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is significantly reduced. This technique is therefore often used when motion artefact is likely to be a problem. However, scan times may increase.

       Centric k‐space: Centric k‐space fills the centre lines of k‐space first and then the outer lines. This ensures that signal and contrast are optimized as data are collected before the signal decays. This technique is mainly used in fast GRE pulse sequences.

        Volume imaging: Volume imaging or 3D acquisitions collect data from an imaging volume or slab rather than from individual slices. An extra phase encoding is undertaken along the slice‐select axis. This is called slice encoding. Very thin slices with no gap are obtained and the data set may be viewed in any plane. However, the scan time in volume imaging depends not only on the TR, the phase matrix and the NEX/NSA but also on the number of slice locations in the volume. Therefore, scan times are considerably longer than in 2D imaging. For this reason, fast pulse sequences such as steady‐state sequences and FSE/TSE are commonly used (see Pulse sequences). To maintain spatial resolution in all viewing planes, the voxels should be isotropic, that is, they have the same dimensions in all three planes. This is achieved by selecting an even matrix and a slice thickness equal to, or less than, the pixel size. For example, if a matrix size of 256×256 is chosen and the FOV is 256 mm, a slice thickness of 1 mm achieves a voxel measuring 1 mm × 1 mm × 1 mm. With a larger FOV, a slightly thicker slice can be used. The penalty of isotropic voxels, however, is a reduction in SNR due to the use of smaller voxels. In addition, more slices may be required to cover the imaging volume, resulting in long scan times. This is compensated for to some degree by the fact that as there are no gaps, a greater volume of tissue is excited and therefore overall signal return is greater. Nevertheless, when volume imaging is used, the need for good spatial resolution in all planes must be weighed against longer scan times.As slices are not individually excited as in conventional acquisitions, but are located by an extra phase encoding gradient, aliasing along the slice select axis can occur. This originates from anatomy that lies within the coil (and therefore produces signal) and exists outside the volume along the slice encoding axis. It manifests itself by the first and last few slices of the imaging volume wrapping into each other and potentially obscuring important anatomy. To avoid this, always overprescribe the volume slab so that the region of interest (ROI) and some anatomy on either side of it are included (see Flow phenomena and artefacts). Volume imaging is commonly used in the brain and to examine joint anatomy, especially when very thin slices are required. In Part 2, the following terms and approximate parameters are suggested when discussing volume imaging (see also Table 2.1):

       A thin slice is 1 mm or less.

       A thick slice is more than 3 mm.

       A small number of slice locations is approximately 32.

       A medium number of slice locations is approximately 64.

       A large number of slice locations is approximately 128 or more.

      To optimize image quality, data should have a high SNR and good spatial resolution and be acquired in a short scan time. This is usually impossible, however, as the factors that must be increased to improve SNR may have to be decreased to gain spatial resolution. An example of this is matrix selection. A coarse matrix is required to obtain large voxels and therefore a high SNR. However, a fine matrix with small voxels and low SNR is not only necessary to maintain good spatial resolution, but also increases the scan time as more phase encodings are performed. The MRI practitioner must decide which factor (either SNR, phase resolution or scan time) is the most important, optimize this and sacrifice the others. When discussing these issues in Part 2, the importance of good SNR over the other factors is emphasized. There is little point in having an image with good spatial resolution if the SNR is so poor that the image has no diagnostic value.

      Source: Catherine Westbrook and John Talbot, MRI in Practice, 5th ed., John Wiley & Sons, 2019.

To optimize image Adjusted parameter Consequence
Maximize SNR ↑NSA ↑Scan time
↓Image matrix (fixed FOV) ↓Scan time (pMatrix)
↓Resolution
↑Slice thickness ↓Resolution
↓Receive bandwidh ↑Minimum TE
↑Chemical shift
↑FOV (fixed matrix) ↓Resolution
↑TR ↓T1 contrast (during incomplete recovery)
↑Number of slices
↓TE ↓T2 contrast
Maximize resolution (assuming a square FOV) ↓Slice thickness ↓SNR
↑Image matrix (fixed FOV) ↓SNR
↑Scan time (pMatrix)
↓FOV (fixed matrix) ↓SNR
Minimize scan time ↓TR

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