Acute aortic syndromes are life-threatening conditions with high morbidity and mortality. The principal pathological feature is acute wall damage with possible evolution towards aortic rupture. Accurate and timely diagnosis is mandatory to avoid catastrophic consequences. Indeed, misdiagnosis with other conditions mimicking acute aortic syndromes is associated with premature death. In this view, cardiovascular imaging is necessary for the correct diagnosis and management. Echocardiography, computed tomography, magnetic resonance imaging, and aortography allow for diagnosis, guarantee immediate treatment, and detect associated complications. Multimodality imaging is essential in the diagnostic work-up to confirm or rule out acute aortic syndromes. The aim of this review is to highlight the contemporary evidence on the role of single cardiovascular imaging techniques and multimodality imaging in the diagnosis and management of acute aortic syndromes.

Cardiac magnetic resonance (CMR) imaging has an important emerging role in the evaluation and management of patients with cardiomyopathies, especially in patients with dilated cardiomyopathy (DCM). It allows a non-invasive characterization of myocardial tissue, thus assisting early diagnosis and precise phenotyping of the different cardiomyopathies, which is an essential step for early and individualized treatment of patients. Using imaging techniques such as late gadolinium enhancement (LGE), standard and advanced quantification as well as quantitative mapping parameters, CMR-based tissue characterization is useful in the differential diagnosis of DCM and risk stratification. The purpose of this article is to review the utility of CMR in the diagnosis and management of idiopathic DCM, as well as risk prediction and prognosis based on standard and emerging CMR contrast and non-contrast techniques. This is consistent with current evidence and guidance moving beyond traditional prognostic markers such as ejection fraction.

Cardiomyopathies (CMPs) are a group of myocardial disorders that are characterized by structural and functional abnormalities of the heart muscle. These abnormalities occur in the absence of coronary artery disease (CAD), hypertension, valvular disease, and congenital heart disease. CMPs are an increasingly important topic in the field of cardiovascular diseases due to the complexity of their diagnosis and management. In 2023, the ESC guidelines on cardiomyopathies were first published, marking significant progress in the field. The growth of techniques such as cardiac magnetic resonance imaging (CMR) and genetics has been fueled by the development of multimodal imaging approaches. For the diagnosis of CMPs, a multimodal imaging approach, including CMR, is recommended. CMR has become the standard for non-invasive analysis of cardiac morphology and myocardial function. This document provides an overview of the role of CMR in CMPs, with a focus on tissue mapping. CMR enables the characterization of myocardial tissues and the assessment of cardiac functions. CMR sequences and techniques, such as late gadolinium enhancement (LGE) and parametric mapping, provide detailed information on tissue composition, fibrosis, edema, and myocardial perfusion. These techniques offer valuable insights for early diagnosis, prognostic evaluation, and therapeutic guidance of CMPs. The use of quantitative CMR markers enables personalized treatment plans, improving overall patient outcomes. This review aims to serve as a guide for the use of these new tools in clinical practice.

Hypertrophic cardiomyopathy (HCM) is often associated with left ventricular outflow tract (LVOT) obstruction, which affects a substantial proportion of patients. This obstruction results from a range of anatomical abnormalities involving both the valvular and subvalvular structures. Pharmacological therapies play a pivotal role in the management of LVOT obstruction, with a range of drug classes exhibiting distinct mechanisms of action. Beta-blockers, including atenolol and nadolol, are considered the first-line treatment due to their ability to reduce heart rate and myocardial contractility and enhance diastolic filling. Non-dihydropyridine calcium channel blockers, such as verapamil and diltiazem, are utilized as second-line agents when beta-blockers are ineffective or contraindicated. Disopyramid, a Class 1A antiarrhythmic agent, is employed for patients who do not respond to initial therapeutic interventions and can reduce LVOT gradients. Recent advancements in cardiac myosin modulators, such as Mavacamten and Aficamten, offer targeted therapies by modulating myosin–actin interactions to reduce LVOT gradients and improve symptoms, with promising results from clinical trials. Although gene therapy is still in its nascent stages, it has the potential to address the genetic basis of HCM by employing techniques such as genome editing, gene replacement, and the modulation of signaling pathways. For patients exhibiting severe symptoms or demonstrating unresponsiveness to medical treatment, invasive therapies, such as septal reduction therapy and alcohol septal ablation, are considered. Ultimately, the treatment and prevention of atrial fibrillation and sudden cardiac death are two key points of HCM management in both obstructive and non-obstructive forms. This review aims to provide an overview of current pharmacological and invasive strategies, as well as emerging therapies, in the management of HCM.

Cardiac amyloidosis (CA) is a cardiac storage disease caused by the progressive extracellular deposition of misfolded proteins in the myocardium. Despite the increasing interest in this pathology, it remains an underdiagnosed condition. Non-invasive diagnostic techniques play a central role in the suspicion and detection of CA, also thanks to the continuous scientific and technological advances in these tools. The 12-lead electrocardiography is an inexpensive and reproducible test with a diagnostic accuracy that, in some cases, exceeds that of imaging techniques, as recent studies have shown. Echocardiography is the first-line imaging modality, although none of its parameters are pathognomonic. According to the 2023 ESC Guidelines, a left ventricular wall thickness ≥ 12 mm is mandatory for the suspicion of CA, making this technique crucial. Cardiac magnetic resonance provides high-resolution images associated with tissue characterization. The use of contrast and non-contrast sequences enhances the diagnostic power of this imaging modality. Nuclear imaging techniques, including bone scintigraphy and positron emission tomography, allow the detection of amyloid deposition in the heart, and their role is also central in assessing the prognosis and response to therapy. The role of computed tomography was recently evaluated by several studies, above in population affected by aortic stenosis undergoing transcatheter aortic valve replacement, with promising results. Finally, machine learning and artificial intelligence-derived algorithms are gaining ground in this scenario and provide the basis for future research. Understanding the new insights into non-invasive diagnostic techniques is critical to better diagnose and manage patients with CA and improve their survival.

Hypertrophic cardiomyopathy (HCM) is a condition characterized by left ventricular hypertrophy, with physiopathological remodeling that predisposes patients to atrial fibrillation (AF). The electrocardiogram is a basic diagnostic tool for evaluating heart electrical activity. Key electrocardiographic features that correlate with AF onset are P-wave duration, P-wave dispersion, and electromechanical delay in left atrium (LA). Clinical markers, including age, body mass index, New York Heart Association functional class, and heart failure symptoms, are also strong predictors of AF in HCM. Risk scores have been created using multiple variables to better predict AF development. Increasing knowledge of genetic subsets in HCM and cardiovascular pathology in general has provided novel insight in this context. Structural and mechanical LA remodeling, including fibrosis, altered LA function, and changes in atrial size, further contribute to AF risk prediction. Cardiovascular magnetic resonance (CMR) and echocardiographic measures provide accurate information about atrial structure and function. Machine learning models are increasingly being utilized to refine risk prediction, incorporating a wide range of variables. This review highlights the multifaceted approach required to understand and predict AF development in HCM. Such an approach is imperative to enhance prognostic accuracy and improve the quality of life of these patients. Further research is necessary to refine patient outcomes and develop customized management strategies for HCM-associated AF.