Long-term prognostic value of morphological plaque features on coronary computed tomography angiography

Standards for quantitative assessments by coronary computed tomography angiography (CCTA): An expert consensus document of the society of cardiovascular computed tomography (SCCT)

In current clinical practice, qualitative or semi-quantitative measures are primarily used to report coronary artery disease on cardiac CT. With advancements in cardiac CT technology and automated post-processing tools, quantitative measures of coronary disease severity have become more broadly available. Quantitative coronary CT angiography has great potential value for clinical management of patients, but also for research. This document aims to provide definitions and standards for the performance and reporting of quantitative measures of coronary artery disease by cardiac CT.

Impact of coronary plaque characteristics on periprocedural myocardial injury in elective percutaneous coronary intervention

OBJECTIVES

To investigate the relationship between periprocedural myocardial injury (PMI) and plaque characteristics detected by multidetector computed tomography (MDCT) and cardiac magnetic resonance imaging (CMR).

MATERIALS AND METHODS

This observational retrospective study, between July 2012 and October 2019, included chronic coronary syndrome patients undergoing elective percutaneous coronary intervention (PCI) after MDCT and CMR. High-intensity plaque (HIP) on non-contrast T1-weighted imaging was defined as a coronary plaque-to-myocardium signal intensity ratio of ≥ 1.4. High-risk plaque (HRP) in MDCT displayed ≥ 2 features: positive remodeling, low-attenuation plaque, spotty calcification, and napkin-ring sign. PMI was defined as an increase in cardiac troponin T levels > 5 times the upper normal limit at 24 h after PCI.

RESULTS

Ninety-five target lesions in 76 patients (mean age ± standard deviation, 67 years ± 9; 62 males [82%]) were included. Twenty-one patients (24 lesions) were assigned to the PMI group, while 55 patients (71 lesions) to the non-PMI group. Presence of HRP characteristics on MDCT and HIP on CMR was significantly higher in the PMI group. Multivariate logistic regression analysis showed that HRP in MDCT and HIP in CMR were significant independent predictors of PMI. Target lesions with HRP on MDCT and HIP on CMR were significantly more likely to develop PMI. In 141 plaques with ≥ 50% stenosis (76 patients), patients with PMI had significantly more frequent HRP in MDCT and HIP in CMR in target and non-target lesions.

CONCLUSIONS

MDCT and CMR can play an important role in the detection of high-risk lesions for PMI following elective PCI.

KEY POINTS

• Multivariate logistic regression analysis showed that high-risk plaque on MDCT and high-intensity plaque on MRI were significant independent predictors of periprocedural myocardial injury (PMI). • Target lesions with high-risk plaque on MDCT and high-intensity plaque on CMR were significantly more likely to develop PMI. • In 141 plaques with ≥ 50% stenosis, patients with PMI were significantly more likely to have high-risk plaques on MDCT and high-intensity plaque on CMR in target and non-target lesions.

Artificial Intelligence—A Good Assistant to Multi-Modality Imaging in Managing Acute Coronary Syndrome

Acute coronary syndrome is the leading cause of cardiac death and has a significant impact on patient prognosis. Early identification and proper management are key to ensuring better outcomes and have improved significantly with the development of various cardiovascular imaging modalities. Recently, the use of artificial intelligence as a method of enhancing the capability of cardiovascular imaging has grown. AI can inform the decision-making process, as it enables existing modalities to perform more efficiently and make more accurate diagnoses. This review demonstrates recent applications of AI in cardiovascular imaging to facilitate better patient care.

Clinical Course of Optical Coherence Tomography-Detected Lipid-Rich Coronary Plaque After Optimal Medical Therapy

Background: The aim of this study was to evaluate optical coherence tomography (OCT)-detected lipid-rich coronary plaques (LRCPs) with coronary computed tomography angiography (CCTA) 10 months after optimal medical therapy (OMT).

Methods and Results: Baseline OCT detected 28 LRCPs in non-culprit lesions. High-risk plaque features (HRPFs), such as positive remodeling, very low attenuation plaques, napkin-ring sign, and spotty calcification, were observed in 67.9%, 67.9%, 21.4%, and 64.3% of LRCPs, respectively, at the 10-month follow-up CCTA. Lesions with ≥3 HRPFs were defined as high-risk LRCPs (n=12); the remaining were defined as low-risk LRCPs (n=16). The maximum lipid arc on baseline OCT was larger in high- than low-risk LRCPs (221±62° vs. 179±44°, respectively; P=0.04). Receiver operating characteristic curve analysis indicated that a maximum lipid arc >154° on baseline OCT was the optimal cut-off value to predict high-risk LRCPs 10 months after OMT. Patients with high-risk LRCPs had worse clinical outcomes, defined as a composite of cardiac death, target lesion-related myocardial infarction, and target lesion-related revascularization, during follow-up than those with low-risk LRCPs (33.3% vs. 0%; P=0.01).

Conclusions: A high-risk LRCP at follow-up CCTA was correlated with a larger maximum lipid arc on baseline OCT. Further aggressive treatment for patients with large LRCPs may reduce vulnerable plaque features and prevent future cardiac events.

The Impact of Coronary Artery Calcification on Long-Term Cardiovascular Outcomes

Decades of research and experimental studies have investigated various strategies to prevent acute coronary events. However, significantly efficient preventive methods have not been developed and still remains a challenge to determine if a coronary atherosclerotic plaque will become vulnerable and unstable. This review aims to assess the significance of plaque vulnerability markers, more precisely the role of spotty calcifications in the development of major cardiac events, given that coronary calcification is a hallmark of atherosclerosis. Recent studies have suggested that microcalcifications, spotty calcifications, and the presence of the napkin-ring sign are predictive vulnerable plaque features, and their presence may cause plaque instability.

From CT to artificial intelligence for complex assessment of plaque-associated risk

The recent technological developments in the field of cardiac imaging have established coronary computed tomography angiography (CCTA) as a first-line diagnostic tool in patients with suspected coronary artery disease (CAD). CCTA offers robust information on the overall coronary circulation and luminal stenosis, also providing the ability to assess the composition, morphology, and vulnerability of atherosclerotic plaques. In addition, the perivascular adipose tissue (PVAT) has recently emerged as a marker of increased cardiovascular risk. The addition of PVAT quantification to standard CCTA imaging may provide the ability to extract information on local inflammation, for an individualized approach in coronary risk stratification. The development of image post-processing tools over the past several years allowed CCTA to provide a significant amount of data that can be incorporated into machine learning (ML) applications. ML algorithms that use radiomic features extracted from CCTA are still at an early stage. However, the recent development of artificial intelligence will probably bring major changes in the way we integrate clinical, biological, and imaging information, for a complex risk stratification and individualized therapeutic decision making in patients with CAD. This review aims to present the current evidence on the complex role of CCTA in the detection and quantification of vulnerable plaques and the associated coronary inflammation, also describing the most recent developments in the radiomics-based machine learning approach for complex assessment of plaque-associated risk.

Increased serum bile acid level is associated with high-risk coronary artery plaques in an asymptomatic population detected by coronary computed tomography angiography

Background

There are limited data on the association between serum total bile acid level and coronary plaque characteristics. This study investigated the relationship between serum total bile acid level and the severity of coronary stenosis and coronary plaque features in an asymptomatic population using coronary computed tomography angiography (CTA).

Methods

A total of 1,137 consecutive participants with no known coronary artery disease (CAD) undergoing CTA as part of a general routine health evaluation were recruited. Serum total bile acid level and clinical parameters were assayed. Coronary stenosis and high-risk plaques features (napkin-ring sign, low-attenuation plaque, spotty calcification, positive remodelling) were evaluated. Associations between serum total bile acid concentration and high-risk coronary plaques was tested through univariate and multivariate analyses.

Results

A total of 101 high-risk coronary plaques subjects and 93 controls were eligible for study inclusion. The severity of coronary artery stenosis and high-risk coronary plaques increased with serum total bile acid level quartiles (all P<0.001). The independent predictor of high-risk coronary plaques in multivariate analysis was serum total bile acid level (P<0.001). Receiver operating characteristic (ROC) confirmed that serum total bile acid concentration significantly differentiated high-risk coronary plaques [the area under the curve (AUC) =0.876; P<0.001, with a sensitivity of 87.13% and a specificity of 86.02%].

Conclusions

Higher serum total bile acid level was associated with the severity of coronary artery stenosis and high-risk coronary artery plaques detected by CTA in asymptomatic populations.