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Principles of MRI
Physics and Engineering

          Allen W. Song
 Brain Imaging and Analysis Center
         Duke University
What if the RF field is not synchronized?

Using the swingset example: now the driving force is no longer
synchronized with the swing frequency, thus the efficiency of
driving the swing is less.

In a real spin system, there is a term called “effective B1
field”,
given by                                         ∆ω/γ         B1eff
              B1eff = B1 + ∆ω /γ
where                                                         B1
              ∆ω = ω o – ω e
Part II.1
Image Formation
What is image formation?

To define the spatial location of the proton
pools that contribute to the MR signal after
spin excitation.
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.
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.
Spatial Encoding – along x




 x
Spatial Encoding – along y


                             y
0.8

      Spatial Encoding of the MR Signal




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




         Frequency
        Decomposition
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
RF Field: Excitation Pulse
    Fo




                    FT
0               t                 Fo Fo+1/ t

    Time                       Frequency

           Fo                     Fo
                    FT

                                ∆F= 1/ t
           t
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          f
60 KHz   [63 MHz at 1.5 T]
                                      Gx = 1 Gauss/cm = 10 mTesla/m
                                         = strength of gradient field
                                                                        x-axis
Left = –7 cm                                                 Right = +7 cm
 Exciting and Receiving Mxy in a Thin Slice of Tissue
  Excite:     Source of RF frequency on resonance


              Addition of small frequency variation


            Amplitude modulation with “sinc” function


                       RF power amplifier


                             RF coil
 Exciting and Receiving Mxy in a Thin Slice of Tissue
  Receive:               RF coil


                      RF preamplifier


                          Filters


                 Analog-to-Digital Converter


                     Computer memory
Slice Selection
Slice Selection – along z




 z
Determining slice thickness
Resonance frequency range as the result
of slice-selective gradient:
             ∆F = γH * Gsl * dsl
The bandwidth of the RF excitation pulse:
              ∆ω/2π

Thus the slice thickness can be derived as
      dsl = ∆ω / (γH * Gsl * 2π)
Changing slice thickness

There are two ways to do this:

(a) Change the slope of the slice selection gradient

(b) Change the bandwidth of the RF excitation pulse

Both are used in practice, with (a) being more popular
Changing slice thickness




                       new slice
                       thickness
Selecting different slices
In theory, there are two ways to select different slices:
(a) 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 = γH (Bo + Gsl * Lsl )

Option (b) is usually used as it is not easy to change the
isocenter of a given gradient coil.
Selecting different slices




new slice
 location
 Readout Localization (frequency encoding)
♦ After RF pulse (B ) ends, acquisition (readout) of
                        1
  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 f varies across subject in a known way, we
    can assign each component v(f ) to the place it comes from
Readout of the MR Signal




        Constant            Varying
        Magnetic            Magnetic
         Field               Field
 w/o encoding        w/ encoding
Readout of the MR Signal




     Fourier Transform
A typical diagram for MRI frequency encoding:
             Gradient-echo imaging
Excitation

   Slice
Selectio                 TE
n
Frequency
  Encoding
                      readout
 Readout

              Data points collected during this
              period corrspond to one-line in k-space
Phase History
                     TE
Gradient




Phase



                 digitizer on
A typical diagram for MRI frequency encoding:
              Spin-echo imaging

Excitation

   Slice
Selectio                      TE
n
Frequency
  Encoding
                            readout
 Readout
Phase History
               180o        TE

Gradient



Phase
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
Calculation of the Field of View (FOV)
 along frequency encoding direction


   γ* Gf * FOVf = BW = 1/∆t
    *

   Which means FOVf = 1/ (γ Gf ∆t)

   where BW is the bandwidth for the
   receiver digitizer.
 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 φ of each v(f ) component
    of V(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
A typical diagram for MRI phase encoding:
              Gradient-echo imaging
Excitation

   Slice
Selectio
n
 Frequency
  Encoding
 Phase
Encoding
                      readout
 Readout
A typical diagram for MRI phase encoding:
                 Spin-echo imaging
Excitation

   Slice
Selectio
n
 Frequency
  Encoding
 Phase
Encoding
                             readout
 Readout
Calculation of the Field of View (FOV)
    along phase encoding direction
γ* Gp * FOVp = Np / Tp
 *

Which means FOVp = 1/ (γ Gp Tp/Np)
                 = 1/ (γ Gp ∆t)

where Tp is the duration and Np the number
of the phase encoding gradients, Gp is the
maximum amplitude of the phase encoding
gradient.
Multi-slice acquisition

Total acquisition time =
Number of views * Number of excitations * TR

         Is this the best we can do?


      Interleaved excitation method
TR

Excitation
                                  ……
   Slice
Selectio
n                                 ……
 Frequency
  Encoding
                                      ……
 Phase
Encoding
             readout        readout        readout
 Readout
Part II.2 Introduction to k-space
    (a space of the spatial frequency)

        Image         k-space
Acquired MR Signal
Mathematical Representation:
                                        − i 2π ( k x x + k y y )
 S (k x , k y ) = ∫   ∫   I ( x, y )e                              dxdy

           Kx = γ/2π ∫0t Gx(t) dt
           Ky = γ/2π ∫0t Gy(t) dt
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.
Acquired MR Signal

By physically adding all the signals from each voxel up under
the gradients we use.

                                         − i 2π ( k x x + k y y )
  S (k x , k y ) = ∫   ∫   I ( x, y )e                              dxdy

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.
Two Spaces

   k-space                   Image space
       ky                          y
                     IFT

                kx                         x
                     FT



Acquired Data                Final Image
Image   K
The k-space Trajectory
Equations that govern k-space trajectory:

      Kx = γ/2π ∫0t Gx(t) dt

      Ky = γ/2π ∫0t Gy(t) dt
             Gx (amplitude)
                              Kx (area)

                                    time
             0          t
A typical diagram for MRI frequency encoding:
             A k-space perspective
               90o
Excitation

   Slice
Selectio
n
Frequency
  Encoding
                                readout
 Readout

             Exercise drawing its k-space representation
The k-space Trajectory
A typical diagram for MRI frequency encoding:
             A k-space perspective
               90o              180o
Excitation

   Slice
Selectio
n
Frequency
  Encoding
                                           readout
 Readout

             Exercise drawing its k-space representation
The k-space Trajectory
A typical diagram for MRI phase encoding:
              A k-space perspective
                90o
Excitation

   Slice
Selectio
n
 Frequency
  Encoding
 Phase
Encoding
                               readout
 Readout
             Exercise drawing its k-space representation
The k-space Trajectory
A typical diagram for MRI phase encoding:
              A k-space perspective
                90 o             180o
Excitation

   Slice
Selectio
n
 Frequency
  Encoding
 Phase
Encoding
                                           readout
 Readout
             Exercise drawing its k-space representation
The k-space Trajectory
Sampling in k-space
       ..........
       ..........            ∆k
       ..........
       ..........
       ..........
       ..........
       ..........
kmax   ..........
       ..........
       ..........            ∆k = 1 / FOV
                             Refer to slide
                             32, 36
A
..........
..........
..........              B
                     .....
..........
..........           .....
..........           .....
                     .....
..........           .....
..........
..........
..........           FOV:
                     Pixel Size:

  FOV: 10 cm
  Pixel Size: 1 cm
A                       B
..........
..........           .   .     .       .   .
..........           .   .     .       .   .
..........
..........
..........           .   .     .       .   .
..........           .   .     .       .   .
..........
..........
..........           .   .     .       .   .
  FOV: 10 cm             FOV:
  Pixel Size: 1 cm       Pixel Size:
A
..........
..........                B
..........           ..........
                       .........
..........
..........
                     .
                     ..........
                     ..........
                     ..........
..........
..........
                     ..........
                     ..........
                     ..........
..........
..........
                     ..........
                     ..........

..........             FOV:
                       Pixel Size:

  FOV: 10 cm
  Pixel Size: 1 cm
..........
..........
..........                                                                          .      .       .      .      .
..........                                     .....
                                               .....                                .      .       .      .      .
..........
..........                                     .....
..........                                     .....                                .      .       .      .      .
..........                                     .....                                .      .       .      .      .
..........
..........                                                                          .      .       .      .      .




 Figure 4.16. Effects of sampling in k-space upon the resulting images. Field of view and resolution have an inverse
 relation between image space and k-space. Shown in (A) is a schematic representation of densely sampled k-space with a
 wide field of view, resulting in the high-resolution image below. If only the center of k-space is sampled (B), albeit with
 the same sampling density, then the resulting image below has the same field of view, but does not have as high of spatial
 resolution. Conversely, if k-space is sampled across a wide field of view but with limited sampling rate (C), the resulting
 image will have a small field of view but high resolution.
Original image          K-space trajectory              Displaced image


                                                                           Spatial Displacement




                                     Original image               Distorted image




Figure 4.17. Spatial and intensity distortions due to magnetic field inhomogeneities during readout. If there is a
systematic change in the spin frequency over time, the resulting image may be spatially displaced (B). Another possible
type of distortion results from local field inhomogeneities, which in turn cause the resonant frequency to vary slightly
across spatial locations, affecting the intensity of the image over space.
Original image               K-space trajectory                    Distorted Image




Figure 4.18. Image distortions caused by gradient problems during readout. Each row shows the ideal image, the problem with acquisition in k-
space, and the resulting distorted image. Distortions along the x-gradient will affect the length of the trajectory in k-space, resulting in an image that
appears stretched (A). Distortions along the y-gradient will affect the path taken through k-space over time, resulting in a skewed image (B). Distortions
along the z-gradient will affect the match of excitation pulse and slice selection gradient, influencing the signal intensity (C).

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W4 physics 2003

  • 1. Principles of MRI Physics and Engineering Allen W. Song Brain Imaging and Analysis Center Duke University
  • 2. What if the RF field is not synchronized? Using the swingset example: now the driving force is no longer synchronized with the swing frequency, thus the efficiency of driving the swing is less. In a real spin system, there is a term called “effective B1 field”, given by ∆ω/γ B1eff B1eff = B1 + ∆ω /γ where B1 ∆ω = ω o – ω e
  • 3.
  • 5. What is image formation? To define the spatial location of the proton pools that contribute to the MR signal after spin excitation.
  • 6. 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.
  • 7. 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.
  • 10. 0.8 Spatial Encoding of the MR Signal Constant Varying Magnetic Magnetic Field Field w/o encoding w/ encoding
  • 11. Spatial Encoding of the MR Signal Frequency Decomposition
  • 12. 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
  • 13. RF Field: Excitation Pulse Fo FT 0 t Fo Fo+1/ t Time Frequency Fo Fo FT ∆F= 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 f 60 KHz [63 MHz at 1.5 T] 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 Excite: Source of RF frequency on resonance Addition of small frequency variation Amplitude modulation with “sinc” function RF power amplifier RF coil
  • 16.  Exciting and Receiving Mxy in a Thin Slice of Tissue Receive: RF coil RF preamplifier Filters Analog-to-Digital Converter Computer memory
  • 18. Slice Selection – along z z
  • 19. Determining slice thickness Resonance frequency range as the result of slice-selective gradient: ∆F = γH * Gsl * dsl The bandwidth of the RF excitation pulse: ∆ω/2π Thus the slice thickness can be derived as dsl = ∆ω / (γH * Gsl * 2π)
  • 20. Changing slice thickness There are two ways to do this: (a) Change the slope of the slice selection gradient (b) Change the bandwidth of the RF excitation pulse Both are used in practice, with (a) being more popular
  • 21. Changing slice thickness new slice thickness
  • 22. Selecting different slices In theory, there are two ways to select different slices: (a) 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 = γH (Bo + Gsl * Lsl ) Option (b) is usually used as it is not easy to change the isocenter of a given gradient coil.
  • 24.  Readout Localization (frequency encoding) ♦ After RF pulse (B ) ends, acquisition (readout) of 1 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 f varies across subject in a known way, we can assign each component v(f ) to the place it comes from
  • 25. Readout of the MR Signal Constant Varying Magnetic Magnetic Field Field w/o encoding w/ encoding
  • 26. Readout of the MR Signal Fourier Transform
  • 27. A typical diagram for MRI frequency encoding: Gradient-echo imaging Excitation Slice Selectio TE n Frequency Encoding readout Readout Data points collected during this period corrspond to one-line in k-space
  • 28. Phase History TE Gradient Phase digitizer on
  • 29. A typical diagram for MRI frequency encoding: Spin-echo imaging Excitation Slice Selectio TE n Frequency Encoding readout Readout
  • 30. Phase History 180o TE Gradient Phase
  • 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 γ* Gf * FOVf = BW = 1/∆t * Which means FOVf = 1/ (γ Gf ∆t) 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 φ of each v(f ) component of V(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. A typical diagram for MRI phase encoding: Gradient-echo imaging Excitation Slice Selectio n Frequency Encoding Phase Encoding readout Readout
  • 35. A typical diagram for MRI phase encoding: Spin-echo imaging Excitation Slice Selectio n Frequency Encoding Phase Encoding readout Readout
  • 36. Calculation of the Field of View (FOV) along phase encoding direction γ* Gp * FOVp = Np / Tp * Which means FOVp = 1/ (γ Gp Tp/Np) = 1/ (γ Gp ∆t) 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. Multi-slice acquisition Total acquisition time = Number of views * Number of excitations * TR Is this the best we can do? Interleaved excitation method
  • 38. TR Excitation …… Slice Selectio n …… Frequency Encoding …… Phase Encoding readout readout readout Readout
  • 39. Part II.2 Introduction to k-space (a space of the spatial frequency) Image k-space
  • 40. Acquired MR Signal Mathematical Representation: − i 2π ( k x x + k y y ) S (k x , k y ) = ∫ ∫ I ( x, y )e dxdy Kx = γ/2π ∫0t Gx(t) dt Ky = γ/2π ∫0t Gy(t) dt
  • 41. 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.
  • 42. Acquired MR Signal By physically adding all the signals from each voxel up under the gradients we use. − i 2π ( k x x + k y y ) S (k x , k y ) = ∫ ∫ I ( x, y )e dxdy 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.
  • 43. Two Spaces k-space Image space ky y IFT kx x FT Acquired Data Final Image
  • 44. Image K
  • 45. The k-space Trajectory Equations that govern k-space trajectory: Kx = γ/2π ∫0t Gx(t) dt Ky = γ/2π ∫0t Gy(t) dt Gx (amplitude) Kx (area) time 0 t
  • 46. A typical diagram for MRI frequency encoding: A k-space perspective 90o Excitation Slice Selectio n Frequency Encoding readout Readout Exercise drawing its k-space representation
  • 48. A typical diagram for MRI frequency encoding: A k-space perspective 90o 180o Excitation Slice Selectio n Frequency Encoding readout Readout Exercise drawing its k-space representation
  • 50. A typical diagram for MRI phase encoding: A k-space perspective 90o Excitation Slice Selectio n Frequency Encoding Phase Encoding readout Readout Exercise drawing its k-space representation
  • 52. A typical diagram for MRI phase encoding: A k-space perspective 90 o 180o Excitation Slice Selectio n Frequency Encoding Phase Encoding readout Readout Exercise drawing its k-space representation
  • 54. Sampling in k-space .......... .......... ∆k .......... .......... .......... .......... .......... kmax .......... .......... .......... ∆k = 1 / FOV Refer to slide 32, 36
  • 55. A .......... .......... .......... B ..... .......... .......... ..... .......... ..... ..... .......... ..... .......... .......... .......... FOV: Pixel Size: FOV: 10 cm Pixel Size: 1 cm
  • 56. A B .......... .......... . . . . . .......... . . . . . .......... .......... .......... . . . . . .......... . . . . . .......... .......... .......... . . . . . FOV: 10 cm FOV: Pixel Size: 1 cm Pixel Size:
  • 57. A .......... .......... B .......... .......... ......... .......... .......... . .......... .......... .......... .......... .......... .......... .......... .......... .......... .......... .......... .......... .......... FOV: Pixel Size: FOV: 10 cm Pixel Size: 1 cm
  • 58. .......... .......... .......... . . . . . .......... ..... ..... . . . . . .......... .......... ..... .......... ..... . . . . . .......... ..... . . . . . .......... .......... . . . . . Figure 4.16. Effects of sampling in k-space upon the resulting images. Field of view and resolution have an inverse relation between image space and k-space. Shown in (A) is a schematic representation of densely sampled k-space with a wide field of view, resulting in the high-resolution image below. If only the center of k-space is sampled (B), albeit with the same sampling density, then the resulting image below has the same field of view, but does not have as high of spatial resolution. Conversely, if k-space is sampled across a wide field of view but with limited sampling rate (C), the resulting image will have a small field of view but high resolution.
  • 59. Original image K-space trajectory Displaced image Spatial Displacement Original image Distorted image Figure 4.17. Spatial and intensity distortions due to magnetic field inhomogeneities during readout. If there is a systematic change in the spin frequency over time, the resulting image may be spatially displaced (B). Another possible type of distortion results from local field inhomogeneities, which in turn cause the resonant frequency to vary slightly across spatial locations, affecting the intensity of the image over space.
  • 60. Original image K-space trajectory Distorted Image Figure 4.18. Image distortions caused by gradient problems during readout. Each row shows the ideal image, the problem with acquisition in k- space, and the resulting distorted image. Distortions along the x-gradient will affect the length of the trajectory in k-space, resulting in an image that appears stretched (A). Distortions along the y-gradient will affect the path taken through k-space over time, resulting in a skewed image (B). Distortions along the z-gradient will affect the match of excitation pulse and slice selection gradient, influencing the signal intensity (C).