title: Assessment of regularization techniques for electrocardiographic imaging.
abstract: A widely used approach to solving the inverse problem in electrocardiography involves computing potentials on the epicardium from measured electrocardiograms (ECGs) on the torso surface. The main challenge of solving this electrocardiographic imaging (ECGI) problem lies in its intrinsic ill-posedness. While many regularization techniques have been developed to control wild oscillations of the solution, the choice of proper regularization methods for obtaining clinically acceptable solutions is still a subject of ongoing research. However there has been little rigorous comparison across methods proposed by different groups. This study systematically compared various regularization techniques for solving the ECGI problem under a unified simulation framework, consisting of both 1) progressively more complex idealized source models (from single dipole to triplet of dipoles), and 2) an electrolytic human torso tank containing a live canine heart, with the cardiac source being modeled by potentials measured on a cylindrical cage placed around the heart. We tested 13 different regularization techniques to solve the inverse problem of recovering epicardial potentials, and found that non-quadratic methods (total variation algorithms) and first-order and second-order Tikhonov regularizations outperformed other methodologies and resulted in similar average reconstruction errors.
authors.affiliation: Jozef Stefan Institute, Ljubljana, Slovenia.
authors.forename: Matija
authors.initials: M
authors.lastname: Milanič
authors.affiliation: Institute of Mathematics, Physics, and Mechanics, Ljubljana, Slovenia. Electronic address: vojko.jazbinsek@imfm.si.
authors.forename: Vojko
authors.initials: V
authors.lastname: Jazbinšek
authors.affiliation: Scientific Computing and Imaging (SCI) Institute, University of Utah, Salt Lake City, UT, USA.
authors.forename: Robert S
authors.initials: RS
authors.lastname: Macleod
authors.affiliation: Department of Electrical and Computer Engineering, Northeastern University, Boston, MA, USA.
authors.forename: Dana H
authors.initials: DH
authors.lastname: Brooks
authors.affiliation: Jozef Stefan Institute, Ljubljana, Slovenia.
authors.forename: Rok
authors.initials: R
authors.lastname: Hren
mesh_terms: D000200:Action Potentials / Q000502:physiology*; D018780:Body Surface Potential Mapping / Q000379:methods*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D006329:Heart Conduction System / Q000502:physiology*; D006339:Heart Rate / Q000502:physiology*; D006801:Humans; D008955:Models, Cardiovascular; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
keywords: Conjugate gradient; Electrocardiographic inverse problem; MINRES method; Tikhonov regularization; Total variation; Truncated singular value decomposition; ν-method