Rationale

1. LPPDLaboratory for Product and Process Design Rational Design of a Decision-Making Tool for Brain SurgeonsNicholas Vaičaitis, Brian Henry, Cierra M. HallLaboratory for Product and Process Design, Dept. of Bioengineering, University of Illinois at Chicago UIC Senior Design Exposition 2011, Chicago, ILAdvisor: Professor Andreas A. Linninger Rationale Clinical Applications Vasculature Reconstruction and Generation Manual Vasculature Reconstruction Disease States Motivation Atherosclerosis: Image-guided neurosurgery: -No quantitative measurements -Doctors rely on experience and qualitative information • Plaque buildup thickens and stiffens vessel walls. • Treatment with stents or bypass surgery. Arteriovenous Malformations: A Tool to Provide Quantitative Information: • Direct connection between arteries and veins causing drastic pressure drops. • Treat by gluing vessels to divert flow. • Leading cause of stroke in people under 25. Illustration of the manual vasculature reconstruction process utilizing MRA imaging. Free Growth Generation Algorithm • Create patient-specific brain vasculature models that are capable of performing simulations of blood pressure and blood flow. • Based on simulations of treatment strategies, provide neurosurgeons with decision-making guidance. 3. Make random point inside and connect to segment midpoint 1. Initialize domain size and make first segment 2. Scale Domain Aneurysm: • Abnormal widening orballooning of an artery. • Requires immediate image-guided neurosurgery. • Treat by insertion of an expanding polymer to cover hole or by clipping aneurysm off. Pt 1 (0,10 )) Pt 1 (0,10)) 4. Calculate volumeV of tree 5. Perturb bifurcation point until minimal volume of tree is found Process Flow Simulations k, # of tree segments r, radius of segment i l, length of segment i Physiological Meshes Blood flow and pressure simulation on reconstructed vascular tree. Use Free Growth Algorithm to Add Microvasculature Acknowledgements Brain meshes including a volumetric mesh and DTI meshes. References Generated Trees Karch, R., F. Neumann, et al. (1999). "A three-dimensional model for arterial tree representation, generated by constrained constructive optimization." Comput Biol Med 29(1): 19-38. Schreiner, W. and P. F. Buxbaum (1993). "Computer-optimization of vascular trees." IEEE Trans Biomed Eng 40(5): 482-491. Collaborations Fady T. Charbel, MD, FACS. Professor and Head of the College of Medicine at UIC. Chief of Neurovascular Section. Ali Alaraj, MD. Assistant Professor at the College of Medicine at UIC. Endovascular/Cerebrovascular. Bullitt E, Zeng D, Gerig G, Aylward S, Joshi S, Smith JK, Lin W, Ewend MG (2005) Vessel tortuosity and brain tumor malignancy: A blinded study. Academic Radiology 12:1232-1240. *The MR brain images from healthy volunteers used in this paper were collected and made available by the CASILab at The University of North Carolina at Chapel Hill and were distributed by the MIDAS Data Server at Kitware, Inc.* Quantify Blood flow, pressure Treatment outcome likelihood Trees generated with manual reconstruction and the free growth algorithm. Observe Physical Phenomena -Magnetic Resonance Angiography (MRA) -Magnetic Resonance Imaging (MRI) -Computed Tomography (CT) Reconstruct Patient’s Main Vasculature Simulate