Glaucoma Simulation & Visualization

1. Glaucoma Simulation & Visualization Presenter Farid Harhad. IGERT Associate. Computer Science Spring 2007 High School Workshop

2. Overview • Motivation • What is Glaucoma? • Anatomy of the Eye • CFD Simulation of the Disease • Eye Simulation Data • Visualization of the Simulation • Tutorial Highlights

3. Motivation • Investigating fundamental mechanisms of flow in the eye helps us understand the leading causes of glaucoma • CFD simulation of glaucoma produces large amounts of data that can only be interpreted and analyzed using visualization

4. Part 1: Overview of the Disease

5. What is Glaucoma? • Glaucoma leads to blindness by damaging the retinal cells[1] • Elevated pressure in the eye is a risk factor, but even people with normal pressure can lose vision[1] • World wide, second leading cause of blindness[1]

6. Anatomy of the Eye (1/2) [2] • Light enters the eye by passing through • Cornea, • anterior chamber, pupil, • lens, • vitreous body, • retina • Optic nerve carries signal from retina to brain • High fluid pressure damages retinal nerve fibers and optic disc begins to hallow [3]

7. Anatomy of the Eye (2/2) • Ciliary body consists of ciliary muscle and ciliary processes • Ciliary processes is a vascularized layer which secretes a fluid called the aqueous humor (AH) [2]

8. Eye Fluid Drainage • AH flows radially inward from ciliary body and drains in the trabecular meshwork and Schlemm’s canals • CFD simulation done for angle-closure glaucoma • In angle-closure glaucoma, the iris deforms and blocks normal flow [5] [5]

9. Eye Vascular System [4]

10. Part 2: CFD Simulation of the Disease

11. CFD Simulation of Angle-Closure Glaucoma • Natural convection due to temperature difference between the ambient air (25 °C / 77 °F) and the interior of the eye (37 °C / 98.6 °F) leads to a buoyancy flow. • Apply the conservation of momentum law (fluid form of Newton’s law) to model the flow in the eye. [2]

12. Buoyancy Effect in the Eye

13. CFD Simulation of Glaucoma • Mathematical equations of the physical model are numerically solved w/ computers: • Material particle method (deformable iris) • Immersed boundary (iris+fluid) • Fluid solver (fluid) • Eye geometry information was modeled using ANSYS software and fed into the numerical model

14. Part 3: Visual Analysis of the Simulation Results

15. Eye Simulation Data • Two types of datasets used: • irisgeometry: consists of the vertices of the tessellated bottom surface of the iris • flow information: time-dependent velocities (u, v, w), P, & T at 69741 locations in the eye.

16. Scalars • Scalars • Physical quantities that are completely characterized by one number • Examples: mass of an object, temperature of an object, electrical potential, height … 2844 lbs 100 ºF 1.5 V

17. Vectors [7] • Vector • Consists of a magnitude and direction • Vectors are often represented graphically by arrows • Examples: velocity of an object, gravity, magnetic field ... • Example: 30 ~ 60 μ Tesla [8] 112 mph [6]

18. Visualization Techniques • Vector data: velocity distribution • LIC (Line Integral Convolution) basic idea [9]

19. Visualization Techniques • Scalar data: pressure distribution w/ colormaps • Eg. often a color lookup table, is used to map a range of scalar data to a predefined color

20. Visualization Process T=0, T=1, … T=1573 Image Sequence (1574 timesteps) render geometry using polygons Eye geometry T=0, T=1, … T=1573 Vector data render using LIC render using a colormap Scalar data Data Visualization Movie Generation CFD Simulation (2) (3) (1)

21. Visualization of The Results

22. Recap • Glaucoma is a group of diseases that leads to blindness • Common cause is when the aqueous humor does not drain properly and pressure buildup damages the optic nerve • CFD computer model takes into account the buoyancy flow and conservation of momentum • We visualize the velocity of the flow in the eye using LIC (line integral convolution) • We visualize the pressure distribution in the eye using colormaps

23. Tutorial Overview • Two parts: • Part 1 (~10 min): familiarize yourself with visualization software • Part 2 (~25 min): load iris + flow data and visualize them

24. Credits • References: • http://en.wikipedia.org/wiki/Glaucoma • C. Ross et al. Ocular Biomechanics and Biotransport. Annu. Rev. Biomed. Eng. 2004. • Ian Albert. Anatomy of the Eye. http://ian-albert.com/graphics/anatomy.php • Moore, Keith L. Moore. Essential Clinical Anatomy, 2nd Edition. LWW, 2002. 8.6.3 • National Eye Institute. http://www.nei.nih.gov/photo/search/keyword.asp?keyword=glaucoma • http://en.wikipedia.org/wiki/Vector_%28spatial%29 • http://www.calstatela.edu/faculty/acolvil/plates/magnetic_field.jpg • 3D Turbulent flow over a car. http://www.cmis.csiro.au/cfd/fem/car/index.htm

25. Credits • References (continued): • G. Erlebacher . Texture and Feature based Visualization. http://www-hagen.informatik.uni-kl.de/vis06-tutorial/materials/erlebacherVis06slides.pdf • Simulation Datasets: • Dr. Anvar Gilmanov • Eye Flow Movie: • Farid Harhad

26. Thank you 