Modeling Left Ventricular Blood Flow Using Smoothed Particle Hydrodynamics

• Authors: Andres Caballero, Georgia Institute of Technology; Wenbin Mao, Georgia Institute of Technology; Liang Liang, Georgia Institute of Technology; John Oshinski, Emory University; Charles Primiano, Hartford Hospital; Raymond McKay, Hartford Hospital; Susheel Kodali, Columbia University; Wei Sun, Georgia Institute of Technology
• Journal Title: Cardiovascular Engineering and Technology
• Volume: Volume 8, Number 4
• Publisher: Springer (part of Springer Nature): Springer Open Choice Hybrid Journals | 2017-12-01, Pages 465-479
• Type of Work: Article | Post-print: After Peer Review
• Publisher DOI: http://doi.org/10.1007/s13239-017-0324-z
• Subjects: Health Sciences, Epidemiology; Engineering, Biomedical
• Keywords: Science & Technology; Life Sciences & Biomedicine; Technology; Cardiac & Cardiovascular Systems; Engineering, Biomedical; Cardiovascular System & Cardiology; Engineering; Left ventricle; Smoothed particle hydrodynamics; Hemodynamics; Computational fluid dynamics; Cardiac magnetic resonance; COMPUTATIONAL FLUID-DYNAMICS; VIVO MRI DATA; MAGNETIC-RESONANCE; LEFT-HEART; NUMERICAL-SIMULATION; UNSTEADY-FLOW; VISCOUS FLOWS; WHOLE HEART; SPH METHOD; 4D FLOW

Abstract

This study aims to investigate the capability of smoothed particle hydrodynamics (SPH), a fully Lagrangian mesh-free method, to simulate the bulk blood flow dynamics in two realistic left ventricular (LV) models. Three dimensional geometries and motion of the LV, proximal left atrium and aortic root are extracted from cardiac magnetic resonance imaging and multi-slice computed tomography imaging data. SPH simulation results are analyzed and compared with those obtained using a traditional finite volume-based numerical method, and to in vivo phase contrast magnetic resonance imaging and echocardiography data, in terms of the large-scale blood flow phenomena usually clinically measured. A quantitative comparison of the velocity fields and global flow parameters between the in silico models and the in vivo data shows a reasonable agreement, given the inherent uncertainties and limitations in the modeling and imaging techniques. The results indicate the capability of SPH as a promising tool for predicting clinically relevant large-scale LV flow information.