Fluid-structure Interaction in the Cerebral Venous Transverse Sinus

The biomechanics of the cerebral venous system plays an important role in determining blood flow to the brain. Computational approaches to help elucidate the role of the cerebral venous system in health and disease have largely focused on lumped-parameter models and one-dimensional computational fluid dynamics simulations. To expand upon the prior work, and to investigate the possible role of cerebral venous collapse in normal physiology and pathological conditions, we developed a fluid-structure interaction (FSI) model of the cerebral venous transverse sinus (TS), coupled to a lumpedparameter representation of the upstream cerebral circulation to provide boundary conditions for the FSI simulation. We simulated the effects of local venous hemodynamics on the TS distention and investigated TS vascular collapse under increased intracranial pressure, as has been hypothesized in the pathogenesis of idiopathic intracranial hypertension. Our baseline simulations reproduced pressures and flows in the cerebral venous system that compared favorably with what has been reported in the literature. The FSI simulations under increased intracranial pressure showed a decreased venous flow through and progressive collapse of the TS veins. Our simulations captured the dynamic behavior of the vascular collapse and may help shed light on the interactions between the cerebrovascular and cerebrospinal fluid spaces in health and disease.

[1]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[2]  Yuri Bazilevs,et al.  CHALLENGES AND DIRECTIONS IN COMPUTATIONAL FLUID–STRUCTURE INTERACTION , 2013 .

[3]  Nina Sundström,et al.  Postural effects on intracranial pressure: modeling and clinical evaluation. , 2013, Journal of applied physiology.

[4]  J. Reddy An introduction to nonlinear finite element analysis , 2004 .

[5]  Soon-Sung Kwon,et al.  A novel patient-specific model to compute coronary fractional flow reserve. , 2014, Progress in biophysics and molecular biology.

[6]  M. Ursino,et al.  A new hemodynamic model for the study of cerebral venous outflow. , 2015, American journal of physiology. Heart and circulatory physiology.

[7]  S. Schreiber,et al.  Postural dependency of the cerebral venous outflow , 2000, The Lancet.

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

[9]  J. P. Holt,et al.  Flow through collapsible tubes and through in situ veins. , 1969, IEEE transactions on bio-medical engineering.

[10]  S. Schultz Principles of Neural Science, 4th ed. , 2001 .

[11]  M. Koji,et al.  Introduction to Nonlinear Finite Element Analysis , 2008 .

[12]  Hsiao-Ying Shadow Huang,et al.  Constitutive modeling of jugular vein-derived venous valve leaflet tissues. , 2017, Journal of the mechanical behavior of biomedical materials.

[13]  R G Mark,et al.  Numerical analysis of blood flow through a stenosed artery using a coupled multiscale simulation method , 2000, Computers in Cardiology 2000. Vol.27 (Cat. 00CH37163).

[14]  Lucas O. Müller,et al.  Enhanced global mathematical model for studying cerebral venous blood flow. , 2014, Journal of biomechanics.

[15]  R. Jensen,et al.  Understanding idiopathic intracranial hypertension: mechanisms, management, and future directions , 2016, The Lancet Neurology.

[16]  Thomas Brinker,et al.  A new look at cerebrospinal fluid circulation , 2014, Fluids and Barriers of the CNS.