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Aims To assess the progression of the disease and evolution of the main echocardiographic variables for quantifying AS in patients with severe low-flow low-gradient (LFLG) AS compared to other severe AS subtypes. Methods and results Longitudinal, observational, multicenter study including consecutive asymptomatic patients with severe AS (aortic valve area, AVA < 1.0 cm²) and normal left ventricle ejection fraction (LVEF ≥ 50%). Patients were classified according to baseline echocardiography into: HG (high gradient; mean gradient ≥ 40 mmHg), NFLG (normal-flow low-gradient; mean gradient < 40 mmHg, indexed systolic volume (SVi) > 35mL/m2), or LFLG (mean gradient < 40 mmHg, SVi ≤ 35 mL/m²). AS progression was analyzed by comparing patients’ baseline measurements and their last follow-up measurements or those taken prior to aortic valve replacement (AVR). Of the 903 included patients, 401 (44.4%) were HG, 405 (44.9%) NFLG, and 97 (10.7%) LFLG. Progression of the mean gradient in a linear mixed regression model was greater in low-gradient groups: LFLG vs. HG (regression coefficient 0.124, P = 0.005) and NFLG vs. HG (regression coefficient 0.068, P = 0.018). No differences were observed between the LFLG and NFLG groups (regression coefficient 0.056, P = 0.195). However, AVA reduction was slower in the LFLG group compared to the NFLG (P < 0.001). During follow-up, in conservatively-managed patients, 19.1% (n = 9) of LFLG patients evolved to having NFLG AS and 44.7% (n = 21) to having HG AS. In patients undergoing AVR, 58.0% (n = 29) of LFLG baseline patients received AVR with a HG AS. Conclusion LFLG AS shows an intermediate AVA and gradient progression compared to NFLG and HG AS. The majority of patients initially classified as having LFLG AS changed over time to having other severe forms of AS, and most of them received AVR with a HG AS.

Instituto de Salud Carlos III (ISCIII), European Regional Development Fund/European Social Fund "A way to make Europe"/" Investing in your future" [PI18/0004, PI20/0320, PT17/0015/0043]; ISCIII; MCIN; Pro-CNIC Foundation; Severo Ochoa Centers of Excellence program [CEX2020-001041-S]; ISCIII [CM20/00101], Frutos F. de, Ochoa JP, Navarro-Peñalver M, Baas A, Bjerre JV, Zorio E, Méndez I, Lorca R, Verdonschot JAJ, García-Granja PE, Bilinska Z, Fatkin D, Fuentes-Cañamero ME, García-Pinilla JM, García-Álvarez MI, Girolami F, Barriales-Villa R, Díez-López C, Lopes LR, Wahbi K, García-Álvarez A, Rodríguez-Sánchez I, Rekondo-Olaetxea J, Rodríguez-Palomares JF, Gallego-Delgado M, Meder B, Kubanek M, Hansen FG, Restrepo-Córdoba MA, Palomino-Doza J, Ruiz-Guerrero L, Sarquella-Brugada G, Perez-Perez AJ, Bermúdez-Jiménez FJ, Ripoll-Vera T, Rasmussen TB, Jansen M, Sabater-Molina M, Elliot PM, Garcia-Pavia P; European Genetic Cardiomyopathies Initiative Investigators

Background: Patients with mitral valve prolapse (MVP) may develop adverse outcomes even in the absence of mitral regurgitation or left ventricular (LV) dysfunction. Purpose: To investigate the prognostic value of mitral annulus disjunction (MAD) and myocardial fibrosis at late gadolinium enhancement (LGE) cardiac MRI in patients with MVP without moderate-to-severe mitral regurgitation or LV dysfunction. Materials and Methods: In this longitudinal retrospective study, 118 144 cardiac MRI studies were evaluated between October 2007 and June 2020 at 15 European tertiary medical centers. Follow-up was from the date of cardiac MRI examination to June 2020; the minimum and maximum follow-up intervals were 6 months and 156 months, respectively. Patients were excluded if at least one of the following conditions was present: cardiomyopathy, LV ejection fraction less than 40%, ischemic heart disease, congenital heart disease, inflammatory heart disease, moderate or worse mitral regurgitation, participation in competitive sport, or electrocardiogram suggestive of channelopathies. In the remainder, cardiac MRI studies were reanalyzed, and patients were included if they were aged 18 years or older, MVP was diagnosed at cardiac MRI, and clinical information and electrocardiogram monitoring were available within 3 months from cardiac MRI examination. The end point was a composite of adverse outcomes: sustained ventricular tachycardia (VT), sudden cardiac death (SCD), or unexplained syncope. Multivariable Cox regression analysis was performed. Results: A total of 474 patients (mean age, 47 years ± 16 [SD]; 244 women) were included. Over a median follow-up of 3.3 years, 18 patients (4%) reached the study end point. LGE presence (hazard ratio, 4.2 [95% CI: 1.5, 11.9]; P = .006) and extent (hazard ratio, 1.2 per 1% increase [95% CI: 1.1, 1.4]; P = .006), but not MAD presence (P = .89), were associated with clinical outcome. LGE presence had incremental prognostic value over MVP severity and sustained VT and aborted SCD at baseline (area under the receiver operating characteristic curve, 0.70 vs 0.62; P = .03). Conclusion: In contrast to mitral annulus disjunction, myocardial fibrosis determined according to late gadolinium enhancement at cardiac MRI was associated with adverse outcome in patients with mitral valve prolapse without moderate-to-severe mitral regurgitation or left ventricular dysfunction.

The aim of this collaborative document is to provide an update for clinicians on best antithrombotic strategies in patients with aortic and/or peripheral arterial diseases. Antithrombotic therapy is a pillar of optimal medical treatment for these patients at very high cardiovascular risk. While the number of trials on antithrombotic therapies in patients with aortic or peripheral arterial diseases is substantially smaller than for those with coronary artery disease, recent evidence deserves to be incorporated into clinical practice. In the absence of specific indications for chronic oral anticoagulation due to concomitant cardiovascular disease, a single antiplatelet agent is the basis for long-term antithrombotic treatment in patients with aortic or peripheral arterial diseases. Its association with another antiplatelet agent or low-dose anticoagulants will be discussed, based on patient’s ischaemic and bleeding risk as well therapeutic paths (e.g. endovascular therapy). This consensus document aims to provide a guidance for antithrombotic therapy according to arterial disease localizations and clinical presentation. However, it cannot substitute multidisciplinary team discussions, which are particularly important in patients with uncertain ischaemic/bleeding balance. Importantly, since this balance evolves over time in an individual patient, a regular reassessment of the antithrombotic therapy is of paramount importance.

Dilatació aòrtica; Aneurisma de l'aorta ascendent; Anàlisi espai-temporal Dilatación aórtica; Aneurisma de la aorta ascendente; Análisis espacio-temporal Aortic dilation; Ascending aorta aneurysm; Spatiotemporal analysis Motivated by the evidence that the onset and progression of the aneurysm of the ascending aorta (AAo) is intertwined with an adverse hemodynamic environment, the present study characterized in vivo the hemodynamic spatiotemporal complexity and organization in human aortas, with and without dilated AAo, exploring the relations with clinically relevant hemodynamic and geometric parameters. The Complex Networks (CNs) theory was applied for the first time to 4D flow magnetic resonance imaging (MRI) velocity data of ten patients, five of them presenting with AAo dilation. The time-histories along the cardiac cycle of velocity-based quantities were used to build correlation-based CNs. The CNs approach succeeded in capturing large-scale coherent flow features, delimiting flow separation and recirculation regions. CNs metrics highlighted that an increasing AAo dilation (expressed in terms of the ratio between the maximum AAo and aortic root diameter) disrupts the correlation in forward flow reducing the correlation persistence length, while preserving the spatiotemporal homogeneity of secondary flows. The application of CNs to in vivo 4D MRI data holds promise for a mechanistic understanding of the spatiotemporal complexity and organization of aortic flows, opening possibilities for the integration of in vivo quantitative hemodynamic information into risk stratification and classification criteria. Open access funding provided by Politecnico di Torino within the CRUI-CARE Agreement.

Aims: Genotype and left ventricular scar on cardiac magnetic resonance (CMR) are increasingly recognized as risk markers for adverse outcomes in non-ischaemic dilated cardiomyopathy (DCM). We investigated the combined influence of genotype and late gadolinium enhancement (LGE) in assessing prognosis in a large cohort of patients with DCM. Methods and results: Outcomes of 600 patients with DCM (53.3 ± 14.1 years, 66% male) who underwent clinical CMR and genetic testing were retrospectively analysed. The primary endpoints were end-stage heart failure (ESHF) and malignant ventricular arrhythmias (MVA). During a median follow-up of 2.7 years (interquartile range 1.3–4.9), 24 (4.00%) and 48 (8.00%) patients had ESHF and MVA, respectively. In total, 242 (40.3%) patients had pathogenic/likely pathogenic variants (positive genotype) and 151 (25.2%) had LGE. In survival analysis, positive LGE was associated with MVA and ESHF (both, p < 0.001) while positive genotype was associated with ESHF (p = 0.034) but not with MVA (p = 0.102). Classification of patients according to genotype (G+/G−) and LGE presence (L+/L−) revealed progressively increasing events across L−/G−, L−/G+, L+/G− and L+/G+ groups and resulted in optimized MVA and ESHF prediction (p < 0.001 and p = 0.001, respectively). Hazard ratios for MVA and ESHF in patients with either L+ or G+ compared with those with L−/G− were 4.71 (95% confidence interval: 2.11–10.50, p < 0.001) and 7.92 (95% confidence interval: 1.86–33.78, p < 0.001), respectively. Conclusion: Classification of patients with DCM according to genotype and LGE improves MVA and ESHF prediction. Scar assessment with CMR and genotyping should be considered to select patients for primary prevention implantable cardioverter-defibrillator placement, This work was supported by grants from the Instituto de Salud Carlos III (ISCIII) (PI18/0004, PI19/01283, PI20/0320). (Co-funded by European Regional Development Fund/European Social Fund ‘A way to make Europe’/‘Investing in your future’). The Hospital Universitario Puerta de Hierro Majadahonda, the Hospital Clinic, the Hospital Vall d’Hebron, the Hospital General Universitario Gregorio Marañón and the Hospital Universitario Virgen de la Arrixaca are members of the European Reference Network for rare, low-prevalence, and complex diseases of the heart (ERN GUARD-Heart). The CNIC is supported by the ISCIII, MCIN, the Pro-CNIC Foundation, and the Severo Ochoa Centers of Excellence program (CEX2020-001041-S). Conflict of interest: none declared

Background: The domain generalization problem has been widely investigated in deep learning for non -contrast imaging over the last years, but it received limited attention for contrast-enhanced imaging. However, there are marked differences in contrast imaging protocols across clinical centers, in particular in the time between contrast injection and image acquisition, while access to multi-center contrast-enhanced image data is limited compared to available datasets for non-contrast imaging. This calls for new tools for generalizing single-domain, single-center deep learning models across new unseen domains and clinical centers in contrast-enhanced imaging. Methods: In this paper, we present an exhaustive evaluation of deep learning techniques to achieve generaliz-ability to unseen clinical centers for contrast-enhanced image segmentation. To this end, several techniques are investigated, optimized and systematically evaluated, including data augmentation, domain mixing, transfer learning and domain adaptation. To demonstrate the potential of domain generalization for contrast-enhanced imaging, the methods are evaluated for ventricular segmentation in contrast-enhanced cardiac magnetic resonance imaging (MRI). Results: The results are obtained based on a multi-center cardiac contrast-enhanced MRI dataset acquired in four hospitals located in three countries (France, Spain and China). They show that the combination of data augmentation and transfer learning can lead to single-center models that generalize well to new clinical centers not included during training. Conclusions: Single-domain neural networks enriched with suitable generalization procedures can reach and even surpass the performance of multi-center, multi-vendor models in contrast-enhanced imaging, hence eliminating the need for comprehensive multi-center datasets to train generalizable models.

Published on behalf of the European Society of Cardiology. All rights reserved. © The Author(s) 2019. For permissions, please email: journals.permissions@oup.com., Cardiovascular magnetic resonance (CMR) has become one of the main imaging techniques for the diagnosis and prognostic stratification of the different cardiovascular diseases. Proof of this is the growing interest in training in this imaging technique which was evident in the past EuroCMR 2019 where 1379 specialists (26.5% more than in the previous edition) met in Lido (Venice) to discuss the latest scientific advances in the CMR field. In this review, we will discuss the most recent research presented during this congress that aroused maximum interest.