1. Introduction to Finite Element Modeling in Biomechanics Dr. N. Fatouraee Biomedical Engineering Faculty December, 2004

2. Overview Introduction and Definitions Basic finite element methods –1-D model problem Application Examples

3. Overview Finite Element Method –numerical method to solve differential equations E.g.: Flow Problem u(r) Heat Transfer Problem T(r,t)

4. The “Continuum” Concept biomechanics example: blood flow through aorta –diameter of aorta  25 mm –diameter of red blood cell  8  m (0.008 mm) –treat blood as homogeneous and ignore cells

5. The “Continuum” Concept biomechanics example: blood flow through capillaries –diameter of capillary can be 7  m –diameter of red blood cell  8  m –clearly must include individual blood cells in model

6. Continuous vs. Discrete Solution What if the equation had no “analytical solution” (e.g., due to nonlinearities)?

7. Continuous vs. Discrete Solution What if the equation had no “analytical solution” (e.g., due to nonlinearities)? How would you solve an ordinary differential equation on the computer? Numerical methods –Runge-Kutta –Euler method

8. Discretization 01 01

9. 01 in general, Euler method is given by: Start with initial condition: y(x 0 )=y 0 Calculate f(x 0,y 0 ) Calculate y 1 =y 0 + f(x 0,y 0 )  x Calculate f(x 1,y 1 ) …………..

10. Euler Example 2 Steps 4 Steps 8 Steps Exact Solution x y ODE:dy/dx (x,y) = 0.05 y Initial Cond.:y(0)=100 Euler, 2 steps: dy/dt(0,100) = 5;  x = 20 y(20) = y(0) +  x*dy/dt(0,100) = 100 + 20*5= 200 y(40) = y(20) +  x*dy/dt(20,200) = 200 + 20* 10 = 400 Problem: Use Euler with 2 steps: Calculate y(x) between at x=20 and x=40

11. Discretization in general, the process by which a continuous, differential equation is transformed into a set of algebraic equations to be solved on a computer various forms of discretization –finite element, finite difference, finite volume

12. Finite Element Method discretization steps in finite element method –weak form of differential equation –interpolation functions within elements –solution of resulting algebraic equations

13. Basic Finite Element Methods: A 1-D Example solve for u(x)

14. Basic Finite Element Methods: A 1-D Example Note that for a=0, b=1:

15. Basic Finite Element Method seek solution to allied formulation referred to as “weak” statement

16. Basic Finite Element Method seek solution to allied formulation referred to as “weak” statement

17. Basic Finite Element Method The integral form is as valid as the original differential equation.

18. Basic Finite Element Method note that by the chain rule:

19. Basic Finite Element Method note that by the chain rule:

20. Basic Finite Element Method

21. recall: w(x) is arbitrary  no loss in generality to require w(a)=w(b)=0 i.e., subject w to same boundary conditions as u

22. Basic Finite Element Method “weak statement”: the above expression is “continuous” i.e., must be evaluated for all x

23. Discretization 01 01 “nodes” “elements”

24. Discretization “nodes” “elements” 123456 12345 u defined at nodes  u 1, u 2 … = u(x 1 ), u(x 2 ) … goal  solve for u i

25. Discretization “nodes” “elements” 123456 12345

26. Consider a Typical Element e x1x1 x2x2

27. Interpolation Functions Within the element we interpolate between u 1 and u 2 :

28. Interpolation Functions

30. e x1x1 x2x2 at x = x 1 : u = u 1 at x = x 2 : u = u 2 x 1 < x < x 2 : interpolation between u 1 and u 2 u 1, u 2  unknowns to be solved for i.e., nodal values of u

31. Approximation Functions - referred to as “Galerkin” method Now we have to choose functions for w:

32. We end up with a system of algebraic equations, that can be solved by the computer

33. How many elements do we need? 01 “nodes” “elements” 123456 12345

34. 2 elements 5 elements 10 elements 20 elements

35. Practical Finite Element Analysis many commercial finite element codes exist for different disciplines –FIDAP, FLUENT: fluid mechanics –ANSYS, LS-Dyna, Abaqus: solid mechanics

36. Using a Commercial Code choose most appropriate software for problem at hand –not always trivial –can the code handle the key physical processes e.g., spatially varying material properties, nonlinearities

37. Steps in Finite Element Method (FEM) Geometry Creation –Material properties (e.g. mass density) –Initial Conditions (e.g. temperature) –Boundary Conditions –Loads (e.g. forces) Mesh Generation Solution –Time discretization (for transient problems) –Adjustment of Loads and Boundary Conditions Visualization –Contour plots (on cutting planes) –Iso surfaces/lines –Vector plots –Animations Validation

38. Model Validation most important part of the process, but hardest and often not done two types of validation –code validation: are the equations being solved correctly as written (i.e., grid resolution, etc.) –model validation: is the numerical model representative of the system being simulated (very difficult)

39. Example 1: Liver Cancer Treatment

40. Radiofrequency Ablation for Liver Cancer Surgical Resection is currently the gold-standard, and offers 5-year survival of around 30% Surgical Resection only possible in 10-20% of the cases Radiofrequency Ablation heats up tissue by application of electrical current Once tumor tissue reaches 50°C, cancer cells die

41. Effects of RF energy on tissue Electrical Current is applied to tissue Electrical current causes heating by ionic friction Temperatures above ~50 °C result in cell death (necrosis) Na + Cl - K+K+ Electric Field

42. Clinical procedure Insertion Probe Extension Application of RF power (~12-25 min) Ground pad placed on patients back or thighs Patient under local anesthesia and conscious sedation, or light general anesthesia

43. 9-prong probe, 5 cm diameter, (Rita Medical) Cool-Tip probe, 17-gauge needle, (Radionics / Tyco) 12-prong probe, 4 cm diameter, (Boston Scientific) 200W RF-generator (Radionics / Tyco) Current RF Devices

44. RF Lesion Pathology Coagulation Zone (= RF lesion, >50 °C) Hyperemic Zone (increased perfusion)

45. Finite Element Modeling for Radiofrequency Ablation Purpose of Models: –Investigate shortcomings of current devices –Simulate improved devices –Estimate RF lesion dimensions for treatment planning Thermo-Electrically Coupled Model: –Solve Electric Field problem (Where is heat generated) –Solve thermal problem (Heat Conduction in Tissue, Perfusion, Vessels)

46. Electric Field Problem (Where is heat being generated?) Laplace’s Equation P  M M Boundary Conditions Electric Field

47. Thermal Problem: Conservation of Energy rate of change of energy in a body = + rate of energy generation + rate of energy addition - rate of energy lost

48. energy storage by tissue energy added by electric current (Power = current*voltage) energy added due to metabolism energy transfer to blood flow carrying heat away (“convected”) energy transferred (“conducted”) back to electrode energy transfer (“conducted”) to surrounding tissue

49. Model Geometry 1 cm 2-D axisymmetric model

50. Animations Electrical Current Density (Where is heat being generated?) Temperature

51. Model Results 1 cm Temperature at end of ablation

52. Ex-vivo Validation in Animal Tissue Verify Temperature, Impedance and Lesion Diameter We applied same power as in computer model

53. Experimental Setup

54. Comparison Model  Experiment Impedance Temperature

55. Conclusion Lesion Diameter: Model: 33 mm Experiment:29 ± 3 mm RF Lesion in model 14% larger Information on Electrical Tissue Conductivity vs. Temperature needed

56. Computer Model Geometry: 12-prong probe next to 10mm-vessel (e.g. portal vein) Flow rate 23 cm/s Vessel cooling simulated by estimating convective heat transfer coefficient Impact of large vessels

57. Temperature at end of ablation 50 °C 100 °C 37 °C Model Results Cancer cells next to vessel could survive

58. Computer 3D-Model Geometry Improved configuration heats from both sides, and may create lesions closer to vessel Improved Configuration

59. Bipolar 50 °C 100 °C 37 °C Monopolar Improved configuration creates lesion up to vessel Next Step: Experimental Validation Temperature at End of Ablation

60. Example 2: Simulation of Artificial Heart Valve Phantom I

62. MR Imaging: Bioprosthetic Valve

64. Comparison between Experiment and Simulation MRI simulation

65. Example 3: Artificial Heart Valve II

66. J. De Hart et al. / Journal of Biomechanics 36 (2003) 699–712 703

67. Configurations of the fiber-reinforced stentless valve and corresponding velocityvector fields taken at six successive points in time. The left and right diagram at the bottom of each frame denote the applied velocityand pressure curves, respectively.

69. Maximum principle Cauchystresses in the leaflet matrix material during systole. In all frames the right leaflet is taken from the nonreinforced model for comparison. MPSr denotes the maximum principle stress ratio of the reinforced and non- reinforced leaflets. The stress scale on the bottom is given in kPa.

71. Other Examples in Biomedical Engineering

72. from Shirazi-Adl et al., J. Biomech. Engr. 123:391 2001

73. from Miga et al., J. Biomech. Engr. 123:354 2001 Pressure on vertebrae disks

74. Ene-Iordache et al., 2001 Blood flow in Vessel Aneurism

77. Weiss et al., 2001 Strain in Knee Ligaments

78. Electric Heart Activity McLeod et al., 2001