title: Patient-specific modeling of ventricular activation pattern using surface ECG-derived vectorcardiogram in bundle branch block.
abstract: Patient-specific computational models have promise to improve cardiac disease diagnosis and therapy planning. Here a new method is described to simulate left-bundle branch block (LBBB) and RV-paced ventricular activation patterns in three dimensions from non-invasive, routine clinical measurements. Activation patterns were estimated in three patients using vectorcardiograms (VCG) derived from standard 12-lead electrocardiograms (ECG). Parameters of a monodomain model of biventricular electrophysiology were optimized to minimize differences between the measured and computed VCG. Electroanatomic maps of local activation times measured on the LV and RV endocardial surfaces of the same patients were used to validate the simulated activation patterns. For all patients, the optimal estimated model parameters predicted a time-averaged mean activation dipole orientation within 6.7 ± 0.6° of the derived VCG. The predicted local activation times agreed within 11.5 ± 0.8 ms of the measured electroanatomic maps, on the order of the measurement accuracy.
authors.affiliation: Department of Bioengineering, University of California, La Jolla, CA 92093, USA.
authors.forename: Christopher T
authors.initials: CT
authors.lastname: Villongco
authors.affiliation: Department of Medicine (Cardiology), University of California, San Diego, CA 92093, USA; US Department of Veterans Affairs San Diego Healthcare System, San Diego, CA 92161, USA.
authors.forename: David E
authors.initials: DE
authors.lastname: Krummen
authors.affiliation: Department of Radiology, University of California, San Diego, CA 92093, USA; US Department of Veterans Affairs San Diego Healthcare System, San Diego, CA 92161, USA.
authors.forename: Paul
authors.initials: P
authors.lastname: Stark
authors.affiliation: Department of Bioengineering, University of California, La Jolla, CA 92093, USA; Department of Medicine (Cardiology), University of California, San Diego, CA 92093, USA.
authors.forename: Jeffrey H
authors.initials: JH
authors.lastname: Omens
authors.affiliation: Department of Bioengineering, University of California, La Jolla, CA 92093, USA; Department of Medicine (Cardiology), University of California, San Diego, CA 92093, USA. Electronic address: amcculloch@ucsd.edu.
authors.forename: Andrew D
authors.initials: AD
authors.lastname: McCulloch
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D018780:Body Surface Potential Mapping / Q000379:methods; D002037:Bundle-Branch Block / Q000150:complications / Q000175:diagnosis / Q000503:physiopathology*; D003198:Computer Simulation; D004562:Electrocardiography / Q000379:methods*; D006329:Heart Conduction System / Q000503:physiopathology*; D006801:Humans; D008297:Male; D008955:Models, Cardiovascular; D009200:Myocardial Contraction; D066230:Patient-Specific Modeling; D014672:Vectorcardiography / Q000379:methods*; D018754:Ventricular Dysfunction / Q000175:diagnosis / Q000209:etiology / Q000503:physiopathology*
keywords: Monodomain model; Patient-specific model; Vectorcardiogram
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