Prevalence of non-stenotic vulnerable carotid plaques in embolic stroke of undetermined source

INTRODUCTION

The latest research in ischaemic stroke pathogenesis is directed to unveil what is inside embolic stroke of undetermined source (ESUS). Whether vulnerable non stenotic carotid plaques (NSTEPS), i.e. atherosclerotic lesions in carotid arteries determining a stenosis lower than 50%, may represent a cause of stroke in ESUS is a matter of debate. We aimed to study the prevalence of NSTEPS in an ESUS population.

PATIENTS AND METHODS

We retrospectively identified a consecutive ESUS population admitted to the Stroke-Unit of Careggi Hospital, Italy from 2019 to 2022. Characteristics of atherosclerotic plaques (thickness, ulceration, hypodensity) and their location (ipsilateral versus contralateral to the stroke) were studied on carotid CT angiography (CTA). Follow-up data were recorded up to 24 months after stroke.

RESULTS

We identified 57 ESUS patients with unilateral ischaemic lesions studied with CTA; 53 (93%) had an ipsilateral carotid plaque, 81% contralateral, (p = 0.754) and 74% both. Plaques ipsilateral to stroke were ≥ 3 mm thick in 15 (28%) patients; hypodense in 14 (26%) and ulcerated in 5 (9%). The frequency of hypodensity was higher in ipsilateral compared to contralateral plaques (26% vs. 13%, p = 0.039) and ulceration was around four times more frequent, although not statistically significant (9% vs. 2%, p = 0.219). At follow-up, six patients had stroke recurrence (11%), 2 of them were in the same vascular territory of the former.

DISCUSSION AND CONCLUSIONS

Our data suggest that plaques ipsilateral to stroke seem to be more frequently vulnerable and consequently more prone to embolization. Prospective data are needed to clarify the causal role of NSTEPS in ESUS.

Deep learning approach for cardiovascular disease risk stratification and survival analysis on a Canadian cohort

The quantification of carotid plaque has been routinely used to predict cardiovascular risk in cardiovascular disease (CVD) and coronary artery disease (CAD). To determine how well carotid plaque features predict the likelihood of CAD and cardiovascular (CV) events using deep learning (DL) and compare against the machine learning (ML) paradigm. The participants in this study consisted of 459 individuals who had undergone coronary angiography, contrast-enhanced ultrasonography, and focused carotid B-mode ultrasound. Each patient was tracked for thirty days. The measurements on these patients consisted of maximum plaque height (MPH), total plaque area (TPA), carotid intima-media thickness (cIMT), and intraplaque neovascularization (IPN). CAD risk and CV event stratification were performed by applying eight types of DL-based models. Univariate and multivariate analysis was also conducted to predict the most significant risk predictors. The DL's model effectiveness was evaluated by the area-under-the-curve measurement while the CV event prediction was evaluated using the Cox proportional hazard model (CPHM) and compared against the DL-based concordance index (c-index). IPN showed a substantial ability to predict CV events (p < 0.0001). The best DL system improved by 21% (0.929 vs. 0.762) over the best ML system. DL-based CV event prediction showed a ~ 17% increase in DL-based c-index compared to the CPHM (0.86 vs. 0.73). CAD and CV incidents were linked to IPN and carotid imaging characteristics. For survival analysis and CAD prediction, the DL-based system performs superior to ML-based models.

Peak systolic velocity ratio for evaluation of internal carotid artery stenosis correlated with plaque morphology: substudy results of the ANTIQUE study

Background

Accurate assessment of carotid stenosis severity is important for proper patient management. The present study aimed to compare the evaluation of carotid stenosis severity using four duplex sonography (DUS) measurements, including peak systolic velocity (PSV), PSV ratio in stenosis and distal to stenosis (PSVICA/ICA ratio), end-diastolic velocity (EDV), and B-mode, with computed tomography angiography (CTA), and to evaluate the impact of plaque morphology on correlation between DUS and CTA.

Methods

Consecutive patients with carotid stenosis of ≥40% examined using DUS and CTA were included. Plaque morphology was also determined using magnetic resonance imaging. Spearman's correlation and Kendall's rank correlation were used to evaluate the results.

Results

A total of 143 cases of internal carotid artery stenosis of ≥40% based on DUS were analyzed. The PSVICA/ICA ratio showed the highest correlation [Spearman's correlation r = 0.576) with CTA, followed by PSV (r = 0.526), B-mode measurement (r = 0.482), and EDV (r = 0.441; p < 0.001 in all cases]. The worst correlation was found for PSV when the plaque was calcified (r = 0.238), whereas EDV showed a higher correlation (r = 0.523). Correlations of B-mode measurement were superior for plaques with smooth surface (r = 0.677), while the PSVICA/ICA ratio showed the highest correlation in stenoses with irregular (r = 0.373) or ulcerated (r = 0.382) surfaces, as well as lipid (r = 0.406), fibrous (r = 0.461), and mixed (r = 0.403; p < 0.01 in all cases) plaques. Nevertheless, differences between the mentioned correlations were not statistically significant (p > 0.05 in all cases).

Conclusion

PSV, PSVICA/ICA ratio, EDV, and B-mode measurements showed comparable correlations with CTA in evaluation of carotid artery stenosis based on their correlation with CTA results. Heavy calcifications and plaque surface irregularity or ulceration negatively influenced the measurement accuracy.

MR Angiography of Extracranial Carotid Disease

Magnetic resonance angiography sequences, such as time-of-flight and contrast-enhanced angiography, provide clear depiction of vessel lumen, traditionally used to evaluate carotid pathologic conditions such as stenosis, dissection, and occlusion; however, atherosclerotic plaques with a similar degree of stenosis may vary tremendously from a histopathological standpoint. MR vessel wall imaging is a promising noninvasive method to evaluate the content of the vessel wall at high spatial resolution. This is particularly interesting in the case of atherosclerosis as vessel wall imaging can identify higher risk, vulnerable plaques as well as has potential applications in the evaluation of other carotid pathologic conditions.

Pearls and Pitfalls of Carotid Artery Imaging: Ultrasound, Computed Tomography Angiography, and MR Imaging

Stroke represents a major cause of morbidity and mortality worldwide with carotid atherosclerosis responsible for a large proportion of ischemic strokes. Given the high burden of the disease , early diagnosis and optimal secondary prevention are essential elements in clinical practice. For a long time, the degree of stenosis had been considered the parameter to judge the severity of carotid atherosclerosis. Over the last 30 years, literature has shifted attention from stenosis to structural characteristics of atherosclerotic lesion, eventually leading to the "vulnerable plaque" model. These "vulnerable plaques" frequently demonstrate high-risk imaging features that can be assessed by various non-invasive imaging modalities.

Inflammation, Microcalcification, and Increased Expression of Osteopontin Are Histological Hallmarks of Plaque Vulnerability in Patients with Advanced Carotid Artery Stenosis

Background: severe carotid artery stenosis is a major cause of ischemic stroke and consequent neurological deficits. The most important steps of atherosclerotic plaque development, leading to carotid stenosis, are well-known; however, their exact timeline and intricate causal relationships need to be more characterized. Methods: in a cohort of 119 patients, who underwent carotid endarterectomy, we studied the histological correlations between arterial calcification patterns and localization, the presence of the inflammatory infiltrate and osteopontin expression, with ulceration, thrombosis, and intra-plaque hemorrhage, as direct signs of vulnerability. Results: in patients with an inflammatory infiltrate, aphasia was more prevalent, and microcalcification, superficial calcification, and high-grade osteopontin expression were characteristic. Higher osteopontin expression was also correlated with the presence of a lipid core. Inflammation and microcalcification were significantly associated with plaque ulceration in logistic regression models; furthermore, ulceration and the inflammatory infiltrate were significant determinants of atherothrombosis. Conclusion: our results bring histological evidence for the critically important role of microcalcification and inflammatory cell invasion in the formation and destabilization of advanced carotid plaques. In addition, as a calcification organizer, high-grade osteopontin expression is associated with ulceration, the presence of a large lipid core, and may also have an intrinsic role in plaque progression.

Identifying vulnerable plaques: A 3D carotid plaque radiomics model based on HRMRI

Background

Identification of vulnerable carotid plaque is important for the treatment and prevention of stroke. In previous studies, plaque vulnerability was assessed qualitatively. We aimed to develop a 3D carotid plaque radiomics model based on high-resolution magnetic resonance imaging (HRMRI) to quantitatively identify vulnerable plaques.

Methods

Ninety patients with carotid atherosclerosis who underwent HRMRI were randomized into training and test cohorts. Using the radiological characteristics of carotid plaques, a traditional model was constructed. A 3D carotid plaque radiomics model was constructed using the radiomics features of 3D T₁-SPACE and its contrast-enhanced sequences. A combined model was constructed using radiological and radiomics characteristics. Nomogram was generated based on the combined models, and ROC curves were utilized to assess the performance of each model.

Results

48 patients (53.33%) were symptomatic and 42 (46.67%) were asymptomatic. The traditional model was constructed using intraplaque hemorrhage, plaque enhancement, wall remodeling pattern, and lumen stenosis, and it provided an area under the curve (AUC) of 0.816 vs. 0.778 in the training and testing sets. In the two cohorts, the 3D carotid plaque radiomics model and the combined model had an AUC of 0.915 vs. 0.835 and 0.957 vs. 0.864, respectively. In the training set, both the radiomics model and the combination model outperformed the traditional model, but there was no significant difference between the radiomics model and the combined model.

Conclusions

HRMRI-based 3D carotid radiomics models can improve the precision of detecting vulnerable carotid plaques, consequently improving risk classification and clinical decision-making in patients with carotid stenosis.

Cardiovascular/Stroke Risk Stratification in Diabetic Foot Infection Patients Using Deep Learning-Based Artificial Intelligence: An Investigative Study

A diabetic foot infection (DFI) is among the most serious, incurable, and costly to treat conditions. The presence of a DFI renders machine learning (ML) systems extremely nonlinear, posing difficulties in CVD/stroke risk stratification. In addition, there is a limited number of well-explained ML paradigms due to comorbidity, sample size limits, and weak scientific and clinical validation methodologies. Deep neural networks (DNN) are potent machines for learning that generalize nonlinear situations. The objective of this article is to propose a novel investigation of deep learning (DL) solutions for predicting CVD/stroke risk in DFI patients. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) search strategy was used for the selection of 207 studies. We hypothesize that a DFI is responsible for increased morbidity and mortality due to the worsening of atherosclerotic disease and affecting coronary artery disease (CAD). Since surrogate biomarkers for CAD, such as carotid artery disease, can be used for monitoring CVD, we can thus use a DL-based model, namely, Long Short-Term Memory (LSTM) and Recurrent Neural Networks (RNN) for CVD/stroke risk prediction in DFI patients, which combines covariates such as office and laboratory-based biomarkers, carotid ultrasound image phenotype (CUSIP) lesions, along with the DFI severity. We confirmed the viability of CVD/stroke risk stratification in the DFI patients. Strong designs were found in the research of the DL architectures for CVD/stroke risk stratification. Finally, we analyzed the AI bias and proposed strategies for the early diagnosis of CVD/stroke in DFI patients. Since DFI patients have an aggressive atherosclerotic disease, leading to prominent CVD/stroke risk, we, therefore, conclude that the DL paradigm is very effective for predicting the risk of CVD/stroke in DFI patients.

Characteristics of Calcification and Their Association with Carotid Plaque Vulnerability

BACKGROUND

Carotid plaque vulnerability is one of the important features for evaluating the risk of subsequent ischemic stroke. Although magnetic resonance imaging (MRI) is the gold standard modality for evaluating plaque vulnerability, some patients cannot undergo MRI because of physical or economic issues. Computed tomography (CT) is more readily available. The purpose of this study was to establish a new category of calcification on CT and to assess its usefulness for detecting vulnerable plaque.

MATERIALS AND METHODS

We retrospectively evaluated consecutive patients who underwent plaque imaging using CT and MRI before carotid revascularization at our institute. Calcifications were classified into 4 types according to the new calcium classification. The patients were divided into 2 groups, the double layer sign (DLS)-positive group and the DLS-negative group. Signal intensity ratio (SIR) of carotid plaque was measured on MRI for evaluating plaque vulnerability and compared between type of calcification and SIR.

RESULTS

Among the 132 patients evaluated, 50 patients (62.5%) in DLS positive group and 16 patients (30.8%) in DLS negative group had calcification with vulnerable plaque (SIR > 1.47) (P < 0.01). Substantial interobserver agreement of type of calcification was observed (kappa, 0.79; P < 0.01). Multivariate analysis showed that DLS (odds ratio 3.03; 95% confidence interval 1.35-6.8; P < 0.01) and male sex (odds ratio 3.15; 95% confidence interval 1.02-9.68; P = 0.04) were independent predictors of vulnerable plaque.

CONCLUSIONS

DLS in our new classification of calcification on CT reliably detects vulnerable plaque and could thus be used in patients who cannot undergo MRI.

Deep learning artificial intelligence framework for multiclass coronary artery disease prediction using combination of conventional risk factors, carotid ultrasound, and intraplaque neovascularization

OBJECTIVE

Cardiovascular disease (CVD) is a major healthcare challenge and therefore early risk assessment is vital. Previous assessment techniques use either "conventional CVD risk calculators (CCVRC)" or machine learning (ML) paradigms. These techniques are ad-hoc, unreliable, not fully automated, and have variabilities. We, therefore, introduce AtheroEdge-MCDLAI (AE3.0DL) windows-based platform using multiclass Deep Learning (DL) system.

METHODS

Data was collected on 500 patients having both carotid ultrasound and corresponding coronary angiography scores (CAS), measured as stenosis in coronary arteries and considered as the gold standard. A total of 39 covariates were used, clubbed into three clusters, namely (i) Office-based: age, gender, body mass index, smoker, hypertension, systolic blood pressure, and diastolic blood pressure; (ii) Laboratory-based: Hyperlipidemia, hemoglobin A1c, and estimated glomerular filtration rate; and (iii) Carotid ultrasound image phenotypes: maximum plaque height, total plaque area, and intra-plaque neovascularization. Baseline characteristics for four classes (target labels) having significant (p < 0.0001) values were calculated using Chi-square and ANOVA. For handling the cohort's imbalance in the risk classes, AE3.0DL used the synthetic minority over-sampling technique (SMOTE). AE3.0DL used Recurrent Neural Network (RNN) and Long Short-Term Memory (LSTM) DL models and the performance (accuracy and area-under-the-curve) was computed using 10-fold cross-validation (90% training, 10% testing) frameworks. AE3.0DL was validated and benchmarked.

RESULTS

The AE3.0DL using RNN and LSTM showed an accuracy and AUC (p < 0.0001) pairs as (95.00% and 0.98), and (95.34% and 0.99), respectively, and showed an improvement of 32.93% and 9.94% against CCVRC and ML, respectively. AE3.0DL runs in <1 s.

CONCLUSION

DL algorithms are a powerful paradigm for coronary artery disease (CAD) risk prediction and CVD risk stratification.

Brain Tumor Characterization Using Radiogenomics in Artificial Intelligence Framework

Brain tumor characterization (BTC) is the process of knowing the underlying cause of brain tumors and their characteristics through various approaches such as tumor segmentation, classification, detection, and risk analysis. The substantial brain tumor characterization includes the identification of the molecular signature of various useful genomes whose alteration causes the brain tumor. The radiomics approach uses the radiological image for disease characterization by extracting quantitative radiomics features in the artificial intelligence (AI) environment. However, when considering a higher level of disease characteristics such as genetic information and mutation status, the combined study of "radiomics and genomics" has been considered under the umbrella of "radiogenomics". Furthermore, AI in a radiogenomics' environment offers benefits/advantages such as the finalized outcome of personalized treatment and individualized medicine. The proposed study summarizes the brain tumor's characterization in the prospect of an emerging field of research, i.e., radiomics and radiogenomics in an AI environment, with the help of statistical observation and risk-of-bias (RoB) analysis. The PRISMA search approach was used to find 121 relevant studies for the proposed review using IEEE, Google Scholar, PubMed, MDPI, and Scopus. Our findings indicate that both radiomics and radiogenomics have been successfully applied aggressively to several oncology applications with numerous advantages. Furthermore, under the AI paradigm, both the conventional and deep radiomics features have made an impact on the favorable outcomes of the radiogenomics approach of BTC. Furthermore, risk-of-bias (RoB) analysis offers a better understanding of the architectures with stronger benefits of AI by providing the bias involved in them.

Vascular Implications of COVID-19: Role of Radiological Imaging, Artificial Intelligence, and Tissue Characterization: A Special Report

The SARS-CoV-2 virus has caused a pandemic, infecting nearly 80 million people worldwide, with mortality exceeding six million. The average survival span is just 14 days from the time the symptoms become aggressive. The present study delineates the deep-driven vascular damage in the pulmonary, renal, coronary, and carotid vessels due to SARS-CoV-2. This special report addresses an important gap in the literature in understanding (i) the pathophysiology of vascular damage and the role of medical imaging in the visualization of the damage caused by SARS-CoV-2, and (ii) further understanding the severity of COVID-19 using artificial intelligence (AI)-based tissue characterization (TC). PRISMA was used to select 296 studies for AI-based TC. Radiological imaging techniques such as magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound were selected for imaging of the vasculature infected by COVID-19. Four kinds of hypotheses are presented for showing the vascular damage in radiological images due to COVID-19. Three kinds of AI models, namely, machine learning, deep learning, and transfer learning, are used for TC. Further, the study presents recommendations for improving AI-based architectures for vascular studies. We conclude that the process of vascular damage due to COVID-19 has similarities across vessel types, even though it results in multi-organ dysfunction. Although the mortality rate is ~2% of those infected, the long-term effect of COVID-19 needs monitoring to avoid deaths. AI seems to be penetrating the health care industry at warp speed, and we expect to see an emerging role in patient care, reduce the mortality and morbidity rate.

Deep Learning Paradigm for Cardiovascular Disease/Stroke Risk Stratification in Parkinson’s Disease Affected by COVID-19: A Narrative Review

Background and Motivation: Parkinson’s disease (PD) is one of the most serious, non-curable, and expensive to treat. Recently, machine learning (ML) has shown to be able to predict cardiovascular/stroke risk in PD patients. The presence of COVID-19 causes the ML systems to become severely non-linear and poses challenges in cardiovascular/stroke risk stratification. Further, due to comorbidity, sample size constraints, and poor scientific and clinical validation techniques, there have been no well-explained ML paradigms. Deep neural networks are powerful learning machines that generalize non-linear conditions. This study presents a novel investigation of deep learning (DL) solutions for CVD/stroke risk prediction in PD patients affected by the COVID-19 framework. Method: The PRISMA search strategy was used for the selection of 292 studies closely associated with the effect of PD on CVD risk in the COVID-19 framework. We study the hypothesis that PD in the presence of COVID-19 can cause more harm to the heart and brain than in non-COVID-19 conditions. COVID-19 lung damage severity can be used as a covariate during DL training model designs. We, therefore, propose a DL model for the estimation of, (i) COVID-19 lesions in computed tomography (CT) scans and (ii) combining the covariates of PD, COVID-19 lesions, office and laboratory arterial atherosclerotic image-based biomarkers, and medicine usage for the PD patients for the design of DL point-based models for CVD/stroke risk stratification. Results: We validated the feasibility of CVD/stroke risk stratification in PD patients in the presence of a COVID-19 environment and this was also verified. DL architectures like long short-term memory (LSTM), and recurrent neural network (RNN) were studied for CVD/stroke risk stratification showing powerful designs. Lastly, we examined the artificial intelligence bias and provided recommendations for early detection of CVD/stroke in PD patients in the presence of COVID-19. Conclusion: The DL is a very powerful tool for predicting CVD/stroke risk in PD patients affected by COVID-19.

Cardiovascular Risk Stratification in Diabetic Retinopathy via Atherosclerotic Pathway in COVID-19/non-COVID-19 Frameworks using Artificial Intelligence Paradigm: A Narrative Review

Diabetes is one of the main causes of the rising cases of blindness in adults. This microvascular complication of diabetes is termed diabetic retinopathy (DR) and is associated with an expanding risk of cardiovascular events in diabetes patients. DR, in its various forms, is seen to be a powerful indicator of atherosclerosis. Further, the macrovascular complication of diabetes leads to coronary artery disease (CAD). Thus, the timely identification of cardiovascular disease (CVD) complications in DR patients is of utmost importance. Since CAD risk assessment is expensive for low-income countries, it is important to look for surrogate biomarkers for risk stratification of CVD in DR patients. Due to the common genetic makeup between the coronary and carotid arteries, low-cost, high-resolution imaging such as carotid B-mode ultrasound (US) can be used for arterial tissue characterization and risk stratification in DR patients. The advent of artificial intelligence (AI) techniques has facilitated the handling of large cohorts in a big data framework to identify atherosclerotic plaque features in arterial ultrasound. This enables timely CVD risk assessment and risk stratification of patients with DR. Thus, this review focuses on understanding the pathophysiology of DR, retinal and CAD imaging, the role of surrogate markers for CVD, and finally, the CVD risk stratification of DR patients. The review shows a step-by-step cyclic activity of how diabetes and atherosclerotic disease cause DR, leading to the worsening of CVD. We propose a solution to how AI can help in the identification of CVD risk. Lastly, we analyze the role of DR/CVD in the COVID-19 framework.

A hybrid deep learning paradigm for carotid plaque tissue characterization and its validation in multicenter cohorts using a supercomputer framework

BACKGROUND

Early and automated detection of carotid plaques prevents strokes, which are the second leading cause of death worldwide according to the World Health Organization. Artificial intelligence (AI) offers automated solutions for plaque tissue characterization. Recently, solo deep learning (SDL) models have been used, but they do not take advantage of the tandem connectivity offered by AI's hybrid nature. Therefore, this study explores the use of hybrid deep learning (HDL) models in a multicenter framework, making this study the first of its kind.

METHODS

We hypothesize that HDL techniques perform better than SDL and transfer learning (TL) techniques. We propose two kinds of HDL frameworks: (i) the fusion of two SDLs (Inception with ResNet) or (ii) 10 other kinds of tandem models that fuse SDL with ML. The system Atheromatic™ 2.0_HDL (AtheroPoint, CA, USA) was designed on an augmentation framework and three kinds of loss functions (cross-entropy, hinge, and mean-square-error) during training to determine the best optimization paradigm. These 11 combined HDL models were then benchmarked against one SDL model and five types of TL models; thus, this study considers a total of 17 AI models.

RESULTS

Among the 17 AI models, the best performing HDL system was that comprising CNN and decision tree (DT), as its accuracy and area-under-the-curve were 99.78 ± 1.05% and 0.99 (p<0.0001), respectively. These values are 6.4% and 3.2% better than those recorded for the SDL and TL models, respectively. We validated the performance of the HDL models with diagnostics odds ratio (DOR) and Cohen and Kappa statistics; here, HDL outperformed DL and TL by 23% and 7%, respectively. The online system ran in <2 s.

CONCLUSION

HDL is a fast, reliable, and effective tool for characterizing the carotid plaque for early stroke risk stratification.

Carotid Plaque Composition Assessed by CT Predicts Subsequent Cardiovascular Events among Subjects with Carotid Stenosis

BACKGROUND AND PURPOSE

Currently, the characteristics of carotid plaques are considered important factors for identifying subjects at high risk of stroke. This study aimed to test the hypothesis that carotid plaque composition assessed by CTA is associated with an increased risk of future major adverse cardiovascular events among asymptomatic subjects with moderate-to-severe carotid artery stenosis.

MATERIALS AND METHODS

This single-center, retrospective cohort study included 194 carotid plaques from 176 asymptomatic subjects with moderate-to-severe carotid artery stenosis. The association of CTA-determined plaque composition with the risk of subsequent adverse cardiovascular events was analyzed.

RESULTS

During a median follow-up of 41 months, the adverse cardiovascular event incidence among 194 carotid plaques was 19.6%. There were significant differences in plaque Hounsfield units (P < .001) and spotty calcium presence (P < .001) between carotid plaques from subjects with and without subsequent adverse cardiovascular events. Multivariable analysis revealed carotid plaque Hounsfield unit density (P < .001) and spotty calcium (P < .001) as independent predictors of subsequent adverse cardiovascular events. In association with moderate carotid artery stenosis, the plaque Hounsfield unit values were significantly lower among carotid plaques from subjects who experienced subsequent adverse cardiovascular events (P = .002), strokes (P = .01), and cardiovascular deaths (P = .04); the presence of spotty calcium was significantly associated with the occurrence of adverse cardiovascular events (P = .001), acute coronary syndrome (P = .01), and cardiovascular death (P = .04).

CONCLUSIONS

Carotid plaque Hounsfield unit density and spotty calcium were independent predictors of a greater risk of adverse cardiovascular event occurrence.

Computed Tomography Texture Analysis of Carotid Plaque as Predictor of Unfavorable Outcome after Carotid Artery Stenting: A Preliminary Study

Novel biomarkers are advocated to manage carotid plaques. Therefore, we aimed to test the association between textural features of carotid plaque at computed tomography angiography (CTA) and unfavorable outcome after carotid artery stenting (CAS). Between January 2010 and January 2021, were selected 172 patients (median age, 77 years; 112/172, 65% men) who underwent CAS with CTA of the supra-aortic vessels performed within prior 6 months. Standard descriptors of the density histogram were derived by open-source software automated analysis obtained by CTA plaque segmentation. Multiple logistic regression analysis, receiver operating characteristic (ROC) curve analysis and the area under the ROC (AUC) were used to identify potential prognostic variables and to assess the model performance for predicting unfavorable outcome (periprocedural death or myocardial infarction and any ipsilateral acute neurological event). Unfavorable outcome occurred in 17/172 (10%) patients (median age, 79 years; 12/17, 70% men). Kurtosis was an independent predictor of unfavorable outcome (odds ratio, 0.79; confidence interval, 0.65-0.97; p = 0.029). The predictive model for unfavorable outcome including CTA textural features outperformed the model without textural features (AUC 0.789 vs. 0.695, p = 0.004). In patients with stenotic carotid plaque, kurtosis derived by CTA density histogram analysis is an independent predictor of unfavorable outcome after CAS.

Expression of miRNAs Targeting ATP Binding Cassette Transporter 1 (ABCA1) among Patients with Significant Carotid Artery Stenosis

Background: Carotid artery stenosis is a dynamic process associated with an increased risk of cardiovascular events. However, knowledge of biomarkers useful for identifying and quantifying high-risk carotid plaques associated with the increased incidence of cerebrovascular events is insufficient. Therefore, the objectives of this study were to evaluate the expression of ATP binding cassette transporter 1 (ABCA1) and validate its target microRNA (miRNA) candidates in human carotid stenosis arteries to identify its potential as a biomarker. Methods: In human carotid stenosis arterial tissues and plasma, the expression of ABCA1 and its target miRNAs (miRNA-33a-5p, 33b-5p, and 148a-3p) were evaluated by quantitative real time-polymerase chain reaction (qRT-PCR), immunohistochemistry, and enzyme-linked immunosorbent assay (ELISA). Results: The expression of ABCA1 was significantly decreased in the plasma of stenosis patients, but its expression was not different in arterial tissues (p < 0.05). However, significantly more target miRNAs were secreted by stenosis patients than normal patients (p < 0.05). Interestingly, lipotoxicity induced by the oleic and palmitic acid (OAPA) or lipopolysaccharide (LPS) treatment of human umbilical vein endothelial cells (HUVECs) dramatically enhanced the gene expression of adipogenic and inflammatory factors, whereas ABCA1 expression was significantly decreased. Conclusions: Therefore, miRNA-33a-5p, 33b-5p, and 148a-3p represent possible biomarkers of carotid artery stenosis by directly targeting ABCA1.

Circumferential degree of carotid calcification is associated with new ischemic brain lesions after carotid artery stenting

Background

The relationship between plaque calcification and new ischemic brain lesions after carotid artery stenting (CAS) remains controversial. The purpose of this study was to determine if the circumferential degree of carotid calcification is associated with new ischemic brain lesions on diffusion-weighted imaging (DWI) after CAS.

Methods

A total of 96 patients with carotid stenosis of ≥50% who underwent CAS were enrolled in the study. All patients underwent preoperative carotid computed tomography (CT), and preoperative and postoperative brain MRI. The brain MRI sequences included T1WI, T2WI, T2-fluid-attenuated inversion recovery (FLAIR), and DWI. The location, circumferential degree, volume, percentage volume, maximum density, mean density, Agatston score of carotid calcification, and total plaque volume were assessed and compared between patients with and without new ischemic brain lesions after CAS. Univariate and multivariate analyses were performed to evaluate predictors of new ischemic brain lesions.

Results

All of the 96 patients (67.8±6.8 years of age, 83.3% men) were included in the analysis. New ischemic brain lesions on DWI were observed in 40 patients (41.7%). Patients with new ischemic brain lesions after CAS had a larger circumferential degree of calcification than those without new ischemic brain lesions (P<0.001). There was only a possible trend toward significance for the percentage volume of calcification between the two groups with and without new brain ischemic lesions (P=0.07). No significant differences were found regarding the location (P=0.18), volume (P=0.37), maximum density (P=0.44), mean density (P=0.39), Agatston score (P=0.28), and total plaque volume (P=0.33) of carotid calcification between the DWI+ and DWI- groups. In the multivariate analysis, an increased risk of new ischemic brain lesions was observed in patients with a high score for the circumferential degree of calcification [score 3; odds ratio (OR): 10.7, P<0.001; score 4, OR: 11.7, P=0.038].

Conclusions

The circumferential degree of carotid calcification was associated with new ischemic brain lesions after CAS. CAS should be avoided if possible for carotid stenosis with large circumferential calcified plaques.

Assessment of carotid atherosclerotic plaque using 3D motion-sensitized driven-equilibrium prepared rapid gradient echo: a comparative study

Background

3D motion-sensitized driven-equilibrium prepared rapid gradient echo (MERGE) can characterize carotid atherosclerotic plaque morphology and composition. The present study aimed to evaluate its performance by comparing it with reference images and assessing the inter-reader agreement.

Methods

Eighty-four patients were prospectively recruited and scanned with 3D MERGE. Two trained magnetic resonance imaging (MRI) readers measured and calculated the maximum wall thickness (WT), maximum vessel diameter, total vessel area, lumen area, wall area, normalized wall index, plaque volume, intraplaque hemorrhage (IPH) volume, and calcification volume independently. IPH, calcification, mixed calcification, and ulceration were identified. The intraclass correlation coefficient (ICC) with 95% confidence interval (CI) was used to assess the inter-reader agreement. MERGE performance was assessed in terms of sensitivity, specificity, positive predictive value, negative predictive value, positive likelihood ratio, negative likelihood ratio, kappa value (κ), and the results of the Bland-Altman analysis and compared with reference images.

Results

MERGE showed excellent inter-reader agreement (All ICCs >0.90). MERGE and simultaneous non-contrast angiography and intraplaque hemorrhage (SNAP) showed excellent agreement in detecting IPH (κ=0.938) and measuring IPH volume (ICC =0.995; 95% CI: 0.991-0.997). MERGE and computed tomography angiography (CTA) showed strong consistency in detecting calcification (κ=0.814) and mixed calcification (κ=0.972), and in measuring calcification volume (ICC =0.996; 95% CI: 0.993-0.997). MERGE and digital subtraction angiography (DSA) showed relatively strong consistency in identifying ulceration (κ=0.737).

Conclusions

MERGE showed excellent performance in identifying and measuring IPH and calcification in carotid atherosclerotic plaques. Therefore, MERGE can be a promising imaging approach in atherosclerotic-vulnerable plaque.

CARotid plaqUe StabilizatiOn and regression with evolocumab: Rationale and design of the CARUSO study

BACKGROUND

While the experience with PCSK9i in patients with coronary artery disease has been wide, and coronary plaque regression has been documented, little is known regarding the role of these drugs on carotid plaque regression. The CARotid plaqUe StabilizatiOn and regression with evolocumab (CARUSO) study is a randomized, single-center, investigator-initiated trial aiming at evaluating carotid plaque morphological stabilization and regression following, respectively, 6 and 12 months of therapy with evolocumab.

METHODS

Asymptomatic patients with uni- or bilateral de novo carotid artery stenosis ≥50% and LDL-C values ≥100 mg/dl despite maximum tolerated lipid lowering therapy (LLT) will be randomized to evolocumab 140 mg s.c. every 2 weeks on top of ongoing LLT, or no additional treatment. 100 patients (50 in each arm) will be enrolled. Serial carotid duplex ultra-sonography will be performed to monitor the carotid plaque morphology and stenosis over time.

RESULTS

The primary end point of the study is, (a) carotid plaque morphological stabilization at 6 months, defined as defined as the disappearance of ulcerations and fluffy components and the achievement of a regular plaque morphology with prevalence of fibrous atheroma and/or (b) carotid plaque regression at 12 months, defined as reduction of the entity of the stenosis and/or peak systolic velocity by at least 5%, as compared with baseline.

CONCLUSION

The CARUSO trial will test the superiority of evolocumab on top of ongoing LLT versus ongoing LLT alone regarding carotid plaque morphological stabilization and regression. The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

Plaque Composition as a Predictor of Plaque Ulceration in Carotid Artery Atherosclerosis: The Plaque At RISK Study

BACKGROUND AND PURPOSE

Plaque ulceration is a marker of previous plaque rupture. We studied the association between atherosclerotic plaque composition at baseline and plaque ulceration at baseline and follow-up.

MATERIALS AND METHODS

We included symptomatic patients with a carotid stenosis of <70% who underwent MDCTA and MR imaging at baseline (n = 180). MDCTA was repeated at 2 years (n = 73). We assessed the presence of ulceration using MDCTA. Baseline MR imaging was used to assess the vessel wall volume and the presence and volume of plaque components (intraplaque hemorrhage, lipid-rich necrotic core, and calcifications) and the fibrous cap status. Associations at baseline were evaluated with binary logistic regression and reported with an OR and its 95% CI. Simple statistical testing was performed in the follow-up analysis.

RESULTS

At baseline, the prevalence of plaque ulceration was 27% (49/180). Increased wall volume (OR  = 12.1; 95% CI, 3.5-42.0), higher relative lipid-rich necrotic core (OR = 1.7; 95% CI, 1.3-2.2), higher relative intraplaque hemorrhage volume (OR = 1.7; 95% CI, 1.3-2.2), and a thin-or-ruptured fibrous cap (OR = 3.4; 95% CI, 1.7-6.7) were associated with the presence of ulcerations at baseline. In 8% (6/73) of the patients, a new ulcer developed. Plaques with a new ulceration at follow-up had at baseline a larger wall volume (1.04 cm³ [IQR, 0.97-1.16 cm³] versus 0.86 cm³ [IQR, 0.73-1.00 cm³]; P = .029), a larger relative lipid-rich necrotic core volume (23% [IQR, 13-31%] versus 2% [IQR, 0-14%]; P = .002), and a larger relative intraplaque hemorrhage volume (14% [IQR, 8-24%] versus 0% [IQR, 0-5%]; P < .001).

CONCLUSIONS

Large atherosclerotic plaques and plaques with intraplaque hemorrhage and lipid-rich necrotic cores were associated with plaque ulcerations at baseline and follow-up.

Normalized wall index, intraplaque hemorrhage and ulceration of carotid plaques correlate with the severity of ischemic stroke

BACKGROUND AND AIMS

Carotid atherosclerosis is considered an important cause of ischemic stroke. Tthis study aimed to explore the relationship between plaque features and the severity of stroke, and to identify plaque risk factors for the assessment of the severity of ischemic stroke.

METHODS

Symptomatic patients with carotid atherosclerotic plaques were prospectively recruited and underwent high-resolution vessel wall magnetic resonance imaging (VW-MRI). Two trained MRI readers independently identified intraplaque hemorrhage (IPH), calcification (CA), surface CA, deep CA, and ulceration. They measured and calculated the maximum vessel diameter (Max VD), maximum wall thickness (Max WT), total vessel area, lumen area, normalized wall index (NWI), plaque volume, IPH volume, IPH proportion, CA volume, and CA proportion. Patients were divided into two groups according to their National Institutes of Health Stroke Scale (NIHSS) scores (NIHSS ≤1 vs. NIHSS >1). Clinical characteristics and carotid plaque features were compared using the Mann-Whitney U test or Chi-square test as appropriate. Odds ratio (OR) and corresponding 95% confidence interval (CI) of plaque features to distinguish patients with NIHSS >1 were calculated. Spearman's rank correlations or Pearson correlations were determined for plaque features and NIHSS scores.

RESULTS

Of the 97 included patients, 34 (35.05%) with NIHSS >1 had significantly greater NWI (p < 0.05), larger IPH volume (p < 0.01), and greater IPH proportion (p < 0.01), and higher prevalence of IPH (OR, 5.654; 95%CI, 2.272-14.070; p < 0.01) and ulceration (OR, 2.891; 95%CI, 1.090-7.667; p = 0.033) than patients with NIHSS ≤1. Max WT (r = 0.24, p = 0.018), NWI (r = 0.22, p = 0.032), IPH (r = 0.27, p = 0.007), IPH volume (r = 0.35, p < 0.01), IPH proportion (r = 0.28, p = 0.005), and ulceration (r = 0.35, p < 0.01) had positive correlations with NIHSS scores.

CONCLUSIONS

NWI, IPH, and ulceration of carotid atherosclerotic plaque based on high-resolution VW-MRI may be useful indicators for assessing the severity of ischemic stroke in patients with atherosclerosis. NIHSS score is related to max WT, NWI, IPH, IPH volume, IPH proportion, and ulceration.

CT imaging features of carotid artery plaque vulnerability

Despite steady advances in medical care, cardiovascular disease remains one of the main causes of death and long-term morbidity worldwide. Up to 30% of strokes are associated with the presence of carotid atherosclerotic plaques. While the degree of stenosis has long been recognized as the main guiding factor in risk stratification and therapeutical decisions, recent evidence suggests that features of unstable, or ‘vulnerable’, plaques offer better prognostication capabilities. This paradigmatic shift has motivated researchers to explore the potentialities of non-invasive diagnostic tools to image not only the lumen, but also the vascular wall and the structural characteristics of the plaque. The present review will offer a panoramic on the imaging modalities currently available to characterize carotid atherosclerotic plaques and, in particular, it will focus on the increasingly important role covered by multidetector computed tomographic angiography.

Plaque imaging volume analysis: technique and application

The prevention and management of atherosclerosis poses a tough challenge to public health organizations worldwide. Together with myocardial infarction, stroke represents its main manifestation, with up to 25% of all ischemic strokes being caused by thromboembolism arising from the carotid arteries. Therefore, a vast number of publications have focused on the characterization of the culprit lesion, the atherosclerotic plaque. A paradigm shift appears to be taking place at the current state of research, as the attention is gradually moving from the classically defined degree of stenosis to the identification of features of plaque vulnerability, which appear to be more reliable predictors of recurrent cerebrovascular events. The present review will offer a perspective on the present state of research in the field of carotid atherosclerotic disease, focusing on the imaging modalities currently used in the study of the carotid plaque and the impact that such diagnostic means are having in the clinical setting.

Morphological Carotid Plaque Area Is Associated With Glomerular Filtration Rate: A Study of South Asian Indian Patients With Diabetes and Chronic Kidney Disease

We evaluated the association between automatically measured carotid total plaque area (TPA) and the estimated glomerular filtration rate (eGFR), a biomarker of chronic kidney disease (CKD). Automated average carotid intima-media thickness (cIMTave) and TPA measurements in carotid ultrasound (CUS) were performed using AtheroEdge (AtheroPoint). Pearson correlation coefficient (CC) was then computed between the TPA and eGFR for (1) males versus females, (2) diabetic versus nondiabetic patients, and (3) between the left and right carotid artery. Overall, 339 South Asian Indian patients with either type 2 diabetes mellitus (T2DM) or CKD, or hypertension (stage 1 or stage 2) were retrospectively analyzed by acquiring cIMTave and TPA measurements of their left and right common carotid arteries (CCA; total CUS: 678, mean age: 54.2 ± 9.8 years; 75.2% males; 93.5% with T2DM). The CC between TPA and eGFR for different scenarios were (1) for males and females -0.25 (P < .001) and -0.35 (P < .001), respectively; (2) for T2DM and non-T2DM -0.26 (P < .001) and -0.49 (P = .02), respectively, and (3) for left and right CCA -0.25 (P < .001) and -0.23 (P < .001), respectively. Automated TPA is an equally reliable biomarker compared with cIMTave for patients with CKD (with or without T2DM) with subclinical atherosclerosis.

Carotid Vessel Wall Imaging on CTA

Vessel wall imaging has been increasingly used to characterize plaque beyond luminal narrowing to identify patients who may be at the highest risk of cerebrovascular ischemia. Although detailed plaque information can be obtained from many imaging modalities, CTA is particularly appealing for carotid plaque imaging due to its relatively low cost, wide availability, operator independence, and ability to discern high-risk features. The present Review Article describes the current understanding of plaque characteristics on CTA by describing commonly encountered plaque features, including calcified and soft plaque, surface irregularities, neovascularization, and inflammation. The goal of this Review Article was to provide a more robust understanding of clinically relevant plaque features detectable on routine CTA of the carotid arteries.

Massive Cerebral Microemboli after Protected Carotid Artery Angioplasty and Stenting Using a Distal Filter Embolic Protection Device for a Vulnerable Plaque with a Lipid Rich Necrotic Core and Intraplaque Hemorrhage: A Case Report

A major concern associated with carotid artery angioplasty and stenting (CAS) is a periprocedural distal cerebral embolization. To prevent distal embolization, embolic protection devices (EPDs) have been developed. However, the risk of cerebral embolism after protected CAS in patents with a vulnerable plaque is controversial and either a silent or a symptomatic stroke can occur despite the use of EPDs. Here, we report a case of a massive cerebral microemboli after a protected CAS using a distal filter EPD for a vulnerable plaque with a lipid rich necrotic core and intraplaque hemorrhage.

Imaging modalities to diagnose carotid artery stenosis: progress and prospect

In the past few decades, imaging has been developed to a high level of sophistication. Improvements from one-dimension (1D) to 2D images, and from 2D images to 3D models, have revolutionized the field of imaging. This not only helps in diagnosing various critical and fatal diseases in the early stages but also contributes to making informed clinical decisions on the follow-up treatment profile. Carotid artery stenosis (CAS) may potentially cause debilitating stroke, and its accurate early detection is therefore important. In this paper, the technical development of various CAS diagnosis imaging modalities and its impact on the clinical efficacy is thoroughly reviewed. These imaging modalities include duplex ultrasound (DUS), computed tomography angiography (CTA) and magnetic resonance angiography (MRA). For each of the imaging modalities considered, imaging methodology (principle), critical imaging parameters, and the extent of imaging the vulnerable plaque are discussed. DUS is usually the initial recommended CAS diagnostic examination. However, for the therapeutic intervention, either MRA or CTA is recommended for confirmation, and for added information on intracranial cerebral circulation and aortic arch condition for procedural planning. Over the past few decades, the focus of CAS diagnosis has also shifted from pure stenosis quantification to plaque characterization. This has led to further advancement in the existing imaging tools and development of other potential imaging tools like Optical coherence tomography (OCT), photoacoustic tomography (PAT), and infrared (IR) thermography.

Carotid artery imaging: The study of intra-plaque vascularization and hemorrhage in the era of the "vulnerable" plaque

Intraplaque hemorrhage (IPH) is one of the main factors involved in atherosclerotic plaque (AP) instability. Its recognition is crucial for the correct staging and management of patients with carotid artery plaques to limit ischemic stroke. Imaging plays a crucial role in identifying IPH, even if the great variability of intraplaque vascularization and the limitations of our current imaging technologies make it difficult. The intent of this review is to give a general overview of the main features of intraplaque vascularization and IPH on Ultrasound (US), Computed Tomography (CT), Magnetic Resonance (MR) and Nuclear Medicine, and a brief description on the future prospectives.

Imaging biomarkers of vulnerable carotid plaques for stroke risk prediction and their potential clinical implications

Stroke represents a massive public health problem. Carotid atherosclerosis plays a fundamental part in the occurence of ischaemic stroke. European and US guidelines for prevention of stroke in patients with carotid plaques are based on quantification of the percentage reduction in luminal diameter due to the atherosclerotic process to select the best therapeutic approach. However, better strategies for prevention of stroke are needed because some subtypes of carotid plaques (eg, vulnerable plaques) can predict the occurrence of stroke independent of the degree of stenosis. Advances in imaging techniques have enabled routine characterisation and detection of the features of carotid plaque vulnerability. Intraplaque haemorrhage is accepted by neurologists and radiologists as one of the features of vulnerable plaques, but other characteristics-eg, plaque volume, neovascularisation, and inflammation-are promising as biomarkers of carotid plaque vulnerability. These biomarkers could change current management strategies based merely on the degree of stenosis.

Retrospective Study of Hemodynamic Changes Before and After Carotid Stenosis Formation by Vessel Surface Repairing

Prospective observation of hemodynamic changes before and after the formation of atherosclerotic stenosis in the carotid artery is difficult. Thus, a vessel surface repairing method was used for retrospective hemodynamic study before and after atherosclerotic stenosis formation in carotid artery. The three-dimensional geometry of sixteen sinus atherosclerotic stenosis carotid arteries were repaired and restored as normal arteries. Computational fluid dynamics analysis was performed to estimate wall shear stress (WSS), velocity and vortex in atherosclerosis-free areas and sinus in stenosis-repaired carotid artery. The analysis was also performed in the stenotic segment and upstream and downstream of stenosis in stenotic carotid artery. Compared to the atherosclerosis-free areas in stenosis-repaired carotid artery, sinus presented significantly lower WSS (P < 0.05), lower velocity (P < 0.05) and apparent vortex. Compared to the sinus, the WSS in the upstream of stenosis was lower (P < 0.05), while in the downstream area was similar (P = 0.87), both upstream and downstream of stenosis demonstrated similar velocity to sinus (P = 0.76 and P = 0.36, respectively) and apparent vortex. Atherosclerosis-prone areas including normal carotid sinus and upstream and downstream of stenosis in stenotic carotid artery were subjected to lower WSS and velocity as well as apparent vortex, thereby might be associated with the formation and progress of atherosclerosis.

Carotid Artery Wall Imaging: Perspective and Guidelines from the ASNR Vessel Wall Imaging Study Group and Expert Consensus Recommendations of the American Society of Neuroradiology

Identification of carotid artery atherosclerosis is conventionally based on measurements of luminal stenosis and surface irregularities using in vivo imaging techniques including sonography, CT and MR angiography, and digital subtraction angiography. However, histopathologic studies demonstrate considerable differences between plaques with identical degrees of stenosis and indicate that certain plaque features are associated with increased risk for ischemic events. The ability to look beyond the lumen using highly developed vessel wall imaging methods to identify plaque vulnerable to disruption has prompted an active debate as to whether a paradigm shift is needed to move away from relying on measurements of luminal stenosis for gauging the risk of ischemic injury. Further evaluation in randomized clinical trials will help to better define the exact role of plaque imaging in clinical decision-making. However, current carotid vessel wall imaging techniques can be informative. The goal of this article is to present the perspective of the ASNR Vessel Wall Imaging Study Group as it relates to the current status of arterial wall imaging in carotid artery disease.

Imaging of the ulcerated carotid atherosclerotic plaque: a review of the literature

Abstract

Carotid atherosclerotic disease constitutes a major modern health problem whose diagnosis primarily relies on imaging. Grading of stenosis has been long used as the main factor for risk stratification and guiding of management. Nevertheless, increasing evidence has shown that additional plaque characteristics such as plaque composition and surface morphology play an important role in the occurrence of symptoms, justifying the term “vulnerable plaque”. Carotid plaque surface characteristics either in the form of surface irregularities or ulceration represent an important factor of vulnerability and are associated with the occurrence of neurologic symptoms. The delineation of the carotid plaque surface can be performed with virtually all imaging modalities including ultrasound, contrast-enhanced ultrasound, multi-detector computed tomography angiography, magnetic resonance angiography and the traditional reference method of angiography. These techniques have shown varying levels of diagnostic accuracy for the identification of ulcerated carotid plaques or plaque surface irregularities. As a consequence and given its high clinical significance, radiologists should be familiar with the various aspects of this entity, including its definition, classification, imaging findings on different imaging modalities and associations. The purpose of this review is to present the current literature regarding carotid plaque ulcerations and present illustrative images of ulcerated carotid plaques.

Teaching Points

• Plaque surface and ulceration represent risk factors for stroke in carotid disease.

• Characterisation of the plaque surface and ulcerations can be performed with every modality.

• US is the first-line modality for carotid disease and identification of ulcerations.

• The administration of microbubbles increases US accuracy for diagnosis of carotid ulceration.

• MDCTA and MRA are valuable for diagnosing ulceration and evaluating plaque composition.

Imaging Carotid Atherosclerosis Plaque Ulceration: Comparison of Advanced Imaging Modalities and Recent Developments

Atherosclerosis remains the leading cause of long-term mortality and morbidity worldwide, despite remarkable advancement in its management. Vulnerable atherosclerotic plaques are principally responsible for thromboembolic events in various arterial territories such as carotid, coronary, and lower limb vessels. Carotid plaque ulceration is one of the key features associated with plaque vulnerability and is considered a notable indicator of previous plaque rupture and possible future cerebrovascular events. Multiple imaging modalities have been used to assess the degree of carotid plaque ulceration for diagnostic and research purposes. Early diagnosis and management of carotid artery disease could prevent further cerebrovascular events. In this review, we highlight the merits and limitations of various imaging techniques for identifying plaque ulceration.

Carotid and cerebral CT angiography using low volume of iodinated contrast material and low tube voltage

PURPOSE

To evaluate image quality of carotid computed tomography angiography (CTA) using a low voltage (80kV) and low amount of iodinated contrast material.

MATERIALS-METHODS

A total of 101 patients referred for carotid CTA were randomly assigned to receive a specific protocol. In group A patients received intravenous administration of contrast material at a dose of 1mL/kg and CTA examinations were performed at 100kV. In group B, patients received intravenous administration of contrast material at a dose of 0.5mL/kg and CTA examinations were performed at 80kV. The same nonionic iodinated contrast material containing 370mg of iodine per mL was used in both groups. Attenuation values were measured from the center of specific arterial segments using regions of interest. Attenuation values above 300HU were accepted as significant. Institutional review board approval was obtained.

RESULTS

A total of 50 patients were included in group A (38 men, 12 women; mean age, 63.56 years±13.18 [SD]) and 51 patients in group B (33 men, 18 women; mean age, 59.60 years±16.63 [SD]). A total of 1615 arterial segments (1515 common carotid artery-middle cerebral artery and 101 aortic arches) were analyzed. Venous contamination was not observed in either group. The mean attenuation values of all arterial segments in both groups were greater than 300HU. Mean arterial attenuation value in group B (499.22HU±97.25 [SD]) was significantly greater than in group A (374.36HU±73.79 [SD]) (P<0.01). Hemodynamically significant stenosis (grade III stenosis or >70%) was detected in 2 segments in group A and in 3 segments in group B, while grade IV stenosis (occlusion) was detected in 2 segments in group B. Distal common carotid artery dissection was detected in 1 patient and aortic dissection was detected in 1 patient in group B. Total dose-length product (DLP) value was significantly greater in group A (225.74mGy·cm±21.80 [SD]) than in group B (116.60mGy·cm±21.22 [SD]) (P<0.01). The mean tube current was similar in group A (2013.11mAs±195.92 [SD]) and in group B (2096.64 mAs±309.03 [SD]) (P<0.05).

CONCLUSION

Carotid and cerebral CTA examinations using 128-section CT can be successfully obtained using an imaging protocol that combines low voltage and 50% reduction in the volume of iodinated contrast material. This provides good image quality with low radiation dose.

Longitudinal assessment of carotid atherosclerosis after Radiation Therapy using Computed Tomography: A case control Study

OBJECTIVES

To study the carotid artery plaque composition and its volume changes in a group of patients at baseline and 2 years after head and neck radiation therapy treatment (HNXRT).

METHODS

In this retrospective study, 62 patients (41 males; mean age 63 years; range 52-81) who underwent HNXRT and 40 patients (24 males; mean age 65) who underwent surgical resection of neoplasm and did not undergo HNXRT were assessed, with 2-year follow-up. The carotid artery plaque volumes, as well as the volume of the sub-components (fatty-mixed-calcified), were semiautomatically quantified. Mann-Whitney and Wilcoxon tests were used to test the hypothesis.

RESULTS

In the HNXRT group, there was a statistically significant increase in the total volume of the carotid artery plaques (from 533 to 746 mm(3); p = 0.001), in the fatty plaques (103 vs. 202 mm(3); p = 0.001) and mixed plaque component volume (328 vs. 419 mm(3); p = 0.034). A statistically significant variation (from 21.8 % to 27.6 %) in the percentage of the fatty tissue was found.

CONCLUSIONS

Results of this preliminary study suggest that HNXRT promotes increased carotid artery plaque volume, particularly the fatty plaque component.

KEY POINTS

HNXRT increases carotid plaque volume. Plaque volume increase is mainly due to increase.in fatty plaque component. Patients who undergo HNXRT have a progression of carotid artery disease.

Intraplaque Hemorrhage and the Plaque Surface in Carotid Atherosclerosis: The Plaque At RISK Study (PARISK)

BACKGROUND AND PURPOSE

An important characteristic of vulnerable plaque, intraplaque hemorrhage, may predict plaque rupture. Plaque rupture can be visible on noninvasive imaging as a disruption of the plaque surface. We investigated the association between intraplaque hemorrhage and disruption of the plaque surface.

MATERIALS AND METHODS

We selected the first 100 patients of the Plaque At RISK study, an ongoing prospective noninvasive plaque imaging study in patients with mild-to-moderate atherosclerotic lesions in the carotid artery. In carotid artery plaques, disruption of the plaque surface (defined as ulcerated plaques and/or fissured fibrous cap) and intraplaque hemorrhage were assessed by using MDCTA and 3T MR imaging, respectively. We used a χ(2) test and multivariable logistic regression to assess the association between intraplaque hemorrhage and disrupted plaque surface.

RESULTS

One hundred forty-nine carotid arteries in 78 patients could be used for the current analyses. Intraplaque hemorrhage and plaque ulcerations were more prevalent in symptomatic compared with contralateral vessels (hemorrhage, 38% versus 11%; P < .001; and ulcerations, 27% versus 7%; P = .001). Fissured fibrous cap was more prevalent in symptomatic compared with contralateral vessels (13% versus 4%; P = .06). After adjustment for age, sex, diabetes mellitus, and degree of stenosis, intraplaque hemorrhage was associated with disrupted plaque surface (OR, 3.13; 95% CI, 1.25-7.84) in all vessels.

CONCLUSIONS

Intraplaque hemorrhage is associated with disruption of the plaque surface in patients with a carotid artery stenosis of <70%. Serial studies are needed to investigate whether intraplaque hemorrhage indeed increases the risk of plaque rupture and subsequent ischemic stroke during follow-up.

Computed tomography angiography vs 3 T black-blood cardiovascular magnetic resonance for identification of symptomatic carotid plaques

BACKGROUND

The purpose of this prospective study was to perform a head-to-head comparison of the two methods most frequently used for evaluation of carotid plaque characteristics: Multi-detector Computed Tomography Angiography (MDCTA) and black-blood 3 T-cardiovascular magnetic resonance (bb-CMR) with respect to their ability to identify symptomatic carotid plaques.

METHODS

22 stroke unit patients with unilateral symptomatic carotid disease and >50% stenosis by duplex ultrasound underwent MDCTA and bb-CMR (TOF, pre- and post-contrast fsT1w-, and fsT2w- sequences) within 15 days of symptom onset. Both symptomatic and contralateral asymptomatic sides were evaluated. By bb-CMR, plaque morphology, composition and prevalence of complicated AHA type VI lesions (AHA-LT6) were evaluated. By MDCTA, plaque type (non-calcified, mixed, calcified), plaque density in HU and presence of ulceration and/or thrombus were evaluated. Sensitivity (SE), specificity (SP), positive and negative predictive value (PPV, NPV) were calculated using a 2-by-2-table.

RESULTS

To distinguish between symptomatic and asymptomatic plaques AHA-LT6 was the best CMR variable and presence / absence of plaque ulceration was the best CT variable, resulting in a SE, SP, PPV and NPV of 80%, 80%, 80% and 80% for AHA-LT6 as assessed by bb-CMR and 40%, 95%, 89% and 61% for plaque ulceration as assessed by MDCTA. The combined SE, SP, PPV and NPV of bb-CMR and MDCTA was 85%, 75%, 77% and 83%, respectively.

CONCLUSIONS

Bb-CMR is superior to MDCTA at identifying symptomatic carotid plaques, while MDCTA offers high specificity at the cost of low sensitivity. Results were only slightly improved over bb-CMR alone when combining both techniques.

The role of imaging in acute ischemic stroke

Neuroimaging has expanded beyond its traditional diagnostic role and become a critical tool in the evaluation and management of stroke. The objectives of imaging include prompt accurate diagnosis, treatment triage, prognosis prediction, and secondary preventative precautions. While capitalizing on the latest treatment options and expanding upon the "time is brain" doctrine, the ultimate goal of imaging is to maximize the number of treated patients and improve the outcome of one the most costly and morbid disease. A broad overview of comprehensive multimodal stroke imaging is presented here to affirm its utilization.

Multi-modal CT scanning in the evaluation of cerebrovascular disease patients

Ischemic stroke currently represents one of the leading causes of severe disability and mortality in the Western World. Until now, angiography was the most used imaging technique for the detection of the extra-cranial and intracranial vessel pathology. Currently, however, non-invasive imaging tool like ultrasound (US), magnetic resonance (MR) and computed tomography (CT) have proven capable of offering a detailed analysis of the vascular system. CT in particular represents an advanced system to explore the pathology of carotid arteries and intracranial vessels and also offers tools like CT perfusion (CTP) that provides valuable information of the brain's vascular physiology by increasing the stroke diagnostic. In this review, our purpose is to discuss stroke risk prediction and detection using CT.