title: Effects of fibrosis morphology on reentrant ventricular tachycardia inducibility and simulation fidelity in patient-derived models.
abstract: Myocardial fibrosis detected via delayed-enhanced magnetic resonance imaging (MRI) has been shown to be a strong indicator for ventricular tachycardia (VT) inducibility. However, little is known regarding how inducibility is affected by the details of the fibrosis extent, morphology, and border zone configuration. The objective of this article is to systematically study the arrhythmogenic effects of fibrosis geometry and extent, specifically on VT inducibility and maintenance. We present a set of methods for constructing patient-specific computational models of human ventricles using in vivo MRI data for patients suffering from hypertension, hypercholesterolemia, and chronic myocardial infarction. Additional synthesized models with morphologically varied extents of fibrosis and gray zone (GZ) distribution were derived to study the alterations in the arrhythmia induction and reentry patterns. Detailed electrophysiological simulations demonstrated that (1) VT morphology was highly dependent on the extent of fibrosis, which acts as a structural substrate, (2) reentry tended to be anchored to the fibrosis edges and showed transmural conduction of activations through narrow channels formed within fibrosis, and (3) increasing the extent of GZ within fibrosis tended to destabilize the structural reentry sites and aggravate the VT as compared to fibrotic regions of the same size and shape but with lower or no GZ. The approach and findings represent a significant step toward patient-specific cardiac modeling as a reliable tool for VT prediction and management of the patient. Sensitivities to approximation nuances in the modeling of structural pathology by image-based reconstruction techniques are also implicated.
authors.affiliation: EECS Department, College of Engineering, University of Toledo, Toledo, OH, USA.
authors.forename: Jordan
authors.initials: J
authors.lastname: Ringenberg
authors.affiliation: Department of Engineering, Norfolk State University, Norfolk, VA, USA.
authors.forename: Makarand
authors.initials: M
authors.lastname: Deo
authors.affiliation: Cardiac Electrophysiology Unit, Hospital Clínico San Carlos, Madrid, Spain. ; Atherothrombosis, Imaging and Epidemiology Department, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain.
authors.forename: David
authors.initials: D
authors.lastname: Filgueiras-Rama
authors.affiliation: Atherothrombosis, Imaging and Epidemiology Department, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain. ; Department of Cardiology, Hospital Universitario Quirón, Universidad Europea de Madrid, Madrid, Spain.
authors.forename: Gonzalo
authors.initials: G
authors.lastname: Pizarro
authors.affiliation: Atherothrombosis, Imaging and Epidemiology Department, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain.
authors.forename: Borja
authors.initials: B
authors.lastname: Ibañez
authors.affiliation: Cardiology Department, Hospital Universitario La Paz, Madrid, Spain.
authors.forename: Rafael
authors.initials: R
authors.lastname: Peinado
authors.affiliation: Cardiology Department, Hospital Universitario La Paz, Madrid, Spain.
authors.forename: José L
authors.initials: JL
authors.lastname: Merino
authors.affiliation: Center for Arrhythmia Research, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA.
authors.forename: Omer
authors.initials: O
authors.lastname: Berenfeld
authors.affiliation: EECS Department, College of Engineering, University of Toledo, Toledo, OH, USA.
authors.forename: Vijay
authors.initials: V
authors.lastname: Devabhaktuni
keywords: arrhythmia; cardiac MRI; image-based 3D ventricular modeling; ventricular tachycardia