Why selective screening for asymptomatic carotid stenosis is currently appropriate: a special report.

INTRODUCTION: Two of the main reasons recent guidelines do not recommend routine population-wide screening programs for asymptomatic carotid artery stenosis (AsxCS) is that screening could lead to an increase of carotid revascularization procedures and that such mass screening programs may not be cost-effective. Nevertheless, selective screening for AsxCS could have several benefits. This article presents the rationale for such a program. AREAS COVERED: The benefits of selective screening for AsxCS include early recognition of AsxCS allowing timely initiation of preventive measures to reduce future myocardial infarction (MI), stroke, cardiac death and cardiovascular (CV) event rates. EXPERT OPINION: Mass screening programs for AsxCS are neither clinically effective nor cost-effective. Nevertheless, targeted screening of populations at high risk for AsxCS provides an opportunity to identify these individuals earlier rather than later and to initiate a number of lifestyle measures, risk factor modifications, and intensive medical therapy in order to prevent future strokes and CV events. For patients at 'higher risk of stroke' on best medical treatment, a prophylactic carotid intervention may be considered.

Quantifying Carotid Stenosis: History, Current Applications, Limitations, and Potential: How Imaging Is Changing the Scenario.

Carotid artery stenosis is a major cause of morbidity and mortality. The journey to understanding carotid disease has developed over time and radiology has a pivotal role in diagnosis, risk stratification and therapeutic management. This paper reviews the history of diagnostic imaging in carotid disease, its evolution towards its current applications in the clinical and research fields, and the potential of new technologies to aid clinicians in identifying the disease and tailoring medical and surgical treatment.

Carotid Plaque-RADS: A Novel Stroke Risk Classification System.

BACKGROUND: Carotid artery atherosclerosis is highly prevalent in the general population and is a well-established risk factor for acute ischemic stroke. Although the morphological characteristics of vulnerable plaques are well recognized, there is a lack of consensus in reporting and interpreting carotid plaque features. OBJECTIVES: The aim of this paper is to establish a consistent and comprehensive approach for imaging and reporting carotid plaque by introducing the Plaque-RADS (Reporting and Data System) score. METHODS: A panel of experts recognized the necessity to develop a classification system for carotid plaque and its defining characteristics. Using a multimodality analysis approach, the Plaque-RADS categories were established through consensus, drawing on existing published reports. RESULTS: The authors present a universal classification that is applicable to both researchers and clinicians. The Plaque-RADS score offers a morphological assessment in addition to the prevailing quantitative parameter of "stenosis." The Plaque-RADS score spans from grade 1 (indicating complete absence of plaque) to grade 4 (representing complicated plaque). Accompanying visual examples are included to facilitate a clear understanding of the Plaque-RADS categories. CONCLUSIONS: Plaque-RADS is a standardized and reliable system of reporting carotid plaque composition and morphology via different imaging modalities, such as ultrasound, computed tomography, and magnetic resonance imaging. This scoring system has the potential to help in the precise identification of patients who may benefit from exclusive medical intervention and those who require alternative treatments, thereby enhancing patient care. A standardized lexicon and structured reporting promise to enhance communication between radiologists, referring clinicians, and scientists.

An international, multispecialty, expert-based Delphi Consensus document on controversial issues in the management of patients with asymptomatic and symptomatic carotid stenosis.

OBJECTIVE: Despite the publication of various national/international guidelines, several questions concerning the management of patients with asymptomatic (AsxCS) and symptomatic (SxCS) carotid stenosis remain unanswered. The aim of this international, multi-specialty, expert-based Delphi Consensus document was to address these issues to help clinicians make decisions when guidelines are unclear. METHODS: Fourteen controversial topics were identified. A three-round Delphi Consensus process was performed including 61 experts. The aim of Round 1 was to investigate the differing views and opinions regarding these unresolved topics. In Round 2, clarifications were asked from each participant. In Round 3, the questionnaire was resent to all participants for their final vote. Consensus was reached when ≥75% of experts agreed on a specific response. RESULTS: Most experts agreed that: (1) the current periprocedural/in-hospital stroke/death thresholds for performing a carotid intervention should be lowered from 6% to 4% in patients with SxCS and from 3% to 2% in patients with AsxCS; (2) the time threshold for a patient being considered "recently symptomatic" should be reduced from the current definition of "6 months" to 3 months or less; (3) 80% to 99% AsxCS carries a higher risk of stroke compared with 60% to 79% AsxCS; (4) factors beyond the grade of stenosis and symptoms should be added to the indications for revascularization in AsxCS patients (eg, plaque features of vulnerability and silent infarctions on brain computed tomography scans); and (5) shunting should be used selectively, rather than always or never. Consensus could not be reached on the remaining topics due to conflicting, inadequate, or controversial evidence. CONCLUSIONS: The present international, multi-specialty expert-based Delphi Consensus document attempted to provide responses to several unanswered/unresolved issues. However, consensus could not be achieved on some topics, highlighting areas requiring future research.

Recent advances and controversial issues in the optimal management of asymptomatic carotid stenosis.

OBJECTIVE: The optimal management of patients with asymptomatic carotid stenosis (AsxCS) is enduringly controversial. We updated our 2021 Expert Review and Position Statement, focusing on recent advances in the diagnosis and management of patients with AsxCS. METHODS: A systematic review of the literature was performed up to August 1, 2023, using PubMed/PubMed Central, EMBASE and Scopus. The following keywords were used in various combinations: "asymptomatic carotid stenosis," "carotid endarterectomy" (CEA), "carotid artery stenting" (CAS), and "transcarotid artery revascularization" (TCAR). Areas covered included (i) improvements in best medical treatment (BMT) for patients with AsxCS and declining stroke risk, (ii) technological advances in surgical/endovascular skills/techniques and outcomes, (iii) risk factors, clinical/imaging characteristics and risk prediction models for the identification of high-risk AsxCS patient subgroups, and (iv) the association between cognitive dysfunction and AsxCS. RESULTS: BMT is essential for all patients with AsxCS, regardless of whether they will eventually be offered CEA, CAS, or TCAR. Specific patient subgroups at high risk for stroke despite BMT should be considered for a carotid revascularization procedure. These patients include those with severe (≥80%) AsxCS, transcranial Doppler-detected microemboli, plaque echolucency on Duplex ultrasound examination, silent infarcts on brain computed tomography or magnetic resonance angiography scans, decreased cerebrovascular reserve, increased size of juxtaluminal hypoechoic area, AsxCS progression, carotid plaque ulceration, and intraplaque hemorrhage. Treatment of patients with AsxCS should be individualized, taking into consideration individual patient preferences and needs, clinical and imaging characteristics, and cultural, ethnic, and social factors. Solid evidence supporting or refuting an association between AsxCS and cognitive dysfunction is lacking. CONCLUSIONS: The optimal management of patients with AsxCS should include BMT for all individuals and a prophylactic carotid revascularization procedure (CEA, CAS, or TCAR) for some asymptomatic patient subgroups, additionally taking into consideration individual patient needs and preference, clinical and imaging characteristics, social and cultural factors, and the available stroke risk prediction models. Future studies should investigate the association between AsxCS with cognitive function and the role of carotid revascularization procedures in the progression or reversal of cognitive dysfunction.

Polygenic Risk Score for Cardiovascular Diseases in Artificial Intelligence Paradigm: A Review.

Cardiovascular disease (CVD) related mortality and morbidity heavily strain society. The relationship between external risk factors and our genetics have not been well established. It is widely acknowledged that environmental influence and individual behaviours play a significant role in CVD vulnerability, leading to the development of polygenic risk scores (PRS). We employed the PRISMA search method to locate pertinent research and literature to extensively review artificial intelligence (AI)-based PRS models for CVD risk prediction. Furthermore, we analyzed and compared conventional vs. AI-based solutions for PRS. We summarized the recent advances in our understanding of the use of AI-based PRS for risk prediction of CVD. Our study proposes three hypotheses: i) Multiple genetic variations and risk factors can be incorporated into AI-based PRS to improve the accuracy of CVD risk predicting. ii) AI-based PRS for CVD circumvents the drawbacks of conventional PRS calculators by incorporating a larger variety of genetic and non-genetic components, allowing for more precise and individualised risk estimations. iii) Using AI approaches, it is possible to significantly reduce the dimensionality of huge genomic datasets, resulting in more accurate and effective disease risk prediction models. Our study highlighted that the AI-PRS model outperformed traditional PRS calculators in predicting CVD risk. Furthermore, using AI-based methods to calculate PRS may increase the precision of risk predictions for CVD and have significant ramifications for individualized prevention and treatment plans.

A Pharmaceutical Paradigm for Cardiovascular Composite Risk Assessment Using Novel Radiogenomics Risk Predictors in Precision Explainable Artificial Intelligence Framework: Clinical Trial Tool.

BACKGROUND: Cardiovascular disease (CVD) is challenging to diagnose and treat since symptoms appear late during the progression of atherosclerosis. Conventional risk factors alone are not always sufficient to properly categorize at-risk patients, and clinical risk scores are inadequate in predicting cardiac events. Integrating genomic-based biomarkers (GBBM) found in plasma/serum samples with novel non-invasive radiomics-based biomarkers (RBBM) such as plaque area, plaque burden, and maximum plaque height can improve composite CVD risk prediction in the pharmaceutical paradigm. These biomarkers consider several pathways involved in the pathophysiology of atherosclerosis disease leading to CVD. OBJECTIVE: This review proposes two hypotheses: (i) The composite biomarkers are strongly correlated and can be used to detect the severity of CVD/Stroke precisely, and (ii) an explainable artificial intelligence (XAI)-based composite risk CVD/Stroke model with survival analysis using deep learning (DL) can predict in preventive, precision, and personalized (aiP3) framework benefiting the pharmaceutical paradigm. METHOD: The PRISMA search technique resulted in 214 studies assessing composite biomarkers using radiogenomics for CVD/Stroke. The study presents a XAI model using AtheroEdgeTM 4.0 to determine the risk of CVD/Stroke in the pharmaceutical framework using the radiogenomics biomarkers. CONCLUSIONS: Our observations suggest that the composite CVD risk biomarkers using radiogenomics provide a new dimension to CVD/Stroke risk assessment. The proposed review suggests a unique, unbiased, and XAI model based on AtheroEdgeTM 4.0 that can predict the composite risk of CVD/Stroke using radiogenomics in the pharmaceutical paradigm.

Stroke risk management in carotid atherosclerotic disease: A Clinical Consensus Statement of the ESC Council on Stroke and the ESC Working Group on Aorta and Peripheral Vascular Diseases.

Carotid atherosclerotic disease continues to be an important cause of stroke, often disabling or fatal. Such strokes could be largely prevented through optimal medical therapy and carotid revascularization. Advancements in discovery research and imaging along with evidence from recent pharmacology and interventional clinical trials and registries and the progress in acute stroke management have markedly expanded knowledge base for clinical decisions in carotid stenosis. Nevertheless, there is variability in carotid-related stroke prevention and management strategies across medical specialities. Optimal patient care can be achieved by (1) establishing a unified knowledge foundation and (2) fostering multi-specialty collaborative guidelines. The emergent Neuro-Vascular Team concept, mirroring the multi-disciplinary Heart Team, embraces diverse specializations, tailores personalized, stratified medicine approaches to individual patient needs, and integrates innovative imaging and risk-assessment biomarkers. Proposed approach integrates collaboration of multiple specialists central to carotid artery stenosis management such as neurology, stroke medicine, cardiology, angiology, ophthalmology, vascular surgery, endovascular interventions, neuroradiology and neurosurgery. Moreover, patient education regarding current treatment options, their risks and advantages, is pivotal, promting patient's active role in clinical care decisions. This enables optimization of interventions ranging from lifestyle modification, carotid revascularization by stenting or endarterectomy, as well as pharmacological management encompassing statins, novel lipid-lowering and antithrombotic strategies and targeting inflammation and vascular dysfunction. This consensus document provides a harmonized multi-specialty approach to multimorbidity prevention in carotid stenosis patients, based on comprehensive knowledge review, pinpointing research gaps in an evidence-based medicine approach. It aims to be a foundational tool for interdisciplinary collaboration and prioritized patient-centric decision-making.

Cardiovascular disease/stroke risk stratification in deep learning framework: a review.

The global mortality rate is known to be the highest due to cardiovascular disease (CVD). Thus, preventive, and early CVD risk identification in a non-invasive manner is vital as healthcare cost is increasing day by day. Conventional methods for risk prediction of CVD lack robustness due to the non-linear relationship between risk factors and cardiovascular events in multi-ethnic cohorts. Few recently proposed machine learning-based risk stratification reviews without deep learning (DL) integration. The proposed study focuses on CVD risk stratification by the use of techniques mainly solo deep learning (SDL) and hybrid deep learning (HDL). Using a PRISMA model, 286 DL-based CVD studies were selected and analyzed. The databases included were Science Direct, IEEE Xplore, PubMed, and Google Scholar. This review is focused on different SDL and HDL architectures, their characteristics, applications, scientific and clinical validation, along with plaque tissue characterization for CVD/stroke risk stratification. Since signal processing methods are also crucial, the study further briefly presented Electrocardiogram (ECG)-based solutions. Finally, the study presented the risk due to bias in AI systems. The risk of bias tools used were (I) ranking method (RBS), (II) region-based map (RBM), (III) radial bias area (RBA), (IV) prediction model risk of bias assessment tool (PROBAST), and (V) risk of bias in non-randomized studies-of interventions (ROBINS-I). The surrogate carotid ultrasound image was mostly used in the UNet-based DL framework for arterial wall segmentation. Ground truth (GT) selection is vital for reducing the risk of bias (RoB) for CVD risk stratification. It was observed that the convolutional neural network (CNN) algorithms were widely used since the feature extraction process was automated. The ensemble-based DL techniques for risk stratification in CVD are likely to supersede the SDL and HDL paradigms. Due to the reliability, high accuracy, and faster execution on dedicated hardware, these DL methods for CVD risk assessment are powerful and promising. The risk of bias in DL methods can be best reduced by considering multicentre data collection and clinical evaluation.