Pulmonary congestion is a key determinant of heart failure, but for a long time it has been an elusive target for the clinical cardiologist in the pre-B-line era, despite research efforts of Carlo Giuntini, a pneumologist who attempted the quantification of lung water in the seventies with too insensitive chest X-ray lung water score, too cumbersome nuclear medicine, and too complex invasive thermodilution techniques. Daniel Lichtenstein, is a French intensivist who first discovered lung ultrasound as a sign of extravascular lung water in 1997. B-lines (also known as ultrasound lung comets) detectable by lung ultrasound arise from the pleural line, extend towards the edge of the screen, and move synchronously with respiration. In cardiology, B-lines were introduced in 2004 and are now the dominant technique for research applications and clinical purposes. B-lines showed a prognostic value in several clinical scenarios, largely independent and additive over echocardiographic predictors such as ejection fraction. The methodology became user-friendly in the last years, with a reduction of the scanning sites from the original 28 to a simplified 4-site scan now extracting information on lung water in < 1 minute. More recently, B-lines were also studied during physical and pharmacological stress. Signs of pulmonary congestion are found during stress in 1 out of 3 all-comers with normal findings at rest. Artificial intelligence applied to ultrasound and clinical data allows for the detection of B lines, their quantification, and the assessment of their nature. The B-lines phenotype can cluster around different endotypes: dry (in systemic sclerosis and lung interstitial fibrosis); wet (water); sterile (as in cardiogenic edema); infective (as in COVID-19 and interstitial pneumonia); right heart-sided (as in pulmonary arterial hypertension); left-heart sided (as in heart failure or valvular heart disease). Artificial intelligence B-lines and pocket-size insonation of the B-lines-driven decongestion therapy are now on the horizon.

Ischemic heart disease (IHD) is a major global health issue, frequently resulting in myocardial infarction and ischemic cardiomyopathy. Prompt and precise diagnosis is essential to avert complications such as heart failure and sudden cardiac death. Although invasive coronary angiography remains the gold standard for high-risk patients, noninvasive multimodality imaging is becoming more prevalent for those at low-to-intermediate risk. This review evaluated the current state of multimodality imaging in IHD, including echocardiography, nuclear cardiology, cardiac magnetic resonance imaging (MRI), computed tomography (CT) angiography, and invasive coronary angiography. Each modality has distinct strengths and limitations, and their complementary use provides a comprehensive assessment of cardiac health. Integrating artificial intelligence (AI) into imaging workflows holds promise for enhancing diagnostic accuracy and efficiency. AI algorithms can optimize image acquisition, processing, and interpretation of complex imaging data. Emerging technologies like 4D flow MRI, molecular imaging, and hybrid systems [e.g., positron emission tomography (PET)/MRI, PET/CT] integrate anatomical, functional, and molecular data, providing comprehensive insights into cardiac pathology and potentially revolutionizing the management of IHD. This review also explored the clinical applications and impact of multimodality imaging on patient outcomes, emphasizing its role in improving diagnostic precision and guiding therapeutic decisions. Future directions include AI-driven decision support systems and personalized medicine approaches. Addressing regulatory and ethical challenges, such as data privacy and algorithm transparency, is crucial for the broader adoption of these advanced technologies. This review highlighted the transformative potential of AI-enhanced multimodality imaging in improving the diagnosis and management of IHD.

Pregnancy complications such as pre-eclampsia, gestational diabetes, and intrauterine growth restriction (IUGR) not only present immediate risks to maternal and fetal health but also have long-term implications for the cardiovascular health of offspring. Emerging evidence suggests that these complications may induce epigenetic changes, which in turn predispose offspring to cardiovascular diseases (CVDs) later in life. Epigenetic modifications, including DNA methylation, histone modifications, and non-coding RNA regulation, play crucial roles in fetal development by influencing gene expression without altering the DNA sequence. Aberrant DNA methylation patterns have been observed in offspring exposed to adverse intrauterine environments, affecting genes that regulate blood pressure, lipid metabolism, and inflammation, key factors in CVDs development. Similarly, histone modifications linked to pregnancy complications can disrupt the expression of genes involved in vascular function, contributing to increased cardiovascular risk. Additionally, dysregulation of microRNAs in response to complications like gestational diabetes may influence pathways related to insulin signaling and atherosclerosis. This review synthesizes current knowledge on the epigenetic mechanisms by which pregnancy complications increase CVDs risk in offspring, highlighting potential avenues for early intervention and therapeutic strategies. Understanding these mechanisms could lead to the development of targeted interventions during pregnancy, potentially reducing the intergenerational transmission of cardiovascular risk and improving long-term health outcomes for both mothers and their children.

Exposure to ionizing radiation has recognized detrimental cancer and non-cancer health effects. These effects are now well-proven not only for high doses > 1,000 millisieverts (mSv) associated with head radiotherapy but also for moderate (100–1,000 mSv) and even low (< 100 mSv) doses, of interest for professionally exposed cardiologists. The head of interventional cardiologists is highly exposed to ionizing radiation, with possible damage to the eye and brain. Unprotected interventional cardiologists experience head radiation doses up to ten times greater than chest doses below lead aprons, with marked exposure to the left hemisphere of the brain reaching up to 2 Sv—equivalent to 10,000 chest X-rays over a professional lifetime. This narrative review aims to provide an overview of the background of radioprotection, the biological mechanisms involved, and the epidemiological evidence regarding the health effects of head exposure to ionizing radiation in invasive cardiologists. These health effects include cataracts, brain cancer, cerebrovascular diseases, neurodegeneration, and mood disorders. The evidence gathered from other exposed populations, which experienced similar eye and brain doses, has also been reviewed. This is important because the doses, risks, and effects are consistent in cases of repeated exposures, which occur more frequently for patients, and in situations involving chronic low doses, as seen with interventional cardiologists. Despite these risks, effective protective measures—such as suspended lead ceilings, curtains, and specialized eyewear—can reduce radiation exposure to near-zero levels. In some fields, like interventional cardiac electrophysiology, a groundbreaking near-zero radiation approach using non-fluoroscopic methods has been created, eliminating radiation exposure and alleviating orthopedic stress and operational discomfort. The race to zero radiation in interventional cardiology is ongoing.