Coronary Artery Calcification: Current Concepts and Clinical Implications.

Coronary artery calcification (CAC) accompanies the development of advanced atherosclerosis. Its role in atherosclerosis holds great interest because the presence and burden of coronary calcification provide direct evidence of the presence and extent of coronary artery disease; furthermore, CAC predicts future events independently of concomitant conventional cardiovascular risk factors and to a greater extent than any other noninvasive biomarker of this disease. Nevertheless, the relationship between CAC and the susceptibility of a plaque to provoke a thrombotic event remains incompletely understood. This review summarizes the current understanding and literature on CAC. It outlines the pathophysiology of CAC and reviews laboratory, histopathological, and genetic studies, as well as imaging findings, to characterize different types of calcification and to elucidate their implications. Some patterns of calcification such as microcalcification portend increased risk of rupture and cardiovascular events and may improve prognosis assessment noninvasively. However, contemporary computed tomography cannot assess early microcalcification. Limited spatial resolution and blooming artifacts may hinder estimation of degree of coronary artery stenosis. Technical advances such as photon counting detectors and combination with nuclear approaches (eg, NaF imaging) promise to improve the performance of cardiac computed tomography. These innovations may speed achieving the ultimate goal of providing noninvasively specific and clinically actionable information.

The Role of Artificial Intelligence in Cardiac Imaging.

Artificial intelligence (AI) is having a significant impact in medical imaging, advancing almost every aspect of the field, from image acquisition and postprocessing to automated image analysis with outreach toward supporting decision making. Noninvasive cardiac imaging is one of the main and most exciting fields for AI development. The aim of this review is to describe the main applications of AI in cardiac imaging, including CT and MR imaging, and provide an overview of recent advancements and available clinical applications that can improve clinical workflow, disease detection, and prognostication in cardiac disease.

Non-invasive coronary imaging in elderly population.

Age is a non-modifiable cardiovascular risk factor, which leads to development and progression of chronic conditions, such as coronary artery disease, by promoting atherosclerosis. Aging is responsible for morphological structure changes of the coronary arteries and specific atherosclerotic plaque features, which can be studied with non-invasive coronary imaging techniques, particularly coronary CT angiography. The aim of this review is to evaluate current knowledge on this technique applied to the elderly population, and to describe CAD manifestation and plaque features of coronary atherosclerosis in this particular set of patients. We also discuss the clinical implication of frailty assessment and customization of diagnostic strategies in order to shift the approach from disease-centered to patient-centered care.

Metabolomic Profiles on Antiblastic Cardiotoxicity: New Perspectives for Early Diagnosis and Cardioprotection.

Antiblastic drugs-induced cardiomyopathy remains a relevant cause of morbidity and mortality, during and after chemotherapy, despite the progression in protective therapy against cardiovascular diseases and myocardial function. In the last few decades, many groups of researchers have focused their attention on studying the metabolic profile, first in animals, and, subsequently, in humans, looking for profiles which could be able to predict drug-induced cardiotoxicity and cardiovascular damage. In clinical practice, patients identified as being at risk of developing cardiotoxicity undergo a close follow-up and more tailored therapies. Injury to the heart can be a consequence of both new targeted therapies, such as tyrosine kinase inhibitors, and conventional chemotherapeutic agents, such as anthracyclines. This review aims to describe all of the studies carried on this topic of growing interest.

Non-invasive coronary imaging in patients with COVID-19: A narrative review.

SARS-CoV-2 infection, responsible for COVID-19 outbreak, can cause cardiac complications, worsening outcome and prognosis. In particular, it can exacerbate any underlying cardiovascular condition, leading to atherosclerosis and increased plaque vulnerability, which may cause acute coronary syndrome. We review current knowledge on the mechanisms by which SARS-CoV-2 can trigger endothelial/myocardial damage and cause plaque formation, instability and deterioration. The aim of this review is to evaluate current non-invasive diagnostic techniques for coronary arteries evaluation in COVID-19 patients, such as coronary CT angiography and atherosclerotic plaque imaging, and their clinical implications. We also discuss the role of artificial intelligence, deep learning and radiomics in the context of coronary imaging in COVID-19 patients.

Quantitative and qualitative features of carotid and coronary atherosclerotic plaque among men and women.

Cardiovascular diseases (CVDs), particularly ischemic heart disease (IHD) and stroke, present epidemiologically in a different way among sexes. The reasons of these sex-based differences should be delved into sex-specific cardiovascular (CV) risk factors and different mechanisms of atherosclerotic progression. Imaging techniques of both carotid and coronary atherosclerotic plaques represent a tool to demonstrate sex-related features which might be used to further and better assess CV risk of male and female population. The aim of this review is to evaluate current knowledge on sex-specific qualitative and quantitative plaque features of coronary and carotid atherosclerosis. We also discuss the clinical implication of a sex-based plaque phenotype, evaluated with non-invasive imaging techniques, such as CT-angiography and MRI-angiography, to stratify CV risk.