Complexity AF score as a novel marker of atrial fibrillation instability.

Atrial fibrillation (AF) is a heart disease affecting millions of Americans. Clinicians evaluate AF-related risk by assessing the temporal pattern, variation, and severity of AF episodes through AF burden (AFB). However, existing prognostic tools based on these metrics are suboptimal, as they do not account for electrical complexity of AF signals.

Atherosclerotic Calcifications Have a Local Effect on the Peel Behavior of Human Aortic Media.

Aortic dissections, characterized by the propagation of a tear through the layers of the vessel wall, are critical, life-threatening events. Aortic calcifications are a common comorbidity in both acute and chronic dissections, yet their impact on dissection mechanics remains unclear. Using micro-computed tomography (CT) imaging, peel testing, and finite element modeling, this study examines the interplay between atherosclerotic calcifications and dissection mechanics.

Image-Decomposition-Enhanced Deep Learning for Detection of Rotor Cores in Cardiac Fibrillation.

Objective: Rotors, regions of spiral wave reentry in cardiac tissues, are considered as the drivers of atrial fibrillation (AF), the most common arrhythmia. Whereas physics-based approaches have been widely deployed to detect the rotors, in-depth knowledge in cardiac physiology and electrogram interpretation skills are typically needed. The recent leap forward in smart sensing, data acquisition, and Artificial Intelligence (AI) has offered an unprecedented opportunity to transform diagnosis and treatment in cardiac ailment, including AF.

Complexity analysis of electrical activity during endocardial and epicardial biventricular mapping of ventricular fibrillation.

Background: Ventricular fibrillation (VF) is a lethal cardiac arrhythmia that is a significant cause of sudden cardiac death. Comprehensive studies of spatiotemporal characteristics of VF in situ are difficult to perform with current mapping systems and catheter technology.

Objective: The goal of this study was to develop a computational approach to characterize VF using a commercially available technology in a large animal model.