MR Image Formation

1. MR Image Formation FMRI Graduate Course (NBIO 381, PSY 362) Dr. Scott Huettel, Course Director FMRI – Week 3 – Image Formation Scott Huettel, Duke University

2. Introductory Exercise • Write down the major steps involved in the generation of MR signal • Just write an outline, not an essay • Note what scanner component contributes to each step FMRI – Week 3 – Image Formation Scott Huettel, Duke University

3. Generation of MR Signal FMRI – Week 3 – Image Formation Scott Huettel, Duke University

4. T1 T2 FMRI – Week 3 – Image Formation Scott Huettel, Duke University

5. Relaxation Times and Rates • Net magnetization changes in an exponential fashion • Constant rate (R) for a given tissue type in a given magnetic field • R = 1/T, leading to equations like e–Rt • T1 (recovery): Relaxation of Mback to alignment with B0 • Usually 500-1000 ms in the brain (lengthens with bigger B0) • T2 (decay): Loss of transverse magnetization over a microscopic region ( 5-10 micron size) • Usually 50-100 ms in the brain (shortens with bigger B0) • T2*: Overall decay of the observable RF signal over a macroscopic region (millimeter size) • Usually about half of T2 in the brain (i.e., faster relaxation) FMRI – Week 3 – Image Formation Scott Huettel, Duke University

6. T1 Recovery FMRI – Week 3 – Image Formation Scott Huettel, Duke University

7. T2 Decay FMRI – Week 3 – Image Formation Scott Huettel, Duke University

8. T1 and T2 parameters By selecting appropriate pulse sequence parameters (Week 4’s lecture), images can be made sensitive to tissue differences in T1, T2, or a combination. FMRI – Week 3 – Image Formation Scott Huettel, Duke University

9. I FMRI – Week 3 – Image Formation Scott Huettel, Duke University

10. FMRI – Week 3 – Image Formation Scott Huettel, Duke University

11. Gradients change the Strength, not Direction of the Magnetic Field FMRI – Week 3 – Image Formation Scott Huettel, Duke University

12. Parts of 2D Image Formation • Slice selection • Linear z-gradient • Tailored excitation pulse • Spatial encoding within the slice • Frequency encoding • Phase encoding FMRI – Week 3 – Image Formation Scott Huettel, Duke University

13. Slice Selection FMRI – Week 3 – Image Formation Scott Huettel, Duke University

14. FMRI – Week 3 – Image Formation Scott Huettel, Duke University

15. Linear z-gradient FMRI – Week 3 – Image Formation Scott Huettel, Duke University

16. Why can’t we just use an excitation pulse of a single frequency? FMRI – Week 3 – Image Formation Scott Huettel, Duke University

17. Selecting a Band of Frequencies FMRI – Week 3 – Image Formation Scott Huettel, Duke University

18. Choosing a Slice FMRI – Week 3 – Image Formation Scott Huettel, Duke University

19. Changing Slice Thickness FMRI – Week 3 – Image Formation Scott Huettel, Duke University

20. Changing Slice Location (Note: manipulating gradient is simpler than changing slice bandwidth.) FMRI – Week 3 – Image Formation Scott Huettel, Duke University

21. … 13 12 Interleaved Slice Acquisition … 3 2 1 FMRI – Week 3 – Image Formation Scott Huettel, Duke University

22. FMRI – Week 3 – Image Formation Scott Huettel, Duke University

23. Spatial Encoding FMRI – Week 3 – Image Formation Scott Huettel, Duke University

24. How not to do spatial encoding… FMRI – Week 3 – Image Formation Scott Huettel, Duke University

25. … a better approach FMRI – Week 3 – Image Formation Scott Huettel, Duke University

26. Temporal Signal = Combination of Frequencies FMRI – Week 3 – Image Formation Scott Huettel, Duke University

27. Effects of Gradients on Phase FMRI – Week 3 – Image Formation Scott Huettel, Duke University

28. Core Concept:k-space coordinate = Integral of Gradient Waveform FMRI – Week 3 – Image Formation Scott Huettel, Duke University

29. k-space Image space ky y kx x Acquired Data Final Image Fourier Transform Inverse Fourier Transform FMRI – Week 3 – Image Formation Scott Huettel, Duke University

30. Spatial Image = Combination of Spatial Frequencies FMRI – Week 3 – Image Formation Scott Huettel, Duke University

31. k Space FMRI – Week 3 – Image Formation Scott Huettel, Duke University

32. Image space and k space FMRI – Week 3 – Image Formation Scott Huettel, Duke University

33. Parts of k space FMRI – Week 3 – Image Formation Scott Huettel, Duke University

34. So, we know that two gradients are necessary for encoding information in a two-dimensional image? What would happen if we turned on both gradients simultaneously? FMRI – Week 3 – Image Formation Scott Huettel, Duke University

35. Frequency Encoding • During readout (or data acquisition, DAQ) • Uses gradient perpendicular to slice-selection gradient • Signal is sampled & digitized about once every few microseconds • Readout window ranges from 5–100 milliseconds • Why not longer than this? • Fourier transform converts signal S(t) into frequency components S(f) FMRI – Week 3 – Image Formation Scott Huettel, Duke University

36. Phase Encoding • Apply a gradient perpendicular to both slice and frequency gradients • The phase of Mxy (its angle in the xy-plane) signal depends on that gradient • Fourier transform measures phase  of each S(f) component of S(t) • By collecting data with many different amounts of phase encoding strength, we can assign each S(f) to spatial locations in 3D FMRI – Week 3 – Image Formation Scott Huettel, Duke University

37. FMRI – Week 3 – Image Formation Scott Huettel, Duke University

38. Echo-Planar Imaging (EPI) FMRI – Week 3 – Image Formation Scott Huettel, Duke University

39. Sampling in k-space K Dk FOV FOV = 1/Dk, Dx = 1/K FMRI – Week 3 – Image Formation Scott Huettel, Duke University

40. Problems in Image Formation FMRI – Week 3 – Image Formation Scott Huettel, Duke University

41. Magnetic Field Inhomogeneity FMRI – Week 3 – Image Formation Scott Huettel, Duke University

42. Gradient Problems FMRI – Week 3 – Image Formation Scott Huettel, Duke University