Motivation

1. Stress and Deformation Analysis in Porous Media for Convection Enhanced Drug Delivery to the Human Brain N. Sindhwani, G. Tsiagalis, O. Ivanchenko and A. LinningerLaboratory for Product and Process Design, Dept. of Bioengineering University of Illinois at ChicagoChicago, IL, USA-60607 Student Research Forum, UIC, April 17 2009 Motivation Goal and Approaches • CNS Diseases: • Neurologic Disorders such as Parkinson’s, Alzheimer’s, and Brain tumors affect more than 50 million Americans each year. • Delivery of drugs to the brain is a problem due to the Blood Brain Barrier which prevents delivery of large molecules to the target site. • Convection Enhanced Delivery: • Direct infusion into the brain parenchyma bypassing the Blood-Brain-Barrier. • Bulk flow mechanism to deliver drugs to target site. • Promising tool for delivery of large molecules to the brain • Problem of Reflux: • Backflow of drug/dye along the catheter shaft. Goal: Experimental investigation and mathematical simulation of tissue deformation under infusion Approaches: Analysis of mathematical models for porous tissue deformation. Visualization of deformation around the catheter in brain surrogate agarose gel. Track deformation in gel using Micro/Nano beads. Simulate deformation for better prediction of drug distribution Visualization of stress field in the porous tissue. Simulation of CED using Fluent. MRI of human brain showing the process of CED Mathematical models Visualization of Stress Field using Photoelasticity • Photoelasticity Theory: • Based on the property of Birefringence, or, Double Refraction of the material. • Plane polarized light is resolved along two principle stress directions. • The stress field can be related to its index of refraction through Maxwell’s stress optic laws.  The Stress-Optic law: Species Transport: Δ= Retardation. σ1 and σ2 are principle stresses. h= Thickness of the sample λ= Wavelength of the light. ρ= density C= concentration De= Diffusion coefficient =Velocity vector R(C)= Reaction term Biot’s model for stress and strain distribution in a porous tissue: Schematic of deformation of the tissue caused due to infusion (Morrison ,1999) ε= strain σ= stress P=pore pressure ζ= incremental fluid content H, R, and K are poroleastic constants Deformation due to change in pressure (Levine 1999): Before infusion Stress field after infusion ur =radial displacement G and ν are constants Simulations Visualization of Deformation Optical Microscopy experiments: Porous Gel before infusion Interface An interface is formed between the gel and the catheter due to infusion. Micro/Nano bead experiments: Porous Gel after infusion Interface Interface tracked using Micro/Nano beads that align along the bulge. Conclusions and Future Work References • Deformation of tissue around catheter causes backflow during CED. • To obtain high quality sequence of micro-images. • Use fluorescent beads to track infusate path and deformation. • Improve resolution of Photoelasticity experiments to observe fringes. • Use circular polariscope and interferometer instead of linear polariscope. • Correlate experimental findings with simulations. Linninger A A, Somayaji M R, Zhang L, Hariharan M S, and Penn R D. Rigorous Mathematical Modeling Techniques for Optimal Delivery of Macromolecules to the Brain. IEEE Transactions on Biomedical Engineering (2008), Vol. 55, No. 9, Linninger A A, Somayaji M R, Mekarski M, Zhang L. Prediction of convection-enhanced drug delivery to the human brain. J Theor. Biol. (2008) 250, 125–138. Linninger A A, Somayaji M R, Erickson T, Guo X, Penn R D. Computational methods for predicting drug transport in anisotropic and heterogeneous brain tissue. J. Biomech. (2008) 41 2176–2187. Levine D N. The Pathogenesis of Normal Pressure Hydrocephalus: A Theoretical Analysis. Bulletin Math. Biol.(1999) 61, 875–916. Morrison P F, Chen M Y, Chadwick R S, Lonser R R and Oldfield E H. Focal delivery during direct infusion to brain: role of flow rate, catheter diameter, and tissue mechanics. Am J Physiol Regulatory Integrative Comp Physiol (1999)277:1218-1229. Acknowledgements • NSF CBET 0730048 • NSF RET EEC 0743068 • NSF REU EEC 0754590