Diagnostic Performance of a Novel Method for Fractional Flow Reserve Computed from Noninvasive Computed Tomography Angiography (NOVEL-FLOW Study)

Diagnosis of perimenopausal coronary heart disease patients using radiomics signature of pericoronary adipose tissue based on coronary computed tomography angiography

To assess whether the radiomics signature of pericoronary adipose tissue (PCAT) from coronary computed tomography angiography (CCTA) can distinguish between perimenopausal women with coronary heart disease (CHD) and those without coronary artery disease (CAD). This single-center retrospective case-control study comprised 140 perimenopausal women with CHD presenting with chest pain who underwent CCTA within 48 h of admission. They were matched with 140 control patients presenting with chest pain but without CAD, based on age, risk factors, radiation dose and CT tube voltage. For all participants, PCAT around the proximal right coronary artery was segmented, from which radiomics features and the fat attenuation index (FAI) were extracted and analyzed. Subsequently, corresponding models were developed and internally validated using Bootstrap methods. Model performance was assessed through measures of identification, calibration, and clinical utility. Using logistic regression analysis, an integrated model that combines clinical features, fat attenuation index and radiomics parameters demonstrated enhanced discrimination ability for perimenopausal CHD (area under the curve [AUC]: 0.80, 95% confidence interval [CI]:0.740-0.845). This model outperformed both the combination of clinical features and PCAT attenuation (AUC 0.67, 95% CI 0.602-0.727) and the use of clinical features alone (AUC 0.66, 95% CI 0.603-0.732). Calibration curves for the three predictive models indicated satisfactory fit (all p > 0.05). Moreover, decision curve analysis demonstrated that the integrated model offered greater clinical benefit compared to the other two models. The CCTA-based radiomics signature derived from the PCAT model outperforms the FAI model in differentiating perimenopausal CHD patients from non-CAD individuals. Integrating PCAT radiomics with the FAI could enhance the diagnostic accuracy for perimenopausal CHD.

Noninvasive Coronary Physiological Assessment Derived From Computed Tomography

Identifying functional significance using physiological indexes is a standard approach in decision-making for treatment strategies in patients with coronary artery disease. Recently, coronary computed tomography angiography-based physiological assessments, such as computed tomography perfusion and fractional flow reserve derived from coronary computed tomography angiography (FFR-CT), have emerged. These methods have provided incremental diagnostic values for ischemia-causing lesions over anatomical stenosis defined solely by coronary computed tomography angiography. Clinical data have demonstrated their prognostic value in the prediction of adverse cardiovascular events. Several randomized controlled studies have shown that clinical use of FFR-CT can reduce unnecessary invasive procedures compared to usual care. Recent studies have also expanded the role of FFR-CT in defining target lesions for revascularization by acquiring noninvasive lesion-specific hemodynamic indexes like ΔFFR-CT. This review encompasses the current evidence of the diagnostic and prognostic performance of computed tomography-based physiological assessment in defining ischemia-causing lesions and adverse cardiac events, its clinical impact on treatment decision-making, and implications for revascularization.

Performance of a Novel CT-Derived Fractional Flow Reserve Measurement to Detect Hemodynamically Significant Coronary Stenosis

BACKGROUND

Fractional flow reserve (FFR) based on computed tomography (CT) has been shown to better identify ischemia-causing coronary stenosis. However, this current technology requires high computational power, which inhibits its widespread implementation in clinical practice. This prospective, multicenter study aimed at validating the diagnostic performance of a novel simple CT based fractional flow reserve (CT-FFR) calculation method in patients with coronary artery disease.

METHODS

Patients who underwent coronary CT angiography (CCTA) within 90 days and invasive coronary angiography (ICA) were prospectively enrolled. A hemodynamically significant lesion was defined as an FFR ≤ 0.80, and the area under the receiver operating characteristic curve (AUC) was the primary measure. After the planned analysis for the initial algorithm A, we performed another set of exploratory analyses for an improved algorithm B.

RESULTS

Of 184 patients who agreed to participate in the study, 151 were finally analyzed. Hemodynamically significant lesions were observed in 79 patients (52.3%). The AUC was 0.71 (95% confidence interval [CI], 0.63-0.80) for CCTA, 0.65 (95% CI, 0.56-0.74) for CT-FFR algorithm A (P = 0.866), and 0.78 (95% CI, 0.70-0.86) for algorithm B (P = 0.112). Diagnostic accuracy was 0.63 (0.55-0.71) for CCTA alone, 0.66 (0.58-0.74) for algorithm A, and 0.76 (0.68-0.82) for algorithm B.

CONCLUSION

This study suggests the feasibility of automated CT-FFR, which can be performed on-site within several hours. However, the diagnostic performance of the current algorithm does not meet the a priori criteria for superiority. Future research is required to improve the accuracy.

CT Assessment of Myocardial Perfusion and Fractional Flow Reserve in Coronary Artery Disease: A Review of Current Clinical Evidence and Recent Developments

Coronary computed tomography angiography (CCTA) is routinely used for anatomical assessment of coronary artery disease (CAD). However, invasive measurement of fractional flow reserve (FFR) is the current gold standard for the diagnosis of hemodynamically significant CAD. CT-derived FFRCT and CT perfusion are two emerging techniques that can provide a functional assessment of CAD for risk stratification and clinical decision making. Several clinical studies have shown that the diagnostic performance of concomitant CCTA and functional CT assessment for detecting hemodynamically significant CAD is at least non-inferior to that of other routinely used imaging modalities. This article aims to review the current clinical evidence and recent developments in functional CT techniques.

Diagnostic performance of computed tomography-based fraction flow reserve in identifying myocardial ischemia caused by coronary artery stenosis: A meta-analysis

BACKGROUND

As a new noninvasive diagnostic technique, computed tomography (CT)-based fraction flow reserve (FFR) has been used to identify hemodynamically significant coronary artery stenosis. This meta-analysis used invasive FFR as the standard to evaluate the diagnostic performance of FFRCT.

METHODS

We searched the PubMed, Cochrane library, and EMBASE for articles published between January 2009 and January 2021. The synthesized sensitivity and specificity of invasive FFR and FFRCT were analyzed at both the patient and vessel levels. We generated a summary receiver operating characteristic curve (SROC) and then calculated the area under the curve (AUC).

RESULTS

We included a total of 23 studies, including 2,178 patients and 3,029 vessels or lesions. Analysis at each patient level demonstrated a synthesized sensitivity of 88%, specificity of 79%, LR+ of 4.16, LR-of 0.15, and AUC of 0.89 for FFRCT. Analysis at the level of each vessel or lesion showed a synthesized sensitivity of 85%, specificity of 81%, LR+ of 4.44, LR-of 0.19, and AUC of 0.87 for FFRCT.

CONCLUSION

Our research reveals that FFRCT has high diagnostic performance in patients with coronary artery stenosis, regardless of whether it is at the patient level or the vessel level.

Clinical application of computed tomography angiography and fractional flow reserve computed tomography in patients with coronary artery disease: A meta-analysis based on pre- and post-test probability

PURPOSE

To assess the diagnostic role of coronary computed tomography angiography (CCTA) and fractional flow reserve computed tomography (FFRCT) in confirming or excluding ischemic coronary artery disease (CAD) and to provide a rational use of CCTA and FFRCT in different pre-test probability (PTP) of CAD.

METHODS

We searched the electronic databases from the earliest relevant literature to July 2020 comparing FFRCT or CCTA with FFR. The bivariate random-effects models and Bayes' theorem were used to investigate the diagnostic performance of CCTA and FFRCT with the sensitivity, specificity, pre- and post-test probability.

RESULTS

Fifty-three articles with 4817 patients and 7026 vessels finally met our inclusion criteria. At the patient level, the sensitivity and specificity of CCTA were (0.94, 0.89-0.97), and (0.50, 0.43-0.58), respectively. For FFRCT, the sensitivity and specificity were (0.90, 0.87-0.93) and (0.81, 0.73-0.87). CCTA or FFRCT could increase the post-test probability to >85 % in patients with a PTP > 74.9 % or 54.5 %; CCTA or FFRCT could decrease the post-test probability to <15 % in patients with a pre-test probability <61.3 % or 59.3 %.

CONCLUSIONS

In patients with low to intermediate PTP, CCTA is suggested to exclude CAD, while the time-consuming calculation of FFRCT may be unnecessary. If CCTA detects significant or uncertain stenosis with intermediate to high PTP of CAD, further FFRCT is suggested. The advantages of FFRCT for guiding CAD treatment have sufficiently been demonstrated.

Myocardial Perfusion Simulation for Coronary Artery Disease: A Coupled Patient-Specific Multiscale Model

Patient-specific models of blood flow are being used clinically to diagnose and plan treatment for coronary artery disease. A remaining challenge is bridging scales from flow in arteries to the micro-circulation supplying the myocardium. Previously proposed models are descriptive rather than predictive and have not been applied to human data. The goal here is to develop a multiscale patient-specific model enabling blood flow simulation from large coronary arteries to myocardial tissue. Patient vasculatures are segmented from coronary computed tomography angiography data and extended from the image-based model down to the arteriole level using a space-filling forest of synthetic trees. Blood flow is modeled by coupling a 1D model of the coronary arteries to a single-compartment Darcy myocardium model. Simulated results on five patients with non-obstructive coronary artery disease compare overall well to [\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$^{15}$$\end{document}15O]\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\text {H}_{{2}}$$\end{document}H2O PET exam data for both resting and hyperemic conditions. Results on a patient with severe obstructive disease link coronary artery narrowing with impaired myocardial blood flow, demonstrating the model’s ability to predict myocardial regions with perfusion deficit. This is the first report of a computational model for simulating blood flow from the epicardial coronary arteries to the left ventricle myocardium applied to and validated on human data.

Fractional flow reserve derived from coronary computed tomography: where are we now and where are we heading?

Computed tomography coronary angiography is emerging as the preferred diagnostic tool for patients with chest pain. Additional knowledge of the extent and distribution of myocardial ischemia enables tailored patient management. Computed tomography-derived fractional flow reserve (FFR_CT) employs computed tomography coronary angiography raw data processed via complex computational fluid dynamics and produces a surrogate of the invasive fractional flow reserve (FFR) thus delivering anatomical and physiological assessment in a single test. FFR_CT has been extensively validated against invasive FFR and observational clinical studies have consistently demonstrated its utility as gatekeeper to invasive angiography while also reducing downstream clinical events and costs. Novel workstation-based models of estimating FFR are now being tested. Ongoing and future research results will define their role in clinical practice.

Functional cardiac CT-Going beyond Anatomical Evaluation of Coronary Artery Disease with Cine CT, CT-FFR, CT Perfusion and Machine Learning

The aim of this review is to provide an overview of different functional cardiac CT techniques which can be used to supplement assessment of the coronary arteries to establish the significance of coronary artery stenoses. We focus on cine-CT, CT-FFR, CT-myocardial perfusion and how developments in machine learning can supplement these techniques.

Validation of the diagnostic performance of 'HeartMedi V.1.0', a novel CT-derived fractional flow reserve measurement, for patients with coronary artery disease: a study protocol

INTRODUCTION

Coronary CT angiography (CCTA) is widely used for non-invasive coronary artery evaluation, but it is limited in identifying the nature of functional characteristics that cause ischaemia. Recent computational fluid dynamic (CFD) techniques applied to CCTA images permit non-invasive computation of fractional flow reserve (FFR), a measure of lesion-specific ischaemia. However, this technology has limitations, such as long computational time and the need for expensive equipment, which hinder widespread use.

METHODS AND ANALYSIS

This study is a prospective, multicentre, comparative and confirmatory trial designed to evaluate the diagnostic performance of HeartMedi V.1.0, a novel CT-derived FFR measurement for the detection of haemodynamically significant coronary artery stenoses identified by CCTA, based on invasive FFR as a reference standard. The invasive FFR values ≤0.80 will be considered haemodynamically significant. The study will enrol 184 patients who underwent CCTA, invasive coronary angiography and invasive FFR. Computational FFR (c-FFR) will be analysed by CFD techniques using a lumped parameter model based on vessel length method. Blinded core laboratory interpretation will be performed for CCTA, invasive coronary angiography, invasive FFR and c-FFR. The primary objective of the study is to compare the area under the receiver-operator characteristic curve between c-FFR and CCTA to non-invasively detect the presence of haemodynamically significant coronary stenosis. The secondary endpoints include diagnostic accuracy, sensitivity, specificity, positive predictive value, negative predictive value and correlation of c-FFR with invasive FFR.

ETHICS AND DISSEMINATION

The study has ethic approval from the ethics committee of Seoul National University Bundang Hospital (E-1709/420-001) and informed consent will be obtained for all enrolled patients. The result will be published in a peer-reviewed journal.

TRIAL REGISTRATION NUMBER

KCT0002725; Pre-results.

Diagnostic performance of a vessel-length-based method to compute the instantaneous wave-free ratio in coronary arteries

The instantaneous wave-free ratio (iFR) is a recently introduced vasodilator-free index to assess the functional severity of coronary stenosis in the resting state, while fractional flow reserve (FFR) is the gold standard index in hyperemia. The computed instantaneous wave-free ratio (CT-iFR) is a noninvasive method to estimate iFR using computer simulations. Here, we developed a vessel-length-based CT-iFR method in patient-specific models of coronary arteries. This method was implemented by coupling a three-dimensional computational fluid dynamics model with a lumped parameter model (LPM) of coronary circulation in a non-hyperemic resting state. A time-varying resistance in the LPM was used for the iFR simulation. In total, 50 coronary vessels of 32 patients were computed, and their CT-iFR values were compared with clinically measured iFRs to evaluate the diagnostic performance of the present CT-iFR method. The area under the receiver operating characteristics curve of CT-iFR validation was 0.93. In diagnostic performances of CT-iFR, accuracy, sensitivity, and specificity were 86%, 83.3%, and 86.8%, respectively. These results indicate that this CT-iFR method can be used as a pre-operative aid to establish a percutaneous coronary intervention strategy as a noninvasive alternative to iFR.

CT-Derived Fractional Flow Reserve (FFRCT): From Gatekeeping to Roadmapping

Coronary computed tomography angiography (CCTA) has emerged as the preferred modality in the diagnosis of coronary artery disease, but it is limited by modest specificity. By applying principles of computational fluid dynamics, flow fraction reserve, a measure of lesion-specific ischemia that is used to guide revascularization, can be noninvasively derived from CCTA, the so-called computed tomography–derived flow fractional reserve (FFRCT). The accuracy of FFRCT in discriminating ischemia has been extensively validated, and it has been shown to improve the specificity of CCTA. Compared to other stress myocardial perfusion imaging, FFRCT has superior or comparable accuracy. Clinical studies have provided strong evidence that FFRCT has significant prognostic implications and informs clinical decisions for revascularization, serving as a gatekeeper to invasive coronary angiography. In addition, FFRCT-based tools can be used to simulate the physiological consequences of different revascularization strategies, thus providing the roadmap to achieve complete revascularization. Although challenges remain, ongoing research and randomized controlled trials are expected to address current limitations and better define its role in clinical practice.

Future Directions in Coronary CT Angiography: CT-Fractional Flow Reserve, Plaque Vulnerability, and Quantitative Plaque Assessment

Coronary computed tomography angiography (CCTA) is a well-validated and noninvasive imaging modality for the assessment of coronary artery disease (CAD) in patients with stable ischemic heart disease and acute coronary syndromes (ACSs). CCTA not only delineates the anatomy of the heart and coronary arteries in detail, but also allows for intra- and extraluminal imaging of coronary arteries. Emerging technologies have promoted new CCTA applications, resulting in a comprehensive assessment of coronary plaques and their clinical significance. The application of computational fluid dynamics to CCTA resulted in a robust tool for noninvasive assessment of coronary blood flow hemodynamics and determination of hemodynamically significant stenosis. Detailed evaluation of plaque morphology and identification of high-risk plaque features by CCTA have been confirmed as predictors of future outcomes, identifying patients at risk for ACSs. With quantitative coronary plaque assessment, the progression of the CAD or the response to therapy could be monitored by CCTA. The aim of this article is to review the future directions of emerging applications in CCTA, such as computed tomography (CT)-fractional flow reserve, imaging of vulnerable plaque features, and quantitative plaque imaging. We will also briefly discuss novel methods appearing in the coronary imaging scenario, such as machine learning, radiomics, and spectral CT.

Diagnostic Performance of On-Site Coronary CT Angiography-derived Fractional Flow Reserve Based on Patient-specific Lumped Parameter Models

Purpose

To evaluate the diagnostic performance of a prototype on-site coronary CT angiography-derived fractional flow reserve (CT FFR) algorithm, based on patient-specific lumped parameter models, for the detection of functionally significant stenosis defined by invasive FFR, and to compare the performance to anatomic evaluation of stenosis degree.

Materials and Methods

In this retrospective feasibility study, 77 vessels in 57 patients (42 of 57 [74%]) men; mean age, 58.5 years ± 9.2 [standard deviation]) who underwent clinically indicated coronary CT angiography within 60 days prior to an invasive FFR measurement were analyzed. Invasive FFR less than or equal to 0.80 was used to indicate a functionally significant stenosis. Diagnostic performance of CT FFR was evaluated and compared with evaluation of stenosis degree. Analysis was performed on a per-vessel basis.

Results

Invasive FFR revealed functionally significant stenoses in 37 vessels (48%). CT FFR showed a significantly increased ability to indicate functionally significant stenosis (area under the receiver operating characteristic curve [AUC], 0.87) compared with degree of stenosis at coronary CT angiography (AUC, 0.70; ΔAUC 0.17; P < .01). Using a cutoff of less than or equal to 0.80 for CT FFR and greater than or equal to 50% degree of stenosis at coronary CT angiography to indicate a significant stenosis, sensitivity, specificity, positive predictive value, negative predictive value, and accuracy were 33 of 37 (89.2%), 31 of 40 (77.5%), 33 of 42 (78.6%), 31 of 35 (88.6%), and 64 of 77 (83.1%), respectively, for CT FFR, and 33 of 37 (89.2%), 17 of 40 (42.5%), 33 of 56 (58.9%), 17 of 21 (81.0%), and 50 of 77 (64.9%), respectively, for degree of stenosis at coronary CT angiography.

Conclusion

Diagnostic performance of on-site CT FFR was superior to stenosis evaluation at coronary CT angiography for identification of functionally significant coronary artery stenosis in patients suspected of having or known to have coronary artery disease.© RSNA, 2019See also commentary by Schoepf et al.

Diagnostic performance of a fast non-invasive fractional flow reserve derived from coronary CT angiography: an initial validation study

AIM

To validate the computed tomography (CT)-derived fractional flow reserve (FFR_CT) that was computed by new, fast, automatic software and to compare the diagnostic accuracy between FFR_CT and stenosis diagnosed at coronary CT angiography (CCTA).

MATERIALS AND METHODS

A total of 110 patients (76 males, 59±9 years) and 125 vessels underwent CCTA. FFR_CT was computed by fast automatic software and compared with invasive FFR. The diagnostic performance between FFR_CT and CCTA-diagnosed stenosis were compared on the per-patient and per-vessel level.

RESULTS

The computational time of FFR_CT is 10±5 minutes (averaged over 125 vessels). The FFR_CT has a good correlation with invasive FFR (r=0.59, p<0.0001) with a small bias of -0.02 (-0.26-0.23). The sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of FFR_CT were 76.5, 89.5, 89.7, and 76.1% on a vessel level. The area under the receiver operating characteristic curve of FFR_CT was higher than CCTA-diagnosed stenosis (0.82 versus 0.72, P=0.034).

CONCLUSION

The computation of FFR_CT is possible and reliable when using the new, fast, automatic software first employed in the present clinical study. The FFR_CT has a good correlation with invasive FFR and provides better diagnostic performance than CCTA-diagnosed stenosis.

Prediction of Plaque Progression in Coronary Arteries Based on a Novel Hemodynamic Index Calculated From Virtual Stenosis Method

Rationale

Predicting the sites in coronary arteries that are susceptible to plaque deposition is essential for the development of clinical treatment strategies and prevention. However, to date, no physiological biomarkers for this purpose have been developed. We hypothesized that the possibility of plaque deposition at a specific site in the coronary artery is associated with wall shear stress (WSS) and fractional flow reserve (FFR).

Background and Objective

We proposed a new biomarker called the stenosis susceptibility index (SSI) using the FFR and WSS derived using virtual stenosis method. To validate the clinical efficacy of this index, we applied the method to actual pilot clinical cases. This index non-invasively quantifies the vasodilation effects of vascular endothelial cells relative to FFR variation at a specific coronary artery site.

Methods and Results

Using virtual stenosis method, we computed maximum WSS and FFR according to the variation in stenotic severity at each potential stenotic site and then plotted the variations of maximum WSS (y-axis) and FFR (x-axis). The slope of the graph indicated a site-specific SSI value. Then we determined the most susceptible sites for plaque deposition by comparing SSI values between the potential sites. Applying this method to seven patients revealed 71.4% in per-patient basis analysis 77.8% accuracy in per-vessel basis analysis in percutaneous coronary intervention (PCI) site prediction.

Conclusion

The SSI index can be used as a predictive biomarker to identify plaque deposition sites. Patients with relatively smaller SSI values also had a higher tendency for myocardial infarction. In conclusion, sites susceptible to plaque deposition can be identified using the SSI index.