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The uniformity of the B 0 main field in magnetic resonance imaging (MRI) is critical for artifact-free image formation. MRI scanners are manufactured with a stringent requirement of less than one part-per-million (ppm) a
a In MRI, the variations in B 0 field or the differences in resonant frequencies are so small that they are expressed in “parts per million”, or ppm. For example, 1 ppm inhomogeneity at 1.5 T corresponds to a 1.5 μT variation in the B 0 field. This field variation would in turn result in a 63.87 Hz off-resonance (i.e., one-millionth of the center frequency of f 0 = 63.87 MHz at 1.5 T).
variation in the B 0 field. However, this 1 ppm theoretical homogeneity easily gets distorted once a subject is placed inside the MRI scanner, mainly due to a 9 ppm magnetic susceptibility difference between air and tissue. The presence of any surgical implants further exacerbates the problem, as different tissue types, air, and metal all interact with and distort the applied magnetic field differently. This interaction is quantified by what is called the magnetic susceptibility of a matter.
The susceptibility variations in tissue on a microscopic scale are in fact the source of many useful contrast mechanisms in MRI, such as blood oxygenation level-dependent (BOLD) functional MRI (fMRI) and diagnosis of cerebral hemorrhage. However, a macroscopic susceptibility variation leads to a global field inhomogeneity, which in turn creates off-resonance induced artifacts in the images. These artifacts manifest as faster T 2 ∗ decay, signal dropouts and pileups, geometric distortions, and incomplete fat suppression. High-field MRI scans especially suffer from susceptibility artifacts, as the absolute size of the field perturbations increases linearly with B 0 field strength. For example, the 9 ppm susceptibility difference between air and tissue corresponds to a 575 Hz field variation at 1.5 T, while it is doubled to a 1150 Hz variation at 3 T. While a global frequency shift can be easily dealt with by adjusting the center frequency, it is the local field inhomogeneity that perturbs the imaging process.
In vivo MRI of the spinal cord is especially challenging due to susceptibility variations between various tissue types (e.g., vertebrae, muscle, CSF, gray and white matter, fat, air in the lungs and trachea, bowel gas, and surgical implants) that significantly distort the applied magnetic field. As shown by the B 0 field maps of the spine ( Figure 2.3.1 ), the air in the lungs and nasal cavities as well as the curvature in the neck significantly distort the field around the spinal cord. Furthermore, susceptibility differences between vertebral spinous processes and connective tissue create local field inhomogeneities along the spinal cord itself, as seen in Figure 2.3.1 (B). Bulk physiologic motion from cardiac and respiratory cycles, CSF pulsation, as well as breathing and swallowing further cause temporal variations of these field inhomogeneities.
This chapter gives an overview of susceptibility artifacts and how they manifest in EPI images of the spinal cord. Methods to alleviate these artifacts will be outlined. Please note that while this chapter mostly presents examples of susceptibility artifacts on sagittal images, axial and coronal orientations are equally affected.
Single-shot echo planar imaging (ss-EPI) remains the most frequently used technique for most of the quantitative imaging methods, because it acquires the whole of k -space after a single excitation. This fast imaging capability is especially critical for methods that are sensitive to subject motion (e.g., diffusion-weighted imaging (DWI)) or for methods that require a high temporal resolution (e.g., fMRI).
Although ss-EPI performs relatively well in the brain, the anatomy of the spine as well as the abundance of susceptibility variations make it particularly difficult to produce high-quality ss-EPI images of the spinal cord. The long and narrow anatomy of the spine requires a large field of view (FOV) in the superior-inferior (S/I) direction, and the small cross-sectional size of the spinal cord mandates high-spatial-resolution images. Even in the axial imaging plane, where the spinal cord presents a small region of interest (ROI), the rest of the body dictates a large FOV. Covering a large FOV with high resolution requires long readout durations in EPI, which in turn result in distortions and severe blurring of the images along the phase-encoding (PE) direction. In addition, the long interval between subsequent k -space lines (i.e., echo spacing) causes significant image distortions due to off-resonance effects.
The location-dependent geometric distortion in an EPI image can be expressed as:
Here, d PE ( r ) is the local displacement of a voxel in the PE direction (i.e., the voxel appears at position r + d PE ( r ) instead of at r ), Δ f ( r ) (in Hertz) represents a field inhomogeneity or off-resonance effect observed at position r , and FOV PE is the FOV in the PE direction, T ESP (in seconds) is the time interval between two adjacent echoes during an EPI readout (referred to as the “echo spacing”), N int is the number of interleaves in EPI (e.g., N int = 1 for ss-EPI), and R denotes the acceleration factor for parallel imaging (e.g., R = 1 for no acceleration). As seen in Eqn (2.3.1) , a large FOV, increased readout duration due to a need for high resolution, and increased susceptibility variations all contribute to geometric distortions in EPI images. For example, a local 6 ppm off-resonance at 3 T, a FOV PE = 18 cm, and T ESP = 0.5 ms (all typical numbers in the spine) would cause close to 7 cm local displacement for regular ss-EPI. This level of distortion, as demonstrated in Figure 2.3.2 (C) , can easily render regular ss-EPI images clinically unusable.
ss-EPI images also exhibit a substantial water–fat misalignment, as the frequency term in Eqn (2.3.1) also applies to chemical shifts. For example, for the aforementioned imaging parameters, the fat image would experience a 4 cm shift in the PE direction with respect to the water image (assuming a chemical shift of 3.5 ppm, i.e., 440 Hz at 3 T). Hence, ss-EPI mandates proper shimming of the ROI, as well as a robust fat suppression or spectrally selective excitation. These fat suppression schemes usually take advantage of the chemical shift (i.e., differences in resonant frequencies) between fat and water. Unfortunately, susceptibility variations around the spine can distort the field homogeneity to such an extent that effective fat suppression is often an issue. For example, a local 440 Hz susceptibility-induced off-resonance at 3 T would cause the water signal to be suppressed, instead of the fat signal. Figure 2.3.2 (B) demonstrates this phenomenon, where the susceptibility variations around the cervical spine resulted in an incomplete fat suppression (white arrow) and a signal dropout (red arrow).
The position dependency of susceptibility effects causes different regions in the FOV to experience different levels of displacement, further complicating the problem. This nonrigid distortion is typically observed as signal pileups or dropouts in an EPI image. The cervicothoracic junction in Figure 2.3.2 (C) shows one such case, where the signals from the spinal cord and the CSF are piled up, while the neighboring pixels (where CSF was supposed to be) are left devoid of signal (yellow arrow). A less severe manifestation of this susceptibility artifact is the comb-like appearance of the spinal cord in Figure 2.3.2 (C), which is caused by the local field inhomogeneities along the spinal cord (see Figure 2.3.1 (B)).
There are various approaches that can be used to reduce susceptibility artifacts for spinal cord imaging; unfortunately, many of these methods have only been demonstrated in the research arena and are not available on clinical scanners. These approaches target one (or more) of the variables in Eqn (2.3.1) , which can be rewritten as:
where S k is the speed of k -space traversal, i.e.,
Here, Δ k PE is the distance between adjacent k -space lines during readout, and Δ t PE is the time interval between the echoes from these k -space lines, which is equal to the echo spacing, T ESP .
As seen in Eqn (2.3.2) , one can reduce susceptibility artifacts by reducing the off-resonance effect , or Δ f ( r ). This goal can be achieved to a certain extent by passive or active shimming of the areas of interest (see Section 2.3.3.6 and Chapter 2.2 ); however, local field inhomogeneities remain unaddressed.
The other (rather more tortuous) method is to accelerate the traversal of k-space (i.e., increase S k ) by altering the MRI pulse sequence, as outlined schematically in Figure 2.3.3 . A reduction of the echo spacing ( T ESP ) can be achieved by (1) increasing the EPI bandwidth and/or sampling on the gradient ramps of the EPI trajectory, and/or (2) segmenting the k -space trajectory, such as by the readout-segmented EPI approach (a “multishot” method). Interleaved EPI methods speed up the k -space traversal by dividing the k -space into several sections that are each acquired faster but in separate repetition times (TRs). A reduction in the phase-encoding FOV (FOV PE ) in spine imaging with standard slice-selective pulses can cause undesired aliasing in the PE direction if the object is larger than FOV PE , even after using graphical saturation pulses. Thus, more advanced reduced FOV methods that alter the radiofrequency (RF) pulses or that use outer volume suppression methods have been implemented for the spinal cord. Parallel imaging methods provide acceleration in k -space by utilizing the complementary spatial encoding information from multiple receiver coil elements to reduce the number of acquired k -space lines.
Ideally, a combination of all of these methods could be used; however, each of these techniques presents a rather complicated set of advantages and limitations. The remainder of this section discusses various approaches to reduce susceptibility distortions, and their relative advantages and disadvantages.
Susceptibility effects can be alleviated by reducing the echo spacing between adjacent k -space lines during readout in a single TR. For a fixed image resolution, the easiest way to achieve this goal is (1) to increase the readout bandwidth (BW), and/or (2) to acquire data during the gradient ramps (also known as “ramp sampling”) in addition to the gradient plateaus. Increasing the bandwidth reduces the signal-to-noise ratio (SNR) due to a shorter readout. However, if a region experiences severe off-resonance effects, the decreased readout duration can actually reduce the dephasing in a voxel, resulting in an increase in local signal level. Ramp sampling is an especially important implementation that comes at very little disadvantage, other than the need for 1D-gridding of the data acquired during gradient ramps.
Both ramp sampling and increasing the bandwidth are methods available on most commercial MRI scanners. In some scanners, there is no direct relationship between the echo spacing and the BW, due to hardware limitations (e.g., gradient-switching time). In practice, the user can increase the BW and stop when the echo spacing is at its minimum. Note that although reducing the echo spacing is the easiest way to alleviate susceptibility artifacts, it can fail to provide a significant improvement in image quality, given that the readout bandwidth in an MRI scanner has an upper limit (typically a maximum of ±250 kHz). The methods described in the remainder of this section usually build on top of a ramp-sampled, high-bandwidth EPI sequence, and they provide additional ways to speed up k -space traversal in EPI.
Spinal cord imaging has been shown to benefit from reduced FOV (rFOV) acquisitions that limit the extent of coverage in the phase-encoding direction (i.e., FOV PE ). With a much smaller FOV PE , the number of required k -space lines is also reduced (typically between one-half and one-fourth of the full-FOV case), which in turn significantly reduces off-resonance induced artifacts. As expected, the SNR is also reduced by the square root of the FOV PE reduction factor. Although both reduced-FOV and parallel imaging methods reduce the number of acquired k -space lines to achieve high-quality images, they significantly differ in implementation. Parallel imaging methods (see Section 2.3.3.3 ) take advantage of the orthogonality of coil sensitivities, while the rFOV techniques actively limit the extent of FOV through pulse sequence modifications.
Figure 2.3.4 demonstrates the effectiveness of rFOV techniques, where reducing the FOV PE to one-fourth of its full-FOV value alleviates the distortions in the ss-EPI image of the spinal cord, even in the presence of metallic implants. Recently, a number of rFOV methods have been proposed for high-resolution ss-EPI of the spinal cord. A schematic explanation of some of these methods is given in Figure 2.3.5 .
One of these rFOV methods utilizes outer-volume suppression pulses preceding the excitation pulse (shown in Figure 2.3.5 (A)). This technique can be implemented by placing suppression bands anterior and/or posterior to the spine. Similar implementations of this method are available on most commercial MRI scanners, and they usually involve graphical prescription of suppression and saturation bands. However, because the suppression efficiency is generally limited, it can lead to partial aliasing artifacts in the PE direction of the images. These artifacts are sometimes difficult to detect, as the aliased signal can resemble noise due to its attenuated amplitude. Hence, it is imperative to perform phantom tests to assess the level of signal suppression outside the desired FOV PE .
Another rFOV technique applies excitation and refocusing RF pulses orthogonally (see Figure 2.3.5 (B)), which significantly decreases the SNR of the neighboring slices if interleaved acquisition is performed. This is because the 180° pulse acts as an inversion pulse on the neighboring slice locations. A method called ZOOM-EPI mitigates the SNR loss problem by applying the 180° refocusing pulse at an oblique angle, as shown in Figure 2.3.5 (C). This way, the neighboring slices do not experience the refocusing pulse. However, if the neighboring slices are close to each other in space, there can still be a partial cross-saturation of the adjacent slices, resulting in a signal drop along the edges of the FOV in the PE direction. This signal drop can be alleviated by spacing the slices apart (i.e., by placing slice skips) or by extending FOV PE . A recent approach called contiguous-slice zonally oblique multislice (CO-ZOOM) mitigates the cross-saturation problem by double refocusing the signal with two 180° pulses applied orthogonally as in Figure 2.3.5 (B). However, the resulting prolonged echo time (TE) decreases the signal level.
Instead of utilizing a 1D excitation pulse, 2D spatially selective RF pulses can be used to excite only the ROI for rFOV imaging. As shown in Figure 2.3.5 (D), because the adjacent slices are not excited, this method is compatible with contiguous multislice imaging without the need for a slice skip. Depending on the implementation, these 2D-RF pulses have excitation profiles periodic in either the phase or the slice direction. A subsequent 180° refocusing pulse can be utilized to refocus only the main lobe of the excitation while preserving the rFOV imaging capabilities, as demonstrated in Figure 2.3.5 (D). When the profile is periodic in the slice direction, the fat and water profiles are also shifted in volume in the slice direction. This feature can be exploited by designing a 2D-RF pulse with nonoverlapping fat–water profiles. Then, the subsequent 180° refocusing pulse suppresses the signal from fat without the need for additional fat suppression pulses. However, the periodicity in the slice direction may also restrict the coverage in the slice direction. Likewise, if the excitation profile is periodic in the phase direction, it may place a restriction on the maximum size of the subject. This is because the periodic lobes in the phase direction can otherwise cause aliasing artifacts, as those lobes are now refocused with the 180° pulse. Furthermore, because the 2D-RF pulses tend to have long durations, the slice profiles may be sensitive to off-resonance effects.
Each of these rFOV methods has its own strengths and weaknesses, and the method of choice depends on the application. In the end, they all significantly reduce the susceptibility-induced artifacts in EPI.
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