Fast personalized electrophysiological models from computed tomography images for ventricular tachycardia ablation planning

This paper presents a novel evolutionary optimization strategy based on the derandomized evolution strategy with covariance matrix adaptation (CMA-ES). This new approach is intended to reduce the number of generations required for convergence to the optimum. Reducing the number of generations, i.e., the time complexity of the algorithm, is important if a large population size is desired: (1) to reduce the effect of noise; (2) to improve global search properties; and (3) to implement the algorithm on (highly) parallel machines. Our method results in a highly parallel algorithm which scales favorably with large numbers of processors. This is accomplished by efficiently incorporating the available information from a large population, thus significantly reducing the number of generations needed to adapt the covariance matrix. The original version of the CMA-ES was designed to reliably adapt the covariance matrix in small populations but it cannot exploit large populations efficiently. Our modifications scale up the efficiency to population sizes of up to 10n, where n is the problem dimension. This method has been applied to a large number of test problems, demonstrating that in many cases the CMA-ES can be advanced from quadratic to linear time complexity.

Ventricular tachycardias occurring in the chronic phase of myocardial infarction are caused by reentry. Areas of slow conduction, facilitating reentry, are often found in the infarcted zone. The purpose of this study was to elucidate the mechanism of slow conduction in the chronic infarcted human heart. Spread of activation was studied in infarcted papillary muscles from hearts of patients who underwent heart transplantation because of infarction. Recordings were carried out on 10 papillary muscles that were superfused in a tissue bath. High-resolution mapping was performed in areas revealing slow conduction. Activation delay between sites perpendicular to the fiber direction and 1.4 mm apart could be as long as 45 milliseconds. Analysis of activation times revealed that activation spread in tracts parallel to the fiber direction. Conduction velocity in the tracts was between 0.6 and 1 m/s. Although tracts were separated from each other over distances up to 8 mm, they often connected with each other at one or more sites, forming a complex network of connected tracts. In this network, wave fronts could travel perpendicular to the fiber direction. Separation of tracts was due to collagenous septa. At sites where tracts were interconnected, the collagenous barriers were interrupted. Slow conduction perpendicular to the fiber direction in infarcted myocardial tissue is caused by a "zigzag" course of activation at high speed. Activation proceeds along pathways lengthened by branching and merging bundles of surviving myocytes ensheathed by collagenous septa.

In vivo description of ventricular tachycardia (VT) circuits is limited by insufficient spatiotemporal resolution. We used a novel high-resolution mapping technology to characterize the electrophysiological properties of the postinfarction reentrant VT circuit.