Carotid Artery Plaque Progression: Proposal of a New Predictive Score and Role of Carotid Intima-Media Thickness

Value of carotid intima thickness in assessing advanced carotid plaque vulnerability: a study based on carotid artery ultrasonography and carotid plaque histology

Background

Research has shown that carotid intima-media thickness (CIMT) could help to predict carotid plaque (CP) progression in patients with mild carotid stenosis. However, the debate continues as to the value of carotid intima thickness (CIT) in monitoring the development of CP in patients with severe carotid stenosis. This study sought to evaluate the relationships between CIT and the ultrasonic characteristics of CP and to analyze the value of CIT and the ultrasonic parameters of CP in assessing plaque vulnerability in advanced human carotid atherosclerosis.

Methods

A total of 55 individuals who underwent carotid endarterectomy (CEA) were included in the study (mean age: 65±7 years; female: 9.1%). CIMT and CIT were examined at the common carotid artery (CCA). Plaque textural features, such as the gray-scale median (GSM), superb microvascular imaging (SMI) level, and total plaque area (TPA), were also identified. A Spearman correlation coefficient analysis was performed to examine the relationship between CIT and the ultrasonic parameters of CP. The CIT of various plaque types was compared. Receiver operating characteristic (ROC) curves were used to analyze the diagnostic values of the ultrasound characteristics to evaluate CP vulnerability.

Results

The mean CIT of all the participants was 0.382±0.095 mm, the mean CIT of the participants with stable plaques was 0.328±0.031 mm, and the mean CIT of participants with vulnerable plaques was 0.424±0.106 mm (P<0.001). CIT was associated with the SMI level (Spearman's correlation coefficient: r=0.392, P=0.005), TPA (Spearman's correlation coefficient: r=0.337, P=0.012). Patients with thicker CIT had larger lipid cores, higher levels of plaque vulnerability, and more intraplaque hemorrhages (IPHs). The areas under the ROCs (AUCs) with 95% confidence interval (CI) for CIMT, CIT, the SMI level, the GSM, the TPA, and the combined model for identifying vulnerable plaques were 0.673 (0.533-0.793), 0.849 (0.727-0.932), 0.771 (0.629-0.879), 0.669 (0.529-0.790), 0.858 (0.738-0.938), and 0.949 (0.854-0.990), respectively.

Conclusions

CIT was associated with both the histology and ultrasonic features of CP. CIT may be helpful in the detection of severe CP development.

Association of Circular RNAs levels in blood and Essential Hypertension with Carotid Plaque

BACKGROUND

As one of the essential hypertension (EH)-mediated target organ damage, carotid plaque is a crucial subclinical precursor for cardiovascular events. Therefore, it is vital to identify the risk factors and pathogenesis for EH with carotid plaque.

METHODS

Based on our previous microarray analysis, we selected four circRNAs as the candidate circRNAs and detected their expression levels in blood of 192 subjects (64 healthy controls, 64 EH patients, and 64 EH patients with carotid plaque) by qRT-PCR analysis. The regulatory mechanism of circRNAs involved in carotid plaque was predicted by bioinformatics analysis.

RESULTS

The level of hsa_circ_0124782 increased significantly and the levels of hsa_circ_0131618 and hsa_circ_0127342 decreased significantly in the EH group and EH with carotid plaque group compared with the control group (P < .05). Functional enrichment analysis showed that three circRNAs might be implicated in pathogenesis for carotid plaque.

CONCLUSION

Our study revealed the relationship between three circRNAs and carotid plaque, suggesting that they may serve as potential biomarkers for EH with carotid plaque.

The association of stroke risk factors with the future thickness of carotid atherosclerotic plaques

OBJECTIVES

An advancing atherosclerotic plaque is a risk factor for stroke. We conducted this study to assess the relationship between risk factors of stroke with changing in the thickness of carotid plaques thickness evident on sonography.

METHODS

We carried out a secondary analysis of data from a study on carotid bifurcation plaques. Data were collected in the sonography laboratories of two university hospitals. In total, 564 (240; 42.6% men) patients with atherosclerotic plaques in the carotid bifurcation and internal carotid artery with stenosis ≥ 30% evident on duplex sonography were included. We developed machine learning models using an extreme gradient boosting algorithm with Shapley additive explanation method to find important risk factors and their interactions. The outcome was a change in the carotid plaque thickness after 36 months, and the predictors were initial plaque thickness and the risk factors of stroke.

RESULTS

Two regression models were developed for left and right carotid arteries. The R-squared values were 0.964 for the left, and 0.993 for the right model. Overall, the three top features were BMI, age, and initial plaque thickness for both left and right plaques. However, the risk factors of stroke showed stronger interaction in predicting plaque thickening of the left carotid more than the right carotid artery.

DISCUSSION

The effect of each predictor on plaque thickness is complicated by interactions with other risk factors, particularly for the left carotid artery. The side of carotid artery involvement should be considered for stroke prevention.

Low appendicular skeletal muscle index increases the risk of carotid artery plaque in postmenopausal women with and without hypertension/hyperglycemia: a retrospective study

BACKGROUND

This study aimed to evaluate whether the low appendicular skeletal muscle index (ASMI) is closely associated with the risk of carotid artery plaque (CAP) in postmenopausal women with and without hypertension/hyperglycemia stratified by body mass index (BMI) categories.

METHODS

A total of 2048 Chinese postmenopausal women aged 40-88 years were eventually enrolled in this retrospective study. Skeletal muscle mass was estimated by using segmental multifrequency bioelectrical impedance analysis. ASMI was defined as follows: appendicular skeletal muscle mass(kg)/[height(m)]². CAP was assessed by B-mode ultrasound. We explored the association between ASMI quartiles or low skeletal muscle mass and the risk of CAP by using multivariate-adjusted logistic regression models. A potential nonlinear relationship was also tested using restricted cubic spline regression.

RESULTS

CAP was observed in 289/1074 (26.9%) normal-weight and 319/974 (32.8%) overweight/obese postmenopausal women. Individuals with CAP had significantly lower ASMI values than those without (P < 0.001). The ASMI value also showed a linear relationship with the CAP risk in postmenopausal women stratified by BMI category (P_{for non-linearity} > 0.05). In comparison with the highest ASMI quartile, the lowest ASMI quartile was significantly associated with a high risk of CAP development in non-hypertensive individuals with normal weight (odds ratio [OR] = 2.43; 95% confidence interval [CI]: 1.44 ~ 4.12) or overweight/obesity (OR = 4.82, 95% CI: 2.79 ~ 8.33), hypertensive individuals with normal weight (OR = 5.90, 95% CI: 1.46 ~ 11.49) or overweight/obesity (OR = 7.63, 95% CI: 1.62 ~ 35.86), non-hyperglycemic individuals with normal weight (OR = 2.61, 95% CI: 1.54 ~ 4.43) or overweight/obesity (OR = 2.94, 95% CI: 1.84 ~ 4.70), and hyperglycemic individuals with normal weight (OR = 6.66, 95% CI: 1.08 ~ 41.10) or overweight/obesity (OR = 8.11, 95% CI: 2.69 ~ 24.49). Moreover, low skeletal muscle was independently associated with the risk of CAP in postmenopausal women, regardless of the BMI category.

CONCLUSION

ASMI was inversely associated with the risk of CAP development in postmenopausal women, especially in patients with high blood sugar and/or hypertension, indicating that skeletal muscle mass maintenance may contribute to prevention of CAP in postmenopausal women.

Stroke territory and atherosclerosis in ischemic stroke patients with a history of migraine with aura

Introduction

The mechanisms subtending the increased stroke risk in migraine with aura (MA) are not fully understood. Our study aims to evaluate if the clinical profile in stroke patients with MA differentiates from those without MA.

Methods

We retrieved the prospective registered electronic clinical dossiers of adult patients younger than 60 years with acute ischemic stroke admitted in four hospitals between January 2016 and June 2022. Patients were classified by the history of MA (MA+ and MA-).

Results

We identified 851 stroke patients (59 MA+, 6.9%). Compared to MA-, MA+ patients were characterized by younger age (44.0 ± 10.6 vs 50.1 ± 8.2 years), female sex (59.3% vs 29.0%), and affected by cryptogenic (OR 2.594 95% CI 1.483-4.537), and cerebellar stroke (OR 3.218 95% CI 1.657-6.250; p ≤ 0.001 for all comparisons). After adjusting for age and sex, MA+ patients presented less frequently hypertension (OR 0.349 95% CI 0.167-0.470; p=0.005) and dyslipidemia (OR 0.523 95% CI 0.280-0.974; p = 0.041). After adjusting also for risk factors, the MA+ group had less frequently symptomatic large vessel stenosis (OR 0.126 95% CI 0.017-0,924; p = 0.042) and clinical atherosclerosis (OR 0.103 95% CI 0.014-0.761; p = 0.026), while intima-media thickness did not differ (p = 0.395).

Discussion

Cryptogenic and cerebellar stroke and fewer vascular risk factors and clinical atherosclerosis seem to characterize stroke patients with MA.

Carotid Plaque Features and Inflammatory Biomarkers as Predictors of Restenosis and Mortality Following Carotid Endarterectomy

BACKGROUND

Carotid endarterectomy (CEA) is the first-line surgical intervention for cases of severe carotid stenoses. Unfortunately, the restenosis rate is high after CEA. This study aims to demonstrate the predictive role of carotid plaque features and inflammatory biomarkers (monocyte-to-lymphocyte ratio (MLR), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic inflammatory index (SII), Systemic Inflammation Response Index (SIRI), and Aggregate Index of Systemic Inflammation (AISI)) in carotid restenosis and mortality at 12 months following CEA.

METHODS

The present study was designed as an observational, analytical, retrospective cohort study and included all patients over 18 years of age with a minimum of 70% carotid stenosis and surgical indications for CEA admitted to the Vascular Surgery Clinic, Emergency County Hospital of Targu Mures, Romania between 2018 and 2021.

RESULTS

According to our results, the high pre-operative values of inflammatory biomarkers-MLR (OR: 10.37 and OR: 6.11; p < 0.001), NLR (OR: 34.22 and OR: 37.62; p < 0.001), PLR (OR: 12.02 and OR: 16.06; p < 0.001), SII (OR: 18.11 and OR: 31.70; p < 0.001), SIRI (OR: 16.64 and OR: 9.89; p < 0.001), and AISI (OR: 16.80 and OR: 8.24; p < 0.001)-are strong independent factors predicting the risk of 12-month restenosis and mortality following CEA. Moreover, unstable plaque (OR: 2.83, p < 0.001 and OR: 2.40, p = 0.04) and MI (OR: 3.16, p < 0.001 and OR: 2.83, p = 0.005) were independent predictors of all outcomes. Furthermore, AH (OR: 2.30; p = 0.006), AF (OR: 1.74; p = 0.02), tobacco (OR: 2.25; p < 0.001), obesity (OR: 1.90; p = 0.02), and thrombotic plaques (OR: 2.77; p < 0.001) were all independent predictors of restenosis, but not for mortality in all patients. In contrast, antiplatelet (OR: 0.46; p = 0.004), statin (OR: 0.59; p = 0.04), and ezetimibe (OR:0.45; p = 0.03) therapy were protective factors against restenosis, but not for mortality.

CONCLUSIONS

Our data revealed that higher preoperative inflammatory biomarker values highly predict 12-month restenosis and mortality following CEA. Furthermore, age above 70, unstable plaque, cardiovascular disease, and dyslipidemia were risk factors for all outcomes. Additionally, AH, AF, smoking, and obesity were all independent predictors of restenosis but not of mortality in all patients. Antiplatelet and statin medication, on the other hand, were protective against restenosis but not against mortality.

Trajectories of Lipid Profile and Risk of Carotid Atherosclerosis Progression: A Longitudinal Cohort Study

Background: Early assessment of carotid atherosclerotic plaque characteristics is essential for atherosclerotic cardiovascular disease (ASCVD) risk stratification and prediction. We aimed to identify different trajectories of lipid profiles and investigate the association of lipid trajectories with carotid atherosclerosis (CAS) progression in a large, longitudinal cohort of the Chinese population. Methods: 10,412 participants aged ≥18 years with ≥2 times general health checkups were included in this longitudinally prospective cohort study at Peking University Third Hospital. We used latent class trajectory models to identify trajectories of total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), triglycerides (TG), and high-density lipoprotein cholesterol (HDL-C) over follow-up time (757 days, IQR: 388–844 days). Results: Participants with carotid plaque were more likely to be older, male, have higher body mass index, have a higher prevalence of hypertension and diabetes, and have a higher level of blood pressure, TG, TC, and LDL-C, compared with carotid intima-media thickness (cIMT) and normal group. Subjects were trichotomized according to different trajectory patterns into stable, moderate-stable, and elevated-increasing classes. TC ≥ 5.18 mmol/L and moderate-stable class (hazard ratio (HR): 1.416, 95% confidence interval (CI): 1.285–1.559, p: 0.000), TG ≥ 1.70 mmol/L and moderate-stable class (HR: 1.492, 95% CI: 1.163–1.913, p: 0.002), TG ≥ 1.70 mmol/L and elevated-increasing class (HR: 1.218, 95% CI: 1.094–1.357, p: 0.000), LDL-C ≥ 3.36 mmol/L and stable class (HR: 1.500, 95% CI: 1.361–1.653, p: 0.000) were statistically significant associated with CAS progression compared with the reference group. Conclusions: Borderline elevated baseline lipid (TC, TG, and LDL-C) with stable and elevated-increasing trajectories were associated with CAS progression. Long-term strategies for low-level lipid are beneficial for ASCVD management.

Cerebral Hemodynamics, Right-to-Left Shunt and White Matter Hyperintensities in Patients with Migraine with Aura, Young Stroke Patients and Controls

Background: Migraine with aura (MA) patients present an increased risk of cerebrovascular events. However, whether these patients present an increased white matter hyperintensities (WMHs) load compared to the general population is still under debate. Our study aimed to evaluate the relationship between cerebral hemodynamics, right-to-left shunt (RLS) and WMHs in MA patients, young patients with cryptogenic stroke or motor transient ischemic attack (TIA) and controls. Methods: We enrolled 30 MA patients, 20 young (<60 years) patients with cryptogenic stroke/motor TIA, and 10 controls. All the subjects underwent a transcranial Doppler bubble test to detect RLS and cerebral hemodynamics assessed by the breath holding index (BHI) for the middle (MCA) and posterior (PCA) cerebral arteries. Vascular risk factors were collected. The WMHs load on FLAIR MRI sequences was quantitatively assessed. Results: The stroke/TIA patients presented a higher prevalence of RLS (100%) compared with the other groups (p < 0.001). The MA patients presented a higher BHI compared with the other groups in the PCA (p = 0.010) and higher RLS prevalence (60%) than controls (30%) (p < 0.001). The WMHs load did not differ across groups. BHI and RLS were not correlated to the WMHs load in the groups. Conclusions: A preserved or more reactive cerebral hemodynamics and the presence of a RLS are likely not involved in the genesis of WMHs in MA patients. A higher BHI may counteract the risk related to their higher prevalence of RLS. These results need to be confirmed by further studies to be able to effectively identify the protective role of cerebral hemodynamics in the increased RLS frequency in MA patients.

An accurate and explainable ensemble learning method for carotid plaque prediction in an asymptomatic population

BACKGROUND AND OBJECTIVE

The identification of carotid plaque, one of the most crucial tasks in stroke screening, is of great significance in the assessment of subclinical atherosclerosis and preventing the onset of stroke. However, traditional ultrasound examination is not prevalent or cost-effective for asymptomatic people, particularly low-income individuals in rural areas. Thus, it is necessary to develop an accurate and explainable model for early identification of the risk of plaque prevalence that can help in the primary prevention of stroke.

METHODS

We developed an ensemble learning method to predict the occurrence of carotid plaques. A dataset comprising 1440 subjects (50% with plaques and 50% without plaques) and ten-fold cross-validation were utilized to evaluate the model performance. Four machine learning methods (extreme gradient boosting (XGBoost), gradient boosting decision tree, random forest, and support vector machine) were evaluated. Subsequently, the interpretability of the XGBoost model, which provided the best performance, was analyzed from three aspects: feature importance, feature effect on prediction model, and feature effect on prediction decision for a specific subject.

RESULTS

The XGBoost algorithm provided the best performance (sensitivity: 0.8678, specificity: 0.8592, accuracy: 0.8632, F1 score: 0.8621, area under the curve: 0.8635) in carotid plaque prediction and also had excellent performance under missing data circumstances. Further, interpretability analysis showed that the decisions of the XGBoost model were highly congruent with clinical knowledge.

CONCLUSION

The model results are superior to those of state-of-the-art methods. Thus, it is a promising carotid plaque prediction tool that could be used in the primary prevention of stroke.