The European Network for Translational Research in Atrial Fibrillation (EUTRAF): objectives and initial results.

Atrial fibrillation (AF) is the most common sustained arrhythmia in the general population. As an age-related arrhythmia AF is becoming a huge socio-economic burden for European healthcare systems. Despite significant progress in our understanding of the pathophysiology of AF, therapeutic strategies for AF have not changed substantially and the major challenges in the management of AF are still unmet. This lack of progress may be related to the multifactorial pathogenesis of atrial remodelling and AF that hampers the identification of causative pathophysiological alterations in individual patients. Also, again new mechanisms have been identified and the relative contribution of these mechanisms still has to be established. In November 2010, the European Union launched the large collaborative project EUTRAF (European Network of Translational Research in Atrial Fibrillation) to address these challenges. The main aims of EUTRAF are to study the main mechanisms of initiation and perpetuation of AF, to identify the molecular alterations underlying atrial remodelling, to develop markers allowing to monitor this processes, and suggest strategies to treat AF based on insights in newly defined disease mechanisms. This article reports on the objectives, the structure, and initial results of this network

An Optimized Reverse Genetics System Suitable for Efficient Recovery of Simian, Human, and Murine-Like Rotaviruses

Copyright © 2020 American Society for Microbiology. An entirely plasmid-based reverse genetics (RG) system was recently developed for rotavirus (RV), opening new avenues for in-depth molecular dissection of RV biology, immunology, and pathogenesis. Several improvements to further optimize the RG efficiency have now been described. However, only a small number of individual RV strains have been recovered to date. None of the current methods have supported the recovery of murine RV, impeding the study of RV replication and pathogenesis in an in vivo suckling mouse model. Here, we describe useful modifications to the RG system that significantly improve rescue efficiency of multiple RV strains. In addition to the 11 group A RV segment-specific (+)RNAs [(+)ssRNAs], a chimeric plasmid was transfected, from which the capping enzyme NP868R of African swine fever virus (ASFV) and the T7 RNA polymerase were expressed. Second, a genetically modified MA104 cell line was used in which several components of the innate immunity were degraded. Using this RG system, we successfully recovered the simian RV RRV strain, the human RV CDC-9 strain, a reassortant between murine RV D6/2 and simian RV SA11 strains, and several reassortants and reporter RVs. All these recombinant RVs were rescued at a high efficiency (≥80% success rate) and could not be reliably rescued using several recently published RG strategies

Aortic stiffness in lone atrial fibrillation: A novel risk factor for arrhythmia recurrence

BACKGROUND Recent community-based research has linked aortic stiffness to the development of atrial fibrillation. We posit that aortic stiffness contributes to adverse atrial remodeling leading to the persistence of atrial fibrillation following catheter ablation in lone atrial fibrillation patients, despite the absence of apparent structural heart disease. Here, we aim to evaluate aortic stiffness in lone atrial fibrillation patients and determine its association with arrhythmia re currence following radio-frequency catheter ablation. METHODS We studied 68 consecutive lone atrial fibrillation patients who underwent catheter ablation procedure for atrial fibrillation and 50 healthy age- and sex-matched community controls. We performed radial artery applanation tonometry to obtain central measures of aortic stiffness: pulse pressure, augmentation pressure and augmentation index. Following ablation, arrhythmia recurrence was monitored at months 3, 6, 9, 12 and 6 monthly thereafter. RESULTS Compared to healthy controls, lone atrial fibrillation patients had significantly elevated peripheral pulse pressure, central pulse pressure, augmentation pressure and larger left atrial dimensions (all P<0.05). During a mean follow-up of 2.9±1.4 years, 38 of the 68 lone atrial fibrillation patients had atrial fibrillation recurrence after initial catheter ablation procedure. Neither blood pressure nor aortic stiffness indices differed between patients with and without atrial fibrillation recurrence. However, patients with highest levels (≥75th percentile) of peripheral pulse pressure, central pulse pressure and augmentation pressure had higher atrial fibrillation recurrence rates (all P<0.05). Only central aortic stiffness indices were associated with lower survival free from atrial fibrillation using Kaplan-Meier analysis. CONCLUSION Aortic stiffness is an important risk factor in patients with lone atrial fibrillation and contributes to higher atrial fibrillation recurrence following catheter ablation procedure.Dennis H. Lau, Melissa E. Middeldorp, Anthony G. Brooks, Anand N. Ganesan, Kurt C. Roberts-Thomson, Martin K. Stiles, Darryl P. Leong, Hany S. Abed, Han S. Lim, Christopher X. Wong, Scott R. Willoughby, Glenn D. Young, Jonathan M. Kalman, Walter P. Abhayaratna, Prashanthan Sander

Updated Hemodynamic Definition and Classification of Pulmonary Hypertension.

Pulmonary hypertension (PH) is a pathophysiological manifestation of a heterogeneous group of diseases characterized by abnormally elevated pulmonary arterial pressures diagnosed on right heart catheterization. The 2022 European Society of Cardiology (ESC) and European Respiratory Society (ERS) Guidelines for the diagnosis and treatment of PH provides a new hemodynamic definition to define PH by lowering the threshold of the mean pulmonary artery pressure (mPAP) to 20 mm Hg. Precapillary PH is thus now defined as a mPAP &gt;20 mm Hg together with a normal pulmonary artery wedge pressure (&lt;15 mm Hg) and an increased pulmonary vascular resistance (&gt;2 Wood Units). The ESC/ERS 2022 Guidelines also introduce a revised clinical classification of PH while retaining its previous distinction between the five groups according to the underlying pathophysiology

Towards optimized MR thermometry of the human heart at 3T

International audienc

Motion correction strategies for cardiac MR thermometry during RF-ablation

International audienc

Comparing Reentrant Drivers Predicted by Image-Based Computational Modeling and Mapped by Electrocardiographic Imaging in Persistent Atrial Fibrillation

Electrocardiographic mapping (ECGI) detects reentrant drivers (RDs) that perpetuate arrhythmia in persistent AF (PsAF). Patient-specific computational models derived from late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) identify all latent sites in the fibrotic substrate that could potentially sustain RDs, not just those manifested during mapped AF. The objective of this study was to compare RDs from simulations and ECGI (RDsim/RDECGI) and analyze implications for ablation. We considered 12 PsAF patients who underwent RDECGI ablation. For the same cohort, we simulated AF and identified RDsim sites in patient-specific models with geometry and fibrosis distribution from pre-ablation LGE-MRI. RDsim- and RDECGI-harboring regions were compared, and the extent of agreement between macroscopic locations of RDs identified by simulations and ECGI was assessed. Effects of ablating RDECGI/RDsim were analyzed. RDsim were predicted in 28 atrial regions (median [inter-quartile range (IQR)] = 3.0 [1.0; 3.0] per model). ECGI detected 42 RDECGI-harboring regions (4.0 [2.0; 5.0] per patient). The number of regions with RDsim and RDECGI per individual was not significantly correlated (R = 0.46, P = ns). The overall rate of regional agreement was fair (modified Cohen's κ0 statistic = 0.11), as expected, based on the different mechanistic underpinning of RDsim- and RDECGI. nineteen regions were found to harbor both RDsim and RDECGI, suggesting that a subset of clinically observed RDs was fibrosis-mediated. The most frequent source of differences (23/32 regions) between the two modalities was the presence of RDECGI perpetuated by mechanisms other than the fibrotic substrate. In 6/12 patients, there was at least one region where a latent RD was observed in simulations but was not manifested during clinical mapping. Ablation of fibrosis-mediated RDECGI (i.e., targets in regions that also harbored RDsim) trended toward a higher rate of positive response compared to ablation of other RDECGI targets (57 vs. 41%, P = ns). Our analysis suggests that RDs in human PsAF are at least partially fibrosis-mediated. Substrate-based ablation combining simulations with ECGI could improve outcomes

Evaluation and optimization of novel extraction algorithms for the automatic detection of atrial activations recorded within the pulmonary veins during atrial fibrillation.

The automated detection of atrial activations (AAs) recorded from intracardiac electrograms (IEGMs) during atrial fibrillation (AF) is challenging considering their various amplitudes, morphologies and cycle length. Activation time estimation is further complicated by the constant changes in the IEGM active zones in complex and/or fractionated signals. We propose a new method which provides reliable automatic extraction of intracardiac AAs recorded within the pulmonary veins during AF and an accurate estimation of their local activation times. First, two recently developed algorithms were evaluated and optimized on 118 recordings of pulmonary vein IEGM taken from 35 patients undergoing ablation of persistent AF. The adaptive mathematical morphology algorithm (AMM) uses an adaptive structuring element to extract AAs based on their morphological features. The relative-energy algorithm (Rel-En) uses short- and long-term energies to enhance and detect the AAs in the IEGM signals. Second, following the AA extraction, the signal amplitude was weighted using statistics of the AA sequences in order to reduce over- and undersensing of the algorithms. The detection capacity of our algorithms was compared with manually annotated activations and with two previously developed algorithms based on the Teager-Kaiser energy operator and the AF cycle length iteration, respectively. Finally, a method based on the barycenter was developed to reduce artificial variations in the activation annotations of complex IEGM signals. The best detection was achieved using Rel-En, yielding a false negative rate of 0.76% and a false positive rate of only 0.12% (total error rate 0.88%) against expert annotation. The post-processing further reduced the total error rate of the Rel-En algorithm by 70% (yielding to a final total error rate of 0.28%). The proposed method shows reliable detection and robust temporal annotation of AAs recorded within pulmonary veins in AF. The method has low computational cost and high robustness for automatic detection of AAs, which makes it a suitable approach for online use in a procedural context