Single-shot echo-planar imaging, with parallel imaging and simultaneous multi-slice improvements, remains the most commonly used sequence for diffusion imaging of the brain. Many other sequences have been developed with the goal of increasing the spatial resolution of whole-brain diffusion data and their designs are influenced by several considerations including image artefacts, SNR and efficiency, scan time per image, motion sensitivity, and slice acquisition paradigm. These issues will be discussed and illustrated with examples of recent diffusion sequences.
Diffusion-weighted imaging was enabled by the advent of the single-shot echo-planar imaging (ss-EPI) sequence (1,2), which is relatively immune to motion-related diffusion-encoding artefacts because all the required data for each slice image are acquired in a single “shot” after the diffusion encoding. This insensitivity to motion, specifically cardiac-related brain pulsation, and the ability to rapidly acquire a multi-slice volume are the reasons why spin-echo ss-EPI remains the most commonly-used diffusion imaging sequence for the assessment of acute stroke (3) and white matter anisotropy (4). Recently in-plane (5,6) and SMS (7) parallel imaging have been incorporated into standard diffusion imaging, however, multi-slice ss-EPI has limitations, principally susceptibility artefacts, and there is a continuing desire to increase the spatial resolution of whole-brain diffusion data. Some of the major considerations for improving EPI and designing alternative sequences are discussed below.
Image artefacts
As a consequence of its relatively slow phase-encoding (ky) readout, ss-EPI suffers from the susceptibility-induced geometric distortion artefact, as well as the more subtle blurring due to T2* decay of the signal. These issues limit the achievable spatial resolution, particularly at high field strengths where increased artefact levels directly undermine the goal of improved spatial resolution. Image artefacts can be reduced or modified with:
SNR and imaging efficiency
Signal-to-noise ratio (SNR) scales with voxel volume so SNR drops rapidly for isotropic high-resolution scans. For example, relative to a 2 mm isotropic scan, the SNR drops by a factor of 8 in a 1 mm isotropic protocol. SNR increases with the square root of scan time, so to recover the 2 mm SNR level, the 1 mm scan would require 64 averages. To increase SNR, sequences try to minimise the echo time (TE), which can be accomplished with partial Fourier acquisition, parallel imaging, and non-Cartesian k-space trajectories.
Another limitation of multi-slice ss-EPI with spin-echo diffusion encoding is that it is a very inefficient paradigm from an SNR perspective. The diffusion gradients encode the whole volume, but this time-consuming diffusion-weighting module is repeated for every slice of the volume as thin slices are acquired one at a time. The acquisition of large numbers of slices results in repetition times (TRs) of around 10 seconds, which is much longer than the ~1 s T1 relaxation rates of white and gray matter in the brain. SNR efficiency ( SNR / √(scan time) ) can be improved with:
Scan time per image
Applications of diffusion imaging have different data and scan duration requirements, for example, clinical stroke imaging generally requires three orthogonal directions to form a trace-weighted image but for tractography analysis usually >30 directions are needed and sometimes they are repeated with different b-values. Scan time acceleration is valuable for standard sequences, and also for multi-shot sequences, whose scan times become more reasonable (9-12). SMS can reduce the scan time of a diffusion protocol with minimal loss of SNR and this time saving can be used to shorten scan durations or to acquire more diffusion directions in a fixed time.
Motion sensitivity
When data from multiple “shots” or acquisitions are combined, the random phase caused by brain pulsation (13,14) during the diffusion gradients must be accounted for to avoid ghosting and blurring artefacts. Phase “navigation” measures the phase caused by motion and removes it from each shot so that data can be combined. A low-resolution phase estimate is usually sufficient because it generally varies smoothly. Self-navigated sequences, such as PROPELLER, cover the centre of k-space (low spatial frequencies) in each shot and otherwise a short “navigator” can be added to estimate the phase (15-17). Examples of work in this area:
Multi-slice vs. multi-slab
The combined slice profile of the 90-180 RF pulses degrades for thin slice excitations and cross-talk between adjacent slices reduces signal and affects contrast. Fourier encoding of a thicker slab can provide “true” isotropic resolution, and as, mentioned above, acquiring multiple slabs with TR ~ T1 is SNR efficient (8). However, multi-slab acquisitions also suffer from slice profile-related problems: cross-talk at the slab interfaces from non-ideal excitations alters signal and contrast and it is more noticeable because the interface regions are relatively wide (scale with FWHM of RF pulse). Solutions to this involve overlapping slabs and discarding slices at the edges, which reduces efficiency, or PEN/NPEN can avoid these overlaps and reduce the aliasing in reconstruction (29,30). A lot of recent research on diffusion imaging has focussed on these SNR-efficient sequences and overcoming the slab-joining artefacts.
Recent sequence designs
Some sequences that illustrate the issues mentioned above will be discussed:
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