One of the leading causes of morbidity and mortality worldwide is coronary artery disease, a condition characterized by the narrowing of the artery due to plaque deposits. The standard of care for treating this disease is the introduction of a stent at the lesion site. This life-saving tubular device ensures vessel support, keeping the blood-flow path open so that the cardiac muscle receives its vital nutrients and oxygen supply. Several generations of stents have been iteratively developed towards improving patient outcomes and diminishing adverse side effects following the implanting procedure. Moving from bare-metal stents to drug-eluting stents, and recently reaching bioresorbable stents, this research field is under continuous development. To keep up with how stent technology has advanced in the past few decades, this paper reviews the evolution of these devices, focusing on how they can be further optimized towards creating an ideal vascular scaffold.

The concepts underlying hypertrophic cardiomyopathy (HCM) pathogenesis have evolved greatly over the last 60 years since the pioneering work of the British pathologist Donald Teare, presenting the autopsy findings of “asymmetric hypertrophy of the heart in young adults”. Advances in human genome analysis and cardiac imaging techniques have enriched our understanding of the complex architecture of the malady and shaped the way we perceive the illness continuum. Presently, HCM is acknowledged as “a disease of the sarcomere”, where the relationship between genotype and phenotype is not straightforward but subject to various genetic and nongenetic influences. The focus of this review is to discuss key aspects related to molecular mechanisms and imaging aspects that have prompted genotype–phenotype correlations, which will hopefully empower patient-tailored health interventions.

Several studies showed that right ventricular (RV) dysfunction is a powerful predictor in heart failure (HF). Advanced echocardiographic techniques such as speckle-tracking imaging and three-dimensional (3D) echocardiography proved to be accurate tools for RV assessment, but their clinical significance remains to be clarified. The aim of this study was to evaluate the role of two-dimensional (2D) RV strain and 3D ejection fraction (RVEF) in predicting adverse outcome in patients with non-ischemic dilated cardiomyopathy (DCM). We prospectively screened 81 patients with DCM and sinus rhythm, 50 of whom were enrolled and underwent comprehensive echocardiography, including RV strain and 3D RV volumetric assessment. Patients were followed for a composite endpoint of cardiac death, nonfatal cardiac arrest and acute worsening of HF requiring hospitalization. After a median follow-up of 16 months, 29 patients reached the primary endpoint. Patients with events had more impaired RV global longitudinal strain (− 10.5 ± 4.5% vs. − 14.3 ± 5.2%, p = 0.009), RV free wall longitudinal strain (− 12.9 ± 8.7% vs. − 17.5 ± 7.1%, p = 0.046) and 3D RVEF (38 ± 8% vs. 47 ± 9%, p = 0.001). By Cox proportional hazards multivariable analysis, RV global longitudinal strain and RVEF were independent predictors of outcome after adjustment for age and NYHA class. RVEF remained the only independent predictor of events after further correction for echocardiographic risk factors. By receiver-operating characteristic analysis, the optimal RVEF cut-off value for event prediction was 43.4% (area under the curve = 0.768, p = 0.001). Subjects with RVEF > 43.4% showed more favourable outcome compared to those with RVEF < 43.4% (log-rank test, p < 0.001). In conclusion, 3D RVEF is an independent predictor of major adverse cardiovascular events in patients with DCM.

Introduction: The inflammatory hypothesis of atherosclerosis is appealing in acute coronary syndromes, but the dynamics and precise role are not established.Objectives: The study investigates the levels of C reactive protein (CRP), interleukin 1b (IL-1b) and stromal-derived factor 1a (SDF-1a) at the time of acute myocardial infarction (AMI) and at 1 and 6 months afterwards, compared with a control group. Results: In the acute phase of AMI, CRP and SDF-1a were significantly higher, while IL-1b showed lower levels compared with controls. CRP positively correlated with coronary stenosis severity (rho ¼ 0.3, p¼.05) and negatively related with left ventricle ejection fraction (LVEF) at 1 month (rho¼ À0.43, p¼.05). IL-1b weakly correlated with the severity of coronary lesions (rho ¼0.29, p¼.02) and strongly with LVEF (rho¼ À0.8, p¼.05). SDF-1a, slightly correlated with LVEF at 1 month (rho ¼ 0.22, p¼.01) and with the severity of coronary atherosclerosis (rho¼ À0.41, p¼.003). Conclusions: CRP, IL-1b and SDF-1a have important dynamic in the first 6 months after AMI and CRP and SDF-1a levels correlated with the severity of coronary lesions and LVEF at 1 month after the acute ischaemic event.

Deep learning (DL)-based algorithms have demonstrated remarkable results in potentially improving the performance and the efficiency of healthcare applications. Since the data typically needs to leave the healthcare facility for performing model training and inference, e.g., in a cloud based solution, privacy concerns have been raised. As a result, the demand for privacy-preserving techniques that enable DL model training and inference on secured data has significantly grown. We propose an image obfuscation algorithm that combines a variational autoencoder (VAE) with random non-bijective pixel intensity mapping to protect the content of medical images, which are subsequently employed in the development of DL-based solutions. A binary classifier is trained on secured coronary angiographic frames to evaluate the utility of obfuscated images in the context of model training. Two possible attack configurations are considered to assess the security level against artificial intelligence (AI)-based reconstruction attempts. Similarity metrics are employed to quantify the security against human perception (structural similarity index measure and peak signal-to-noise-ratio). Furthermore, expert readers performed a visual assessment to determine to what extent the reconstructed images are protected against human perception. The proposed algorithm successfully enables DL model training on obfuscated images with no significant computational overhead while ensuring protection against human eye perception and AI-based reconstruction attacks. Regardless of the threat actor’s prior knowledge of the target content, the coronary vessels cannot be entirely recovered through an AI-based attack. Although a drop in accuracy can be observed when the classifier is trained on obfuscated images, the performance is deemed satisfactory in the context of a privacy–accuracy trade-off.

Hypertensive emergencies (HE) represent high cardiovascular risk situations defined by a severe increase in blood pressure (BP) associated with acute, hypertension mediated organ damage (A-HMOD) to the heart, brain, retina, kidneys, and large arteries. Blood pressure values alone do not accurately predict the presence of HE; therefore, the search for A-HMOD should be the first step in the management of acute severe hypertension. A rapid therapeutic intervention is mandatory in order to limit and promote regression of end-organ damage, minimize the risk of complications, and improve patient outcomes. Drug therapy for HE, target BP, and the speed of BP decrease are all dictated by the type of A-HMOD, specific drug pharmacokinetics, adverse drug effects, and comorbidities. Therefore, a tailored approach is warranted. However, there is currently a lack of solid evidence for the appropriate treatment strategies for most HE. This article reviews current pharmacological strategies while providing a stepwise, evidence based approach for the management of HE.

Despite significant progress in treating ischemic cardiac disease and succeeding heart failure, there is still an unmet need to develop effective therapeutic strategies given the persistent high-mortality rate. Advances in stem cell biology hold great promise for regenerative medicine, particularly for cardiac regeneration. Various cell types have been used both in preclinical and clinical studies to repair the injured heart, either directly or indirectly. Transplanted cells may act in an autocrine and/or paracrine manner to improve the myocyte survival and migration of remote and/or resident stem cells to the site of injury. Still, the molecular mechanisms regulating cardiac protection and repair are poorly understood. Stem cell fate is directed by multifaceted interactions between genetic, epigenetic, transcriptional, and post-transcriptional mechanisms. Decoding stem cells’ “panomic” data would provide a comprehensive picture of the underlying mechanisms, resulting in patient-tailored therapy. This review offers a critical analysis of omics data in relation to stem cell survival and differentiation. Additionally, the emerging role of stem cell-derived exosomes as “cell-free” therapy is debated. Last but not least, we discuss the challenges to retrieve and analyze the huge amount of publicly available omics data.

Most patients presenting in an emergency unit with acute coronary syndromes (ACS) (which include non-ST-elevation myocardial infarction (NSTEMI), ST-elevation MI (STEMI), and unstable angina) usually meet at least two cardiovascular risk factors, such as dyslipidemia, arterial hypertension, diabetes mellitus type 2, obesity, history of or current smoking, etc. Most ACS patients suffer from a type of dyslipidemia, and in addition to this there are ACS patients rushed into the emergency units for which the feeding status is unknown. Thus, we set out to evaluate the effect of fasting on 16 blood metabolite concentrations and 114 lipoprotein parameters on one control group and a group of statin-treated ACS patients hospitalized in a cardiovascular emergency unit, using Nuclear Magnetic Resonance (NMR) spectroscopy. The results indicated trends (in terms of number of cases, but not necessarily in terms of the magnitude of the effect) for as many as four metabolites and 48 lipoproteins. The effect was defined as a trend for results showing over 70% of the cases from either one or both groups that experienced parameter changes in the same direction (i.e., either increased or decreased). In terms of magnitude, the effect is rather low, leading to the overall conclusion that in cardiovascular (CV) emergency units, the blood samples analyzed in any feeding status would provide close results and very valuable information regarding prognosis and for fast decisions on patient’s proper management.