Hydrocephalus is a life-threatening condition characterized by excess cerebral spinal fluid (CSF) accumulation in the ventricular system. The result is elevation of intracranial pressure (ICP) causing neurological dysfunction and, in some cases, death. Congenital hydrocephalus is present in 1/500 live births, and acquired hydrocephalus can occur at any age. It is estimated that over 1 million people in the United States alone are inflicted with hydrocephalus, and it is the most common cause for brain surgery in children. The primary treatment for this condition is to implant a shunt to divert the excess fluid to another part of the body. While effective in controlling ICP, this device was developed 50 years ago, and shunt failure is a predominant problem in the treatment of pediatric hydrocephalus. One of the primary causes of failure and reoperation is obstruction of the shunt tubing which is correlated with the fluid dynamics of the catheter. CSF transport into and through the catheter is dependent on many variables such as catheter geometry, location in the ventricle, and in-vivo operating conditions. Therefore, optimization of catheter design, placement, and valve settings to minimize catheter obstruction and shunt failure requires a comprehensive characterization of the operating conditions and the effects of the many variables on the CSF flow field. The objective of this research is to develop a 3D digital surrogate model representing the lateral ventricle and implanted catheter that will be used to simulate catheter effectiveness in relieving intracranial pressure under in-vivo operating conditions. This model will be validated through extensive experimental testing using a novel apparatus, based on a 3D ventricle replica, that measures critical performance metrics (such as pressure, resistance, and flow rate) under pulsatile and transient conditions when the valve is open. Computational simulation using parametric input files run on a world class supercomputer will form the basis of a comprehensive sensitivity study to quantify the effects of the numerous uncertain input parameters on the transport of CSF out of the ventricle. The developed experimental and computational tools coupled with the knowledge gained through sensitivity analysis will provide the first comprehensive 3D characterization of CSF transport through both unobstructed and obstructed ventricular catheters. The results will inform optimization of catheter design to prevent obstructions and to extend the life of obstructed catheters. This systematic characterization of CSF flow and the resulting computational and experimental tools will have a significant impact on pediatric health by providing the critical knowledge required to optimize ventricle catheter design to reduce the likelihood of obstruction.

Public Health Relevance

Pediatric hydrocephalus is a debilitating disease that affects 1/500 newborns, and there is no cure. The traditional treatment is surgical implantation of a shunt system which was designed 50 years ago, and minimal ensuing progress has been made in improving the failure rate of these devices, resulting in the need for multiple brain surgeries during an inflicted child?s lifetime for shunt replacement. This research aims to characterize the fluid dynamics of obstructed ventricular catheters (a prevalent mode of failure for the shunt system) to inform improved design that will prevent shunt failure and reduce the need for multiple brain surgeries.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Academic Research Enhancement Awards (AREA) (R15)
Project #
1R15EB026196-01
Application #
9516428
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Erim, Zeynep
Project Start
2018-07-01
Project End
2021-06-30
Budget Start
2018-07-01
Budget End
2021-06-30
Support Year
1
Fiscal Year
2018
Total Cost
Indirect Cost
Name
University of Tennessee Knoxville
Department
Engineering (All Types)
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
003387891
City
Knoxville
State
TN
Country
United States
Zip Code
37916