CT-based total vessel plaque analyses improves prediction of hemodynamic significance lesions as assessed by fractional flow reserve in patients with stable angina pectoris

Computed Tomography Coronary Plaque Characteristics Predict Ischemia Detected by Invasive Fractional Flow Reserve

PURPOSE

Coronary computed tomography angiography (CCTA) plaque quantification has been proposed to be of incremental value in the prediction of ischemia, although prior studies have shown conflicting results. We aimed to determine whether CCTA plaque features assessed on a commercial vendor platform predict invasive fractional flow reserve (FFR)/instantaneous wave-free ratio (IFR).

METHODS

Consecutive patients who underwent CCTA for evaluation of suspected stable coronary artery disease followed by invasive coronary physiology testing within 60 days at a single academic center were identified retrospectively. Semiautomated plaque quantification of the vessel proximal to the location of FFR/IFR measurement was carried out in TeraRecon, along with simple visual assessment for high-risk plaque features of positive remodeling, spotty calcification, low-attenuation plaque (LAP), and lesion length. Ischemia was defined by FFR ≤0.80 or IFR ≤0.89.

RESULTS

A total of 134 patients (62% male, mean age 62±10 y) were included in this study. On univariate logistic regression, the following visual plaque analysis parameters were predictive of ischemia: positive remodeling (odds ratio [OR] with 95% confidence interval [CI]: 4.96; 2.25-10.95; P<0.001), lesion length (OR for every 1 mm with 95% CI: 1.24; 1.14-1.34; P<0.001), spotty calcification (OR with 95% CI: 6.67; 1.67-26.64; P=0.007), and LAP (OR with 95% CI: 30; 3.78-246; P=0.001). None of the semiautomated plaque quantification parameters, such as noncalcified plaque volume or LAP volume, were predictive of ischemia. On stepwise multivariable logistic regression, lesion length (OR with 95% CI: 1.25; 1.14-1.37; P<0.0001) and LAP (OR with 95% CI: 43; 4.4-438; P=0.001) were significant predictors of ischemia, improving the area under the curve of CCTA from 0.53 to 0.87.

CONCLUSIONS

Simple visual plaque assessment for high-risk plaque features improved the performance of CCTA to predict ischemia. Semiautomated plaque quantification performed on a commercial vendor platform was not predictive of ischemia.

Characteristic findings of microvascular dysfunction on coronary computed tomography angiography in patients with intermediate coronary stenosis

OBJECTIVES

We aimed to assess the prevalence of coexistence of coronary microvascular dysfunction (CMD) in patients with intermediate epicardial stenosis and to explore coronary computed tomography angiography (CCTA)-derived lesion-, vessel-, and cardiac fat-related characteristic findings associated with CMD.

METHODS

A retrospective cross-sectional single-center study included a total of 177 patients with intermediate stenosis in the left anterior descending artery (LAD) who underwent CCTA and invasive physiological measurements. The 320-slice CCTA analysis included qualitative and quantitative assessments of plaque, vessel, epicardial fat volume (ECFV) and epicardial fat attenuation (ECFA), and pericoronary fat attenuation (FAI). CMD was defined by the index of microcirculatory resistance (IMR) ≥ 25.

RESULTS

In the entire cohort, median fractional flow reserve (FFR) and median IMR values were 0.77 (0.69-0.84) and 19.0 (13.7-27.7), respectively. The prevalence of CMD was 32.8 % (58/177) in the total cohort. The coexistence of CMD and functionally significant stenosis was 34.3 % (37/108), whereas CMD in nonsignificant intermediate stenosis was 30.4 % (21/69). CMD was significantly associated with greater lumen volume (p = 0.031), greater fibrofatty and necrotic component (FFNC) volume (p = 0.030), and greater ECFV (p = 0.030), but not with FAI (p = 0.832) and ECFA (p = 0.445). On multivariable logistic regression analysis, vessel volume, vessel lumen volume, lesion remodeling index, ECFV, and lesion FFNC volume were independent predictors of CMD.

CONCLUSIONS

The prevalence of CMD was about one-third in patients with intermediate stenosis in LAD regardless of the presence or absence of functional stenosis significance. The integrated CCTA assessment may help in the identification of CMD.

KEY POINTS

• The coexistence of coronary microvascular dysfunction (CMD) and functionally significant stenosis was 34.3 %, whereas CMD in nonsignificant intermediate stenosis was 30.4 %. • Coronary computed tomography angiography (CCTA)-derived CMD characteristics were vessel volume, vessel lumen volume, remodeling index, epicardial fat volume, and fibrofatty necrotic core volume. • Integrated CCTA assessment may help identify the coexistence of CMD and epicardial stenosis.

Prognostic value of pericoronary inflammation and unsupervised machine-learning-defined phenotypic clustering of CT angiographic findings

BACKGROUND

Pericoronary adipose tissue attenuation expressed by fat attenuation index (FAI) on coronary CT angiography (CCTA) reflects pericoronary inflammation and is associated with cardiac mortality.

OBJECTIVE

The aim of this study was to define the sub-phenotypes of coronary CCTA-defined plaque and whole vessel quantification by unsupervised machine learning (ML) and its prognostic impact when combined with pericoronary inflammation.

METHODS

A total of 220 left anterior descending arteries (LAD) with intermediate stenosis who underwent fractional flow reserve (FFR) measurement and CCTA were studied. After removal of outcome and FAI data, the phenotype heterogeneity of CCTA-defined plaque and whole vessel quantification was investigated by unsupervised hierarchical clustering analysis based on Ward's method. Detailed features of CCTA findings were assessed according to the clusters (CS1 and CS2). Major adverse cardiac events (MACE)-free survivals were assessed according to the stratifications by FAI and the clusters.

RESULTS

Compared with CS2 (n = 119), CS1 (n = 101) were characterized by greater vessel size, increased plaque volume, and high-risk plaque features. FAI was significantly higher in CS1. ROC analyses revealed that best cut-off value of FAI to predict MACE was -73.1. Kaplan-Meier analysis revealed that lesions with FAI ≥ -73.1 had a significantly higher risk of MACE. Multivariate Cox proportional hazards regression analysis revealed that age, FAI ≥ -73.1, and the clusters were independent predictors of MACE.

CONCLUSION

Unsupervised hierarchical clustering analysis revealed two distinct CCTA-defined subgroups and discriminated by high-risk plaque features and increased FAI. The risk of MACE differs significantly according to the increased FAI and ML-defined clusters.

The Incremental Role of Coronary Computed Tomography in Chronic Coronary Syndromes

In the context of chronic coronary syndromes (CCS), coronary computed tomography angiography (CCTA) has gained broad acceptance as a noninvasive anatomical imaging tool with ability of excluding coronary stenosis with strong negative predictive value. Atherosclerotic plaque lesions are independent predictors of cardiovascular outcomes in high risk patients with known coronary artery disease (CAD). Calcium detection is commonly expressed through the coronary artery calcium score (CACS), but further research is warranted to confirm the powerness of a CACS-only strategy in both diagnosis and prognosis assessment. Recent studies evidence how defined plaque composition characteristics effectively relate to the risk of plaque instabilization and the overall ischemic burden. Fractional flow reserve from CCTA (FFR-CT) has been demonstrated as a reliable method for noninvasive functional evaluation of coronary lesions severity, while the assessment of perfusion imaging under stress conditions is growing as a useful tool for assessment of myocardial ischemia. Moreover, specific applications in procedural planning of transcatheter valve substitution and follow-up of heart transplantation have gained recent importance. This review illustrates the incremental role of CCTA, which can potentially revolutionize the diagnosis and management pathway within the wide clinical spectrum of CCS.

Evaluation of Significant Coronary Artery Disease Based on CT Fractional Flow Reserve and Plaque Characteristics Using Random Forest Analysis in Machine Learning

RATIONALE AND OBJECTIVES

Fractional flow reserve (FFR) is an established technique for detecting lesion-specific ischemia but is invasive. Our objective was to investigate the effects of combined assessment of coronary CT angiography (CCTA) imaging features and CT-FFR on detecting lesion-specific ischemia by comparing with invasive FFR.

MATERIALS AND METHODS

Forty-seven patients who had 60 coronary vessels with 30%-90% stenosis were included. Six anatomic CCTA descriptors (Agatston score, stenosis severity, mean plaque CT attenuation value, noncalcified and calcified plaque volumes, remodeling index) and a functional descriptor (CT-FFR) were measured. Random forest was used to identify which descriptors were useful to identify ischemia-related lesion. Receiver-operating characteristic (ROC) curves were calculated for 2 models: i.e. Model-1 for anatomical CT descriptors and Model-2 for anatomical CT descriptors plus CT-FFR.

RESULTS

Stenosis severity (40.8 ± 15.7% vs 57.6 ± 14.1%), noncalcified plaque volume (190 ± 100 vs 254.8 ± 133.3), and remodeling index (1.04 ± 0.12 vs 1.11 ± 0.13) were significantly higher in ischemia-related lesions than nonischemia-related lesions. CT-FFR was 0.84 ± 0.14 and 0.71 ± 0.14, respectively, for ischemia-related and nonischemia-related lesions, and the difference was significant. The area under the ROC curve was 0.738 and 0.835 in Model-1 and Model-2, respectively. Reclassification of ischemic lesion risk was significantly improved after adding CT-FFR: net reclassification improvement was 0.297 and integrated discrimination improvement was 0.254.

CONCLUSION

Combined assessment of anatomical CCTA features and functional CT-FFR was helpful for detecting lesion-specific ischemia.

CCTA in the diagnosis of coronary artery disease

The world of cardiac imaging is proposing to physicians an ever-increasing spectrum of options and tools with the disadvantages of patients presently submitted to multiple, sequential, time-consuming, and costly diagnostic procedures and tests, sometimes with contradicting results. In the last two decades, the CCTA has evolved into a valuable diagnostic test in today's patient care, changing the official existing guidelines and clinical practice with a pivotal role to exclude significant CAD, in the referral of patients to the Cath-Lab, in the follow-up after coronary revascularization, and finally in the cardiovascular risk stratification.

Latest Advances in Cardiac CT

Recent rapid technological advancements in cardiac CT have improved image quality and reduced radiation exposure to patients. Furthermore, key insights from large cohort trials have helped delineate cardiovascular disease risk as a function of overall coronary plaque burden and the morphological appearance of individual plaques. The advent of CT-derived fractional flow reserve promises to establish an anatomical and functional test within one modality. Recent data examining the short-term impact of CT-derived fractional flow reserve on downstream care and clinical outcomes have been published. In addition, machine learning is a concept that is being increasingly applied to diagnostic medicine. Over the coming decade, machine learning will begin to be integrated into cardiac CT, and will potentially make a tangible difference to how this modality evolves. The authors have performed an extensive literature review and comprehensive analysis of the recent advances in cardiac CT. They review how recent advances currently impact on clinical care and potential future directions for this imaging modality.

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.

The clinical utility of hybrid imaging for the identification of vulnerable plaque and vulnerable patients

Despite decades of research and major innovations in technology, cardiovascular disease remains the leading cause of death globally. Our understanding of major cardiovascular events and their prevention is centred around the atherosclerotic plaque and the processes that ultimately lead to acute plaque rupture. Recent advances in hybrid imaging technology allow the combination of high spatial resolution and anatomical detail with molecular assessments of disease activity. This provides the ability to identify vulnerable plaque characteristics and differentiate active and quiescent disease, with the potential to improve patient risk stratification. Combined positron emission tomography and computed tomography is the prototypical non-invasive hybrid imaging technique for coronary artery plaque assessment. In this review we discuss the current state of play in the field of hybrid coronary atherosclerosis imaging.