A toolkit for forward/inverse problems in electrocardiography within the SCIRun problem solving environment

Abstract

Computational modeling in electrocardiography often requires the examination of cardiac forward and inverse problems in order to non-invasively analyze physiological events that are otherwise inaccessible or unethical to explore. The study of these models can be performed in the open-source SCIRun problem solving environment developed at the Center for Integrative Biomedical Computing (CIBC). A new toolkit within SCIRun provides researchers with essential frameworks for constructing and manipulating electrocardiographic forward and inverse models in a highly efficient and interactive way. The toolkit contains sample networks, tutorials and documentation which direct users through SCIRun-specific approaches in the assembly and execution of these specific problems.

Generation of combined-modality tetrahedral meshes

“…For the ECG model [1], recorded, epicardial potentials from a canine heart were mapped onto the heart surface of the MRI by means of registration. Using the Forward/Inverse Toolbox in SCIRun, the torso surface potentials were solved for and error metrics of percent error, correlation coefficient, and RMS error were calculated within MatLab.…”

“…Specifically, it could advance applications of cardiac modeling like the electrocardiography (ECG) inverse and forward problems [1] or the placement of Implantable Cardiac Defibrillators (ICDs) [2] given the close proximity of the sternum, ribcage and bones to the heart.…”

Physics-driven Spatiotemporal Regularization for High-dimensional Predictive Modeling: A Novel Approach to Solve the Inverse ECG Problem

“…5. The data of electric potentials (whose recording length is a complete cycle of heartbeat and t ranges from 0ms to 1000 ms) on the heart and body surfaces, and the torso-heart geometry are obtained from the Center for Integrative Biomedical Computing (CIBC) at the University of Utah28. In this torso-heart geometry, the heart surface consists of 257 nodes and 510 triangles, while the torso surface is formed by 771 nodes and 1538 triangles.…”

Electrical and Anatomical Imaging of Arrhythmogenic Substrates for Scar-related Ventricular Tachycardia

“…Triangulated mesh of the heart and torso were derived from the CMR images. Given the geometrical models, a forward operator that relates ventricular epicardial and endocardial electrograms to body-surface ECG was obtained using the open-source SCIRun toolkit [12]. The inverse solution was calculated at each time instant using a simple second-order Tikhonov regularization to obtain electrograms on the both epicardium and endocardium:…”