Mathematical Modelling of Cerebral Blood Circulation and Cerebral Autoregulation: Towards Preventing Intracranial Hemorrhages in Preterm Newborns

Impaired cerebral autoregulation leads to fluctuations in cerebral blood flow, which can be especially dangerous for immature brain of preterm newborns. In this paper, two mathematical models of cerebral autoregulation are discussed. The first one is an enhancement of a vascular model proposed by Piechnik et al. We extend this model by adding a polynomial dependence of the vascular radius on the arterial blood pressure and adjusting the polynomial coefficients to experimental data to gain the autoregulation behavior. Moreover, the inclusion of a Preisach hysteresis operator, simulating a hysteretic dependence of the cerebral blood flow on the arterial pressure, is tested. The second model couples the blood vessel system model by Piechnik et al. with an ordinary differential equation model of cerebral autoregulation by Ursino and Lodi. An optimal control setting is proposed for a simplified variant of this coupled model. The objective of the control is the maintenance of the autoregulatory function for a wider range of the arterial pressure. The control can be interpreted as the effect of a medicament changing the cerebral blood flow by, for example, dilation of blood vessels. Advanced numerical methods developed by the authors are applied for the numerical treatment of the control problem.

[1]  W. Marsden I and J , 2012 .

[2]  Martin Brokate,et al.  Hysteretic Aspects of CO 2 Sequestration Modelling , 2012 .

[3]  Varvara Turova,et al.  Approximation schemes for solving disturbed control problems with non-terminal time and state constraints , 2012 .

[4]  S. Harigopal,et al.  Neurology: Neonatology Questions and Controversies , 2013 .

[5]  Y. Tzeng,et al.  Cerebrovascular Regulation During Transient Hypotension and Hypertension in Humans , 2010, Hypertension.

[6]  R. Hunt,et al.  Neurology – Neonatology Questions and Controversies , 2009 .

[7]  M. Ursino,et al.  A simple mathematical model of the interaction between intracranial pressure and cerebral hemodynamics. , 1997, Journal of applied physiology.

[8]  Tutut Herawan,et al.  Computational and mathematical methods in medicine. , 2006, Computational and mathematical methods in medicine.

[9]  Nikolai D. Botkin,et al.  Stable Numerical Schemes for Solving Hamilton-Jacobi-Bellman-Isaacs Equations , 2011, SIAM J. Sci. Comput..

[10]  VZ Marmarelis,et al.  Linear and Nonlinear Modeling of Cerebral Flow Autoregulation Using Principal Dynamic Modes , 2012, The open biomedical engineering journal.

[11]  Judy L. LeFlore,et al.  Clinical Factors Influencing Blood Pressure in the Neonate , 2002 .

[12]  Marek Czosnyka,et al.  Cerebral autoregulatory response depends on the direction of change in perfusion pressure. , 2009, Journal of neurotrauma.

[13]  Rune Aaslid,et al.  Asymmetric Dynamic Cerebral Autoregulatory Response to Cyclic Stimuli , 2007, Stroke.

[14]  R. Panerai,et al.  Linear and nonlinear analysis of human dynamic cerebral autoregulation. , 1999, American journal of physiology. Heart and circulatory physiology.

[15]  M. Olufsen,et al.  Dynamics of cerebral blood flow regulation explained using a lumped parameter model. , 2002, American journal of physiology. Regulatory, integrative and comparative physiology.

[16]  D. K. Williams,et al.  The Effects of Hypercapnia on Cerebral Autoregulation in Ventilated Very Low Birth Weight Infants , 2005, Pediatric Research.

[17]  R. Stephenson A and V , 1962, The British journal of ophthalmology.

[18]  Frans N van de Vosse,et al.  A lumped parameter model of cerebral blood flow control combining cerebral autoregulation and neurovascular coupling. , 2012, American journal of physiology. Heart and circulatory physiology.

[19]  S. Sherwin,et al.  Reduced modelling of blood flow in the cerebral circulation: Coupling 1‐D, 0‐D and cerebral auto‐regulation models , 2008 .

[20]  Stefan K. Piechnik,et al.  Modelling vascular reactivity to investigate the basis of the relationship between cerebral blood volume and flow under CO2 manipulation , 2008, NeuroImage.