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Computer Assisted Design of Transport Processes in the Human Brain Laboratory for Product and Process Design, Director A. A. LINNINGER College of Engineering, University of Illinois, Chicago, IL, 60607, U.S.A. Grant Support: NSF, Medtronic, Susman and Asher Foundation. Novel Imaging Techniques Transport & Kinetic Inversion Motivation • Millions of people are affected by diseases of the Central Nervous System (CNS) visualize brain functions (E.g. Blood Flow to pathological organs) structure of the brain and NOT its functions • Systematic design of drug infusion policies based on Transport and Kinetic Inversion Problem (TKIP) • Qualitative & Quantitative prediction of treatment volume of site-specific drug delivery from fluid mechanics • Provide decision support to medical community by specifying the parameters for invasive drug delivery fMRI – Used to CT- Shows the PET- detects MRI- provides an Schematic of BBB in the brain • About seventy thousand people in U.S are affected by hydrocephalus. • Understanding pulsatile CSF dynamics or intracranial dynamics is absolutely necessary to predict and treat hydrocephalus Live Patient MRI DTI- Used to Cine MRI – demonstrate the structural properties of anatomical substructures Flow velocities and Cannot predict intracranial pressure and tissue deformation PET image of F-dopa-derived radioactivity, merged with magnetic resonance image, computational grid and optimal result 0.09 0.08 •These advanced imaging techniques provide only qualitative information. • Non-invasive in-vivo MR measurements cannot fully capture all of the events of intracranial dynamics • A quantitative first principles model is presented that can accurately predict patient-specific intracranial dynamics. radioactive material that is injected or inhaled to produce an image of the brain anatomical view of the brain 0.07 0.06 0.05 •Quantitative information such as drug diffusivity, metabolic reaction constant, binding coefficient are not directly available from these images. 0.04 0.03 0.02 0.01 Hydrocephalic Brain Methodology •Knowledge about these parameters is important in systematic design of drug delivery policies. 0 Clinical concentration field of L-dopa Patient Specific Quantification of Intracranial Dynamics CSF Flow Field during one cardiac cycle – Normal brain MR Imaging Brain Geometry, CSF flow field Reconstruction tools ImageJ, Insight SNAP, Mimics Optimal result, Computational grid M eD Quantification of CSF flow field Direct Experimental Measurements Intracranial Pressure Pulsatility during one cardiac cycle – Normal brain 2D and 3D geometry of the Ventricles and Subarachnoid space Quantification of Intracranial Pressure Geometry Grid Generation Gambit CSF Flow Field during one cardiac cycle – Hydrocephalic brain Computational Mesh Computational Fluid Dynamics Continuity and Navier-Stokes Equations for CSF Motion Quantitative analysis Velocity field and CSF dynamics Prediction of Intracranial pressure (ICP) Intracranial Pressure Pulsatility during one cardiac cycle – Hydrocephalic brain Analysis of flow And pressure patterns t= 0 % t= 60 % t= 30 % Tissue Properties t= 90 % • CSF Pulsatility increases 2.3 times than normal in hydrocephalic case CSF flow and ICP measurements from fluid mechanics • ICP increases by a factor of four in hydrocephalic case Quantitative Prediction of Drug Distribution Boundary Conditions Prediction of treatment volume in a 2D coronal cut of a human brain using NGF as drug 1st week 3rd week 2nd week Regions of interest in targeted drug delivery 4th week Estimation of Penetration Depth Tissue properties Site-specific drug delivery Neurodegenerative disease Drug GDNF Parkinson’s Disease Present Case Study Drug: NGF Target: Caudate Nucleus Injection Location: 1. Thalamus Infusion Site Animal / Human IP: Putamen Rhesus Monkey Gash et al, 2003 IP: Substantia Nigra Rhesus Monkey Gash et al, 2003 IP: Putamen Human Trials Gill S.S et al , 2003 Ventricles & and Central part of the Putamen Rhesus Monkeys Grondin R et al, 2002 ICV Monkeys/Human Trials GDNF/ rmetHUGDNF Parameter Reference Nutt J.G et al, 2003 Conclusions φ–porosity •Higher Treatment Volumes were realized for high flow Infusion at the thalamus Value GM WM 0.2 0.28 k – permeability GM WM 10+16 m-2 X: 10+13 m-2 Y: 10+13 m-2 β – inertia resist. GM WM 8.32*109 m-1 X: 5*108 m-1 Y: 2*108 m-1 Tortuosity 3 1.0 •The total treatment volume at the end of 4 weeks was found to be 0.107 cc GM WM Acknowledgements •Accurately reconstruction of the human brain geometry to quantify transport processes. Dr. Richard Penn, University of Chicago •A novel method for extracting transport and reaction constants from experimental data was presented based on TKIP BRIC, University of Chicago •Prediction of treatment volumes based on site-specific drug delivery for NGF was presented. Fluent Inc, Lebanon, NH •Accurate quantification of CSF flow and Intracranial pressure fields. Materialise Inc, Ann Arbor, MI • Validation of CFD simulations with Cine Phase MRI measurements at select regions of the ventricular system. ImageJ, NIH, MD.