Intracranial Dynamics and its Role in Hydrocephalus Treatment Intracranial Dynamics and its Role in Hydrocephalus Treatment S. S. Basati Basati, B. , B. Sweetman Sweetman, J. Lancaster, A. Linninger , J. Lancaster, A. Linninger Laboratory for Product and Process Design, Department of Bioengineering, University of Illinois at Chicago Mid t Bi di lE i i C f 2011 Model Predictions Model Predictions Midwest BiomedicalEngineering Conference , 2011 Model Generation Model Generation MR imaging Geometry reconstruction Grid generation Computational Motivation Motivation Answerfundamentalquestionsaboutbrainmechanics Answerfundamentalquestionsaboutbrainmechanics Addressneedforbettertreatmentsofbraindiseases Addressneedforbettertreatmentsofbraindiseases CSFFlowDirectionandPressuresinSpinalCanalandCranialSpace I: CINE-MRI measures CSF flow rates and velocities. II: Discrete MR images converted to 3-D surface meshes. What is CSF pressure? Why does CSF pulsate? Do abnormalities in vessel, tissue, CSF interaction contribute to CSF-related disorders? Why is the treatment ineffective? Cost Cost involved involved with with hydrocephalus hydrocephalus treatment treatment 1 An abnormal accumulation of cerebrospinal fluid (CSF) leads to a condition known as Hydrocephalus Hydrocephalus . Over 150,000 people are diagnosed with this disease in the U.S. each year. Modeling additional information not offered by imaging may lead to better treatment. /s] CFD Simulation N =6 15 20 /s] CFD Simulation CINE MRI N HC =5 • Flow in pontine cistern is twice that in hydrocephalic patients times in hydrocephalic patients Cerebrospinal System Porous Parenchyma (black) CSF pathways (light blue) Fluid Equations Continuity Momentum ( ) ( ) 0 u v t x y III: Grid generation leads to a computational domain. IV: Transport quantities are predicted in computational domain. Normal Hydrocephalus Objectives : • Investigate complex mechanical interaction between major components of central nervous system • Quantify mechanical properties of brain tissue, cerebral vasculature, and CSF • Advance understanding of central nervous system physics -20 -10 -5 5 20 40 60 80 100 % Cardiac Cycle CSF Velocity [mm/ -20 -15 -10 -5 0 5 10 0 20 40 60 80 100 % Cardiac Cycle CSF Velocity [mm/ CINE-MRI Lower Aqueduct It il Novel Therapy Design Novel Therapy Design Computer aided Sensor Design and Simulation Porous Spinal Cord ormal ocephalic d G G d p k p q p k t Dq f Dt Solid Equations • Supplement computer models with design of new treatment options 560 580 600 620 640 660 ssure [Pa] 2% 560 580 600 620 640 660 ssure [Pa] • Intracranial pressure amplitude and pressure wave speed are dependent on spinal compliance. • Reduction in CSF reabsorption can cause CSF to accumulate. • Fluid flows from parenchyma to ventricles in normal cases, but reverses its direction under hd h li diti Exploit electrical conductivity differences between CSF and brain tissue. Exploit electrical conductivity differences between CSF and brain tissue. Conclusions and Future Directions Conclusions and Future Directions Spinal SAS No Hydro 1 2 s v G d p t Constraints Dynamic/Kinematic s f d d s f 20 40 60 80 100 480 500 520 540 % Cardiac Cycle Pres 20 40 60 80 100 480 500 520 540 % Cardiac Cycle Pres 22% 0 20 40 60 80 100 -10 -5 0 5 10 Velocity Magnitude [mm/s] flow into canal flow from canal + - + - + 0 20 40 60 80 100 -10 -5 0 5 10 Velocity Magnitude [mm/s] hydrocephalic conditions. 1.13( / ) CSF S m 0.2( / ) BRAIN S m • Generate internal electric field and calculate the electric potential. • Distribution of current is a function Conclusions and Future Directions Conclusions and Future Directions Conclusions Conclusions • A change change in in aqueductal aqueductal to to prepontine prepontine flow flow ratio ratio was was quantified quantified with with our our model, and and changes changes that that occur occur obey obey first first principle principle explanations explanations. • We are able to reproduce the complex flow patterns in the subarachnoidal f Future Directions • Fluid Fluid-structure structure interaction interaction model model including including patient patient-specific specific vasculature, vasculature, CSF CSF spaces, spaces, and and brain brain tissue tissue. • Determine Determine changes changes in in regional regional blood blood flow flow pre/post pre/post shunting shunting. • Quantify Quantify intracranial intracranial dynamics dynamics with with Ak ld t Ak ld t 0 20 40 60 80 100 % Cardiac Cycle 0 20 40 60 80 100 % Cardiac Cycle I II • With constant CSF production from choroid plexus, brain movement is driven by blood flow. • In communicating hydrocephalus, distensible spinal canal and the resultant pressure profiles allow predictions to be made. of volume. Fabrication Fabrication of of ring ring electrodes electrodes onto onto catheter catheter • Dicing Dicing saw saw used used to to create create 60 60 μm μm holes • Pt/Ir Pt/Ir cylinders cylinders bonded bonded to to wires wires and and passed through through. • Sensor Sensor coated coated with with parylene parylene-C for for t bilit t bilit spaces and other areas of the brain and are now able to quantify states that cannot be easily measured such as deformations, strains, and displacements of brain tissue. • Novel treatment was proposed that directly monitors volume as opposed to passive, pressure based valves. • Real Real-time time changes changes in in intracranial intracranial i l i l l b d i Quantify Quantify intracranial intracranial dynamics dynamics with with respect respect to to changes changes in in vasculature vasculature compliance compliance. • Chronic Chronic implantation implantation into into pre pre- hydrocephalic hydrocephalic animal animal model model. • Incorporate Incorporate pressure pressure measurements measurements to to dynamically dynamically record record pressure pressure- volume volume. • Incorporate Incorporate microcontroller microcontroller for for f db k f db k t l t l d i l i l dt dt Acknowledgements Acknowledgements stability stability. B Acute animal hydrocephalus measurement protocol • Verify functionality of treatment option. • First ever dynamic volume measurements. Financial support provided for part of this research under NIH grant 5R21EB4956 is acknowledged. The treatment device is patent pending (# WO/2008/005440). We would also like to thank: • Dr. Richard Penn, UIC • Michael LaRiviere, University of Chicago • Dr. MR Del Bigio, University of Manitoba • Materialise, Inc. • Tim Harris, UIC ventricular ventricular volume volume can can be be measured measured in in vivo, vivo, • Animal Animal model model is is developed developed to to measure measure acute acute and and dynamic dynamic changes changes in in intracranial intracranial ventricular ventricular volume, volume, feedback feedback control control and and wireless wireless data data communications communications. References References 1. Linninger A, Basati S, Dawe R, Penn R. “An impedance sensor to monitor and control cerebral ventricular volume”. Medical engineering & physics. 2009 Sep;31(7):838-45. 2. A. Linninger, B. Sweetman and R. Penn. Normal and hydrocephalic brain dynamics; reduced cerebrospinal fluid reabsorption and ventricular enlargement, Annals of Biomedical Engineering. DOI: 10.1007/s10439-009-9691-4, 2009. 3. Basati, S, Harris, T, Linninger, A. “Dynamic brain phantom for intracranial volume monitoring”. IEEE Trans. Biomed. Eng., 2010. 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