OFR. Results: Among vessels with single stenosis, OFR showed a good correlation with QFR (r = 0.86; p < 0.001). Taking QFR as the standard, the vessel-level diagnosis accuracy, sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) of OFR were 90% (95% CI: 81 to 96), 94% (95% CI: 77 to 99), 88% (95% CI: 74 to 96), 85% (95% CI: 68 to 94) and 95% (95% CI: 82 to 99), respectively. Among vessels with OFR/QFR concordance, both the minimum lumen area (MLA) and minimum lumen diameter (MLD) showed excellent diagnostic efficiency (MLA: area under the curve (AUC) = 0.92, 95% CI: 0.85 to 0.98, p < 0.001; MLD: AUC = 0.93, 95% CI: 0.86 to 0.98, p < 0.001) in determining the functional significance of coronary stenosis in a single stenosis lesion, and the best cutoff values were 1.55 mm2 and 1.40 mm. Conclusions: OFR has a good correlation with QFR. OCT-measured MLA and MLD have excellent diagnostic efficiency in identifying the hemodynamic significance of coronary stenosis in a vessel with single stenosis.

Coronary functional assessment in non-obstructive coronary artery disease: Present situation and future direction

Non-obstructive coronary artery disease (CAD), which is defined as coronary stenosis <50%, has been increasingly recognized as an emerging entity in clinical practice. Vasomotion abnormality and coronary microvascular dysfunction are two major mechanisms contributing to the occur of angina with non-obstructive CAD. Although routine coronary functional assessment is limited due to several disadvantages, functional evaluation can help to understand the pathophysiological mechanism and/or to exclude specific etiologies. In this review, we summarized the potential mechanisms involved in ischemia with non-obstructive coronary arteries (INOCA) and myocardial infarction with non-obstructive coronary arteries (MINOCA), the two major form of non-obstructive CAD. Additionally, we reviewed currently available functional assessment indices and their use in non-obstructive CAD. Furthermore, we speculated that novel technique combined anatomic and physiologic parameters might provide more individualized therapeutic choice for patients with non-obstructive CAD.

Risk Stratification in Acute Coronary Syndrome by Comprehensive Morphofunctional Assessment With Optical Coherence Tomography

Background

Artificial intelligence enables simultaneous evaluation of plaque morphology and computational physiology from optical coherence tomography (OCT).

Objectives

This study sought to appraise the predictive value of major adverse cardiovascular events (MACE) by combined plaque morphology and computational physiology.

Methods

A total of 604 patients with acute coronary syndrome who underwent OCT imaging in ≥1 nonculprit vessel during index coronary angiography were retrospectively enrolled. A novel morphologic index, named the lipid-to-cap ratio (LCR), and a functional parameter to evaluate the physiologic significance of coronary stenosis from OCT, namely, the optical flow ratio (OFR), were calculated from OCT, together with classical morphologic parameters, like thin-cap fibroatheroma (TCFA) and minimal lumen area.

Results

The 2-year cumulative incidence of a composite of nonculprit vessel–related cardiac death, cardiac arrest, acute myocardial infarction, and ischemia-driven revascularization (NCV-MACE) at 2 years was 4.3%. Both LCR (area under the curve [AUC]: 0.826; 95% CI: 0.793-0.855) and OFR (AUC: 0.838; 95% CI: 0.806-0.866) were superior to minimal lumen area (AUC: 0.618; 95% CI: 0.578-0.657) in predicting NCV-MACE at 2 years. Patients with both an LCR of >0.33 and an OFR of ≤0.84 had significantly higher risk of NCV-MACE at 2 years than patients in whom at least 1 of these 2 parameters was normal (HR: 42.73; 95% CI: 12.80-142.60; P < 0.001). The combination of thin-cap fibroatheroma and OFR also identified patients at higher risk of future events (HR: 6.58; 95% CI: 2.83-15.33; P < 0.001).

Conclusions

The combination of LCR with OFR permits the identification of a subgroup of patients with 43-fold higher risk of recurrent cardiovascular events in the nonculprit vessels after acute coronary syndrome.

Towards a Deep-Learning Approach for Prediction of Fractional Flow Reserve from Optical Coherence Tomography

Cardiovascular disease (CVD) is the number one cause of death worldwide, and coronary artery disease (CAD) is the most prevalent CVD, accounting for 42% of these deaths. In view of the limitations of the anatomical evaluation of CAD, Fractional Flow Reserve (FFR) has been introduced as a functional diagnostic index. Herein, we evaluate the feasibility of using deep neural networks (DNN) in an ensemble approach to predict the invasively measured FFR from raw anatomical information that is extracted from optical coherence tomography (OCT). We evaluate the performance of various DNN architectures under different formulations: regression, classification—standard, and few-shot learning (FSL) on a dataset containing 102 intermediate lesions from 80 patients. The FSL approach that is based on a convolutional neural network leads to slightly better results compared to the standard classification: the per-lesion accuracy, sensitivity, and specificity were 77.5%, 72.9%, and 81.5%, respectively. However, since the 95% confidence intervals overlap, the differences are statistically not significant. The main findings of this study can be summarized as follows: (1) Deep-learning (DL)-based FFR prediction from reduced-order raw anatomical data is feasible in intermediate coronary artery lesions; (2) DL-based FFR prediction provides superior diagnostic performance compared to baseline approaches that are based on minimal lumen diameter and percentage diameter stenosis; and (3) the FFR prediction performance increases quasi-linearly with the dataset size, indicating that a larger train dataset will likely lead to superior diagnostic performance.

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

Background

Coronary 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.

Methods

Among 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.

Results

Fusion-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).

Conclusion

CFD-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].

Angiographic Lesion Morphology Provides Incremental Value to Generalize Quantitative Flow Ratio for Predicting Myocardial Ischemia

Aim

The quantitative flow ratio (QFR) is favorable for functional assessment of coronary artery stenosis without pressure wires and induction of hyperemia. The aim of this study was to explore whether angiographic lesion morphology provides incremental value to generalize QFR for predicting myocardial ischemia in unselected patients.

Methods

This study was a substudy to the CT-FFR CHINA trial, referring 345 participants from five centers with suspected coronary artery disease on coronary CT angiography for diagnostic invasive coronary angiography (ICA). Fractional flow reserve (FFR) was measured in all vessels with 30–90% diameter stenosis. QFR was calculated in 186 lesions from 159 participants in a blinded manner. In addition, parameters to characterize lesion features were recorded or measured, including left anterior descending arteries (LADs)-involved lesions, side branch located at stenotic lesion (BL), multiple lesions (ML), minimal lumen diameter (MLD), reference lumen diameter (RLD), percent diameter stenosis (%DS), lesion length (LL), and LL/MLD4. Logistic regression was used to construct two kinds of models by combining single or two lesion parameters with the QFR. The performances of these models were compared with that of QFR on a per-vessel level.

Results

A total of 148 participants (mean age: 59.5 years; 101 men) with 175 coronary arteries were included for final analysis. In total, 81 (46%) vessels were considered hemodynamically significant. QFR correctly classified 82.29% of the vessels using FFR with a cutoff of 0.80 as reference standard. The area under the receiver operating characteristic curve (AUC) of QFR was 0.86 with a sensitivity, specificity, positive predictive value, and negative predictive value of 80.25, 84.04, 81.25, and 83.16%, respectively. The combined models (QFR + LAD + MLD, QFR + LAD + %DS, QFR + BL + MLD, and QFR + BL + %DS) outperformed QFR with higher AUCs (0.91 vs. 0.86, P = 0.02; 0.91 vs. 0.86, P = 0.02; 0.91 vs. 0.86, P = 0.02; 0.90 vs. 0.86, P = 0.03, respectively). Compared with QFR, the sensitivity of the combined models (QFR + BL and QFR + MLD) was improved (91.36 vs. 80.25%, 91.36 vs. 80.25%, respectively, both P &lt; 0.05) without compromised specificity or accuracy.

Conclusion

Combined with angiographic lesion parameters, QFR can be optimized for predicting myocardial ischemia in unselected patients.

Fractional Flow Reserve (FFR) Estimation from OCT-Based CFD Simulations: Role of Side Branches

The computational fluid dynamic method has been widely used to quantify the hemodynamic alterations in a diseased artery and investigate surgery outcomes. The artery model reconstructed based on optical coherence tomography (OCT) images generally does not include the side branches. However, the side branches may significantly affect the hemodynamic assessment in a clinical setting, i.e., the fractional flow reserve (FFR), defined as the ratio of mean distal coronary pressure to mean aortic pressure. In this work, the effect of the side branches on FFR estimation was inspected with both idealized and optical coherence tomography (OCT)-reconstructed coronary artery models. The electrical analogy of blood flow was further used to understand the impact of the side branches (diameter and location) on FFR estimation. Results have shown that the side branches decrease the total resistance of the vessel tree, resulting in a higher inlet flowrate. The side branches located at the downstream of the stenosis led to a lower FFR value, while the ones at the upstream had a minimal impact on the FFR estimation. Side branches with a diameter larger than one third of the main vessel diameter are suggested to be considered for a proper FFR estimation. The findings in this study could be extended to other coronary artery imaging modalities and facilitate treatment planning.

Physiologic and compositional coronary artery disease extension in patients with takotsubo syndrome assessed using artificial intelligence: an optical coherence tomography study

BACKGROUND

Takotsubo syndrome (TTS) is an acute and reversible ventricular motion abnormality without epicardial coronary obstruction. Optical flow ratio (OFR) is an approach to evaluate the coronary stenosis significance based on three-dimensional optical coherence tomography (3D-OCT). The aim of this study is to utilize OCT and an artificial intelligence plaque characterization model to show the prevalence and composition of atherosclerotic disease in coronary vessels of patients with TTS.

METHODS

This is a retrospective and observational study which enrolled patients with TTS who underwent coronary angiography and OCT examination. OCT images were analyzed for tissue characterization and OFR computation using a novel artificial intelligence algorithm.

RESULTS

A total of 37 patients and 49 vessels were studied. All patients were imaged in the left anterior descending coronary artery (LAD) and about two-thirds were also imaged in the left circumflex coronary artery (LCX). Most patients were women (n = 35), and apical was the most common takotsubo type. Tissue composition analysis yielded the following overall plaque types: fibrous (67.1%), lipid (15.5%), and calcium (3.77%). The mean OFR for LAD and LCX was 0.97 ± 0.04 and 0.98 ± 0.02, respectively.

CONCLUSION

Utilizing automatic plaque characterization on OCT images by artificial intelligence, we found that TTS patients have coronary artery disease (i.e. presence of lipid, calcified, or fibrous tissue). The advent of artificial intelligence methods may allow for large-scale studies of patients with TTS.

Microvascular and Prognostic Effect in Lesions With Different Stent Expansion During Primary PCI for STEMI: Insights From Coronary Physiology and Intravascular Ultrasound

Background

While coronary stent implantation in ST-elevation myocardial infarction (STEMI) can mechanically revascularize culprit epicardial vessels, it might also cause distal embolization. The relationship between geometrical and functional results of stent expansion during the primary percutaneous coronary intervention (pPCI) is unclear.

Objective

We sought to determine the optimal stent expansion strategy in pPCI using novel angiography-based approaches including angiography-derived quantitative flow ratio (QFR)/microcirculatory resistance (MR) and intravascular ultrasound (IVUS).

Methods

Post-hoc analysis was performed in patients with acute STEMI and high thrombus burden from our prior multicenter, prospective cohort study (ChiCTR1800019923). Patients aged 18 years or older with STEMI were eligible. IVUS imaging, QFR, and MR were performed during pPCI, while stent expansion was quantified on IVUS images. The patients were divided into three subgroups depending on the degree of stent expansion as follows: overexpansion (>100%), optimal expansion (80%−100%), and underexpansion (<80%). The patients were followed up for 12 months after PCI. The primary endpoint included sudden cardiac death, myocardial infarction, stroke, unexpected hospitalization or unplanned revascularization, and all-cause death.

Results

A total of 87 patients were enrolled. The average stent expansion degree was 82% (in all patients), 117% (in overexpansion group), 88% (in optimal expansion), and 75% (in under-expansion). QFR, MR, and flow speed increased in all groups after stenting. The overall stent expansion did not affect the final QFR (p = 0.08) or MR (p = 0.09), but it reduced the final flow speed (−0.14 cm/s per 1%, p = 0.02). Under- and overexpansion did not affect final QFR (p = 0.17), MR (p = 0.16), and flow speed (p = 0.10). Multivariable Cox analysis showed that stent expansion was not the risk factor for MACE (hazard ratio, HR = 0.97, p = 0.13); however, stent expansion reduced the risk of MACE (HR = 0.95, p = 0.03) after excluding overexpansion patients. Overexpansion was an independent risk factor for no-reflow (HR = 1.27, p = 0.02) and MACE (HR = 1.45, p = 0.007). Subgroup analysis shows that mild underexpansion of 70%−80% was not a risk factor for MACE (HR = 1.11, p = 0.08) and no-reflow (HR = 1.4, p = 0.08); however, stent expansion <70% increased the risk of MACE (HR = 1.36, p = 0.04).

Conclusions

Stent expansion does not affect final QFR and MR, but it reduces flow speed in STEMI. Appropriate stent underexpansion of 70–80% does not seem to be associated with short-term prognosis, so it may be tolerable as noninferior compared with optimal expansion. Meanwhile, overexpansion and underexpansion of <70% should be avoided due to the independent risk of MACEs and no-reflow events.

Diagnostic performance of intravascular ultrasound-based fractional flow reserve versus angiography-based quantitative flow ratio measurements for evaluating left main coronary artery stenosis

OBJECTIVES

We compared the diagnostic performance of the ultrasonic flow ratio (UFR) and quantitative flow ratio (QFR) for left main coronary artery (LMCA) stenosis.

BACKGROUND

Evaluation of LMCA stenosis remains challenging because of its complex pathogenesis and severity. Computing QFR allows rapid determination of fractional flow reserve (FFR) from coronary angiograms. A novel intravascular ultrasound (IVUS)-based FFR (UFR) allows rapid FFR computation from IVUS images. Neither of the computational approaches required a pressure wire or hyperemia induction. Previous studies have validated the good diagnostic accuracy of QFR and UFR in identifying hemodynamically significant coronary stenosis using FFR as the reference standard.

METHODS

This retrospective observational study enrolled consecutive patients with intermediate-grade LMCA stenosis who underwent IVUS evaluation. UFR and QFR of all LMCA stenosis patients were assessed, their correlation and agreement were analyzed, and diagnostic performance of UFR in LMCA stenosis was evaluated.

RESULTS

Eighty-three paired comparisons between UFR and QFR were obtained. UFR excellently correlated with QFR (r = 0.74, p < 0.01). The Bland-Altman plot showed good agreement between UFR and QFR (mean differences: 0.01 ± 0.05, p = 0.34). The area under the curve of UFR for identifying physiological LMCA stenosis was 0.97 (95% confidence interval [CI]: 0.93-1.00, p < 0.01). The overall UFR diagnostic accuracy was 0.95 (95% CI: 0.88-0.99).

CONCLUSIONS

UFR showed excellent correlation and good agreement with QFR in LMCA stenosis assessment, indicating that it is highly feasible to use UFR for functional evaluation of LMCA stenosis.

The Role of Coronary Physiology in Contemporary Percutaneous Coronary Interventions

Invasive assessment of coronary physiology has radically changed the paradigm of myocardial revascularization in patients with coronary artery disease. Despite the prognostic improvement associated with ischemia-driven revascularization strategy, functional assessment of angiographic intermediate epicardial stenosis remains largely underused in clinical practice. Multiple tools have been developed or are under development in order to reduce the invasiveness, cost, and extra procedural time associated with the invasive assessment of coronary physiology. Besides epicardial stenosis, a growing body of evidence highlights the role of coronary microcirculation in regulating coronary flow with consequent pathophysiological and clinical and prognostic implications. Adequate assessment of coronary microcirculation function and integrity has then become another component of the decision-making algorithm for optimal diagnosis and treatment of coronary syndromes. This review aims at providing a comprehensive description of tools and techniques currently available in the catheterization laboratory to obtain a thorough and complete functional assessment of the entire coronary tree (both for the epicardial and microvascular compartments).

Optical flow ratio for assessing stenting result and physiological significance of residual disease

BACKGROUND

Optical flow ratio (OFR) is a novel method for fast computation of fractional flow reserve (FFR) from optical coherence tomography (OCT) images.

AIMS

We aimed to evaluate the accuracy of OFR in predicting post-percutaneous coronary intervention (PCI) FFR and the impact of stent expansion on within-stent OFR pressure drop (in-stent OFR).

METHODS

Post-PCI OFR was computed in patients with both OCT and FFR interrogation immediately after PCI. Calculation of post-PCI OFR (called simulated residual OFR) from pre-PCI OCT pullbacks after elimination of the stenotic segment by virtual stenting was performed in a subgroup of patients who had pre-PCI OCT images. Stent underexpansion was quantified by the minimum expansion index (MEI) of the stented segment.

RESULTS

A total of 125 paired comparisons between post-PCI OFR and FFR were obtained in 119 patients, among which simulated residual OFR was obtained in 64 vessels. Mean post-PCI FFR was 0.92±0.05. Post-PCI OFR showed good correlation (r=0.74, p<0.001) and agreement (mean difference=-0.01±0.03, p=0.051) with FFR. The accuracy in predicting post-PCI FFR ≤0.90 was 84% for post-PCI OFR. Simulated residual OFR significantly correlated with post-PCI FFR (r=0.42, p<0.001). MEI showed a moderate correlation (r=-0.49, p<0.001) with in-stent OFR.

CONCLUSIONS

Post-PCI OFR showed good diagnostic concordance with post-PCI FFR. Simulated residual OFR significantly correlated with post-PCI FFR. Stent underexpansion significantly correlated with in-stent pressure drop.

Optical Coherence Tomography-Derived Changes in Plaque Structural Stress Over the Cardiac Cycle: A New Method for Plaque Biomechanical Assessment

Introduction: Cyclic plaque structural stress has been hypothesized as a mechanism for plaque fatigue and eventually plaque rupture. A novel approach to derive cyclic plaque stress in vivo from optical coherence tomography (OCT) is hereby developed. Materials and Methods: All intermediate lesions from a previous OCT study were enrolled. OCT cross-sections at representative positions within each lesion were selected for plaque stress analysis. Detailed plaque morphology, including plaque composition, lumen and internal elastic lamina contours, were automatically delineated. OCT-derived vessel and plaque morphology were included in a 2-dimensional finite element analysis, loaded with patient-specific intracoronary pressure tracing data, to calculate the changes in plaque structural stress (ΔPSS) on vessel wall over the cardiac cycle. Results: A total of 50 lesions from 41 vessels were analyzed. A significant ΔPSS gradient was observed across the plaque, being maximal at the proximal shoulder (45.7 [32.3, 78.6] kPa), intermediate at minimal lumen area (MLA) (39.0 [30.8, 69.1] kPa) and minimal at the distal shoulder (35.1 [28.2, 72.3] kPa; p = 0.046). The presence of lipidic plaques were observed in 82% of the diseased segments. Larger relative lumen deformation and ΔPSS were observed in diseased segments, compared with normal segments (percent diameter change: 8.2 ± 4.2% vs. 6.3 ± 2.3%, p = 0.04; ΔPSS: 59.3 ± 48.2 kPa vs. 27.5 ± 8.2 kPa, p < 0.001). ΔPSS was positively correlated with plaque burden (r = 0.37, p < 0.001) and negatively correlated with fibrous cap thickness (r = -0.25, p = 0.004). Conclusions: ΔPSS provides a feasible method for assessing plaque biomechanics in vivo from OCT images, consistent with previous biomechanical and clinical studies based on different methodologies. Larger ΔPSS at proximal shoulder and MLA indicates the critical sites for future biomechanical assessment.

Fractional flow reserve for coronary stenosis assessment derived from fusion of intravascular ultrasound and X-ray angiography

Background

Intravascular ultrasound (IVUS) provides good insight into lumen boundary and plaques; however, it is still difficult to detect functionally significant stenosis from IVUS images for the guidance of coronary percutaneous intervention (PCI). This study aimed to develop a novel method to estimate fractional flow reserve (FFR) value for determining the functional significance of coronary artery disease through the fusion of IVUS and X-ray angiographic images.

Methods

We developed a novel approach to 3D vessel reconstruction by integrating IVUS with X-ray angiographic images. Based on the reconstructed geometry and the inlet flow derived from the thrombolysis in myocardial infarction (TIMI) frame count, a simplified fluid dynamics equation was established to compute the pressure drop and IVUS-derived FFR (AccuFFRivus) was subsequently obtained. To validate the feasibility and performance of this IVUS-based FFR method, we performed AccuFFRivus calculations on 32 coronary vessels with invasive FFR as the reference standard.

Results

Great correlation (r=0.86, P<0.001) was observed between AccuFFRivus and FFR. The area under the receiver-operating characteristic curve (AUC) was higher for AccuFFRivus than minimal lumen area (MLA, <4 mm²) and diameter stenosis rate (DS% ≥50%) [0.98 (95% CI: 0.86 to 1.0) vs. 0.78 (95% CI: 0.60 to 0.91) and 0.66 (95% CI: 0.47 to 0.82)]. Bland-Altman plot showed a mean difference value of -0.011 (limits of agreement: -0.156 to 0.134).

Conclusions

AccuFFRivus is a novel method for hybridizing IVUS and X-ray angiographic images to identify functionally significant stenosis with FFR ≤0.80. The good diagnostic performance from the initial validation study demonstrates the potential for clinical utilization of physiologically guided decision-making. Further validation is required in future studies with a large number of cases.

TCT Connect 2020 Trial Update: FORECAST, COMBINE OCT-FFR and DEFINE-PCI

Recent studies reported at TCT Connect 2020 have investigated a number of open clinical questions regarding the role of coronary physiology and the assessment of plaque morphology for diagnosis (FORECAST), risk stratification (COMBINE OCT-FFR) and treatment evaluation (DEFINE-PCI) of patients with coronary artery disease. In this article, the authors provide a critical appraisal of these studies and evaluate how they add to the current evidence base for management of patients with epicardial coronary artery disease. Furthermore, they discuss their potential impact on clinical practice, limitations of these studies and unanswered clinical questions that are areas for future research.