title: Fast data-driven calibration of a cardiac electrophysiology model from images and ECG.
abstract: Recent advances in computational electrophysiology (EP) models make them attractive for clinical use. We propose a novel data-driven approach to calibrate an EP model from standard 12-lead electrocardiograms (ECG), which are in contrast to invasive or dense body surface measurements widely available in clinical routine. With focus on cardiac depolarization, we first propose an efficient forward model of ECG by coupling a mono-domain, Lattice-Boltzmann model of cardiac EP to a boundary element formulation of body surface potentials. We then estimate a polynomial regression to predict myocardium, left ventricle and right ventricle endocardium electrical diffusion from QRS duration and ECG electrical axis. Training was performed on 4,200 ECG simulations, calculated in aproximately 3 s each, using different diffusion parameters on 13 patient geometries. This allowed quantifying diffusion uncertainty for given ECG parameters due to the ill-posed nature of the ECG problem. We show that our method is able to predict myocardium diffusion within the uncertainty range, yielding a prediction error of less than 5 ms for QRS duration and 2 degree for electrical axis. Prediction results compared favorably with those obtained with a standard optimization procedure, while being 60 times faster. Our data-driven model can thus constitute an efficient preliminary step prior to more refined EP personalization.
authors: Siemens Corporation, Corporate Technology, Imaging and Computer Vision, Princeton, NJ, USA.
authors: Oliver
authors: O
authors: Zettinig
authors: Siemens Corporation, Corporate Technology, Imaging and Computer Vision, Princeton, NJ, USA.
authors: Tommaso
authors: T
authors: Mansi
authors: Siemens Corporation, Corporate Technology, Imaging and Computer Vision, Princeton, NJ, USA.
authors: Bogdan
authors: B
authors: Georgescu
authors: University Hospital Heidelberg, Department of Internal Medicine III-Cardiology, Angiology and Pneumology, Heidelberg, Germany.
authors: Elham
authors: E
authors: Kayvanpour
authors: University Hospital Heidelberg, Department of Internal Medicine III-Cardiology, Angiology and Pneumology, Heidelberg, Germany.
authors: Farbod
authors: F
authors: Sedaghat-Hamedani
authors: University Hospital Heidelberg, Department of Internal Medicine III-Cardiology, Angiology and Pneumology, Heidelberg, Germany.
authors: Ali
authors: A
authors: Amr
authors: University Hospital Heidelberg, Department of Internal Medicine III-Cardiology, Angiology and Pneumology, Heidelberg, Germany.
authors: Jan
authors: J
authors: Haas
authors: University Hospital Heidelberg, Department of Internal Medicine III-Cardiology, Angiology and Pneumology, Heidelberg, Germany.
authors: Henning
authors: H
authors: Steen
authors: University Hospital Heidelberg, Department of Internal Medicine III-Cardiology, Angiology and Pneumology, Heidelberg, Germany.
authors: Benjamin
authors: B
authors: Meder
authors: University Hospital Heidelberg, Department of Internal Medicine III-Cardiology, Angiology and Pneumology, Heidelberg, Germany.
authors: Hugo
authors: H
authors: Katus
authors: Computer Aided Medical Procedures, Technische Universitkit Miinchen, Germany.
authors: Nassir
authors: N
authors: Navab
authors: Siemens Corporation, Corporate Technology, Imaging and Computer Vision, Princeton, NJ, USA.
authors: Ali
authors: A
authors: Kamen
authors: Siemens Corporation, Corporate Technology, Imaging and Computer Vision, Princeton, NJ, USA.
authors: Dorin
authors: D
authors: Comaniciul
mesh_terms: D000465:Algorithms; D018780:Body Surface Potential Mapping / Q000379:methods*; D002138:Calibration; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004562:Electrocardiography / Q000379:methods*; D006329:Heart Conduction System / Q000033:anatomy & histology* / Q000502:physiology*; D008955:Models, Cardiovascular; D057285:Precision Medicine / Q000379:methods