Abstract
The movement of cerebrospinal fluid (CSF) is linked to the cardiovascular and respiratory systems. The heart not only drives blood flow but is also at the origin of CSF pulsation through the expansion and contraction of cerebral blood vessels. Respiration modulates this cardiovascular action while also directly influencing spinal subarachnoid space (SAS) volume. CSF dynamics may be altered by pathologies such as hydrocephalus, Chiari malformation, syringomyelia and glioblastoma, and, in turn, dynamics of the CSF can be analysed to aid in disease diagnosis and prognosis. Several reviews delineate the current understanding of CSF motion [1–3]. This chapter describes the basic approach of and trends in computational fluid dynamics (CFD) modelling of CSF flow.
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References
Hladky, S.B., Barrand, M.A.: Mechanisms of fluid movement into, through and out of the brain: evaluation of the evidence. Fluids Barriers CNS. 11(1), 26 (2014)
Linninger, A.A., Tangen, K., Hsu, C.-Y., Frim, D.: Cerebrospinal fluid mechanics and its coupling to cerebrovascular dynamics. Annu. Rev. Fluid Mech. 48(1), 219–257 (2016)
Brinker, T., Stopa, E., Morrison, J., Klinge, P.: A new look at cerebrospinal fluid circulation. Fluids Barriers CNS. 11, 10 (2014)
Bloomfield, I.G., Johnston, I.H., Bilston, L.E.: Effects of proteins, blood cells and glucose on the viscosity of cerebrospinal fluid. Pediatr. Neurosurg. 28(5), 246–251 (1998)
Brydon, H.L., Hayward, R., Harkness, W., Bayston, R.: Physical properties of cerebrospinal fluid of relevance to shunt function. 1: the effect of protein upon CSF viscosity. Br. J. Neurosurg. 9(5), 639–644 (1995)
Jacobson, E.E., Fletcher, D.F., Morgan, M.K., Johnston, I.H.: Fluid dynamics of the cerebral aqueduct. Pediatr. Neurosurg. 24(5), 229–236 (1996)
Caiazzo, A., Vignon-Clementel, I.E.: Mathematical modeling of blood flow in the cardiovascular system. In: Sack, I., Schaeffter, T. (eds.) Quantification of Biophysical Parameters in Medical Imaging, pp. 45–70. Springer, Cham (2018)
Ballester, M.A.G., Zisserman, A., Brady, M.: Segmentation and measurement of brain structures in MRI including confidence bounds. Med. Image Anal. 4(3), 189–200 (2000)
Gupta, S., Soellinger, M., Boesiger, P., Poulikakos, D., Kurtcuoglu, V.: Three-dimensional computational modeling of subject-specific cerebrospinal fluid flow in the subarachnoid space. J. Biomech. Eng. 131(2), 021010 (2009)
Gupta, S., Soellinger, M., Grzybowski, D.M., Boesiger, P., Biddiscombe, J., Poulikakos, D., Kurtcuoglu, V.: Cerebrospinal fluid dynamics in the human cranial subarachnoid space: an overlooked mediator of cerebral disease. I. Computational model. J. R. Soc. Interface. 7(49), 1195–1204 (2010)
Heidari Pahlavian, S., Yiallourou, T., Tubbs, R.S., Bunck, A.C., Loth, F., Goodin, M., Raisee, M., Martin, B.A.: The impact of spinal cord nerve roots and denticulate ligaments on cerebrospinal fluid dynamics in the cervical spine. PLoS One. 9(4), e91888 (2014)
Sass, L.R., Khani, M., Natividad, G.C., Tubbs, R.S., Baledent, O., Martin, B.A.: A 3D subject-specific model of the spinal subarachnoid space with anatomically realistic ventral and dorsal spinal cord nerve rootlets. Fluids Barriers CNS. 14(1), 36 (2017)
Cloyd, M.W., Low, F.N.: Scanning electron microscopy of the subarachnoid space in the dog. I. Spinal cord levels. J. Comp. Neurol. 153(4), 325–368 (1974)
Allen, D.J., Low, F.N.: Scanning electron microscopy of the subarachnoid space in the dog. III. Cranial levels. J. Comp. Neurol. 161(4), 515–539 (1975)
Killer, H.E., Laeng, H.R., Flammer, J., Groscurth, P.: Architecture of arachnoid trabeculae, pillars, and septa in the subarachnoid space of the human optic nerve: anatomy and clinical considerations. Br. J. Ophthalmol. 87(6), 777–781 (2003)
Scott, G.G., Coats, B.: Microstructural characterization of the pia-arachnoid complex using optical coherence tomography. IEEE Trans. Med. Imaging. 34(7), 1452–1459 (2015)
Mortazavi, M.M., Quadri, S.A., Khan, M.A., Gustin, A., Suriya, S.S., Hassanzadeh, T., Fahimdanesh, K.M., Adl, F.H., Fard, S.A., Taqi, M.A., Armstrong, I., Martin, B.A., Tubbs, R.S.: Subarachnoid trabeculae: a comprehensive review of their embryology, histology, morphology, and surgical significance. World Neurosurg. 111, 279–290 (2018)
Vandenwesthuizen, J., Duplessis, J.P.: Quantification of unidirectional fiber bed permeability. J. Compos. Mater. 28(7), 619–637 (1994)
Chai, Z.H., Shi, B.C., Lu, J.H., Guo, Z.L.: Non-Darcy flow in disordered porous media: a lattice Boltzmann study. Comput. Fluids. 39(10), 2069–2077 (2010)
Tully, B., Ventikos, Y.: Cerebral water transport using multiple-network poroelastic theory: application to normal pressure hydrocephalus. J. Fluid Mech. 667, 188–215 (2011)
Kang, Q.J., Zhang, D.X., Chen, S.Y.: Unified lattice Boltzmann method for flow in multiscale porous media. Phys. Rev. E. 66(5), 056307 (2002)
Lesage, D., Angelini, E.D., Bloch, I., Funka-Lea, G.: A review of 3D vessel lumen segmentation techniques: models, features and extraction schemes. Med. Image Anal. 13(6), 819–845 (2009)
Yushkevich, P.A., Piven, J., Hazlett, H.C., Smith, R.G., Ho, S., Gee, J.C., Gerig, G.: User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability. NeuroImage. 31(3), 1116–1128 (2006)
The Vascular Modeling Toolkit. Available from: www.vmtk.org
Jain, K.: Transition to turbulence in physiological flows: Direct numerical simulation of hemodynamics in intracranial aneurysms and cerebrospinal fluid hydrodynamics in the spinal canal. 2016, Universität Siegen
Almotiri, J., Elleithy, K., Elleithy, A.: Retinal vessels segmentation techniques and algorithms: a survey. Appl. Sci. 8(2), 155 (2018)
Simonovsky, M., et al.: A deep metric for multimodal registration. In: 19th International Conference on Medical Image Computing and Computer-Assisted Intervention. Springer, Athens, Greece (2016)
Akkus, Z., Galimzianova, A., Hoogi, A., Rubin, D.L., Erickson, B.J.: Deep learning for brain MRI segmentation: state of the art and future directions. J. Digit. Imaging. 30(4), 449–459 (2017)
Hjelle, Ø., Dæhlen, M.: Triangulations and applications. In: Mathematics and Visualization, p. 234. Springer-Verlag, Berlin/New York (2006)
De Boor, C.: A practical guide to splines. In: Applied Mathematical Sciences, Rev edn, p. 346. Springer. xviii, New York (2001)
Helgeland, A., Mardal, K.A., Haughton, V., Reif, B.A.: Numerical simulations of the pulsating flow of cerebrospinal fluid flow in the cervical spinal canal of a Chiari patient. J. Biomech. 47(5), 1082–1090 (2014)
Kurtcuoglu, V., Soellinger, M., Summers, P., Boomsma, K., Poulikakos, D., Boesiger, P., Ventikos, Y.: Computational investigation of subject-specific cerebrospinal fluid flow in the third ventricle and aqueduct of Sylvius. J. Biomech. 40(6), 1235–1245 (2007)
Stoverud, K.H., Langtangen, H.P., Ringstad, G.A., Eide, P.K., Mardal, K.A.: Computational investigation of cerebrospinal fluid dynamics in the posterior cranial fossa and cervical subarachnoid space in patients with Chiari I malformation. PLoS One. 11(10), e0162938 (2016)
Rutkowska, G., Haughton, V., Linge, S., Mardal, K.A.: Patient-specific 3D simulation of cyclic CSF flow at the craniocervical region. Am. J. Neuroradiol. 33(9), 1756–1762 (2012)
Jain, K., Ringstad, G., Eide, P.K., Mardal, K.A.: Direct numerical simulation of transitional hydrodynamics of the cerebrospinal fluid in Chiari I malformation: the role of cranio-vertebral junction. Int. J. Numer. Method Biomed. Eng. 33(9), (2017)
Stockman, H.W.: Effect of anatomical fine structure on the flow of cerebrospinal fluid in the spinal subarachnoid space. J. Biomech. Eng. 128(1), 106 (2005)
Mittal, R., Iaccarino, G.: Immersed boundary methods. Annu. Rev. Fluid Mech. 37, 239–261 (2005)
Haslam, M., Zamir, M.: Pulsatile flow in tubes of elliptic gross sections. Ann. Biomed. Eng. 26(5), 780–787 (1998)
Gupta, S., Poulikakos, D., Kurtcuoglu, V.: Analytical solution for pulsatile viscous flow in a straight elliptic annulus and application to the motion of the cerebrospinal fluid. Phys. Fluids. 20(9), (2008)
Boutsianis, E., Gupta, S., Boomsma, K., Poulikakos, D.: Boundary conditions by Schwarz-Christoffel mapping in anatomically accurate hemodynamics. Ann. Biomed. Eng. 36(12), 2068–2084 (2008)
Enzmann, D.R., Pelc, N.J.: Brain motion: measurement with phase-contrast MR imaging. Radiology. 185(3), 653–660 (1992)
Soellinger, M., Rutz, A.K., Kozerke, S., Boesiger, P.: 3D cine displacement-encoded MRI of pulsatile brain motion. Magn. Reson. Med. 61(1), 153–162 (2009)
Pahlavian, S.H., Oshinski, J., Zhong, X., Loth, F., Amini, R.: Regional quantification of brain tissue strain using displacement-encoding with stimulated echoes magnetic resonance imaging. J. Biomech. Eng. 140(8), (2018)
Shannon, C.E.: Communication in the presence of noise. Proceedings of the Institute of Radio Engineers. 37(1), 10–21 (1949)
Luke, H.D.: The origins of the sampling theorem. IEEE Commun. Mag. 37(4), 106–108 (1999)
Terem, I., Ni, W.W., Goubran, M., Rahimi, M.S., Zaharchuk, G., Yeom, K.W., Moseley, M.E., Kurt, M., Holdsworth, S.J.: Revealing sub-voxel motions of brain tissue using phase-based amplified MRI (aMRI). Magn. Reson. Med. 80, 2549 (2018)
Ma, Q., Ineichen, B.V., Detmar, M., Proulx, S.T.: Outflow of cerebrospinal fluid is predominantly through lymphatic vessels and is reduced in aged mice. Nat. Commun. 8(1), 1434 (2017)
Grzybowski, D.M., Herderick, E.E., Kapoor, K.G., Holman, D.W., Katz, S.E.: Human arachnoid granulations part I: a technique for quantifying area and distribution on the superior surface of the cerebral cortex. Cerebrospinal Fluid Res. 4, 6 (2007)
Holman, D.W., Kurtcuoglu, V., Grzybowski, D.M.: Cerebrospinal fluid dynamics in the human cranial subarachnoid space: an overlooked mediator of cerebral disease. II. In vitro arachnoid outflow model. J. R. Soc. Interface. 7(49), 1205–1218 (2010)
Eide, P.K., Vatnehol, S.A.S., Emblem, K.E., Ringstad, G.: Magnetic resonance imaging provides evidence of glymphatic drainage from human brain to cervical lymph nodes. Sci. Rep. 8(1), 7194 (2018)
Ma, Q., Ries, M., Decker, Y., Muller, A., Riner, C., Bucker, A., Fassbender, K., Detmar, M., Proulx, S.T.: Rapid lymphatic efflux limits cerebrospinal fluid flow to the brain. Acta Neuropathol. 137, 151 (2019)
Linge, S.O., Haughton, V., Lovgren, A.E., Mardal, K.A., Langtangen, H.P.: CSF flow dynamics at the craniovertebral junction studied with an idealized model of the subarachnoid space and computational flow analysis. Am. J. Neuroradiol. 31(1), 185–192 (2010)
Siyahhan, B., Knobloch, V., de Zelicourt, D., Asgari, M., Schmid Daners, M., Poulikakos, D., Kurtcuoglu, V.: Flow induced by ependymal cilia dominates near-wall cerebrospinal fluid dynamics in the lateral ventricles. J. R. Soc. Interface. 11(94), 20131189 (2014)
Xie, L.L., Kang, H.Y., Xu, Q.W., Chen, M.J., Liao, Y.H., Thiyagarajan, M., O'Donnell, J., Christensen, D.J., Nicholson, C., Iliff, J.J., Takano, T., Deane, R., Nedergaard, M.: Sleep drives metabolite clearance from the adult brain. Science. 342(6156), 373–377 (2013)
Rikhtegar, F., Edelman, E.R., Olgac, U., Poulikakos, D., Kurtcuoglu, V.: Drug deposition in coronary arteries with overlapping drug-eluting stents. J. Control. Release. 238, 1–9 (2016)
Rodi, W.: Turbulence modeling and simulation in hydraulics: a historical review. J. Hydraul. Eng. 143(5), (2017)
Jacobson, E.E., Fletcher, D.F., Morgan, M.K., Johnston, I.H.: Computer modelling of the cerebrospinal fluid flow dynamics of aqueduct stenosis. Med. Biol. Eng. Comput. 37(1), 59–63 (1999)
Fin, L., Grebe, R.: Three dimensional modeling of the cerebrospinal fluid dynamics and brain interactions in the aqueduct of sylvius. Comput. Methods Biomech. Biomed. Engin. 6(3), 163–170 (2003)
Kurtcuoglu, V., Poulikakos, D., Ventikos, Y.: Computational modeling of the mechanical behavior of the cerebrospinal fluid system. J. Biomech. Eng. 127(2), 264–269 (2005)
Du Boulay, G., O'Connell, J., Currie, J., Bostick, T., Verity, P.: Further investigations on pulsatile movements in the cerebrospinal fluid pathways. Acta Radiol. Diagn. 13(0), 496–523 (1972)
Kurtcuoglu, V., Soellinger, M., Summers, P., Poulikakos, D., Boesiger, P.: Mixing and modes of mass transfer in the third cerebral ventricle: a computational analysis. J. Biomech. Eng. 129(5), 695–702 (2007)
Cheng, S., Tan, K., Bilston, L.E.: The effects of the interthalamic adhesion position on cerebrospinal fluid dynamics in the cerebral ventricles. J. Biomech. 43(3), 579–582 (2010)
Howden, L., Giddings, D., Power, H., Aroussi, A., Vloeberghs, M., Garnett, M., Walker, D.: Three-dimensional cerebrospinal fluid flow within the human ventricular system. Comput. Methods Biomech. Biomed. Engin. 11(2), 123–133 (2008)
Bergsneider, M., Black, P.M., Klinge, P., Marmarou, A., Relkin, N.: Surgical management of idiopathic normal-pressure hydrocephalus. Neurosurgery. 57(3 Suppl), S29–S39; discussion ii--v (2005)
Gholampour, S., Fatouraee, N., Seddighi, A.S., Seddighi, A.: Numerical simulation of cerebrospinal fluid hydrodynamics in the healing process of hydrocephalus patients. J. Appl. Mech. Tech. Phys. 58(3), 386–391 (2017)
Demerdash, A., Rocque, B.G., Johnston, J., Rozzelle, C.J., Yalcin, B., Oskouian, R., Delashaw, J., Tubbs, R.S.: Endoscopic third ventriculostomy: a historical review. Br. J. Neurosurg. 31(1), 28–32 (2017)
Gholampour, S.: FSI simulation of CSF hydrodynamic changes in a large population of non-communicating hydrocephalus patients during treatment process with regard to their clinical symptoms. PLoS One. 13(4), e0196216 (2018)
Farnoush, A., Tan, K., Juge, L., Bilston, L.E., Cheng, S.: Effect of endoscopic third ventriculostomy on cerebrospinal fluid pressure in the cerebral ventricles. J. Clin. Neurosci. 23, 63–67 (2016)
Khani, M., Sass, L., Xing, T., Sharp, M.K., Balédent, O., Martin, B.: Anthropomorphic model of intrathecal cerebrospinal fluid dynamics within the spinal subarachnoid space: spinal cord nerve roots increase steady-streaming. J. Biomech. Eng. 140, 081012 (2018)
Elliott, N.S.J., Bertram, C.D., Martin, B.A., Brodbelt, A.R.: Syringomyelia: a review of the biomechanics. J. Fluids Struct. 40, 1–24 (2013)
Shaffer, N., Martin, B., Loth, F.: Cerebrospinal fluid hydrodynamics in type I Chiari malformation. Neurol. Res. 33(3), 247–260 (2011)
Loth, F., Yardimci, M.A., Alperin, N.: Hydrodynamic modeling of cerebrospinal fluid motion within the spinal cavity. J. Biomech. Eng. 123(1), 71–79 (2001)
The Visible Human Project. 1997 [cited 2011 February]; Available from: http://www.nlm.nih.gov/research/visible/visible_human.html
Stockman, H.W.: Effect of anatomical fine structure on the flow of cerebrospinal fluid in the spinal subarachnoid space. J. Biomech. Eng. 128(1), 106–114 (2006)
Sweetman, B., Linninger, A.A.: Cerebrospinal fluid flow dynamics in the central nervous system. Ann. Biomed. Eng. 39(1), 484–496 (2011)
Linninger, A.A., Xenos, M., Zhu, D.C., Somayaji, M.R., Kondapalli, S., Penn, R.D.: Cerebrospinal fluid flow in the normal and hydrocephalic human brain. IEEE Trans. Biomed. Eng. 54(2), 291–302 (2007)
Sweetman, B., Xenos, M., Zitella, L., Linninger, A.A.: Three-dimensional computational prediction of cerebrospinal fluid flow in the human brain. Comput. Biol. Med. 41(2), 67–75 (2011)
Yiallourou, T.I., Kroger, J.R., Stergiopulos, N., Maintz, D., Martin, B.A., Bunck, A.C.: Comparison of 4D phase-contrast MRI flow measurements to computational fluid dynamics simulations of cerebrospinal fluid motion in the cervical spine. PLoS One. 7(12), e52284 (2012)
Lindstrom, E.K., Schreiner, J., Ringstad, G.A., Haughton, V., Eide, P.K., Mardal, K.A.: Comparison of phase-contrast MR and flow simulations for the study of CSF dynamics in the cervical spine. Neuroradiol. J. 31(3), 292–298 (2018)
Clarke, E.C., Fletcher, D.F., Stoodley, M.A., Bilston, L.E.: Computational fluid dynamics modelling of cerebrospinal fluid pressure in Chiari malformation and syringomyelia. J. Biomech. 46(11), 1801–1809 (2013)
Heidari Pahlavian, S., Bunck, A.C., Loth, F., Shane Tubbs, R., Yiallourou, T., Kroeger, J.R., Heindel, W., Martin, B.A.: Characterization of the discrepancies between four-dimensional phase-contrast magnetic resonance imaging and in-silico simulations of cerebrospinal fluid dynamics. J. Biomech. Eng. 137(5), 051002 (2015)
Heidari Pahlavian, S., Bunck, A.C., Thyagaraj, S., Giese, D., Loth, F., Hedderich, D.M., Kroger, J.R., Martin, B.A.: Accuracy of 4D flow measurement of cerebrospinal fluid dynamics in the cervical spine: an in vitro verification against numerical simulation. Ann. Biomed. Eng. 44(11), 3202–3214 (2016)
Thyagaraj, S., Pahlavian, S.H., Sass, L.R., Loth, F., Vatani, M., Choi, J.W., Tubbs, R.S., Giese, D., Kroger, J.R., Bunck, A.C., Martin, B.A.: An MRI-compatible hydrodynamic simulator of cerebrospinal fluid motion in the cervical spine. IEEE Trans. Biomed. Eng. (2017)
Martin, B.A., Yiallourou, T.I., Pahlavian, S.H., Thyagaraj, S., Bunck, A.C., Loth, F., Sheffer, D.B., Kroger, J.R., Stergiopulos, N.: Inter-operator reliability of magnetic resonance image-based computational fluid dynamics prediction of cerebrospinal fluid motion in the cervical spine. Ann. Biomed. Eng. 44(5), 1524–1537 (2016)
Bunck, A.C., Kroger, J.R., Juttner, A., Brentrup, A., Fiedler, B., Schaarschmidt, F., Crelier, G.R., Schwindt, W., Heindel, W., Niederstadt, T., Maintz, D.: Magnetic resonance 4D flow characteristics of cerebrospinal fluid at the craniocervical junction and the cervical spinal canal. Eur. Radiol. 21(8), 1788–1796 (2011)
Bunck, A.C., Kroeger, J.R., Juettner, A., Brentrup, A., Fiedler, B., Crelier, G.R., Martin, B.A., Heindel, W., Maintz, D., Schwindt, W., Niederstadt, T.: Magnetic resonance 4D flow analysis of cerebrospinal fluid dynamics in Chiari I malformation with and without syringomyelia. Eur. Radiol. 22(9), 1860–1870 (2012)
Khani, M., Xing, T., Gibbs, C., Oshinski, J.N., Stewart, G.R., Zeller, J.R., Martin, B.A.: Nonuniform moving boundary method for computational fluid dynamics simulation of intrathecal cerebrospinal flow distribution in a cynomolgus monkey. J. Biomech. Eng. 139(8), (2017)
Gardner, W.J.: Hydrodynamic mechanism of Syringomyelia: its relationship to Myelocele. J. Neurol. Neurosurg. Psychiatry. 28, 247–259 (1965)
Williams, B.: On the pathogenesis of syringomyelia: a review. J. R. Soc. Med. 73(11), 798–806 (1980)
Lockey, P., Poots, G., Williams, B.: Theoretical aspects of the attenuation of pressure pulses within cerebrospinal-fluid pathways. Med. Biol. Eng. 13(6), 861–869 (1975)
Berkouk, K., Carpenter, P.W., Lucey, A.D.: Pressure wave propagation in fluid-filled co-axial elastic tubes, part 1: basic theory. J. Biomech. Eng. 125(6), 852–856 (2003)
Carpenter, P.W., Berkouk, K., Lucey, A.D.: Pressure wave propagation in fluid-filled co-axial elastic tubes, part 2: mechanisms for the pathogenesis of syringomyelia. J. Biomech. Eng. 125(6), 857–863 (2003)
Carpenter, P.W., Berkouk, K., Lucey, A.D.: A theoretical model of pressure wave propagation in the human spinal CSF system. Eng. Mech. 6(4/5), 213–228 (1999)
Bertram, C.D., Brodbelt, A.R., Stoodley, M.A.: The origins of syringomyelia: numerical models of fluid/structure interactions in the spinal cord. J. Biomech. Eng. 127(7), 1099–1109 (2005)
Elliott, N.S.J., Lockerby, D.A., Brodbelt, A.R.: The pathogenesis of syringomyelia: a re-evaluation of the elastic-jump hypothesis. J. Biomech. Eng. 131(4), 044503–1–6 (2009)
Chang, H.S., Nakagawa, H.: Hypothesis on the pathophysiology of syringomyelia based on simulation of cerebrospinal fluid dynamics. J. Neurol. Neurosurg. Psychiatry. 74(3), 344–347 (2003)
Bertram, C.D., Bilston, L.E., Stoodley, M.A.: Tensile radial stress in the spinal cord related to arachnoiditis or tethering: a numerical model. Med. Biol. Eng. Comput. 46(7), 701–707 (2008)
Bertram, C.D., Heil, M.: A poroelastic fluid/structure-interaction model of cerebrospinal fluid dynamics in the cord with syringomyelia and adjacent subarachnoid-space stenosis. J. Biomech. Eng. 139(1), (2017)
Heil, M., Bertram, C.D.: A poroelastic fluid-structure interaction model of syringomyelia. J. Fluid Mech. 809, 360–389 (2016)
Elliott, N.S., Lockerby, D.A., Brodbelt, A.R.: A lumped-parameter model of the cerebrospinal system for investigating arterial-driven flow in posttraumatic syringomyelia. Med. Eng. Phys. 33(7), 874–882 (2011)
Elliott, N.S.: Syrinx fluid transport: modeling pressure-wave-induced flux across the spinal pial membrane. J. Biomech. Eng. 134(3), 031006 (2012)
Elliott, N.S.J., Lucey, A.D., Lockerby, D.A., Brodbelt, A.R.: Fluid-structure interactions in a cylindrical layered wave guide with application in the spinal column to syringomyelia. J. Fluids Struct. 70, 464–499 (2017)
Cirovic, S., Lloyd, R., Jovanovik, J., Volk, H.A., Rusbridge, C.: Computer simulation of syringomyelia in dogs. BMC Vet. Res. 14(1), 82 (2018)
Cirovic, S.: A coaxial tube model of the cerebrospinal fluid pulse propagation in the spinal column. J. Biomech. Eng. 131(2), 021008 (2009)
Cirovic, S., Kim, M.: A one-dimensional model of the spinal cerebrospinal-fluid compartment. J. Biomech. Eng. 134(2), 021005 (2012)
Cheng, S., Fletcher, D., Hemley, S., Stoodley, M., Bilston, L.: Effects of fluid structure interaction in a three dimensional model of the spinal subarachnoid space. J. Biomech. 47(11), 2826–2830 (2014)
Cheng, S., Stoodley, M.A., Wong, J., Hemley, S., Fletcher, D.F., Bilston, L.E.: The presence of arachnoiditis affects the characteristics of CSF flow in the spinal subarachnoid space: a modelling study. J. Biomech. 45(7), 1186–1191 (2012)
Bilston, L.E., Fletcher, D.F., Stoodley, M.A.: Focal spinal arachnoiditis increases subarachnoid space pressure: a computational study. Clin. Biomech. 21(6), 579–584 (2006)
Roldan, A., Wieben, O., Haughton, V., Osswald, T., Chesler, N.: Characterization of CSF hydrodynamics in the presence and absence of tonsillar ectopia by means of computational flow analysis. Am. J. Neuroradiol. 30(5), 941–946 (2009)
Linge, S.O., Haughton, V., Lovgren, A.E., Mardal, K.A., Helgeland, A., Langtangen, H.P.: Effect of tonsillar herniation on cyclic CSF flow studied with computational flow analysis. Am. J. Neuroradiol. 32(8), 1474–1481 (2011)
Martin, B.A., Kalata, W., Shaffer, N., Fischer, P., Luciano, M., Loth, F.: Hydrodynamic and longitudinal impedance analysis of cerebrospinal fluid dynamics at the craniovertebral junction in type I Chiari malformation. PLoS One. 8(10), e75335 (2013)
Shaffer, N., Martin, B.A., Rocque, B., Madura, C., Wieben, O., Iskandar, B.J., Dombrowski, S., Luciano, M., Oshinski, J.N., Loth, F.: Cerebrospinal fluid flow impedance is elevated in type I Chiari malformation. J. Biomech. Eng. 136(2), 021012 (2014)
Pahlavian, S.H., Loth, F., Oshinski, J.N., Luciano, M.G., Martin, B.A.: Cardiac related neural tissue motion impacts cerebrospinal fluid dynamics at the cervical-medullary junction: a patient-specific moving-boundary computational fluid dynamics model of type 1 Chiari malformation. Ann. Biomed. Eng. (2015)
Papisov, M.I., Belov, V.V., Gannon, K.S.: Physiology of the Intrathecal bolus: the Leptomeningeal route for macromolecule and particle delivery to CNS. Mol. Pharm. 10(5), 1522–1532 (2013)
O’Donnell, J., Ding, F., Nedergaard, M.: Distinct functional states of astrocytes during sleep and wakefulness: is norepinephrine the master regulator? Curr. Sleep Med. Rep. 1(1), 1–8 (2015)
Patel, T., Zhou, J.B., Piepmeier, J.M., Saltzman, W.M.: Polymeric nanoparticles for drug delivery to the central nervous system. Adv. Drug Deliv. Rev. 64(7), 701–705 (2012)
Lu, C.T., Zhao, Y.Z., Wong, H.L., Cai, J., Peng, L., Tian, X.Q.: Current approaches to enhance CNS delivery of drugs across the brain barriers. Int. J. Nanomedicine. 9, 2241–2256 (2014)
Watanabe, Y., Kazuki, Y., Kazuki, K., Ebiki, M., Nakanishi, M., Nakamura, K., Yoshida Yamakawa, M., Hosokawa, H., Ohbayashi, T., Oshimura, M., Nakashima, K.: Use of a human artificial chromosome for delivering trophic factors in a rodent model of amyotrophic lateral sclerosis. Mol. Ther. Nucleic Acids. 4, e253 (2015)
Deepa, P., Shahani, N., Alladi, P.A., Vijayalakshmi, K., Sathyaprabha, T.N., Nalini, A., Ravi, V., Raju, T.R.: Down regulation of trophic factors in neonatal rat spinal cord after administration of cerebrospinal fluid from sporadic amyotrophic lateral sclerosis patients. J. Neural Transm. 118(4), 531–538 (2011)
Myers, M.R.: A numerical investigation into factors affecting anesthetic distribution during spinal anesthesia. J. Biomech. 29(2), 139–149 (1996)
Kuttler, A., Dimke, T., Kern, S., Helmlinger, G., Stanski, D., Finelli, L.A.: Understanding pharmacokinetics using realistic computational models of fluid dynamics: biosimulation of drug distribution within the CSF space for intrathecal drugs. J. Pharmacokinet. Pharmacodyn. 37(6), 629–644 (2010)
Hsu, Y., Hettiarachchi, H.D., Zhu, D.C., Linninger, A.A.: The frequency and magnitude of cerebrospinal fluid pulsations influence intrathecal drug distribution: key factors for interpatient variability. Anesth. Analg. 115(2), 386–394 (2012)
Haga, P.T., Pizzichelli, G., Mortensen, M., Kuchta, M., Pahlavian, S.H., Sinibaldi, E., Martin, B.A., Mardal, K.A.: A numerical investigation of intrathecal isobaric drug dispersion within the cervical subarachnoid space. PLoS One. 12(3), e0173680 (2017)
Tangen, K.M., Leval, R., Mehta, A.I., Linninger, A.A.: Computational and in vitro experimental investigation of intrathecal drug distribution: parametric study of the effect of injection volume, cerebrospinal fluid pulsatility, and drug uptake. Anesth. Analg. 124(5), 1686–1696 (2017)
Tangen, K.M., Hsu, Y., Zhu, D.C., Linninger, A.A.: CNS wide simulation of flow resistance and drug transport due to spinal microanatomy. J. Biomech. 48(10), 2144–2154 (2015)
Linninger, A.A., Somayaji, M.R., Mekarski, M., Zhang, L.: Prediction of convection-enhanced drug delivery to the human brain. J. Theor. Biol. 250(1), 125–138 (2008)
Sarntinoranont, M., Banerjee, R.K., Lonser, R.R., Morrison, P.F.: A computational model of direct interstitial infusion of macromolecules into the spinal cord. Ann. Biomed. Eng. 31(4), 448–461 (2003)
Støverud, K.H., Darcis, M., Helmig, R., Hassanizadeh, S.M.: Modeling concentration distribution and deformation during convection-enhanced drug delivery into brain tissue. Transp. Porous Media. 92(1), 119–143 (2012)
Tangen, K., Linninger, A., Narasimhan, N.S.: Clearance of subarachnoid hemorrhage from the central nervous system via lumbar drain - a bench-top and computational study. Cerebrovasc. Dis. 41, 202–202 (2016)
Tangen, K., Narasimhan, N.S., Sierzega, K., Preden, T., Alaraj, A., Linninger, A.A.: Clearance of subarachnoid hemorrhage from the cerebrospinal fluid in computational and in vitro models. Ann. Biomed. Eng. (2016)
Dichiro, G.: Movement of the cerebrospinal fluid in human beings. Nature. 204, 290–291 (1964)
Asgari, M., de Zelicourt, D.A., Kurtcuoglu, V.: Barrier dysfunction or drainage reduction: differentiating causes of CSF protein increase. Fluids Barriers CNS. 14(1), 14 (2017)
Sanchez, A.L., Martinez-Bazan, C., Gutierrez-Montes, C., Criado-Hidalgo, E., Pawlak, G., Bradley, W., Haughton, V., Lasheras, J.C.: On the bulk motion of the cerebrospinal fluid in the spinal canal. J. Fluid Mech. 841, 203–227 (2018)
Bilston, L.E., Fletcher, D.F., Brodbelt, A.R., Stoodley, M.A.: Arterial pulsation-driven cerebrospinal fluid flow in the perivascular space: a computational model. Comput. Methods Biomech. Biomed. Engin. 6(4), 235–241 (2003)
Lloyd, R.A., Fletcher, D.F., Clarke, E.C., Bilston, L.E.: Chiari malformation may increase perivascular cerebrospinal fluid flow into the spinal cord: a subject-specific computational modelling study. J. Biomech. 65, 185–193 (2017)
Wang, P., Olbricht, W.L.: Fluid mechanics in the perivascular space. J. Theor. Biol. 274(1), 52–57 (2011)
Bilston, L.E., Stoodley, M.A., Fletcher, D.F.: The influence of the relative timing of arterial and subarachnoid space pulse waves on spinal perivascular cerebrospinal fluid flow as a possible factor in syrinx development. J. Neurosurg. 112(4), 808–813 (2010)
Schley, D., Carare-Nnadi, R., Please, C.P., Perry, V.H., Weller, R.O.: Mechanisms to explain the reverse perivascular transport of solutes out of the brain. J. Theor. Biol. 238(4), 962–974 (2006)
Asgari, M., de Zelicourt, D., Kurtcuoglu, V.: How astrocyte networks may contribute to cerebral metabolite clearance. Sci. Rep. 5, (2015)
Sharp, M.K., Diem, A.K., Weller, R.O., Carare, R.O.: Peristalsis with oscillating flow resistance: a mechanism for periarterial clearance of amyloid beta from the brain. Ann. Biomed. Eng. 44(5), 1553–1565 (2016)
Asgari, M., de Zelicourt, D., Kurtcuoglu, V.: Glymphatic solute transport does not require bulk flow. Sci. Rep. 6, (2016)
Rey, J., Sarntinoranont, M.: Pulsatile flow drivers in brain parenchyma and perivascular spaces: a resistance network model study. Fluids Barriers CNS. 15, (2018)
Diem, A.K., Sharp, M.M., Gatherer, M., Bressloff, N.W., Carare, R.O., Richardson, G.: Arterial pulsations cannot drive intramural periarterial drainage: significance for a beta drainage. Front. Neurosci. 11, (2017)
Jin, B.J., Smith, A.J., Verkman, A.S.: Spatial model of convective solute transport in brain extracellular space does not support a “glymphatic” mechanism. J. Gen. Physiol. 148(6), 489–501 (2016)
Coloma, M., Schaffer, J.D., Carare, R.O., Chiarot, P.R., Huang, P.: Pulsations with reflected boundary waves: a hydrodynamic reverse transport mechanism for perivascular drainage in the brain. J. Math. Biol. 73(2), 469–490 (2016)
Holter, K.E., Kehlet, B., Devor, A., Sejnowski, T.J., Dale, A.M., Omholt, S.W., Ottersen, O.P., Nagelhus, E.A., Mardal, K.A., Pettersen, K.H.: Interstitial solute transport in 3D reconstructed neuropil occurs by diffusion rather than bulk flow. Proc. Natl. Acad. Sci. U. S. A. 114(37), 9894–9899 (2017)
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Kurtcuoglu, V., Jain, K., Martin, B.A. (2019). Modelling of Cerebrospinal Fluid Flow by Computational Fluid Dynamics. In: Miller, K. (eds) Biomechanics of the Brain. Biological and Medical Physics, Biomedical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-04996-6_9
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