Title :
Transmural Imaging of Ventricular Action Potentials and Post-Infarction Scars in Swine Hearts
Author :
Linwei Wang ; Dawoud, F. ; Sai-Kit Yeung ; Pengcheng Shi ; Wong, K.C.L. ; Huafeng Liu ; Lardo, A.C.
Author_Institution :
Comput. Biomed. Lab., Rochester Inst. of Technol., Rochester, NY, USA
Abstract :
The problem of using surface data to reconstruct transmural electrophysiological (EP) signals is intrinsically ill-posed without a unique solution in its unconstrained form. Incorporating physiological spatiotemporal priors through probabilistic integration of dynamic EP models, we have previously developed a Bayesian approach to transmural electrophysiological imaging (TEPI) using body-surface electrocardiograms. In this study, we generalize TEPI to using electrical signals collected from heart surfaces, and we test its feasibility on two pre-clinical swine models provided through the STACOM 2011 EP simulation Challenge. Since this new application of TEPI does not require whole-body imaging, there may be more immediate potential in EP laboratories where it could utilize catheter mapping data and produce transmural information for therapy guidance. Another focus of this study is to investigate the consistency among three modalities in delineating scar after myocardial infarction: TEPI, electroanatomical voltage mapping (EAVM), and magnetic resonance imaging (MRI). Our preliminary data demonstrate that, compared to the low-voltage scar area in EAVM, the 3-D electrical scar volume detected by TEPI is more consistent with anatomical scar volume delineated in MRI. Furthermore, TEPI could complement anatomical imaging by providing EP functional features related to both scar and healthy tissue.
Keywords :
Bayes methods; bioelectric phenomena; biomedical MRI; cardiovascular system; catheters; electrocardiography; image reconstruction; medical image processing; muscle; patient treatment; physiological models; physiology; 3D electrical scar volume detection; Bayesian approach; EP functional features; STACOM 2011 EP simulation; TEPI; anatomical imaging; anatomical scar volume; body-surface electrocardiograms; catheter mapping data; dynamic EP models; electrical signals; electroanatomical voltage mapping; healthy tissue; heart surfaces; low-voltage scar area; magnetic resonance imaging; myocardial infarction; physiological spatiotemporal; post-infarction scars; probabilistic integration; scar delineation; scar tissue; surface data; therapy guidance; transmural electrophysiological imaging; transmural electrophysiological signal reconstruction; transmural information; ventricular action potentials; whole-body imaging; Computational modeling; Equations; Heart; Magnetic resonance imaging; Mathematical model; Myocardium; Solid modeling; Bayesian estimation; electroanatomical mapping; inverse problem of electrocardiography; magnetic resonance imaging (MRI); post-infarction scar; transmural electrophysiological imaging; Action Potentials; Algorithms; Animals; Bayes Theorem; Cicatrix; Electrophysiologic Techniques, Cardiac; Heart; Heart Ventricles; Imaging, Three-Dimensional; Magnetic Resonance Imaging; Myocardial Infarction; Myocardium; Signal Processing, Computer-Assisted; Swine;
Journal_Title :
Medical Imaging, IEEE Transactions on
DOI :
10.1109/TMI.2012.2236567