Although the vast majority of fMRI studies is still performed with 2D-EPI, there are several other BOLD-sensitive sequences, available on most clinical platforms, that may perform better. The main alternatives to 2D-EPI are 3D-EPI and SMS-EPI, although EVI, MR-encephalography, ME-EPI and SE-EPI have also recently gathered interest. All these sequences will be discussed and compared to one another in terms of their strengths, weaknesses and artifacts. Specific situations in which a specific sequence would be preferred will be used to highlight the relevant strong points.
The main alternatives to 2D-EPI are 3D-EPI and SMS-EPI, although EVI, MR-encephalography, spiral imaging, ME-EPI, GRASE and SE-EPI have also gathered interest. The acquisition schemes behind the acronyms will be presented and compared to one another. The strengths and weaknesses of especially the widely used sequences will be compared in terms of SNR, BOLD sensitivity and temporal stability. Example studies employing each method will be highlighted.
Both SMS-EPI, also known as multiband EPI, and 3D-EPI are relatively small modifications in the 2D-EPI sequence with large effects on the type of data that can be acquired. In 3D-EPI, the imaging slab is excited as a whole and following each excitation, a plane in k-space is acquired within this slab, rather than the thin slices acquired one-by-one in 2D-EPI. Sequence modifications include the extra phase-encoding step and rf and gradient spoiling. In the reconstruction, an extra Fourier Transform in the slab-encoding direction is required. That the slab-selection direction is phase-encoded, means that undersampling strategies using parallel imaging techniques such as GRAPPA and SENSE or partial fourier/half-scan can be used to accelerate the acquisition. This undersampling yields much greater time-savings than undersampling in the first phase-encode direction, because of the requirement to keep TE roughly equal to the gray matter T2*(Poser et al., 2010). The increased image SNR of 3D-EPI compared to 2D-EPI renders it a good alternative for low-SNR protocols, such as the sub-millimetre acquisitions used to study BOLD responses as a function of cortical depth (Petridou et al., 2013). The longer sampling time does mean that the signal contributions of physiological processes, such as heartbeat and breathing, are also increased, especially in high-SNR, low resolution cases (Van Der Zwaag et al., 2012). In such protocols, physiological noise removal is important to regain BOLD sensitivity (Jorge et al., 2013; Lutti et al., 2013).
SMS, or Multiband EPI, is a different approach to accelerate the acquisition of a large number of echo planar images. As the name suggests, multiple slices are excited and acquired simultaneously (Müller, 1988) and signal originating from these is subsequently separated using coil information from multi-channel coils. The most important sequence modification required is the replacement of the excitation pulse by one exciting multiple slices. In addition, shifting the signal in the images with a phase-encode ‘blip’, to reduce the overlap between the simultaneously acquired slices, improves the unfolding process significantly (Setsompop et al., 2012). The excitation pulses are more SAR-intensive than for standard single-slice excitation EPI, which can be problematic at higher fields (Grissom et al., 2006). However, with the short repetition times one typically tries to achieve, the optimal flip angles are lower and the SAR limitation is usually not problematic. Another disadvantage of the simultaneous acquisition of multiple slices is the potential crosstalk between those slices after unfolding (Barth et al., 2016; Todd et al., 2016). 3D-EPI and SMS-EPI can be considered in a generalized framework (Zahneisen et al., 2014) and in a fast-acquisition regime they also behave similarly (Reynaud et al., 2017). Specific acquisitions, the different implementations on different scanners or local data handling pipelines may lead the researchers to favour the use of one approach over the other.
Even faster acquisitions such as MESH (Boyacioğlu et al., 2017), EVI (Posse et al., 2012; van der Zwaag et al., 2006), MR encephalography (Hennig et al., 2007; Kiviniemi et al., 2016) usually have insufficient spatial resolution to compete with SMS-EPI and 3D-EPI, but may be useful for applications where temporal resolution below 0.5s is required.
Besides the increases in temporal resolution, efforts are also made to improve the spatial specificity of the BOLD response. Most notably, the sensitivity to BOLD signal in the small vessels is thought to be much higher in T2-weighted sequences (Uludağ et al., 2009) such as SE-EPI (Norris, 2012; Siero et al., 2013) or GRASE (De Martino et al., 2013). Unfortunately, both at 3T (Parkes et al., 2005) and at 7T (Sanchez Panchuelo et al., 2015) the SNR of these sequences is still rather low. Hence, these are still not as widely used as the T2*-weighted GRE-based EPI acquisitions (Marques and Norris, 2017).
For true whole-brain coverage, including areas in close proximity to the air-water interfaces, the use of multi-echo EPI has also shown its worth. In this final flavour of the EPI sequences, multiple images are acquired at different TE’s, achieving optimal BOLD sensitivity independent of the exact local T2*(Boyacioğlu et al., 2015; Puckett et al., 2017).
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