Sex Differences in Plaque Composition and Morphology Among Symptomatic Patients With Mild-to-Moderate Carotid Artery Stenosis

Background and Purpose: Incidence of ischemic stroke differs between men and women, with substantially higher rates in men. The underlying mechanism of this difference remains poorly understood but may be because of differences in carotid atherosclerosis. Using an in-depth imaging-based approach, we investigated differences between carotid plaque composition and morphology in male and female patients with stroke, taking into account differences in total plaque burden. Additionally, we investigated all possible within-artery combinations of plaque characteristics to explore differences between various plaque phenotypes. Methods: We included 156 men and 68 women from the PARISK (Plaque At Risk) study, a prospective cohort study of patients with recent ischemic cerebrovascular symptoms and <70% ipsilateral carotid stenosis. Plaque characteristics (intraplaque hemorrhage [IPH], lipid-rich necrotic core [LRNC], calcifications, thin-or-ruptured fibrous cap, ulcerations, total plaque volume) were assessed with magnetic resonance imaging and multidetector-row computed tomography angiography. We used multivariable logistic and linear regression analyses to assess sex differences in plaque characteristics. Results: We found significant difference in total plaque volume between men and women (β=22.9 mm 3 [95% CI, 15.4–30.5]; mean volume in men 1399±425 mm 3 , in women 1011±242 mm 3 ). Additionally, men were more likely to have IPH (odds ratio [OR]=2.8 [95% CI, 1.3–6.3]; IPH proportion in men 49%, in women 16%) and LRNC (OR=2.4 [95% CI, 1.2–4.7]; LRNC proportion in men 73%, in women 41%) even after adjustment for total plaque volume. We found no sex-specific differences in plaque volume-corrected volumes of IPH, LRNC, and calcifications. In terms of coexistence of plaque characteristics, we found that men had more often a plaque with coexistence of calcifications, LRNC, and IPH (OR=2.7 [95% CI, 1.2–7.0]), with coexistence of thin-or-ruptured fibrous cap/ulcerations, LRNC, and IPH (OR=2.4 [95% CI, 1.1–5.9]), and with coexistence of all plaque characteristics (OR=3.0 [95% CI, 1.2–8.6]). Conclusions: In symptomatic patients with mild-to-moderate carotid stenosis, men are more likely to have a high-risk carotid plaque with IPH and LRNC than women, regardless of total plaque burden. Men also have more often a plaque with multiple vulnerable plaque components, which could comprise an even higher stroke risk. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT01208025.

Radiation dose reduction with deep-learning image reconstruction for coronary computed tomography angiography

Objectives Deep-learning image reconstruction (DLIR) offers unique opportunities for reducing image noise without degrading image quality or diagnostic accuracy in coronary CT angiography (CCTA). The present study aimed at exploiting the capabilities of DLIR to reduce radiation dose and assess its impact on stenosis severity, plaque composition analysis, and plaque volume quantification. Methods This prospective study includes 50 patients who underwent two sequential CCTA scans at normal-dose (ND) and lower-dose (LD). ND scans were reconstructed with Adaptive Statistical Iterative Reconstruction-Veo (ASiR-V) 100%, and LD scans with DLIR. Image noise (in Hounsfield units, HU) and quantitative plaque volumes (in mm3) were assessed quantitatively. Stenosis severity was visually categorized into no stenosis (0%), stenosis (< 20%, 20–50%, 51–70%, 71–90%, 91–99%), and occlusion (100%). Plaque composition was classified as calcified, non-calcified, or mixed. Results Reduction of radiation dose from ND scans with ASiR-V 100% to LD scans with DLIR at the highest level (DLIR-H; 1.4 mSv vs. 0.8 mSv, p < 0.001) had no impact on image noise (28 vs. 27 HU, p = 0.598). Reliability of stenosis severity and plaque composition was excellent between ND scans with ASiR-V 100% and LD scans with DLIR-H (intraclass correlation coefficients of 0.995 and 0.974, respectively). Comparison of plaque volumes using Bland–Altman analysis revealed a mean difference of − 0.8 mm3 (± 2.5 mm3) and limits of agreement between − 5.8 and + 4.1 mm3. Conclusion DLIR enables a reduction in radiation dose from CCTA by 43% without significant impact on image noise, stenosis severity, plaque composition, and quantitative plaque volume. Key Points •Deep-learning image reconstruction (DLIR) enables radiation dose reduction by over 40% for coronary computed tomography angiography (CCTA). •Image noise remains unchanged between a normal-dose CCTA reconstructed by ASiR-V and a lower-dose CCTA reconstructed by DLIR. •There is no impact on the assessment of stenosis severity, plaque composition, and quantitative plaque volume between the two scans.

A multivariate analysis identifies genetic loci associated with atherosclerotic plaque composition and cardiovascular disease trajectory

Background From cross-sectional studies we have learned that composition of atherosclerotic plaques differs between individuals, and this contributes to the inter-individual differences in susceptibility to incident coronary and cerebral events. In pathological studies the extent and type of atherosclerosis is commonly assessed based on histological plaque characteristics that are linked to plaque rupture and erosion. A better understanding of the biology underlying variability in plaque composition will provide insights into the progression of cardiovascular diseases. Objectives We investigated the genetics of the plaque through multivariate and integrative genome-wide analyses (GWAS) of individual plaque characteristics. Methods We included carotid endarterectomy patients from the Athero-Express Biobank Study (n=2,124) with high-density imputed data and extensive histochemical plaque phenotyping available. We used slideToolKit to quantify the number of endothelial cells, macrophages and smooth muscle cells (SMCs), and manually assessed the number of intraplaque vessels, the amount of collagen and calcification, the atheroma size, and the presence of plaque hemorrhage. We ran GWAS on all traits correcting for age, sex, array used, and genetic ancestry. Results We identified 3 loci that significantly associate with CD68+ macrophages and ACTA2+ SMCs, p&lt;5x10–8. Statistical finemapping revealed 9 variants in the 95% credible set and functional annotation linked these to genes associated with malignant neoplasms, circulating cholesterol, and transmembrane proteins, suggesting an effect on cellular proliferation and cholesterol metabolism. Conclusions We provide evidence for 3 loci that modulate plaque composition through macrophages and smooth muscle cell plaque proliferation and cell-cell interactions. FUNDunding Acknowledgement Type of funding sources: Public Institution(s). Main funding source(s): European Research Area Network on Cardiovascular Diseases (ERA-CVD, druggable-MI-genes),China Scholarship Council

Differential progression of coronary atherosclerosis according to plaque composition: a cluster analysis of PARADIGM registry data

Patient-specific phenotyping of coronary atherosclerosis would facilitate personalized risk assessment and preventive treatment. We explored whether unsupervised cluster analysis can categorize patients with coronary atherosclerosis according to their plaque composition, and determined how these differing plaque composition profiles impact plaque progression. Patients with coronary atherosclerotic plaque (n = 947; median age, 62 years; 59% male) were enrolled from a prospective multi-national registry of consecutive patients who underwent serial coronary computed tomography angiography (median inter-scan duration, 3.3 years). K-means clustering applied to the percent volume of each plaque component and identified 4 clusters of patients with distinct plaque composition. Cluster 1 (n = 52), which comprised mainly fibro-fatty plaque with a significant necrotic core (median, 55.7% and 16.0% of the total plaque volume, respectively), showed the least total plaque volume (PV) progression (+ 23.3 mm3), with necrotic core and fibro-fatty PV regression (− 5.7 mm3 and − 5.6 mm3, respectively). Cluster 2 (n = 219), which contained largely fibro-fatty (39.2%) and fibrous plaque (46.8%), showed fibro-fatty PV regression (− 2.4 mm3). Cluster 3 (n = 376), which comprised mostly fibrous (62.7%) and calcified plaque (23.6%), showed increasingly prominent calcified PV progression (+ 21.4 mm3). Cluster 4 (n = 300), which comprised mostly calcified plaque (58.7%), demonstrated the greatest total PV increase (+ 50.7mm3), predominantly increasing in calcified PV (+ 35.9 mm3). Multivariable analysis showed higher risk for plaque progression in Clusters 3 and 4, and higher risk for adverse cardiac events in Clusters 2, 3, and 4 compared to that in Cluster 1. Unsupervised clustering algorithms may uniquely characterize patient phenotypes with varied atherosclerotic plaque profiles, yielding distinct patterns of progressive disease and outcome.

Relationship of Neutrophil–Lymphocyte Ratio with coronary artery disease and plaque composition of coronary artery

Evidence suggests that the neutrophil-lymphocyte ratio (NLR) has been considered as useful marker for identifying individuals under risk of coronary artery disease (CAD) and associated events, a more powerful predictor than any other leukocyte subtypes. In this study, we aimed to evaluate association of NLR with CAD and plaque composition of coronary artery analyzed from coronary CT angiography (CCTA). The study population consisted of 469 patients who underwent CCTA due to stable typical or atypical chest pain. The enrolled patients were divided into two groups and three groups according to coronary artery stenosis and tertiles of NLR, respectively. The plaque burden, volume and ratio of calcified, lipid and fibrous components of plaques were measured based on CCTA images. Chi-square, Student’s test, ANOVA, Mann–Whitney U test, KruskalWallis test and multiple logistic regression were used for statistical analysis. Compared with non-CAD group, NLR was significantly higher in CAD group(P = 0.001). The non-calcified plaque volume, fibrotic plaque volume and lipid plaque volume increased with the NLR (P༜0.05). Multivariate logistic regression analysis showed that NLR was an independent risk factor for CAD(OR: 1.792, 95CI 1.067–3.011, P < 0.05). The present study demonstrated that NLR is associated with both the CAD and non-calcified plaque volume of coronary artery.