1. 1212 / mhj BM/i 2 Visualization of Diffusion Tensor Imaging Guus Berenschot May 2003 Supervisor: Bart ter Haar Romeny Daily Supervisor: Anna Vilanova i Bartroli Other committee members: Carola van Pul, Klaas Nicolay and Peter Hilbers

2. 1212 / mhj BM/i 2 6/10/20152 Contents Introduction Diffusion Tensor Imaging (DTI) Visualization Tool for DTI Demonstration Conclusion and Future Work

3. 1212 / mhj BM/i 2 6/10/20153 Introduction Diffusion Tensor Imaging Diffusion is the random motion of molecules, and is characterized by a diffusion coefficient D. In tissue this diffusion hindered by physical barriers. The diffusion coefficient is called Apparent Diffusion Coefficient (ADC)

4. 1212 / mhj BM/i 2 6/10/20154 Diffusion Tensor Imaging is a Magnetic Resonance Imaging (MRI) technique. DTI measures the ADC in 6 directions and computes a symmetric diffusion tensor (D) of this: This diffusion tensor is defined for each voxel in the 3D dataset Introduction Diffusion Tensor Imaging

5. 1212 / mhj BM/i 2 6/10/20155 Diagonalization Diffusion Tensor Diagonalization of this tensor provides three eigenvectors (ev 1, ev 2 and ev 3 ) with three corresponding eigenvalues (λ 1, λ 2 and λ 3 ) ev 1 λ1 ev 2 λ 2 ev 3 λ 3

6. 1212 / mhj BM/i 2 6/10/20156 Anisotropy Indices Linear case: Planar case: Isotropic case:

7. 1212 / mhj BM/i 2 6/10/20157 Problem Definition How to extract meaningful information of a 3D DTI dataset??? –Neonatal brain (Maxima Medical Center, Veldhoven) –Muscles (Magnetic Resonance Laboratory)

8. 1212 / mhj BM/i 2 6/10/20158 Visualization Tool For DTI Anatomical reference Displaying local tensor information Displaying global tensor information Improvements to existing techniques

9. 1212 / mhj BM/i 2 6/10/20159 Multi Planar Reconstruction Planes Anatomical reference Displaying local tensor information in 2D slice

10. 1212 / mhj BM/i 2 6/10/201510 Anisotropy Indices Colorcoding anisotropy indices

11. 1212 / mhj BM/i 2 6/10/201511 Colorcoding Main Diffusion Direction Colorcoding directions Intensity color scaled with anisotropy index A P RL F H Pajevic et al. 1997

12. 1212 / mhj BM/i 2 6/10/201512 Glyphing Glyphs are icons that represent the local tensor information Two types of glyphs can be displayed: –Ellipsoids –Cuboids (Worth et al., 1998)

13. 1212 / mhj BM/i 2 6/10/201513 Cuboids

14. 1212 / mhj BM/i 2 6/10/201514 Fiber Tracking: Introduction Fiber tracking simplifies the tensor field to the vector field of the main eigenvector This vector field is made continuous by interpolation Consider this vector field as a velocity field and drop a free particle on it This particle will follow a trajectory The found trajectory can be seen as a bundle of fibers Xue et al. 1999, Conturo et al. 1999, Mori et al. 1999

15. 1212 / mhj BM/i 2 6/10/201515 Tracking The tracking can be seen as solving the following integral: To solve this integral we use a second order Runge Kutta integration

16. 1212 / mhj BM/i 2 6/10/201516 Seed Points Manual definition of a seed point or seed region Start tracking in all voxels and keep the trajectories that pass a certain region Stopping Criteria Linear Anisotropy (Cl) falls below a certain threshold Angle in a fiber is too big

17. 1212 / mhj BM/i 2 6/10/201517 Fiber Tracking In Healthy Volunteer Optical tractCorpus Callosum

18. 1212 / mhj BM/i 2 6/10/201518 Patient with a tumor Mouse muscle Neonatal brain

19. 1212 / mhj BM/i 2 6/10/201519 Surface Building Fiber tracking gives problems in regions with planar anisotropy; the main eigenvector is not reliable Planar anisotropy can be due to kissing crossing or branching fibers

20. 1212 / mhj BM/i 2 6/10/201520 Surface Building If we enter a region with planar anisotropy: follow all directions defined by local plane and display a surface here If anisotropy is linear again: do the common fiber tracking.

21. 1212 / mhj BM/i 2 6/10/201521 Demonstration

22. 1212 / mhj BM/i 2 6/10/201522 Conclusion The visualization tool is considered as very useful by the MMC and the MRL Results of fiber tracking in neonatal brain is promising Future Work Seeding is biased Noisy data-> smoothing Quantitative information of fibers

23. 1212 / mhj BM/i 2 6/10/201523 Thanks Anna Vilanova i Bartroli (daily supervisor) Bart ter Haar Romeny (supervisor) Gustav Strijkers and Anneriet Heemskerk (MRL) Carola van Pul and Maurice Jansen (MMC) George Roos and Jan Buijs (radiologist and neonatologist MMC) Klaas Nicolay and Peter Hilbers (committee members)