Improving electrocardiographic imaging solutions: A comprehensive study on regularization parameter selection in L-curve optimization in the Atria.

Background: In electrocardiographic imaging (ECGI), selecting an optimal regularization parameter (λ) is crucial for obtaining accurate inverse electrograms. The effects of signal and geometry uncertainties on the inverse problem regularization have not been thoroughly quantified, and there is no established methodology to identify when λ is sub-optimal due to these uncertainties. This study introduces a novel approach to λ selection using Tikhonov regularization and L-curve optimization, specifically addressing the impact of electrical noise in body surface potential map (BSPM) signals and geometrical inaccuracies in the cardiac mesh.

Desensitizing the autonomic nervous system to mitigate anti-GD2 monoclonal antibody side effects.

Background: Anti-GD2 monoclonal antibodies (mAbs) have shown to improve the overall survival of patients with high-risk neuroblastoma (HR-NB). Serious adverse events (AEs), including pain, within hours of antibody infusion, have limited the development of these therapies. In this study, we provide evidence of Autonomic Nervous System (ANS) activation as the mechanism to explain the main side effects of anti-GD2 mAbs.

Has the balloon really burst? Analysis of "the UK-REBOA randomized clinical trial".

Background: Uncontrolled hemorrhagic shock is a leading cause of early death after injury. Resuscitative endovascular balloon occlusion of the aorta (REBOA) represents a paradigm shift in achieving hemodynamic stability and its implementation still remain controversial in different settings. The recently published UK-REBOA Randomized Clinical Trial aimed to determine the effectiveness of REBOA in patients with hemorrhagic shock, concluding its increased mortality compared with standard care alone.

Regional conduction velocities determined by noninvasive mapping are associated with arrhythmia-free survival after atrial fibrillation ablation.

Background: Atrial arrhythmogenic substrate is a key determinant of atrial fibrillation (AF) recurrence after pulmonary vein isolation (PVI), and reduced conduction velocities have been linked to adverse outcome. However, a noninvasive method to assess such electrophysiologic substrate is not available to date.

Objective: This study aimed to noninvasively assess regional conduction velocities and their association with arrhythmia-free survival after PVI.

Non-invasive estimation of atrial fibrillation driver position using long-short term memory neural networks and body surface potentials.

Background And Objective: Atrial Fibrillation (AF) is a supraventricular tachyarrhythmia that can lead to thromboembolism, hearlt failure, ischemic stroke, and a decreased quality of life. Characterizing the locations where the mechanisms of AF are initialized and maintained is key to accomplishing an effective ablation of the targets, hence restoring sinus rhythm. Many methods have been investigated to locate such targets in a non-invasive way, such as Electrocardiographic Imaging, which enables an on-invasive and panoramic characterization of cardiac electrical activity using recording Body Surface Potentials (BSP) and a torso model of the patient.