CSF (Cerebrospinal Fluid) Flow, Chiari 1 Malformation & Syringomyelia

CSF (cerebrospinal fluid) motion is affected by Chiari Malformation and Syringomyelia. From an engineering perspective, Chiari I malformation (CM), is a change in hindbrain geometry that is characterized as the cerebellar tonsils descending into the foramen magnum. This alteration in geometry can, and often does, impact the flow of CSF (cerebrospinal fluid) from the cranium into the spinal canal due to the reduction in cross sectional area of the passage way, the spinal subarachnoid space (SSS). Thus, the problem appears to be that of a geometrical nature. However, as is often the case with biological systems, the problem is more complex and a sort of chain reaction may, or may not, occur. First, the geometrical changes make it more difficult for CSF to move between the brain and SSS. The same volume of fluid can still be pushed out of the brain although this requires greater pressure gradients during the cardiac cycle. These altered pressure gradients can potentially move and distort brain tissue and further alter the geometry. Changes in pressure typically alter the elastic properties of the craniospinal system. All these effects could combine to create a flow problem that is far more complicated than a simple change in geometry. These pressure gradients are also thought to cause another craniospinal disorder called syringomyelia (SM).

CSF Flow Study with Engineering Research

Engineering research has sought to better understand the biomechanical forces and hydrodynamics (fluid movement) present in the flow of CSF within the craniospinal system of CM and SM patients. The ultimate goal of these engineering studies is to better understand the biomechanical nature of the disease to improve the treatment experiences of a CM patient. This may be accomplished through novel imaging and simulation tools to improve diagnosis or surgical planning.

Studying CSF System with Computational Fluid Dynamics

The use of computational fluid dynamics (CFD) modeling (i.e., computerized modeling of fluid movement) presents the opportunity to characterize the biomechanical environment of the CSF system non-invasively. CFD modeling of CSF flow typically begins with a CAD model of the geometry of interest, either idealized or reconstructed from anatomic MRI, and flow data obtained from Phase Contrast (PC) MR techniques. Then, by utilizing the equations of motion for a fluid (Navier-Stokes equations) to numerically simulate CSF flow, key mechanical variables in the flow field such as pressure and fluid velocity, can be approximated with good accuracy in both space and time.

An early CFD project to study CSF motion in the spinal SAS was conducted by Loth, et al. [Loth]. This study demonstrated that the flow field in an open spinal canal (no tonsillar or fine structure obstructions) may vary significantly with position in the craniocaudal direction and with position of the spinal cord relative to the subarachnoid boundary. A subsequent study demonstrated that fine structures in the spinal canal (trabeculae, nerve bundles, denticulate ligaments) do not significantly alter gross CSF flow patterns [Stockman], which validated a key assumption in the development of CFD models of the spinal canal. In a study conducted by Roldan, et al., geometrically realistic models (one from the spinal canal of a CM patient, one from a healthy volunteer) were used to confirm the notion from the Loth study that CSF velocities in the spinal canal increase with position in the craniocaudal direction. Those velocity increases, in turn, caused increases in the corresponding CSF pressures, which drive the flow. From the same study, the numerically-determined flow field yielded velocity jetting patterns near the foramen magnum in the CM patient, which matched up well with PCMR data from other studies [Roldan]. Linge, et al., produced similar results using a geometrically idealized model of the posterior cranial fossa and cervical spine [Linge].

CSF Flow Analysis with Computational Fluid Dynamics in Post-Traumatic Syringomyelia

Because CFD analysis is such a time-efficient means of analysis for simple flow geometries, such as the idealized spinal canal, it has also proven useful in the non-invasive analysis of CSF flow fields in post-traumatic SM (PTSM). Bilston, et al, used a simplified model of the spinal canal to demonstrate that the presence of focal arachnoiditis, modeled as a porous medium, creates higher pressure pulses than in an unobstructed spinal canal [Bilston, 2006]. The study hypothesized then that the elevated CSF pressure may be a significant factor in the propagation of the syrinx in PTSM.

CSF Flow in Brain Ventricles and the Cranial Subarachnoid Space Also Being Studied with Computational Fluid Dynamics

CFD modeling is also being used to approximate flow fields in the ventricles of the brain and the cranial subarachnoid space. Initially, such models were used to show that CSF flow fields in the ventricles and cranial SAS could be obtained using CFD methods and, going forward, might prove to be useful in producing a coupled cranial-spinal CSF flow model [Kurtcuoglu, 2005; Kurtcuoglu, 2007]. One concern noted by the authors of these studies was the risk involved in decoupling the cranial CSF system from the spinal CSF system and vice versa, as anomalies in the approximated flow field (i.e. seemingly cryptic or random pressure or velocity fluctuations) may be difficult to justify only in the context of one half of the system. Those studies have also shown that it may be possible to drive CSF flow in a complete CSF system model using brain motion data obtained from MRI. Further studies have used a similar complex modeling methodology to accurately introduce the compliant behavior of the brain, spinal cord, and subarachnoid membrane [Gupta, 2009], which, again, may be critical in forming a complete systemic model of the CSF system, and to study the influence of CSF drainage into the lymphatic system on the pressure and flow environment in the cranial subarachnoid space [Gupta, 2010]. Both of the aforementioned Gupta studies may prove to be useful base models for non-invasively studying transport of metabolites and neuroendocrine substances in the CSF system, which may prove useful in the study of the interrelation of hydrocephalus (and perhaps CM) and dementia/Alzheimer’s disease.

CSF Article References

  1. Loth, F., M.A. Yardimci, and N. Alperin, Hydrodynamic modeling of CSF (cerebrospinal fluid) motion within the spinal cavity. J Biomech Eng, 2001. 123(1): p. 71-9
  2. Kurtcuoglu, V., D. Poulikakos, and Y. Ventikos, Computational modeling of the mechanical behavior of the CSF (cerebrospinal fluid) system. J Biomech Eng, 2005. 127(2): p. 264-9.
  3. Kurtcuoglu, V., D. Poulikakos, and Y. Ventikos, Computational modeling of the mechanical behavior of the CSF (cerebrospinal fluid) system. J Biomech Eng, 2005. 127(2): p. 264-9.
  4. Stockman, H.W., Effect of anatomical fine structure on the flow of CSF (cerebrospinal fluid) in the spinal subarachnoid space. J Biomech Eng, 2006. 128(1): p. 106-14.
  5. Cheng, S., E. Jacobson, and L.E. Bilston, Models of the pulsatile hydrodynamics of CSF (cerebrospinal fluid) flow in the normal and abnormal intracranial system. Comput Methods Biomech Biomed Engin, 2007. 10(2): p. 151-7.
  6. Kurtcuoglu, V., et al., Computational investigation of subject-specific (CSF) cerebrospinal fluid flow in the third ventricle and aqueduct of Sylvius. J Biomech, 2007. 40(6): p. 1235-45
  7. Gupta, S., et al., Three-dimensional computational modeling of subject-specific CSF (cerebrospinal fluid) flow in the subarachnoid space. J Biomech Eng, 2009. 131(2): p. 021010.
  8. Cheng, S., K. Tan, and L.E. Bilston, The effects of the interthalamic adhesion position on CSF (cerebrospinal fluid) dynamics in the cerebral ventricles. J Biomech, 2010. 43(3): p. 579-82.
  9. Gupta, S., et al., CSF (Cerebrospinal fluid) dynamics in the human cranial subarachnoid space: an overlooked mediator of cerebral disease. I. Computational model. J R Soc Interface, 2010.
  10. Hentschel, S., et al., Characterization of Cyclic CSF Flow in the Foramen Magnum and Upper Cervical Spinal Canal with MR Flow Imaging and Computational Fluid Dynamics. AJNR Am J Neuroradiol, 2010.
  11. Holman, D.W., V. Kurtcuoglu, and D.M. Grzybowski, CSF (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, 2010.
  12. Linge, S.O., et al., CSF flow dynamics at the craniovertebral junction studied with an idealized model of the subarachnoid space and computational flow analysis. AJNR Am J Neuroradiol, 2010. 31(1): p. 185-92.

Revised 10/2010

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