The pulmonary valve (PV) is the least imaged among the heart valves. However, pulmonary regurgitation (PR) and pulmonary stenosis (PS) can occur in a variety of patients ranging from fetuses, newborns (e.g., tetralogy of Fallot) to adults (e.g., endocarditis, carcinoid syndrome, complications of operated tetralogy of Fallot). Due to their complexity, PR and PS are studied using multimodality imaging to assess their mechanism, severity, and hemodynamic consequences. Multimodality imaging is crucial to plan the correct management and to follow up patients with pulmonary valvulopathy. Echocardiography remains the first line methodology to assess patients with PR and PS, but the information obtained with this technique are often integrated with cardiac magnetic resonance (CMR) and computed tomography (CT). This state-of-the-art review aims to provide an updated overview of the usefulness, strengths, and limits of multimodality imaging in patients with PR and PS.

In the last decade, artificial intelligence (AI) has influenced the field of cardiac computed tomography (CT), with its scope further enhanced by advanced methodologies such as machine learning (ML) and deep learning (DL). The AI‐driven techniques leverage large datasets to develop and train algorithms capable of making precise evaluations and predictions. The realm of cardiac CT is expanding day by day and multiple tools are offered to answer different questions. Coronary artery calcium score (CACS) and CT angiography (CTA) provide high‐resolution images that facilitate the detailed anatomical evaluation of coronary plaque burden. New tools such as myocardial CT perfusion (CTP) and fractional flow reserve (FFR_CT) have been developed to add a functional evaluation of the stenosis. Moreover, epicardial adipose tissue (EAT) is gaining interest as its role in coronary artery plaque development has been deepened. Seen the great added value of these tools, the demand for new exams has increased such as the burden on imagers. Due to its ability to fast compute multiple data, AI can be helpful in both the acquisition and post‐processing phases. AI can possibly reduce radiation dose, increase image quality, and shorten image analysis time. Moreover, different types of data can be used for risk assessment and patient risk stratification. Recently, the focus of the scientific community on AI has led to numerous studies, especially on CACS and CTA. This narrative review concentrates on AI's role in the post‐processing of CACS, CTA, FFR_CT, CTP, and EAT, discussing both current capabilities and future directions in the field of cardiac imaging.

Background: Our aim is to evaluate the possible persistence of lung parenchyma alterations, in patients who have recovered from Covid-19. Design and methods: We enrolled a cohort of 115 patients affected by Covid-19, who performed a chest CT scan in the Emergency Department and a chest CT 18 months after hospital discharge. We performed a comparison between chest CT scan 18 months after discharge and spirometric data of patients enrolled. We obtained quantitative scores related to well-aerated parenchyma, interstitial lung disease and parenchymal consolidation. A radiologist recorded the characteristics indicated by the Fleischner Society and “fibrotic like” changes, expressed through a CT severity score ranging from 0 (no involvement) to 25 (maximum involvement). Results: 115 patients (78 men, 37 women; mean age 60.15 years old ±12.52). On quantitative analysis, after 18 months, the volume of normal ventilated parenchyma was significantly increased (16.34 points on average ±14.54, p<0.0001). Groundglass opacities and consolidation values tend to decrease (-9.80 and -6.67 points, p<0.0001). On semiquantitative analysis, pneumonia extension, reactive lymph nodes and crazy paving reached statistical significance (p<0.0001). The severity score decreased by 2.77 points on average (SD 4.96; p<0.0001). There were not statistically significant changes on “fibrotic-like” changes correlated with level of treatment and there was not a statistically significant correlation between CT lung score and spirometric results obtained 18 months after discharge. Conclusions: Patients recovered from Covid-19 seem to have an improvement of ventilated parenchyma and “fibrotic-like” alterations. The level of treatment does not appear to influence fibrotic changes.

The advent of immune checkpoint inhibitors (ICIs) has revolutionized cancer treatment, significantly improving patient outcomes across multiple malignancies. Nonetheless, these therapies are associated with immune-related adverse effects, including cardiotoxicity, which remains a critical concern. This review provides a comprehensive analysis of ICI-related cardiotoxicity, encompassing its pathophysiological mechanisms, risk factors, diagnostic modalities, and management strategies. The onset of cardiotoxicity varies widely, ranging from acute myocarditis to long-term cardiovascular complications. Early identification through clinical assessment, biomarkers, and advanced imaging techniques is crucial for timely intervention. Management strategies include high-dose corticosteroids, other immunosuppressive agents, and supportive therapies, with a focus on balancing oncologic efficacy and cardiovascular safety. Additionally, rechallenging patients with ICIs following cardiotoxic events remains a complex clinical decision requiring multidisciplinary evaluation. As immunotherapy indications expand to include high-risk populations in a curative setting too, optimizing screening, prevention, and treatment strategies is essential to mitigate cardiovascular risks. A deep understanding of the molecular and clinical aspects of ICI-related cardiotoxicity will enhance patient safety and therapeutic decision-making, underscoring the need for ongoing research in this rapidly evolving field.

Heart failure (HF) is a chronic and progressive disease that often progresses to an advanced stage where conventional therapy is insufficient to relieve patients' symptoms. Despite the availability of advanced therapies such as mechanical circulatory support or heart transplantation, the complexity of defining advanced HF, which requires multiple parameters and multimodality assessment, often leads to delays in referral to dedicated specialists with the result of a worsening prognosis. In this review, we aim to explore the role of cardiac magnetic resonance (CMR) in advanced HF by showing how CMR is useful at every step in managing these patients: from diagnosis to prognostic stratification, hemodynamic evaluation, follow‐up and advanced therapies such as heart transplantation. The technical challenges of scanning advanced HF patients, which often require troubleshooting of intracardiac devices and dedicated scans, will be also discussed.

Coronary artery disease is still a major cause of death and morbidity worldwide. In the setting of chronic coronary disease, demonstration of inducible ischemia is mandatory to address treatment. Consequently, scientific and technological efforts were made in response to the request for non-invasive diagnostic tools with better sensitivity and specificity. To date, clinicians have at their disposal a wide range of stress-imaging techniques. Among others, stress cardiac magnetic resonance (S-CMR) and computed tomography perfusion (CTP) techniques both demonstrated their diagnostic efficacy and prognostic value in clinical trials when compared to other non-invasive ischemia-assessing techniques and invasive fractional flow reserve measurement techniques. Standardized protocols for both S-CMR and CTP usually imply the administration of vasodilator agents to induce hyperemia and contrast agents to depict perfusion defects. However, both methods have their own limitations, meaning that optimizing their performance still requires a patient-tailored approach. This review focuses on the characteristics, drawbacks, and future perspectives of these two techniques.