The diagnosis of coronary plaque stability by multi-slice computed tomography coronary angiography

Non-calcified plaque-based coronary stenosis grading in contrast enhanced CT

BACKGROUND

The high mortality rate associated with coronary heart disease has led to state-of-the-art non-invasive methods for cardiac diagnosis including computed tomography and magnetic resonance imaging. However, stenosis computation and clinical assessment of non-calcified plaques has been very challenging due to their ambiguous intensity response in CT i.e. a significant overlap with surrounding muscle tissues and blood. Accordingly, this research presents an approach for computation of coronary stenosis by investigating cross-sectional lumen behaviour along the length of 3D coronary segments.

METHODS

Non-calcified plaques are characterized by comparatively lower-intensity values with respect to the surrounding. Accordingly, segment-wise orthogonal volume was reconstructed in 3D space using the segmented coronary tree. Subsequently, the cross sectional volumetric data was investigated using proposed CNN-based plaque quantification model and subsequent stenosis grading in clinical context was performed. In the last step, plaque-affected orthogonal volume was further investigated by comparing vessel-wall thickness and lumen area obstruction w.r.t. expert-based annotations to validate the stenosis grading performance of model.

RESULTS

The experimental data consists of clinical CT images obtained from the Rotterdam CT repository leading to 600 coronary segments and subsequent 15786 cross-sectional images. According to the results, the proposed method quantified coronary vessel stenosis i.e. severity of the non-calcified plaque with an overall accuracy of 83%. Moreover, for individual grading, the proposed model show promising results with accuracy equal to 86%, 90% and 79% respectively for severe, moderate and mild stenosis. The stenosis grading performance of the proposed model was further validated by performing lumen-area versus wall-thickness analysis as per annotations of manual experts. The statistical results for lumen area analysis precisely correlates with the quantification performance of the model with a mean deviation of 5% only.

CONCLUSION

The overall results demonstrates capability of the proposed model to grade the vessel stenosis with reasonable accuracy and precision equivalent to human experts.

A Novel Classification for Predicting Chronic Total Occlusion Percutaneous Coronary Intervention

Aims

Chronic total occlusion (CTO) percutaneous coronary intervention (PCI) is characterized by a low success rate and an increase in complications. This study aimed to explore a new and simple classification method based on plaque composition to predict guidewire (GW) crossing within 30 min of CTO lesions.

Methods

This study consecutively enrolled individuals undergoing attempted PCI of CTO who underwent coronary computed tomographic angiography (CCTA) within 2 months. Lesions were divided into soft and hard CTO groups according to the necrotic core proportion.

Results

In this study, 207 lesions were divided into soft (20.3%) and hard CTO (79.7%) groups according to a necrotic core percentage cutoff value of 72.7%. The rate of successful GW crossing within 30 min (57.6 vs. 85.7%, p = 0.004) and final success (73.3 vs. 95.2%, p = 0.001) were much lower in the hard CTO group. For patients with hard CTO, previous failed attempt, proximal side branch, bending > 45 degrees calcium ≥ 50% cross-sectional area (CSA), and distal reference diameter ≤ 2.5 mm were demonstrated to be associated with GW failure within 30 min. For patients with soft CTO, only blunt entry was proved to be an independent predictive factor of GW failure within 30 min.

Conclusions

Grouping CTO lesions according to the proportion of necrotic core is reasonable and necessary in predicting GW crossing within 30 min. A soft CTO with a necrotic core is more likely to be recanalized compared with a hard CTO with fibrous and/or dense calcium. Different plaque types have variable predictive factors.

Recent Trends in Artificial Intelligence-Assisted Coronary Atherosclerotic Plaque Characterization

Coronary artery disease is a major cause of morbidity and mortality worldwide. Its underlying histopathology is the atherosclerotic plaque, which comprises lipid, fibrous and—when chronic—calcium components. Intravascular ultrasound (IVUS) and intravascular optical coherence tomography (IVOCT) performed during invasive coronary angiography are reference standards for characterizing the atherosclerotic plaque. Fine image spatial resolution attainable with contemporary coronary computed tomographic angiography (CCTA) has enabled noninvasive plaque assessment, including identifying features associated with vulnerable plaques known to presage acute coronary events. Manual interpretation of IVUS, IVOCT and CCTA images demands scarce physician expertise and high time cost. This has motivated recent research into and development of artificial intelligence (AI)-assisted methods for image processing, feature extraction, plaque identification and characterization. We performed parallel searches of the medical and technical literature from 1995 to 2021 focusing respectively on human plaque characterization using various imaging modalities and the use of AI-assisted computer aided diagnosis (CAD) to detect and classify atherosclerotic plaques, including their composition and the presence of high-risk features denoting vulnerable plaques. A total of 122 publications were selected for evaluation and the analysis was summarized in terms of data sources, methods—machine versus deep learning—and performance metrics. Trends in AI-assisted plaque characterization are detailed and prospective research challenges discussed. Future directions for the development of accurate and efficient CAD systems to characterize plaque noninvasively using CCTA are proposed.

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.

[Possibilities of Computed Tomography of the Heart in Risk Stratification and Determination of Optimal Strategy of Primary Prevention of Cardiovascular Complications of Atherosclerosis]

Modern strategies of primary prevention of cardiovascular complications of atherosclerotic etiology are presented in this article: traditional approach based on assessment of risk of development of complication and coming to replace it concept of prevention based on direct application of results of prospective clinical studies. The article contains detailed presentation of new opportunities of computer tomography of the heart allowing to substantially elevate precision of assessment of risk of cardiovascular complications of atherosclerotic etiology. Main attention is paid to the coronary artery calcification index, which determination substantially simpli- fies decision making relative to strategy of primary prevention in clinical practice.