A novel method for non-invasive plaque morphology analysis by coronary computed tomography angiography

Additional prognostic impact of plaque characterization with on-site CT-derived fractional flow reserve in coronary CT angiography

BACKGROUND

On-site computed tomography-derived fractional flow reserve (CT-FFR) is a feasible method for examining lesion-specific ischemia, and plaque analysis of coronary CT angiography (CCTA) is useful for predicting future cardiac events. However, their utility and association on a per-vessel level remain unclear.

METHODS

We analyzed vessels showing 50-90 % stenosis on CCTA where planned revascularization was not performed after CCTA within 90 days. Relevant features, including CT-FFR and the plaque burden [necrotic core to the total plaque volume (% necrotic core), and non-calcified plaque (NCP) to vessel volume (% NCP)] using a novel algorithm for analyzing plaque to predict vessel-oriented composite outcomes (VOCO), including cardiac death, non-fatal myocardial infarction, and unplanned vessel-related revascularization, were assessed.

RESULTS

In 256 patients (68.7 ± 9.4 years; 73.8 % male) with 354 vessels (10.5 % CT-FFR ≤ 0.80), VOCO occurred in 24 vessels (6.8 %) during a median follow-up of 3.6 years. Multivariable Cox analysis revealed CT-FFR ≤ 0.80 had the pronounced impact on VOCO, and moreover, higher % necrotic core and % NCP were independently associated with VOCO [adjusted hazard ratio 3.43 (95 % confidence interval 1.42-8.29) and 4.05 (1.19-13.71), respectively], especially for vessels with CT-FFR > 0.80.

CONCLUSIONS

In vessels without planned revascularization, per-vessel CT-FFR ≤ 0.80 was the notable predictor of future cardiac events. Additionally, necrotic core volume and NCP were identified as independent predictors along with CT-FFR.

Application of Quantitative Assessment of Coronary Atherosclerosis by Coronary Computed Tomographic Angiography

Coronary computed tomography angiography (CCTA) has emerged as a pivotal tool for diagnosing and risk-stratifying patients with suspected coronary artery disease (CAD). Recent advancements in image analysis and artificial intelligence (AI) techniques have enabled the comprehensive quantitative analysis of coronary atherosclerosis. Fully quantitative assessments of coronary stenosis and lumen attenuation have improved the accuracy of assessing stenosis severity and predicting hemodynamically significant lesions. In addition to stenosis evaluation, quantitative plaque analysis plays a crucial role in predicting and monitoring CAD progression. Studies have demonstrated that the quantitative assessment of plaque subtypes based on CT attenuation provides a nuanced understanding of plaque characteristics and their association with cardiovascular events. Quantitative analysis of serial CCTA scans offers a unique perspective on the impact of medical therapies on plaque modification. However, challenges such as time-intensive analyses and variability in software platforms still need to be addressed for broader clinical implementation. The paradigm of CCTA has shifted towards comprehensive quantitative plaque analysis facilitated by technological advancements. As these methods continue to evolve, their integration into routine clinical practice has the potential to enhance risk assessment and guide individualized patient management. This article reviews the evolving landscape of quantitative plaque analysis in CCTA and explores its applications and limitations.

Atherosclerosis evaluation and cardiovascular risk estimation using coronary computed tomography angiography

Clinical risk scores based on traditional risk factors of atherosclerosis correlate imprecisely to an individual's complex pathophysiological predisposition to atherosclerosis and provide limited accuracy for predicting major adverse cardiovascular events (MACE). Over the past two decades, computed tomography scanners and techniques for coronary computed tomography angiography (CCTA) analysis have substantially improved, enabling more precise atherosclerotic plaque quantification and characterization. The accuracy of CCTA for quantifying stenosis and atherosclerosis has been validated in numerous multicentre studies and has shown consistent incremental prognostic value for MACE over the clinical risk spectrum in different populations. Serial CCTA studies have advanced our understanding of vascular biology and atherosclerotic disease progression. The direct disease visualization of CCTA has the potential to be used synergistically with indirect markers of risk to significantly improve prevention of MACE, pending large-scale randomized evaluation.

Innovations in cardiac computed tomography: Imaging in coronary artery disease

Coronary computed tomography angiography (CCTA) has emerged as a pivotal tool in the non-invasive evaluation of coronary artery disease (CAD). Recent advancements in imaging techniques, quantitative plaque assessment methods, assessment of coronary physiology, and perivascular coronary inflammation have propelled CCTA to the forefront of CAD management, enabling precise risk stratification, disease monitoring, and evaluation of treatment response. However, challenges persist, including the need for cardiovascular outcomes data for therapy modifications based on CCTA findings and the lack of standardized quantitative plaque assessment techniques to establish universal guidelines for treatment strategies. This review explores the current utilization of CCTA in clinical practice, highlighting its clinical impact and discussing challenges and opportunities for future development. By addressing these nuances, CCTA holds promise for revolutionizing coronary imaging and improving CAD management in the years to come. Ultimately, the goal is to provide precise risk stratification, optimize medical therapy, and improve cardiovascular outcomes while ensuring cost-effectiveness for healthcare systems.

Advances in Coronary Computed Tomographic Angiographic Imaging of Atherosclerosis for Risk Stratification and Preventive Care

The diagnostic evaluation of coronary artery disease is undergoing a dramatic transformation with a new focus on atherosclerotic plaque. This review details the evidence needed for effective risk stratification and targeted preventive care based on recent advances in automated measurement of atherosclerosis from coronary computed tomography angiography (CTA). To date, research findings support that automated stenosis measurement is reasonably accurate, but evidence on variability by location, artery size, or image quality is unknown. The evidence for quantification of atherosclerotic plaque is unfolding, with strong concordance reported between coronary CTA and intravascular ultrasound measurement of total plaque volume (r >0.90). Statistical variance is higher for smaller plaque volumes. Limited data are available on how technical or patient-specific factors result in measurement variability by compositional subgroups. Coronary artery dimensions vary by age, sex, heart size, coronary dominance, and race and ethnicity. Accordingly, quantification programs excluding smaller arteries affect accuracy for women, patients with diabetes, and other patient subsets. Evidence is unfolding that quantification of atherosclerotic plaque is useful to enhance risk prediction, yet more evidence is required to define high-risk patients across varied populations and to determine whether such information is incremental to risk factors or currently used coronary computed tomography techniques (eg, coronary artery calcium scoring or visual assessment of plaque burden or stenosis). In summary, there is promise for the utility of coronary CTA quantification of atherosclerosis, especially if it can lead to targeted and more intensive cardiovascular prevention, notably for those patients with nonobstructive coronary artery disease and high-risk plaque features. The new quantification techniques available to imagers must not only provide sufficient added value to improve patient care, but also add minimal and reasonable cost to alleviate the financial burden on our patients and the health care system.

The role of cardiac computed tomography in predicting adverse coronary events

Cardiac computed tomography (CCT) is now considered a first-line diagnostic test for suspected coronary artery disease (CAD) providing a non-invasive, qualitative, and quantitative assessment of the coronary arteries and pericoronary regions. CCT assesses vascular calcification and coronary lumen narrowing, measures total plaque burden, identifies plaque composition and high-risk plaque features and can even assist with hemodynamic evaluation of coronary lesions. Recent research focuses on computing coronary endothelial shear stress, a potent modulator in the development and progression of atherosclerosis, as well as differentiating an inflammatory from a non-inflammatory pericoronary artery environment using the simple measurement of pericoronary fat attenuation index. In the present review, we discuss the role of the above in the diagnosis of coronary atherosclerosis and the prediction of adverse cardiovascular events. Additionally, we review the current limitations of cardiac computed tomography as an imaging modality and highlight how rapid technological advancements can boost its capacity in predicting cardiovascular risk and guiding clinical decision-making.

Quantitative assessment of atherosclerotic plaque, recent progress and current limitations

An important advantage of computed tomography coronary angiography (CCTA) is its ability to visualize the presence and severity of atherosclerotic plaque, rather than just assessing coronary artery stenoses. Until recently, assessment of plaque subtypes on CCTA relied on visual assessment of the extent of calcified/non-calcified plaque, or visually identifying high-risk plaque characteristics. Recent software developments facilitate the quantitative assessment of plaque volume or burden on CCTA, and the identification of subtypes of plaque based on their attenuation density. These techniques have shown promise in single and multicenter studies, demonstrating that the amount and type of plaque are associated with subsequent cardiac events. However, there are a number of limitations to the application of these techniques, including the limitations imposed by the spatial resolution of current CT scanners, challenges from variations between reconstruction algorithms, and the additional time to perform these assessments. At present, these are a valuable research technique, but not yet part of routine clinical practice. Future advances that improve CT resolution, standardize acquisition techniques and reconstruction algorithms and automate image analysis will improve the clinical utility of these techniques. This review will discuss the technical aspects of quantitative plaque analysis and present pro and con arguments for the routine use of quantitative plaque analysis on CCTA.

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.

Plaque characteristics on coronary CT angiography associated with the positive findings of fractional flow reserve and instantaneous wave-free ratio

BACKGROUND

Fractional flow reserve (FFR) and instantaneous wave-free ratio (iFR) are useful in determining indications for revascularization of coronary artery disease (CAD). Although the discordance of FFR and iFR was noted in approximately 20%, this cause has not been well established. We investigated patient background and features on coronary CT angiography (CCTA) showing not only FFR- and iFR-positive findings but also discordance between FFR ≤ 0.8 and iFR ≤ 0.89.

METHODS

Subjects were consecutively treated in 83 cases with 105 vessels in which stenosis of 30-90% was detected at one vessel of at least 2 mm or more in the major epicardial vessels and FFR and iFR was performed within subsequent 90 days, among suspected CAD which underwent CCTA. The factors affecting not only FFR- and iFR-positive findings, respectively, but also discordance between FFR and iFR was evaluated using logistic regression analysis on per-patient and per-vessel basis.

RESULTS

FFR- and iFR-positive findings were observed in 42 vessels (40.0%) and 34 vessels (32.3%), respectively. Discordance between FFR ≤ 0.8 and iFR ≤ 0.89 was observed in 22 vessels (21.0%) of 21 patients. In multivariate logistic analysis, LAD (OR 3.55; 95%CI 1.20-11.71; p = 0.0217) and lumen volume/myocardial weight (L/M) ratio (OR 0.93; 0.86-0.99, p = 0.0290) were significant predictors for FFR-positive findings. For iFR-positive findings, LAD (OR 3.86; 95%CI 1.12-13.31; p = 0.0236) was only significant predictor. In FFR ≤ 0.8 and iFR > 0.89 group (15 vessels, 14.3%), positive remodeling (PR) (OR 5.03, 95%CI 1.23-20.48, p = 0.0205) was significant predictor. In FFR > 0.8 and iFR ≤ 0.89 group (7 vessels, 6.7%), there were no significant predictors.

CONCLUSION

On CCTA characteristics, a relevant predictor for FFR-positive findings included low L/M ratio. PR was significant predictor in FFR-positive, iFR-negative patients among those with discordance between the FFR and iFR.

Coronary Computed Tomography Angiography From Clinical Uses to Emerging Technologies: JACC State-of-the-Art Review

Evaluation of coronary artery disease (CAD) using coronary computed tomography angiography (CCTA) has seen a paradigm shift in the last decade. Evidence increasingly supports the clinical utility of CCTA across various stages of CAD, from the detection of early subclinical disease to the assessment of acute chest pain. Additionally, CCTA can be used to noninvasively quantify plaque burden and identify high-risk plaque, aiding in diagnosis, prognosis, and treatment. This is especially important in the evaluation of CAD in immune-driven conditions with increased cardiovascular disease prevalence. Emerging applications of CCTA based on hemodynamic indices and plaque characterization may provide personalized risk assessment, affect disease detection, and further guide therapy. This review provides an update on the evidence, clinical applications, and emerging technologies surrounding CCTA as highlighted at the 2019 National Heart, Lung and Blood Institute CCTA Summit.

Evaluation of image quality of coronary artery plaque with rapid kVp-switching dual-energy CT

We evaluated the virtual monochromatic imaging (VMI) energy levels that maximize image quality of each coronary plaque component in dual-energy computed tomography angiography in 495 coronary segments (45 for each energy level). Maximal signal-to-noise ratios were different for plaque, lumen, fat, and surrounding tissue (p<0.05). Maximal contrast-to-noise ratios were observed at 70keV for calcified plaque (CP), non-calcified plaque (NCP), and fat in comparison with the lumen (p<0.05), and 70keV and 120keV for NCP in comparison with fat (p=0.144). VMI demonstrated maximal image quality at different energy levels for each component of coronary artery plaque.

Prognostic Value of Coronary Computed Tomography (CT) Angiography and Coronary Artery Calcium Score Performed Before Revascularization

BACKGROUND

Cardiac events after revascularization are equally attributable to recurrence at site of culprit lesions and development of nonculprit lesions. We evaluated the hypothesis that coronary computed tomography (CT) angiography and coronary artery calcium score (CACS) performed before revascularization predicts cardiac events after treatment.

METHODS AND RESULTS

Among 2238 consecutive patients without known coronary artery disease who underwent coronary CT angiography and CACS, 359 patients underwent revascularization within 30 days after CT; in 337 of 359 (93.9%) follow-up clinical information was available. In addition to known cardiac risk factors, CT findings were evaluated as predictors of cardiac events after revascularization: CACS and the presence of CT-verified high-risk plaque (CT-HRP). Improvement of predictive accuracy by including CT findings was evaluated from a discrimination (Harrell's C-statistics) standpoint. During the follow-up period (median: 673, interquartile range: 47 to 1529 days), a total of 98 cardiac events occurred. Cox proportional hazard model revealed that age, diabetes, triglyceride, CACS, and nonculprit CT-HRP were significant predictors of overall cardiac events. Although not statistically significant, discriminatory power was greater for the model with CACS (C-stat: 63.2%) and the model with both CACS and CT-HRP (65.8%) compared to the model including neither CACS nor CT-HRP (60.7%).

CONCLUSIONS

High CACS and the presence of nonculprit CT-HRP performed before revascularization are significant predictors of cardiac events after revascularization.