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Magnetic Resonance Imaging

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Presentation on theme: "Magnetic Resonance Imaging"— Presentation transcript:

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

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