Original Research ARTICLE
Bond Graph Model of Cerebral Circulation: Towards Clinically Feasible Systemic Blood Flow Simulations
- 1Auckland Bioengineering Institute, University of Auckland, New Zealand
- 2Laboratório Nacional de Computação Científica (LNCC), Brazil
- 3Laboratório Nacional de Computação Científica (LNCC), Brazil
- 4Department of Structural Engineering, Norwegian University of Science and Technology, Norway
We propose a detailed CellML model of the human cerebral circulation that runs faster than real time on a desktop computer and is designed for use in clinical settings when the speed of response is important. A lumped parameter mathematical model, which is based on a one-dimensional formulation of the flow of an incompressible fluid in distensible vessels, is constructed using a bond graph formulation to ensure mass conservation and energy conservation. The model includes arterial vessels with geometric and anatomical data based on the ADAN circulation model. The peripheral beds are represented by lumped parameter compartments. We compare the hemodynamics predicted by the bond graph formulation of the cerebral circulation with that given by a classical one-dimensional Navier-Stokes model working on top of the whole-body ADAN model. Outputs from the bond graph model, including the pressure and flow signatures and blood volumes, are compared with physiological data.
Keywords: Cardiovascular System, circulation model, Bond graph, CellML, OpenCOR, ADAN model, 0D model, Blood flow
Received: 26 Nov 2017;
Accepted: 13 Feb 2018.
Edited by:Ghassan S. Kassab, California Medical Innovations Institute, United States
Reviewed by:Tim David, University of Canterbury, New Zealand
Steve McKeever, Uppsala University, Sweden
Copyright: © 2018 Safaei, Blanco, Muller, Hellevik and Hunter. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Dr. Soroush Safaei, University of Auckland, Auckland Bioengineering Institute, Auckland, 1010, New Zealand, firstname.lastname@example.org