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Principles of MRI: Image Formation

Principles of MRI: Image Formation

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Principles of MRI: Image Formation

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  1. Principles of MRI:Image Formation Allen W. Song Brain Imaging and Analysis Center Duke University

  2. What is image formation? To define the spatial location of the sources that contribute to the detected signal.

  3. But MRI does not use projection, reflection, or refraction mechanisms commonly used in optical imaging methods to form image.

  4. MR image formation To define the spatial location of the proton pools that contribute to the detected MR signal.

  5. w q = wt q Frequency and Phase Are Our Friends in MR Imaging A 3-D gradient field (dB/dx, dB/dy, dB/dz) would allow a unique correspondence between the spatial location and the magnetic field. Using this information, we will be able to generate maps that contain spatial information – images.

  6. Gradient Coils z z z y y y x x x X gradient Y gradient Z gradient Gradient coils generate varying magnetic field so that spins at different location precess at frequencies unique to their location, allowing us to reconstruct 2D or 3D images.

  7. 0.8 Spatial Encoding of the MR Signal Constant Magnetic Field Varying Magnetic Field w/o encoding w/ encoding

  8. Spatial Encoding of the MR Signal Frequency Decomposition

  9. Spatial Encoding for More Spins – along x x

  10. Spatial Encoding for More Spins – along y y

  11. Steps in 3D Localization • Can only detect total RF signal from inside the “RF coil” (the detecting antenna) • Excite and receive Mxy in a thin (2D) slice of the subject • The RF signal we detect must come from this slice • Reduce dimension from 3D down to 2D • Deliberately make magnetic field strength B depend on location within slice • Frequency of RF signal will depend on where it comes from • Breaking total signal into frequency components will provide more localization information • Make RF signal phase depend on location within slice

  12.  Exciting and Receiving Mxy in a Thin Slice of Tissue Source of RF frequency on resonance Excite: Addition of small frequency variation Amplitude modulation with “sinc” function RF power amplifier RF coil

  13. Electromagnetic Excitation Pulse (RF Pulse) Fo FT Fo Fo+1/ t 0 t Time Frequency Fo Fo FT DF= 1/ t t

  14. Gradient Fields: Spatially Nonuniform B: • During readout (image acquisition) period, turning on gradient field is called frequency encoding --- using a deliberately applied nonuniform field to make the precession frequency depend on location • Before readout (image acquisition) period, turning on gradient field is called phase encoding --- during the readout (image acquisition) period, the effect of gradient field is no longer time-varying, rather it is a fixed phase accumulation determined by the amplitude and duration of the phase encoding gradient. Center frequency [63 MHz at 1.5 T] f 60 KHz Gx = 1 Gauss/cm = 10 mTesla/m = strength of gradient field x-axis Left = –7 cm Right = +7 cm

  15. Exciting and Receiving Mxy in a Thin Slice of Tissue RF coil Receive: RF preamplifier Filters Analog-to-Digital Converter Computer memory

  16. Slice Selection

  17. Slice Selection – along z z

  18. Determining slice thickness Resonance frequency range as the result of slice-selective gradient: DF = gH * Gsl * dsl The bandwidth of the RF excitation pulse: Dw/2p Thus the slice thickness can be derived as dsl = Dw / (gH * Gsl * 2p)

  19. Changing slice thickness • There are two ways to do this: • Change the slope of the slice selection gradient • Change the bandwidth of the RF excitation pulse • Both are used in practice, with (a) being more popular

  20. Changing slice thickness new slice thickness

  21. Selecting different slices • In theory, there are two ways to select different slices: • Change the position of the zero point of the slice • selection gradient with respect to isocenter • (b) Change the center frequency of the RF to correspond • to a resonance frequency at the desired slice • F = gH (Bo + Gsl * Lsl ) • Option (b) is usually used as it is not easy to change the • isocenter of a given gradient coil.

  22. Selecting different slices new slice location

  23.  Readout Localization (frequency encoding) • After RF pulse (B1) ends, acquisition (readout) of NMR RF signal begins • During readout, gradient field perpendicular to slice selection gradient is turned on • Signal is sampled about once every few microseconds, digitized, and stored in a computer • Readout window ranges from 5–100 milliseconds (can’t be longer than about 2T2*, since signal dies away after that) • Computer breaks measured signal V(t) into frequency components v(f) — using the Fourier transform • Since frequency fvaries across subject in a known way, we can assign each component v(f) to the place it comes from

  24. Spatial Encoding of the MR Signal Constant Magnetic Field Varying Magnetic Field w/o encoding w/ encoding

  25. It’d be easy if we image with only 2 voxels … But often times we have imaging matrix at 256 or higher.

  26. A 9×9 case Image Space Time point #3 Time point #2 Time point #1 So each point contains information from all the voxels

  27. A typical diagram for MRI frequency encoding: Gradient-echo imaging Excitation Slice Selection TE Frequency Encoding readout ……… Time point #9 Time point #1 Readout Data points collected during this period corrspond to one-line in k-space

  28. TE Gradient Phases of spins ……… Time point #9 Time point #1 digitizer on Phase Evolution of MR Data

  29. A typical diagram for MRI frequency encoding: Spin-echo imaging Excitation Slice Selection TE Frequency Encoding readout ……… Readout

  30. 180o TE Gradient Phase ……… digitizer on Phase History

  31. Image Resolution (in Plane) • Spatial resolution depends on how well we can separate frequencies in the data V(t) • Resolution is proportional to f = frequency accuracy • Stronger gradients  nearby positions are better separated in frequencies  resolution can be higher for fixed f • Longer readout times  can separate nearby frequencies better in V(t) because phases of cos(ft) and cos([f+f]t) will be more different

  32. Calculation of the Field of View (FOV)along frequency encoding direction • * Gf * FOVf = BW = 1/Dt Which means FOVf = 1/ (g GfDt) where BW is the bandwidth for the receiver digitizer.

  33.  The Second Dimension: Phase Encoding • Slice excitation provides one localization dimension • Frequency encoding provides second dimension • The third dimension is provided by phase encoding: • We make the phase of Mxy (its angle in the xy-plane) signal depend on location in the third direction • This is done by applying a gradient field in the third direction ( to both slice select and frequency encode) • Fourier transform measures phase of each v(f) component ofV(t), as well as the frequency f • By collecting data with many different amounts of phase encoding strength, can break each v(f) into phase components, and so assign them to spatial locations in 3D

  34. Excitation Slice Selection Frequency Encoding Phase Encoding readout ……… Readout A typical diagram for MRI phase encoding:Gradient-echo imaging

  35. Excitation Slice Selection Frequency Encoding Phase Encoding readout ……… Readout A typical diagram for MRI phase encoding: Spin-echo imaging

  36. Calculation of the Field of View (FOV)along phase encoding direction • * Gp * FOVp = Np / Tp Which means FOVp = 1/ (g Gp Tp/Np) = 1/ (g GpDt) where Tp is the duration and Np the number of the phase encoding gradients, Gp is the maximum amplitude of the phase encoding gradient.

  37. Part II.2 Introduction to k-space(a space of the spatial frequency) k-space Image

  38. …….. Phase Encode Step 1 Time point #2 Time point #1 Time point #3 …….. Phase Encode Step 2 Time point #2 Time point #1 Time point #3 …….. Phase Encode Step 3 Time point #2 Time point #1 Time point #3 ……..

  39. Image Space K-Space . . . . . . . . . . . . . . . . . . +Gy . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 0 . . . . . . . . . . . . . . . . . . . . . . . . . . . -Gy -Gx 0 +Gx Figure 4.7. Contributions of different image locations to the raw k-space data. Each data point in k-space (shown in yellow) consists of the summation of MR signal from all voxels in image space under corresponding gradient fields. We have indicated, for four sample k-space points, which gradient vectors contribute at different image space locations to the k-space data.

  40. Acquired MR Signal By physically adding all the signals from each voxel up under the gradients we use. From this equation, it can be seen that the acquired MR signal, which is also in a 2-D space (with kx, ky coordinates), is the Fourier Transform of the imaged object. Kx = g/2p 0tGx(t) dt Ky = g/2p 0tGy(t) dt

  41. k-space Image space ky y kx x Acquired Data Final Image Two Spaces IFT FT

  42. High Signal K Image

  43. Full Image Intensity-Heavy Image Detail-Heavy Image Full k-space Lower k-space Higher k-space

  44. Gx (amplitude) Kx (area) time 0 t The k-space Trajectory Equations that govern k-space trajectory: Kx = g/2p 0tGx(t) dt Ky = g/2p 0tGy(t) dt

  45. A typical diagram for MRI frequency encoding: A k-space perspective 90o Excitation Slice Selection Frequency Encoding readout Readout Exercise drawing its k-space representation

  46. The k-space Trajectory

  47. A typical diagram for MRI frequency encoding: A k-space perspective 180o 90o Excitation Slice Selection Frequency Encoding readout Readout Exercise drawing its k-space representation

  48. The k-space Trajectory

  49. A typical diagram for MRI phase encoding: A k-space perspective 90o Excitation Slice Selection Frequency Encoding Phase Encoding readout Readout Exercise drawing its k-space representation

  50. The k-space Trajectory