Circulation: Arrhythmia And Electrophysiology On The Beat

Paul J. Wang: Welcome to the monthly podcast On the Beat, for Circulation: Arrhythmia and Electrophysiology. I'm Dr. Paul Wang, Editor-in-Chief, with some of the key highlights from this month's issue.   In our first paper, David Okada and associates assess the ability of a novel machine learning approach for quantifying 3D spatial complexity of gray scale patterns on late gadolinium-enhanced cardiac magnetic resonance images to predict ventricular arrhythmias in patients with ischemic cardiomyopathy.   They examined 122 consecutive ischemic cardiomyopathy patients with left ventricular ejection fraction of 35%, without prior history of reentrant ventricular arrhythmias. These patients underwent late gadolinium-enhanced cardiac magnetic resonance imaging. From raw gray scale data, the authors generated graphs encoding the 3D geometry of the left ventricle. They then assess the global regularity of signal intensity patterns using Fourier-like analysis and generated a substrate spatial complexity profile for ea