1. Magnetic Resonance Imaging
Dr Sarah Wayte
University Hospital of Coventry & Warwickshire

3. GE MR Scanner

4. Receiver Coils

5. ‘Typical’ MR Examination
Surface coil selected and positioned
Inside scanner for 20-30min
Series of images in different orientations & with different contrast obtained
It is very noisy

6. MRI in Cov & Warwickshire
Year
No of scanners
Field Strength
1987 1
0.5/1.0T
1997
1.0T
2007 7
5x1.5T, 3.0T
0.35T
2012 8
6x1.5T, 3.0T,
1.5T extremity

7. 1.5T Extremity

8. Wide Bore 1.5T

9. What is so great about MRI?
By changing imaging parameters (TR and TE times) can alter the contrast of the images
Can image easily in ANY plane (axial/sag/coronal) or anywhere in between

12. Spatial Resolution In slice resolution = Field of view / Matrix
Field of view typically 250mm head
Typical matrix 256
In slice resolution ~ 0.98mm
Slice thickness typically 3 to 5 mm
High resolution image
FOV=250mm, 512 matrix, in slice res~0.5mm
Slice thickness 0.5 to 1mm

13. Any Plane

14. Any Plane Magnetic field varied linearly from head to toe
Hydrogen nuclei at various frequency from head to toe (ωo=γBo)
RF pulse at ωo gives slice through nose (resonance)
RF pulse at ωo+  ω gives slice through eye
RF wave
ωo+ω ωo ωo - ω
Slice selection gradient

15. Sagittal/Coronal Plane
Sagittal slice: vary gradient left to right
Coronal slice: apply vary gradient anterior to posterior
Combination of sag & coronal gradient can give any angle between

16. Image Contrast
TR=525ms TE=15ms
TR=2500ms TE=85ms

17. Image Contrast Depends on the pulse sequence timings used (TR/TE)
3 main types of contrast
T1 weighted
T2 weighted
Proton density weighted
Explain for 90 degree RF pulses

18. TR and TE
To form an image have to apply a series of 90o pulses (eg 256) and detect 256 signals
TR = Repetition Time = time between 90o RF pulses
TE = Echo Time = time between 90o pulse and signal detection TR TR
Signal Signal Signal TE TE TE

19. Bloch Equation Bloch Equations BETWEEN 90o RF pulses
Signal=Mo[1-exp(-TR/T1)] exp(-TE/T2)
TR<T1, TE<<T2, T1 weighted
TR~3T1, TE<T2, T2 weighted
TR~3T1, TE<<T2, Mo or proton density weighted TR TR
Signal Signal Signal TE TE TE

20. PD/T1/T2 Weighted Image T1 weighted Water dark Short TR=500ms
Short TE<30ms
T2 weighted
Water bright
Long TR=1500ms (3xT1max)
Long TE>80ms
PD weighted
Long TR=1500ms (3xT1max)
Short TE<30ms

21. T1/T2 Weighted Image
TR = 562ms
TE = 20ms
TR = 4000ms
TE = 132ms

22. T1/T2 Weighted
TR=525ms TE=15ms
TR=2500ms TE=85ms

23. Proton Density/T2
TR = 3070ms
TE = 15ms
TR = 3070ms
TE = 92ms

24. Proton Density/T2
TR = 3070ms
TE = 15ms
TR = 3070ms
TE = 92ms

25. Lumbar Spine Images Disc protrusion L5/S1. Degenerative changes bone.
L5/S1 slight bulge, no harm to theca or nerves.

26. Axial Images of L Spine

27. Imaging Time (Spin Warp)
1 line of image (in k-space) per TR
Imaging time = TR x matrix x Repetitions
Reps typically 2 or 4 (improves SNR)
E.g. TR=0.5s, Matrix=256, Reps=2 Image time = 256s = 4min 16s
During TR image other slices
Max no slices = TR/TE
e.g. 500/20=25 or 2500/120=21

28. Speeding Things Up 1
Spin warp T2 weighted image, 256 matrix, 3.5s TR, 2reps
Imaging time = 3.5 x 256 x 2 ~ 30min!!!
Solution: acquire 21 lines k-space per 90o pulse

29. Imaging time = 3.5 x 256 x 2/21 ~ 1min 25s
Speeding Things Up 2
With 21 signals per 90o pulse for 256 matrix, 3.5s TR, 2reps
Imaging time = 3.5 x 256 x 2/21 ~ 1min 25s
All images I’ve shown so far use this technique
(Fast spin echo or turbo spin echo)

30. Even Faster Imaging
How fast? images in a breath-hold (30 3T)
Use < 90 degree flip (α)
Some Mz magnetisation remains to form the next image, so TR<20ms
Drawback- less magnetisation/signal in transverse plane Mz
Signal = MoCosα

31. T1 Breath-hold Images 14 slices in 23s breath-hold (t1_fl2d_tra_bh)
TR=16.6ms, TE=6ms α=70o

32. T2 breath-hold images 19 slice in 25s breath-hold (t2-trufi_tra_bh)
TR=4.3ms TE=2.1ms α=80o

33. 30 Images in 20s Breath-hold

34. Echo Planar Imaging
Takes TSE/FSE to the extreme by acquiring 64 or 128 image lines (signals) following a single 90 degree RF pulse
Image matrix size (64)2 or (128)2 (poor resolution)

35. EPI Imaging Each slice acquired in 10s of milliseconds
Lower resolution
More artefacts

36. EPI Imaging Each slice acquired in ~10ms
Used as basis for functional MRI (fMRI)
Images acquired during ‘activation’ (e.g. finger tapping) and rest. Sum active and rest and subtract
Right motor cortex excited with left finger tapping, in close proximity with tumour

37. Functional MRI (fMRI)
Concentration of oxyhaemoglobin brighter (longer T2* than de-oxyhaemoglobin) Subtracted image of bright ‘dots’ of activated brain
Super-impose dot image over ‘anatomical’ MR image
fMRI of patient with tumour near right motor cortex
Active area with left finger tapping
Shows right motor cortex close too, but not overlapping tumour

38. Imaging Blood Flow
Apply series of high flip angle pulses very quickly (short TR)
Stationary tissue does NOT have time to recover, becomes saturated
Flowing blood, seen no previous RF pulses, high signal from spins each time
Flip
Flip TR

39. MIPs of Base Image

40. Abnormal MIP with AVM

41. MRA Base Images 72 slices through head
Brain tissue ‘saturated’ high signal from moving blood
Processed by computer to produce Maximum Intensity Projections (MIPs)
Maximum signal along line of site displayed

42. Diffusion Imaging
Uses EPI imaging technique with additional bi-polar gradients in x, y & z directions
Bi-polar gradients also varied in amplitude
No diffusion – high signal
More diffusion- lower signal

43. T2 & EPI Images: Stroke?

44. Different Amp Diffusion Gradient: Ischemic Stroke?
Stroke reduces diffusion
Bright on diffusion weighted image
Amp = 0
Amp = 500
Amp = 1000

45. Diffusion Co-efficient Map & Images
Diffusion image
Intensity α 1/Diffusion (& T2)
Intensity α Diffusion Co-efficient

46. Anisotropic Diffusion
Diffusion gradient
Diffusion gradient

47. Anisotropic Diffusion: Diffusion tensor imaging
Anisotropic diffusion in white matter tracks
Apply diffusion gradients in direction
‘Track’ white matter track direction by diffusion anisotropy
Brainimaging.waisman.wisc.edu