Mitral valve regurgitation (MR) is a multifaceted valvular heart disease. Echocardiography plays a central role in etiology assessment, severity quantification, treatment candidacy, outcome ...evaluation, and patient follow-up. In this review, we describe the comprehensive echocardiographic assessment of MR, including transthoracic (TTE) and transesophageal (TEE) approaches, 2D and 3D modalities, strain imaging, stress echocardiography, and artificial intelligence (AI) applications. Transcatheter edge-to-edge mitral valve repair (TEER) has been established as a key therapy for patients with severe, symptomatic MR and high surgical risk. TEER is performed under TEE guidance. We outline a practical overview of echocardiographic guidance on TEER.
We aimed to evaluate the feasibility and accuracy of machine learning-based automated dynamic quantification of left ventricular (LV) and left atrial (LA) volumes in an unselected population. We ...enrolled 600 unselected patients (12% in atrial fibrillation) clinically referred for transthoracic echocardiography (2DTTE), who also underwent 3D echocardiography (3DE) imaging. LV ejection fraction (EF), LV, and LA volumes were obtained from 2D images; 3D images were analyzed using dynamic heart model (DHM) software (Philips) resulting in LV and LA volume–time curves. A subgroup of 140 patients also underwent cardiac magnetic resonance (CMR) imaging. Average time of analysis, feasibility, and image quality were recorded, and results were compared between 2DTTE, DHM, and CMR. The use of DHM was feasible in 522/600 cases (87%). When feasible, the boundary position was considered accurate in 335/522 patients (64%), while major (n = 38) or minor (n = 149) border corrections were needed. The overall time required for DHM datasets was approximately 40 seconds. As expected, DHM LV volumes were larger than 2D ones (end-diastolic volume: 173 ± 64 vs. 142 ± 58 mL, respectively), while no differences were found for LV EF and LA volumes (EF: 55% ± 12 vs. 56% ± 14; LA volume 89 ± 36 vs. 89 ± 38 mL, respectively). The comparison between DHM and CMR values showed a high correlation for LV volumes (r = 0.70 and r = 0.82, p < 0.001 for end-diastolic and end-systolic volume, respectively) and an excellent correlation for EF (r = 0.82, p < 0.001) and LA volumes. The DHM software is feasible, accurate, and quick in a large series of unselected patients, including those with suboptimal 2D images or in atrial fibrillation.
Prosthetic valve (PV) dysfunction (PVD) is a complication of mechanical or biological PV. Etiologic mechanisms associated with PVD include fibrotic pannus ingrowth, thrombosis, structural valve ...degeneration, and endocarditis resulting in different grades of obstruction and/or regurgitation. PVD can be life threatening and often challenging to diagnose due to the similarities between the clinical presentations of different causes. Nevertheless, identifying the cause of PVD is critical to treatment administration (thrombolysis, surgery, or percutaneous procedure). In this report, we review the role of multimodality imaging in the diagnosis of PVD. Specifically, this review discusses the characteristics of advanced imaging modalities underlying the importance of an integrated approach including 2D/3D transthoracic and transesophageal echocardiography, fluoroscopy, and computed tomography. In this scenario, it is critical to understand the strengths and weaknesses of each modality according to the suspected cause of PVD. In conclusion, for patients with suspected or known PVD, this stepwise imaging approach may lead to a simplified, more rapid, accurate and specific workflow and management.
The Covid-19 pandemic has been the most defining event of our era. The world of healthcare has experienced first-hand the dramatic situation of treating patients in the face of the dangers of ...contagion and limited resources. Difficult choices have everywhere been made alongside ethical reflection. Now that, at least in our part of the world, viral infection seems to be broadly on the decline, there is an urgent need for fresh, anthropological, ethical reflection. It is important to avoid being unprepared in the event of further occasions, but above all, to now think in global terms. This is because the pandemic has forced us to recognise the urgency of building alliance in healthcare and a balanced relationship with the environment.
Myocardial bridging (MB) is a frequent congenital anomaly of the epicardial coronary arteries commonly considered a benign condition. However, in some cases a complex interplay between anatomical, ...clinical and physiology factors may lead to adverse events, including sudden cardiac death. Coronary CT angiography (CCTA) emerged as the gold standard noninvasive imaging technique for the evaluation of MB. Aim of the study was to evaluate MB prevalence and anatomical features in a large population of patients who underwent CCTA for suspected CAD and to identify potential anatomical and clinical predictors of adverse cardiac events at long-term follow-up.
Two-hundred and six patients (mean age 60.3 ± 11.8 years, 128 male) with MB diagnosed at CCTA were considered. A long MB was defined as ≥25 mm of overlying myocardium, whereas a deep MB as ≥2 mm of overlying myocardium. The study endpoint was the sum of the following adverse events: cardiac death, bridge-related acute coronary syndrome, hospitalization for angina or bridge-related ventricular arrhythmias and MB surgical treatment. Of the 206 patients enrolled in the study, 9 were lost to follow-up, whereas 197 (95.6%) had complete follow-up (mean 7.01 ± 3.0 years) and formed the analytic population. Nineteen bridge-related events occurred in 18 patients (acute coronary syndrome in 7, MB surgical treatment in 2 and hospitalization for bridge-related events in 10). Typical angina at the time of diagnosis and long MB resulted as significant independent predictors of adverse outcome.
Typical angina and MB length ≥ 25 mm were independent predictors of cardiac events.
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•CCTA can highly detect and precisely characterize myocardial bridging.•CCTA precisely assess the length and depth of the coronary tunneled segment.•Typical angina and myocardial bridging length ≥ 25 mm were independent predictors of cardiac events.
A Systemic Optimal Risk Transfer Equilibrium (SORTE) was introduced in: “Systemic optimal risk transfer equilibrium”, Mathematics and Financial Economics (2021), for the analysis of the equilibrium ...among financial institutions or in insurance-reinsurance markets. A SORTE conjugates the classical Bühlmann’s notion of a risk exchange equilibrium with a capital allocation principle based on systemic expected utility optimization. In this paper we extend such a notion to the case when the value function to be optimized is multivariate in a general sense, and it is not simply given by the sum of univariate utility functions. This takes into account the fact that preferences of single agents might depend on the actions of other participants in the game. Technically, the extension of SORTE to the new setup requires developing a theory for multivariate utility functions and selecting at the same time a suitable framework for the duality theory. Conceptually, this more general framework allows us to introduce and study a Nash Equilibrium property of the optimizer. We prove existence, uniqueness, and the Nash Equilibrium property of the newly defined Multivariate Systemic Optimal Risk Transfer Equilibrium.
The objective of this paper is to develop a duality between a novel entropy martingale optimal transport (EMOT) problem and an associated optimisation problem. In EMOT, we follow the approach taken ...in the entropy optimal transport (EOT) problem developed in Liero et al. (Invent. Math. 211:969–1117,
2018
), but we add the constraint, typical of martingale optimal transport (MOT) theory, that the infimum of the cost functional is taken over martingale probability measures. In the associated problem, the objective functional, related via Fenchel conjugacy to the entropic term in EMOT, is no longer linear as in (martingale) optimal transport. This leads to a novel optimisation problem which also has a clear financial interpretation as a nonlinear subhedging problem. Our theory allows us to establish a nonlinear robust pricing–hedging duality which also covers a wide range of known robust results. We also focus on Wasserstein-induced penalisations and study how the duality is affected by variations in the penalty terms, with a special focus on the convergence of EMOT to the extreme case of MOT.
In this work, we propose deep learning-based algorithms for the computation of systemic shortfall risk measures defined via multivariate utility functions. We discuss the key related theoretical ...aspects, with a particular focus on the fairness properties of primal optima and associated risk allocations. The algorithms we provide allow for learning primal optimizers, optima for the dual representation and corresponding fair risk allocations. We test our algorithms by comparison to a benchmark model, based on a paired exponential utility function, for which we can provide explicit formulas. We also show evidence of convergence in a case in which explicit formulas are not available.
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