The concept of vulnerable carotid plaques is pivotal in understanding the pathophysiology of ischemic stroke secondary to large-artery atherosclerosis. In macroscopic evaluation, vulnerable plaques are characterized by one or more of the following features: microcalcification; neovascularization; lipid-rich necrotic cores (LRNCs); intraplaque hemorrhage (IPH); thin fibrous caps; plaque surface ulceration; huge dimensions, suggesting stenosis; and plaque rupture. Recognizing these macroscopic characteristics is crucial for estimating the risk of cerebrovascular events, also in the case of non-significant (less than 50%) stenosis. Inflammatory biomarkers, such as cytokines and adhesion molecules, lipid-related markers like oxidized low-density lipoprotein (LDL), and proteolytic enzymes capable of degrading extracellular matrix components are among the key molecules that are scrutinized for their associative roles in plaque instability. Through their quantification and evaluation, these biomarkers reveal intricate molecular cross-talk governing plaque inflammation, rupture potential, and thrombogenicity. The current evidence demonstrates that plaque vulnerability phenotypes are multiple and heterogeneous and are associated with many highly complex molecular pathways that determine the activation of an immune-mediated cascade that culminates in thromboinflammation. This narrative review provides a comprehensive analysis of the current knowledge on molecular biomarkers expressed by symptomatic carotid plaques. It explores the association of these biomarkers with the structural and compositional attributes that characterize vulnerable plaques.

The correct recognition of the etiology of ischemic stroke (IS) allows tempestive interventions in therapy with the aim of treating the cause and preventing a new cerebral ischemic event. Nevertheless, the identification of the cause is often challenging and is based on clinical features and data obtained by imaging techniques and other diagnostic exams. TOAST classification system describes the different etiologies of ischemic stroke and includes five subtypes: LAAS (large-artery atherosclerosis), CEI (cardio embolism), SVD (small vessel disease), ODE (stroke of other determined etiology), and UDE (stroke of undetermined etiology). AI models, providing computational methodologies for quantitative and objective evaluations, seem to increase the sensitivity of main IS causes, such as tomographic diagnosis of carotid stenosis, electrocardiographic recognition of atrial fibrillation, and identification of small vessel disease in magnetic resonance images. The aim of this review is to provide overall knowledge about the most effective AI models used in the differential diagnosis of ischemic stroke etiology according to the TOAST classification. According to our results, AI has proven to be a useful tool for identifying predictive factors capable of subtyping acute stroke patients in large heterogeneous populations and, in particular, clarifying the etiology of UDE IS especially detecting cardioembolic sources.

Peripheral artery disease (PAD) is a clinical manifestation of atherosclerotic disease with a large-scale impact on the economy and global health. Despite the role played by platelets in the process of atherogenesis being well recognized, evidence has been increasing on the contribution of the coagulation system to the atherosclerosis formation and PAD development, with important repercussions for the therapeutic approach. Histopathological analysis and some clinical studies conducted on atherosclerotic plaques testify to the existence of different types of plaques. Likely, the role of coagulation in each specific type of plaque can be an important determinant in the histopathological composition of atherosclerosis and in its future stability. In this review, we analyze the molecular contribution of inflammation and the coagulation system on PAD pathogenesis, focusing on molecular similarities and differences between atherogenesis in PAD and coronary artery disease (CAD) and discussing the possible implications for current therapeutic strategies and future perspectives accounting for molecular inflammatory and coagulation targets. Understanding the role of cross-talking between coagulation and inflammation in atherosclerosis genesis and progression could help in choosing the right patients for future dual pathway inhibition strategies, where an antiplatelet agent is combined with an anticoagulant, whose role, despite pathophysiological premises and trials’ results, is still under debate.

Direct oral anticoagulants (DOACs) have emerged as a preferred alternative to vitamin K antagonists (VKAs) for the prevention and treatment of thromboembolic disorders, offering improved safety, predictable pharmacokinetics, and ease of administration. Despite these advantages, their use in complex clinical scenarios presents significant challenges that necessitate individualized therapeutic strategies. This comprehensive review explores the efficacy, safety, and limitations of DOAC therapy in special populations, including patients with renal or hepatic impairment, obesity, cancer-associated thrombosis, and antiphospholipid syndrome. Additionally, we examine their role in uncommon thrombotic conditions such as superficial venous thrombosis, embolic stroke of undetermined source, upper extremity vein thrombosis, inferior vena cava thrombosis, pelvic vein thrombosis, and cerebral vein thrombosis. The pharmacokinetic variability of DOACs in renal and hepatic dysfunction requires caution to balance the bleeding and thrombotic risks. In obesity, altered drug distribution and metabolism raise concerns regarding appropriate dosing and therapeutic efficacy. Cancer-associated thrombosis presents a complex interplay of prothrombotic mechanisms, necessitating careful selection of anticoagulant therapy. Furthermore, the use of DOACs in antiphospholipid syndrome remains controversial due to concerns about recurrent thrombotic events. Finally, in some unusual scenarios like inferior vena cava, pelvic vein, and cerebral vein thrombosis, the use of DOACs has scarce evidence. This review aims to guide clinicians in optimizing anticoagulation management in challenging patient populations by synthesizing current evidence and providing practical recommendations.

Identifying atherosclerotic disease is the mainstay for the correct diagnosis of the large artery atherosclerosis ischemic stroke subtype and for choosing the right therapeutic strategy in acute ischemic stroke. Classification into symptomatic and asymptomatic plaque and estimation of the cardiovascular risk are essential to select patients eligible for pharmacological and/or surgical therapy in order to prevent future cerebral ischemic events. The difficulties in a “vulnerability” definition and the methodical issues concerning its detectability and quantification are still subjects of debate. Non-invasive imaging studies commonly used to detect arterial plaque are computed tomographic angiography, magnetic resonance imaging, and ultrasound. Characterization of a carotid plaque type using the abovementioned imaging modalities represents the basis for carotid atherosclerosis management. Classification into symptomatic and asymptomatic plaque and estimation of the cardiovascular risk are essential to select patients eligible for pharmacological and/or surgical therapy in order to prevent future cerebral ischemic events. In this setting, artificial intelligence (AI) can offer suggestive solutions for tissue characterization and classification concerning carotid artery plaque imaging by analyzing complex data and using automated algorithms to obtain a final output. The aim of this review is to provide overall knowledge about the role of AI models applied to non-invasive imaging studies for the detection of symptomatic and vulnerable carotid plaques.